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Abstracts

NSCA 2021 Conference Abstracts

Journal of Strength and Conditioning Research: December 2021 - Volume 35 - Issue 12 - p 291-446
doi: 10.1519/JSC.0000000000004141
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(1) Current Strength and Conditioning Practices of College Football: 2019–2020

C. Fitzgerald

Northern Michigan University

Purpose: The primary purpose of the current research study was to identify the common and unique aspects of college football strength and conditioning (S and C) practices during 2019–2020. This study focused on position-specific aspects of the training program and how training variables were manipulated during different mesocycles. Methods: A previously validated survey instrument was utilized. All collected data were entered into SPSS (v. 24.0 IBM) Statistical Analysis Program. All procedures were approved by the Institutional Review Board at Northern Michigan University (NMU). Results: The survey was completed by 92 subjects. Subjects had 12.53 ± 8.98 years of overall S and C coaching experience (n = 89) and 10.85 ± 8.61 years of S and C experience specifically at the college level (n = 91). The results revealed greater variations in the specific mesocycles of physical fitness testing occurred and which specific positions were tested, regarding specific fitness variables. Flexibility exercises were prescribed 4.06 ± 1.39 days per week (n = 80); most commonly during post-workouts periods (n = 71). Subjects reported prescribing speed training exercises 1.63 ± 1.08 days per week during the in-season (n = 65); compared to 2.90 ± 1.12 days per week during the off-season (n = 84). Plyometric exercises were prescribed 2.64 ± 0.94 days per week (n = 85). Subjects reported prescribing resistance training exercises 2.45 ± 0.50 days per week during the in-season (n = 85); compared to 3.78 ± 0.56 days per week during the off-season (n = 84). The top ranked exercise was the “squat” (n = 36); with the most important muscle group to develop being the “lower body” (n = 41). Subjects also indicated training session durations during the in-season and off-season, the duration of both the warm-up and cool down, and the number of mesocycles that made up the macrocycle. A total of 48 subjects reported that they individualized the training program based on specific position. The results revealed greater variations in the methodologies subjects utilized for training load, sets and reps, rest intervals, and exercise order. Most commonly subjects prescribed balance and stability, core training, Olympic weightlifting, injury prevention program, and recovery modalities to “all players” (n = 64; n = 80; n = 74; n = 81; n = 67 respectfully). Subjects reported pre-resistance training meals were consumed 1.24 ± 0.46 hours prior (n = 81); compared to post-resistance training meals being consumed 0.75 ± 0.51 hours post (n = 80). A total of 29 subjects indicated that supplements were administered to athletes. The most common supplement provided was protein (n = 22). Conclusions: These findings suggest that coaches consider position-specific characteristics when implementing various training interventions. Additionally, there is substantial amount of training variable manipulation during the yearly training program. This was the first comprehensive survey to analyze these variables at the college level. Practical Applications: This study describes the common and unique aspects of the college football S and C practices. This data should be useful for future research as a source for comparison. With this new source of information, researchers are able to continue to empirically investigate various aspects of training programing. Additionally, S and C coaches can review this data as a source for new ideas.

(2) Differences in Countermovement Jump Height, Time to Takeoff, and Modified Reactive Strength Index Between Division III Collegiate Teams

S. Connell, M. Chavez, S. Holt, and T. Suchomel

Carroll University

Purpose: To examine the differences in jump height (JH), time to takeoff (TTT), and modified reactive strength index (RSImod) between NCAA Division III collegiate teams. Methods: Three hundred four NCAA Division III athletes performed unloaded countermovement jumps (CMJ) on force plates as part of a long-term athlete monitoring program. Female athletes participated in either softball (n = 23), volleyball (n = 18), lacrosse (n = 23), soccer (n = 40), and basketball (n = 15), while male athletes participated in either football (n = 75), baseball (n = 40), lacrosse (n = 11), soccer (n = 44), or basketball (n = 15). The force-time data from the force plates were used to calculate JH and TTT. RSImod was calculated as the ratio between JH and TTT. A series of one-way ANOVA tests were used to compare the differences in JH, TTT, and RSImod between teams. Results: The descriptive data for each team and statistical differences in JH, TTT, and RSImod between teams are displayed in Table 1. There were no significant differences between the women's teams for JH (p > 0.05); however, the JH of all the men's teams was greater than all the women's teams (p ≤ 0.05). In addition, the JH of the men's football and basketball teams was significantly greater than the men's lacrosse team (p ≤ 0.05). The TTT of the women's lacrosse team (p = 0.013), as well as the men's football (p < 0.001), baseball (p < 0.001), and soccer (p < 0.001) teams, were significantly greater than women's softball. In addition, the TTT of men's baseball was significantly greater than men's basketball (p = 0.034). Similar to JH, there were no significant differences between the women's teams for RSImod (p > 0.05). In contrast, the RSI mod of men's football, baseball, soccer, and basketball was significantly greater compared to all the women's teams (p ≤ 0.05). In addition, the RSImod of men's lacrosse was greater than women's lacrosse (p = 0.001) and basketball teams (p = 0.024). Within the men's teams, the RSImod of football and basketball was greater compared to men's lacrosse (p ≤ 0.05). Finally, the RSImod of the men's basketball team was significantly greater than men's baseball (p = 0.009) and soccer (p = 0.012). Conclusions: The men's teams examined within this study demonstrated greater JH and RSImod magnitudes compared to the women's teams; however, very few differences were displayed amongst all teams regarding TTT. RSImod appears to be more influenced by achieving greater JH magnitudes. Practical Applications: While differences in reactive strength characteristics existed between male and female NCAA Division III collegiate teams, further research is needed to understand why these differences exist. Future research should consider examining the jump strategies used to achieve specific JH, TTT, and RSImod magnitudes and monitor these characteristics longitudinally. Furthermore, practitioners should seek training methods that may be used to enhance JH and minimize TTT.

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Table 1:
Countermovement jump height, time to takeoff, and modified reactive strength index descriptive statistics.

(5) Mechanomyographic Responses to Maximal, Reciprocal, Isokinetic Forearm Flexion and Extension Fatigue

T. Neltner,1 J. Anders,2 R. Smith,1 J. Keller,3 T. Housh,1 R. Schmidt,1 and G. Johnson1

1University of Nebraska - Lincoln;2University of Nebraska- Lincoln; and3University of South Alabama

Purpose: The amplitude (AMP) and mean power frequency (MPF) of the mechanomyographic (MMG) signal have been used to make inferences regarding motor unit activation during fatiguing tasks. The purpose of this study was to examine the MMG AMP and MPF responses from the biceps brachii (BB) and triceps brachii (TB) as a result of maximal, reciprocal, isokinetic fatigue. Methods: Nine women (mean ± SD: age = 21 ± 1.7 years; body mass = 68.5 ± 8.5 kg; height = 168.1 ± 7.1 cm) performed 50 consecutive, maximal, reciprocal, isokinetic muscle actions of the right forearm flexors and extensors at 60 and 180°·s−1. Using accelerometers on the BB and TB, the AMP and MPF contents of the MMG signals were recorded simultaneously throughout the fatiguing task. The average of the first 5 (Initial) and last 5 (Final) repetitions were used for analyses. The MMG and torque values were normalized to pre-test peak torque trials of the same speed. A 2 (Time) × 2 (Speed) × 2 (Movement) repeated measures (RM) ANOVA was used to analyze torque changes across the fatiguing task. A 2 (Time) × 2 (Speed) × 2 (Muscle) × 2 (Movement) RM ANOVA was used to determine mean differences for the MMG parameters. Follow-up pairwise comparisons were used when necessary. Results: The torque analyses indicated a significant main effect for Time, collapsed across Speed and Movement, where Initial (95.3 ± 9.2%) was greater (p < 0.001) than Final (59.5 ± 10.2%). For MMG AMP there was a significant 4-way interaction. Follow-up analyses indicated no change from Initial to Final in either Muscle at either Speed during flexion (p > 0.05), and a significant decrease (p = 0.005) from Initial (149.4 ± 45.9%) to Final (104.9 ± 33.6%), collapsed across both Muscle and Speed during extension. For MMG MPF, there was a significant 3-way interaction for Time × Muscle × Movement, collapsed across Speed. For flexion, there was a significant decrease (p = 0.012) from Initial (95.4 ± 24.1%) to Final (86.4 ± 20.6%), collapsed across Muscle, and for extension there was a significant 2-way interaction. Follow-up paired t-tests revealed a significant decrease (p = 0.004) in the TB from Initial (111.4 ± 19.8%) to Final (93.0 ± 10.8%), and no significant change (p > 0.05) in the BB from Initial (62.3 ± 18.7%) to Final (66.1 ± 22.6%) during extension. Conclusion: Our findings were indicative of fatigue during flexion and extension. Interestingly, the MMG results suggested that the TB was more effected by fatigue than the BB. That is, the fatigue-induced patterns of responses for MMG AMP and MPF suggested there was a decrease in recruitment and firing rates of the TB during extension, there was no change in recruitment of the BB during flexion, and BB recruitment remained unchanged during extension. Thus, the parallel decline in torque in conjunction with differing MMG responses between the muscles could be attributed to larger synergistic muscles, such as the brachioradialis and brachialis, assisting in forearm flexion, compared to the much smaller synergistic contribution of the anconeus to forearm extension. Practical Applications: A sustained fatiguing action of the BB would require longer time to task failure or a greater resistance to experience the same magnitude of neuromuscular fatigue as the TB. Training programs should consider incorporating more exercises to enhance TB endurance to achieve the same level of fatigue resistance as the BB.

Thursday, July 8, 2021, 9:45 am–10:00 am

(6) Kinematic Variables Related to Optimal Free Throw Shooting Performance

D. Cabarkapa,1 A. Fry,1 K. Carlson,2 J. Poggio,1 and M. Deane1

1The University of Kansas; and2Drake University

Basketball is one of the most popular international sports in which successful game outcome is highly contingent upon optimal shooting performance. Although the free throw shot has been considered one of the easiest uncontested shooting motions, many players on various levels of basketball competition struggle with its optimal and consistent execution. Purpose: The purposes of this study were to (1) investigate the difference in kinematic variables between proficient and non-proficient free throw shooters, (2) determine which variables have the greatest contribution to a successful shooting outcome, and (3) determine what variables change when a proficient shooter misses. Methods: Seventeen healthy recreationally active male basketball players (height = 182.7 ± 8.9 cm, weight = 88.9 ± 6.5 kg, age = 29.6 ± 10.1 years) performed 3 sets of 10 free throws while wearing a motion tracking system (XSENS MVN Awinda, Netherlands) encompassing 17 wireless sensors sampling at 60 Hz. Choice of kinematic variables examined in this study were obtained from a panel of expert elite basketball coaches, and included knee angle (maximum internal angle at the knee joint during the preparatory phase of the shooting motion), elbow height (perpendicular distance between the olecranon process and the ground immediately prior to shot initiation, relative to body height), elbow angle (internal angle of the elbow at the initial stage of the shooting motion), forearm angle (angle between the long axis of the forearm and an imaginary vertical line at the initiation of the shooting motion), and shoulder angle (angle between the fully extended arm and a line parallel to the ground at the time point of ball release). Multivariate Hotelling's T-squared test and a full-model multiple discriminant analysis were used to detect the differences in kinematic variables and their contributions in separating proficient (≥70%; n = 10) from non-proficient (<70%; n = 7) free throw shooters. Results: Proficient free throw shooters exhibited greater knee and elbow flexion, lower relative elbow height, and smaller forearm angle values relative to vertical (p < 0.001), while no difference was observed for the shoulder angle (p > 0.05). The multiple discriminant analysis correctly classified free throw shooters in the proficient or non-proficient category in 89.5% of cases. The variables contributing most to the total variance of the discriminant analysis were elbow angle (36.7%) and forearm angle (23.9%). Moreover, the only statistically significant difference in the kinematic variables between made and missed free throw shots within the group of proficient free throw shooters was the forearm angle variable (p < 0.004). Conclusions: Maintaining an optimal range of each of the kinematic variables can allow players to reach an acceptable level of free throw shooting performance, with the elbow and forearm angles being most important. Even among the proficient shooters, failure to maintain the forearm angle differentiated between made and missed free throws. The ability to position a forearm parallel, or close to parallel with the imaginary vertical line during the preparatory phase of the shooting motion may result in a greater number of made free throw shots. Practical Applications: The findings of this study may help basketball players improve their free throw shooting accuracy by improving shooting mechanics, thus increasing their team's chances of winning.

(7) The Amplitude and Frequency Contents of the Mechanomyographic Signal Remain Unchanged Following a Maximal, Isometric, Forearm Flexion Task to Failure

R. Smith,1 T. Neltner,1 J. Anders,1 J. Keller,2 T. Housh,1 R. Schmidt,1 and G. Johnson3

1University of Nebraska - Lincoln;2University of South Alabama; and3University of Nebraska

Mechanomyography (MMG) has been used to investigate the mechanical properties of muscle function during various modes of resistance exercise. It has been suggested that, under some conditions, MMG amplitude (AMP) represents motor unit recruitment and MMG mean power frequency (MPF) is qualitatively related to motor unit firing rate. Purpose: The purpose of this study was to examine the effects of a sustained, maximal, isometric forearm flexion task to failure on the MMG AMP and MPF responses from the agonist and antagonist muscles. Methods: Eleven men (mean ± SD: age = 21.9 ± 2.1 years; height = 180.1 ± 6.0 cm; body mass = 86.8 ± 18.4 kg) performed 2 randomly ordered, 6 s forearm flexion and forearm extension maximal voluntary isometric contractions (MVIC) at elbow joint angles of 135° and 90°, respectively, followed by a continuous, maximal, forearm flexion task to failure (defined as a 20% decrease from the pre-fatigue MVIC). Post-fatigue MVICs were performed in the same manner as pre-fatigue. The MMG signal was assessed from the biceps brachii (BB) and triceps brachii (TB) during testing. For MVIC, a 2 (Time: Pre vs. Post) × 2 (Contraction Type: Flexion vs. Extension) Repeated Measures (RM) ANOVA was used to determine the mean differences and a 2(Time: Pre vs. Post) × 2 (Muscle: BB vs. TB) × 2 (Action: Agonist vs. Antagonist) RM ANOVA was used to determine the mean differences for MMG AMP and MMG MPF responses. Follow-up pairwise comparisons and post-hoc comparisons were used when necessary. Results: For torque, there was a significant main effect for Time (collapsed across Contraction Type) where the pre-fatigue MVIC (50.9 ± 8.5 N·m) was greater than the post-fatigue MVIC (46.9 ± 9.2 N·m; p < 0.001). For MMG AMP, there was a significant three-way interaction for Time × Muscle × Action. Post-hoc comparisons demonstrated that there was a significant difference (p < 0.001) when the BB was the agonist (0.42 ± 0.15 m·s2) compared to when the BB was the antagonist (0.98 ± 0.39 m·s2), with no significant difference (p = 0.132) for the TB when comparing agonist versus antagonist muscle actions. For MMG MPF, there was no significant interaction or main effect for Time, Muscle, or Action. Conclusions: There were parallel, fatigue-induced decreases in MVIC for forearm flexion (9.5%) and forearm extension (6.5%) following the forearm flexion fatiguing task. The lack of changes in the MMG AMP from the BB and TB likely reflected factors related to muscle compliance. The lack of changes in MMG MPF from the BB and TB suggested that there were no changes in global motor unit firing rates following the isometric forearm flexion fatiguing task. These findings suggested that the fatigue-induced decreases in the forearm flexion MVIC and forearm extension MVIC were likely due to aspects of peripheral fatigue, but not central fatigue. Practical Applications: MMG can be used to examine the mechanical aspects of muscle function during and/or following a fatiguing contraction to provide information about the mechanisms of fatigue-induced decreases in muscular strength.

(8) Differences in Bone Density Among Collegiate Athletes Participating in Weight Bearing vs. Non-weight Bearing Sports

M. Magee,1 L. de Jonge,1 J. Fields,2 S. Gallo,3 J. White,4 and M. Jones1

1George Mason University;2Springfield College;3University of Georgia; and4Ohio University

Background: Exercise has been shown to benefit bone health. However, athletes from no-impact, non-weight bearing sports are at risk for lower bone density than athletes from weight-bearing sports. Further, it has been reported that women athletes are more susceptible to lower bone mineral density (BMD) than men athletes. The BMD adjusted Z-score enables comparison across segments of the population because it is calculated based upon sex, age, and race-specific reference populations. Purpose: To compare the BMD Z-scores between men and women athletes participating in weight-bearing (basketball) and non-weight bearing (swimming) sports. Methods: A total of 26 men [basketball (MBB) n = 13; swimming (MSWIM) n = 13] and 24 women [basketball (WBB), n = 13; swimming (WSWIM), n = 11] National Collegiate Athletic Association Division I athletes participated. Whole body BMD was measured using dual-energy x-ray absorptiometry (DXA). BMD Z-score was calculated based upon the 2008 NHANES data. BMD Z-score was compared by sport team using analysis of variance. Bonferroni post-hoc test was used to identify differences among sports teams, which were reported at the level p < 0.05. Effect sizes were calculated using Cohen's d and were reported as follows: large >0.8; medium >0.5; small >0.2. Results: Bone and body composition characteristics are included in Table 1. A significant difference existed among groups (p < 0.001). Post-hoc tests indicated that MBB (p < 0.001) and WBB (p < 0.001) had greater BMD Z-scores than MSWIM. Additionally, there were large effect sizes between MSWIM and MBB (d = 1.6), WBB (d = 2.1), and WSWIM (d = 1.1). Medium and large effect sizes were found between WSWIM and MBB (d = 0.6), and WSWIM and WBB (d = 0.9), respectively. Conclusions: MSWIM had a significantly lower BMD Z-score than other sport groups except WSWIM, although a large effect size was observed. Further, WSWIM had a lower BMD Z-score than MBB and WBB. This may be due to the nature of their sport as swimming is a non-weight bearing sport. Sports that involve ground-based running, jumping, landing, and quick directional changes have athletes with higher BMD than sports that do not require such movements. Since MSWIM and WSWIM have similar sport demands, differences in BMD Z-score warrants further investigation. Practical Applications: It is recommended that practitioners working with athletes from no-impact, non-weight bearing sports include resistance training programming and nutritional counseling in the training plans of their athletes.

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Table 1:
Bone and body composition characteristics by sport team.

(1) The Effect of Squat Fatigue on Yank-Time Characteristics in Recreationally Trained Males: Comparing High Volume-Low Load to Low Volume-High Load

M. Hermes,1 M. Bubak,2 J. Miller,1 K. Stout,1 J. Nicoll,3 P. Gallagher,1 and A. Fry1

1The University of Kansas;2Oklahoma Medical Research Foundation; and3California State University, Northridge

Yank, a time-derivative of force, represents instantaneous rate of force development (RFD) and may be a viable method to understand kinematic and kinetic events during exercise. How yank is affected by fatigue and varying loads during the barbell back squat is unknown. Purpose: To assess the effect of varying load and fatigue on back squat yank-time characteristics. Methods: Recreationally trained males (n = 11) were divided in 2 groups: low volume-high load (LV) (x̄ ± SD; n = 5, age = 22.2 ± 4.5 years, height = 179.4 ± 7.2 cm, mass = 88.4 ± 9.1 kg, 1RM = 162.8 ± 23.9 kg) or high volume-low load (HV) (x̄ ± SD; n = 6, age = 20.0 ± 1.3 years, height = 175.6 ± 3.8 cm, mass = 75. 6 ± 10.0 kg, 1RM = 134.6 ± 11.4 kg). All subjects completed a back squat exercise session at either LV (6 × 5 at 87.5% 1RM, 3 minutes rest) or HV (6 × 20 at 50% 1RM, 45 seconds rest). If repetitions could not be maintained, load was decreased for subsequent sets to maintain repetitions. The first repetition of set one and the last repetition of set 6 were analyzed. Force-time data was collected with a one-dimensional force plate. Position data was collected with a linear position transducer. Yank-time data was derived from force-time data using a low pass Hamming filter with a cutoff frequency of 10 Hz. Six yank events were defined as follows: 1 = squat initiation, 2 = first yank curve trough, 3 = lowest force, 4 = peak yank, 5 = peak force, and 6 = end of repetition. Time duration between events was assessed. A multifactorial repeated measures ANOVA was used to assess intra- and inter-repetition differences in yank phase (YP) duration, peak yank (PY), peak force (PF), squat depth, and repetition time (RT) (p < 0.05). Results: A significant 2-way interaction was found for YP 5–6 duration (p = 0.048, ηp2 = 0.64). Follow up tests indicated that YP 5–6 duration increased with fatigue (p = 0.01, g = 0.925) and that YP 5–6 was longer in LV for first (p < 0.000, ηp2 = 0.953) and last (p = 0.002, ηp2 = 0.827) repetition. A main effect for time was found for PY (p = 0.01, ηp2 = 0.536) showing decreased PY magnitude with fatigue. Though RT was not different across time (p = 0.64), a large effect size was found (ηp2 = 0.331), indicating RT increased with fatigue. Conclusion: Some aspects of yank appear to be fatigue sensitive during the back squat, as training at or near failure saw PY reductions and increased YP 5–6 duration. Although the remainder of the yank phase durations were not different from first repetition to last, this may be influenced by reduced load during the protocol. Further, load and volume did not appear to influence yank, as group differences were not found for other YP durations. Practical Applications: Maintaining RFD magnitude and the temporal location of PY may be desirable when considering training adaptations. Training at or near failure with high and low loads appear to influence PY and lengthen certain YP durations. If maintaining PY is desired, coaches should consider whether to train to failure.

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Table 1:
First and last repetition values for YP durations, squat depth, peak yank, peak force, and repetition time for the LV and HV groups.

(03) The Effect of Acute Fatigue on Countermovement Jump Performance in American Collegiate Football Athletes

M. Lewis,1 and D. Jaskowak2

1Virginia Tech; and2Florida International University

A countermovement jump (CMJ) is routinely used in applied sport settings to assess neuromuscular fatigue. However, there is less clarity regarding which CMJ variables may be most sensitive to fatigue. Purpose: The purpose of this investigation was to investigate the effect of acute fatigue from a football-specific training session on CMJ performance in American collegiate football athletes. Methods: Five collegiate American football athletes participated in this study with testing periods at baseline, 0 hours (immediately post-training), and 24 hours. The fatigue-inducing protocol was a strength training session followed by a football-specific conditioning session (training load was recorded). CMJ performance variables were categorized as either jump output or strategy. Results: At 0 hours, subjects displayed moderate reductions in most jump output variables including jump height, peak velocity, and mean power, while displaying moderate to very large changes in jump strategy variables. At 24 hours, jump output variables were returning towards baseline with small changes, while jump strategy variables remained significantly altered with moderate and very large effects (see Table 1). Conclusions: It was found that fatigue as result of a football-specific training session effected countermovement jump variables considerably with effect sizes ranging from moderate to very large. While both CMJ output and strategy variables were effected by fatigue from the football-specific session, it appeared that strategy variables were altered to a greater degree with larger effect sizes. Moreover, CMJ strategy variables remained significantly altered after 24 hours, while CMJ output variables demonstrated only small reductions. Practical Applications: When monitoring neuromuscular fatigue in American collegiate football athletes, CMJ strategy variables such as flight time-to-contraction time ratio and eccentric duration may be more sensitive to fatigue and provide practitioners with more insight into the time course of recovery.

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Table 1:
Group mean and standard deviation, effect size, and interpretation for baseline, 0 hours, and 24 hours post-training.

(04) The Kettlebell Clean Is a Whole-Body Exercise that Elicits Similar Relative Contributions From Lower Body, Upper Body, and Core Muscles

B. Wax,1 B. Lyons,2 J. Mayo,3 W. Tucker,3 and R. Hendrix4

1Mississippi State University;2University of Mississippi;3University of Central Arkansas; and4College of the Ozarks

The use of Kettlebells (KB) is common in training facilities throughout America; however, there is not much empirical research regarding the muscle activation patterns of individual KB exercises in naive kettlebell users. Purpose: This study investigated the muscle activation of 8 different muscles during a one-arm KB Clean exercise in lifters who had minimal experience with KBs. Methods: Fourteen resistance-trained male subjects (mean ± SD age = 21.5 ± 2.03 years, height = 180.87 ± 3.76 cm, mass = 85.53 ± 8.11 kg, and body fat = 12.86 ± 3.32%) completed the clean using a self-selected 8–10 RM load. Trial sessions consisted of subjects performing 5 repetitions of the KB clean. Mean electromyography (EMG) was used to assess the muscle activation patterns of the biceps brachii (BB), anterior deltoid (AD), posterior deltoid (PD), erector spinae (ES), vastus lateralis (VL), biceps femoris (BF), contralateral external oblique (EO), and gluteus maximus (GM) during the combined concentric and eccentric phases of each repetition using surface electrodes. The raw EMG data were rectified, smoothed, and normalized as a percentage of a maximal voluntary contraction obtained through manual muscle testing. The independent variable was the average muscle activation of the 8 muscles (BB, AD, PD, ES, EO, VL, BF, and GM), allowing relative contributions of the muscles to be compared. The mean activation levels of the 8 muscles were analyzed using a one-way analysis of variance (p ≤ 0.05). Results: The results revealed no significant differences between the individual muscle contributions during the KB Clean (F7,91 = 1.995; p = 0.064). Conclusions: Our data establish that the KB Clean is indeed a whole-body exercise where the BB, AD, PD, ES, VL, BF, EO, and GM make similar relative contributions to the effort. Practical Applications: The KB Clean may be an appropriate and time-efficient exercise for individuals who desire to activate multiple muscles in a balanced manner.

(5) Reliability and Validity of a Wireless Inertia Sensor During Unloaded Countermovement Jumps

C. Odaffer, C. Fields, R. Robinson, N. Eckert, and T. Cayot

University of Indianapolis

Technology use in sport to measure athletes' physical status has grown immensely. Wireless inertia sensors (WIS) may be useful in measuring athletes' physical status because of the freedom of movement, transportability and relative cost. Similar technologies already exist but can be limited to certain movements by the wire connection (i.e., linear position transducers). Because both wired and wireless technologies provide immediate feedback of movement velocity and power during performance, a wireless device may be seen as more useful in a training environment. However, to our knowledge the reliability and concurrent validity of a WIS has yet to be determined during unloaded countermovement jumps (CMJ). Purpose: The study aims were to assess the reliability and concurrent validity of a WIS for determining average velocity (AV), peak velocity (PV), average power (AP), and peak power (PP) during unloaded CMJ. Methods: 22 participants (age = 23 ± 2 years, height = 1.75 ± 0.08 m, weight = 77.3 ± 12.6 kg) completed 2 sessions on separate days. Each session participants performed 3 trials of a single CMJ (SINGLE) followed by one trial of 10 continuous CMJ (10JUMP). The WIS was secured on the center of the lumbar region during testing. During all CMJ trials, AV, PV, AP, and PP were measured simultaneously by the WIS and a force plate. The WIS inter-session reliability was assessed using intraclass correlation coefficients (ICC). Concurrent validity was tested against a force plate using the Pearson's correlation coefficient (r) and typical error estimate (TEE). Results: High to very high inter-session reliability were found for AV (ICCSINGLE = 0.92, ICC10JUMP = 0.92), PV (ICCSINGLE = 0.96, ICC10JUMP = 0.97), AP (ICCSINGLE = 0.97, ICC10JUMP = 0.92), and PP (ICCSINGLE = 0.89, ICC10JUMP = 0.94). Strong correlations were observed between the WIS and force plate for AV (rSINGLE = 0.82, r10JUMP = 0.93), PV (rSINGLE = 0.92, r10JUMP = 0.93), AP (rSINGLE = 0.87, r10JUMP = 0.94), and PP (rSINGLE = 0.89, r10JUMP = 0.94). The TEE was calculated for AV (TEESINGLE = 0.09 m·s−1, TEE10JUMP = 0.07 m·s−1), PV (TEESINGLE = 0.12 m·s−1, TEE10JUMP = 0.12 m·s−1), AP (TEESINGLE = 245 W, TEE10JUMP = 174 W), and PP (TEESINGLE = 456 W, TEE10JUMP = 323 W). Conclusion: Based upon the present findings, the WIS is a reliable and valid method in collecting velocity and power measurements during unloaded CMJ. Practical Applications: Strength and conditioning practitioners should consider utilizing WIS bearing in mind their ease of use, versatility and affordability along with their validity and reliability for collecting velocity and power during a CMJ.

(6) Comparison of Vertical Jump Performance Between Playing Positions in Collegiate Female Volleyball

M. Rush, J. Rush, A. Wright, M. Stegemoeller, and P. Donahue

University of Southern Mississippi

The vertical jump is a contributing factor to having success in the sport of volleyball. Each position within the roster has its own unique demands, thus having an understanding of how vertical jump performance can vary based on playing position can help in both the selection of playing position as well as guide training programs. Purpose: Therefore, the purpose of this investigation was to compare countermovement (CMJ) and squat jump (SJ) performance between the 2 positional groups that rely on jump performance during competition. Methods: Fourteen female Division I collegiate volleyball athletes participated in this investigation (age 19.86 ± 0.86 years, height 180.61 ± 3.99 cm, body 69.93 ± 9.73 kg). Participants completed a general warm up followed by dynamic lower body movements and 5 submaximal CMJ and SJ lasting approximately 10 minutes. All data was collected using a force platform sampling at 1,000 Hz during one preseason testing session. Participants first performed 3 CMJ trials with a PVC dowel (<1.0 kg) placed across the upper back in a high bar squat position. Each participant used a self-selected countermovement depth and foot position to jump to a maximal height. Prior to the initiation of movement, participants were asked to maintain one second of quiet standing to allow for calculation of body mass during post-testing analysis. After a brief rest period (∼2 minutes), 3 SJ trials were performed with the same dowel positioning as the CMJ. Participants were instructed to go to a self-selected semi-squat position and hold that position for 3 seconds prior to attempting to jump to a maximal height without the use of a countermovement. Each SJ trial force—time curve was visually inspected to ensure no countermovement was detected. If a trial displayed a countermovement, it was repeated until 3 successful trials were collected. All trials were separated by 30 seconds of rest. Post testing analysis were performed using a customized spreadsheet, using the impulse—momentum theorem. Jump height, peak net force, peak power and RSIm were calculated for comparison across positional groups. Independent t-tests were used to make statistical comparisons between groups. Results: No significant differences were found between any of the variables of interest in both the CMJ and SJ. Conclusions: As the vertical jump task is a contributing factor to the physical demands of both positions, the lack of differences in the CMJ are predictable. However, in the SJ the outside hitters had increased values in 3 of the 4 variables assessed. The lack of significant difference can be attributed to the small group sizes, which is a limitation of using one team in the analysis. Additionally, removing the arm swing during the CMJ may have limited the findings in this investigation. This is different from the technique both positional groups use during training and competition. Practical Applications: The results of this investigation display that when training collegiate volleyball players, special attention to the individual athletes needs should be addressed rather than the specifics of the playing position.

(7) Effects of Footwear on Countermovement Jump Force-Time Characteristics in Division 1 Collegiate Volleyball Players

K. Barrett, J. Garner, C. Howard-Smith, and J. Mouser

Troy University

Evaluation of jump performance is essential for volleyball players, who jump an estimated 15 to 20 times during each set of a volleyball game. Oftentimes Division 1 volleyball players have the opportunity to choose a high-top or low-top court shoe for use during their season. Because players have multiple options, it is important to determine if these shoes impact the jump force-time characteristics in any way. Purpose: To examine the effects of different types of footwear on countermovement jump characteristics in Division 1 collegiate volleyball players. Methods: Fifteen participants from an NCAA Division 1 volleyball team were recruited for this study; 3 did not complete testing due to unrelated injury or time restraints. All data analysis was completed for the remaining 12 participants (mean ± SD): age: 19.50 ± 1.09 years, height: 178.15 ± 6.60 cm, body mass: 73.93 ± 7.98 kg, BMI: 23.38 ± 2.23 kg·m−2. The lab was visited on 4 separate occasions. Upon arrival, a 5-minute warmup on the cycle ergometer was performed and 3 trials of a countermovement jump test were completed. The Adidas Crazyflight X3 high top (HT), Adidas Crazyflight X3 low top (LT), or Adidas Pureboost Trainer (T) was worn for the duration of each testing visit. Order of shod condition was randomized prior to arrival. GRFz values were recorded using a Bertec force plate for each jump and custom code was written to calculate force-time characteristics. Mixed-model ANOVAs were run using SPSS statistical software. Statistical significance was set a priori at α = 0.05. Results: When sphericity was violated, p-value was adjusted using Greenhouse-Geisser adjustment. There was no significant difference between shod condition in average RFD (HT: 7,958.19 ± 4,314.53 N·s−1, LT: 7,377.09 ± 3,917.21 N·s−1, T: 6,798.75 ± 4,207.34 N·s−1, p = 0.124), eccentric impulse (HT: 71.04 ± 17.22 N·s, LT: 68.79 ± 20.65 N·s, T: 70.49 ± 17.99 N·s, p = 0.667), concentric impulse (HT: 199.51 ± 19.28 N·s, LT: 199.34 ± 18.62 N·s, T: 196.10 ± 18.30 N·s, p = 0.093), eccentric impulse duration (HT: 0.30 ± 0.12 seconds, LT: 0.36 ± 0.10 seconds, T:0.39 ± 0.13 seconds, p = 0.104), concentric impulse duration (HT: 0.26 ± 0.05 seconds, LT:0.26 ± 0.04 seconds, T:0.27 ± 0.05 seconds, p = 0.130), jump height (HT: 0.33 ± 0.04 m, LT: 0.33 ± 0.05 m, T: 0.33 ± 0.4 m, p = 0.427), peak force (HT: 1,114.32 ± 187.43 N, LT: 1,120.23 ± 181.13 N, T: 1,102.30 ± 204.14 N, p = 0.729), peak power (HT:4,006.53 ± 483.74 W, LT: 4,013.48 ± 448.16 W, T: 3,973.29 ± 501.68 W, p = 0.734), eccentric average power (HT: −298.19 ± 65.12 W, LT:-289.26 ± 76.33 W, T: −292.48 ± 61.93 W, p = 0.702), concentric average power (HT: 2058.95 ± 338.15 W, LT: 2049.14 ± 221.29 W, T: 1981.71 ± 275.75 W, p = 0.256), take-off force as a percentage of body weight (%BW) (HT: 253.94 ± 24.25 %BW, LT: 254.85 ± 23.84 %BW, T: 251.98 ± 23.60 %BW, p = 0.676), landing force as a percentage of body weight (HT: 357.14 ± 49.97 %BW, LT: 383.57 ± 68.50 %BW, T: 366.70 ± 59.77 %BW, p = 0.095) or impact (HT: −5,950.00 ± 2,896.43 N·s, LT: −6,799.31 ± 3,673.18 N·s, T: −6,174.99 ± 3,026.36 N·s, p = 0.201). Conclusions: We found no statistically significant difference between shod condition in any of the force-time characteristics of the countermovement jumps. Practical Applications: Of the shoes tested, players can safely choose the shoe they find most comfortable without worrying about differences in jump performance or impact attenuation. Future research should consider comparing shoes across brands to determine if there is one best suited to volleyball players.

(8) Accuracy of an Innovative Smartphone Application for Assessment of Basketball Free Throw Shooting Mechanics

D. Cabarkapa, A. Fry, and G. Jones

The University of Kansas

It has been found that mechanical parameters assessed during both preparatory and release phases of the free throw shooting motion have a major impact on the success of the shooting outcome. While video analysis has been widely used for in-depth assessment of these measurements, it lacks ability to provide players with instantaneous feedback regarding their shooting performance. Purpose: The purpose of this study was to examine the accuracy of an innovative smartphone application for the assessment of mechanical parameters during the free throw shooting motion when compared to video analysis as a criterion measurement. Methods: A former Division-I collegiate basketball player (age = 28 years; hgt = 208 cm, wgt = 113 kg) performed 10 sets of 10 free throw shots (n = 100). A high-definition camera (Canon PowerShot SX530) and a smartphone (iPhone 11) with an innovative shot tracking application (HomeCourt, 3.20.5) were used to capture the free throw shooting motion from a sagittal point of view. Both devices recorded data simultaneously at 30 fps. Video analysis software (Kinovea, 0.8.27) was used to derive the following kinematic variables and compare them with the identical variables acquired from the smartphone application: release angle (RA; relative angle between upper arm and a line parallel to the ground at the time point of the ball release), knee angle at preparatory phase (KAPP; internal angle between thigh and shank assessed with anatomical landmarks at the initial concentric phase of the shooting motion), and knee angle at liftoff phase (KALP; internal angle between thigh and shank assessed with surface landmarks at the initial liftoff phase of the shooting motion). Independent t-tests, Cohen's D effect sizes (ES), and Intraclass Correlation Coefficients (ICC) were used to examine statistically significant differences, magnitude of differences, and absolute agreements between the measurements. Results: The results are presented in Table 1. The innovative smartphone application accurately classified all made and missed free throw attempts, 93 and 7, respectively. Statistically significant differences between the 2 methods of assessments were identified for RA and KAPP kinematic variables. Although the magnitude of difference in RA was minimal, the discrepancy in the KAPP variable was considerably larger. However, no significant difference was observed for the KALP variable. Conclusions: Although the large dissimilarities in the KAPP may be mainly attributed to the selection of anatomical landmarks for assessment methodology, we can conclude that the innovative user-friendly smartphone application demonstrated as a consistent and acceptable method for evaluation of free throw shooting mechanics. Practical Applications: The ability to provide instantaneous feedback regarding which corrections in shooting movement mechanics need to be addressed may be of critical importance for optimal free throw shooting accuracy and long-term athlete development.

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Table 1:
Comparison of the kinematic variables between an innovative smartphone shot tracking application and video analysis software (x̄ + SD).

(9) Changes in Sprint Kinematic Asymmetries in Division I Track and Field Athletes During Off-Season Training

M. Gonzalez, S. Montalvo, M. Dietze-Hermosa, N. Cubillos, and S. Dorgo

University of Texas at El Paso

Inter-limb asymmetries have been defined as the difference in performance between limbs. Current inter-limb asymmetry literature examines how the percent difference in performance between limbs relates to sports performance and risk of injury. However, there is a lack of research examining the longitudinal changes in these inter-limb asymmetries and their relationship to sprint performance. Purpose: To examine the changes in division I track and field athletes sprint kinematic asymmetries during an off-season. Methods: This study recruited 13 Division I track and field sprinters who completed 2 sets of 30-meter fly sprints at 2 different time points (pre; post) 4 months apart during their off-season. The fly sprint protocol consisted of accelerating through a 30-meter untimed zone to achieve maximum sprint velocity prior to entering the 30-meter timing area. Out of 2 attempts, the trial with the fastest completion time was used for analysis. Laser timing gates were used to record sprint completion times and sprint kinematics were recorded using the Optojump photoelectric cells placed in the middle of the 30-meter measuring zone. Recorded sprint kinematic variables included step distance, speed, contact time, flight time, stance time, and contact phase time. Following the data collection, inter-limb asymmetries of the sprint kinematic variables were calculated utilizing the symmetry index equation [(high value-low value)/total × 100]. Data were imported to SPSS for data analysis. As variables were non-normally distributed, the Wilcoxon signed-rank tests were conducted to assess any differences in the inter-limb asymmetries of kinematic variables. Results: When examining the inter-limb asymmetries, there were no significant differences from pre to post for the step length inter-limb asymmetries (z = −0.105; p = 0.917; ES = −0.029), contact time asymmetries (z = −1.712; p = 0.087; ES = −0.475), nor flight time (z = 0.000; p > 0.999 ES = 0.000). Additionally, there were no significant differences in stance phase time inter-limb asymmetries (z = −0.105; p = 0.917; ES = −0.029) nor for the contact phase time inter-limb asymmetries (z = −1.433; p = 0.152; ES = −0.397). Wilcoxon signed-rank tests determined that while on average there was a decrease in speed and step distance, these were not statistically significant (z = −0.943; p = 0.345; ES = −0.262 & z = −1.223; p-value = 0.221; ES = −0.262, respectively). There was a statistically significant decrease in stance time (z = −2.761; p = 0.006; ES = −0.766), however this was not clinically relevant since the decrease was of 0.01 seconds. Additionally, there were no other significant changes in any other kinematic measurements (contact time; z = −1.470, p = 0.142; ES = −0.408; flight time z = −0.311, p = 0.756; ES = −0.086, contact phase time z = −1.470; p = 0.142; ES = −0.408) nor in the sprint completion times (z = 0.000, p > 0.999; ES = 0.000). Conclusions: Based on the results of this study, a four-month off-season does not affect division I track and field athletes sprint performance or inter-limb asymmetry percentages. Practical Applications: Coaches may desire to continue implementing traditional off-season training since it appears to be sufficient to mitigate any negative affects to sprint completion time and sprint kinematic inter-limb asymmetries. Additionally, inter-limb asymmetries should be continued to be monitored to determine if any changes occur during their competitive season.

(10) A Comparison of the Sprint Profile Between Collegiate Sprinters and Long-Distance Runners

S. Rodriguez, M. Dietze-Hermosa, S. Montalvo, M. Gonzalez, N. Cubillos, A. Martinez Ruiz, E. Martinez, J. Del Rio, and S. Dorgo

University of Texas at El Paso

The sprint profile is a compilation of measures that describes an individual's sprinting ability. The sprint profile is useful for strength and conditioning practitioners because it gives insight to mechanical measures during sprinting. However, it has yet to be examined whether a difference in sprint profile measures exists between collegiate track athletes who compete at different running distances. Purpose: To compare differences in sprint profile variables among collegiate sprinters (competing up to 400 m events) and long-distance runners (competing in running events above 800 m). Methods: Twenty-seven Division I track and field athletes (sprinters = 13; long distance runners = 14) participated in this study. Subjects completed 2 sprint acceleration trials over a 30-meter timing zone. Subjects were instructed to sprint with maximal efforts through the 30-meter zone. An iPad with the MySprint mobile application was used to calculate the subjects' sprint profile including maximal theoretical horizontal force, maximal theoretical velocity, optimal velocity, maximal theoretical power, maximal speed, maximal ratio of force, force-velocity slope, and decrease in ratio of force. The fastest trial was used for statistical analysis. Independent samples t-tests or Mann-Whitney U tests were used to determine differences between each group (sprinters; long-distance runners) and the effect sizes (ES) were calculated with Cohen's d for parametric and r for non-parametric data. Results: Significant differences were seen whereas sprinters outperformed distance runners for maximal theoretical power (t(25) = 3.906; p = 0.001; Cohen's d = 1.49; large), theoretical maximal horizontal force (t(25) = 3.397; p = 0.002; Cohen's d = 1.19; moderate), maximal speed (t(25) = 3.256; p = 0.003 Cohen's d = 1.26, large), ratio of force (t(25) = 3.200; p = 0.004, Cohen's d = 1.25, large), maximal theoretical velocity, (t(25) = 3.105; p = 0.005; Cohen's d = 1.197; moderate), and optimal velocity (t(25) = 3.105; p = 0.005; 1.196, moderate). Furthermore, sprinters had significantly lower mean ranks for the force-velocity slope (z = −2.71, p = 0.007; ES = 0.41, large) and the decrease in the ratio of force (z = −2.475, p = 0.013; ES = 0.47, large). Conclusions: There are differences in all sprint profile variables between sprinters and long-distance runners with large to moderate effect sizes. Sprinters had a greater mean for maximal theoretical horizontal force, maximal theoretical velocity, maximal theoretical power, ratio of force, optimal velocity, and maximal speed, and lower mean ranks for the force-velocity slope and decrease in the ratio of force. These differences may be due to differences in training adaptations between explosive sprint training and low intensity long-distance running. Practical Applications: The sprint profile may be used to monitor the progress of track and field athletes and distinguish those who have sprint profiles similar to sprinters and/or long-distance runners.

(11) Leukocyte Response to a High-Volume Bout of Back Squats: Influence of Sex

E. Arroyo,1 E. Tagesen,1 J. Laudato,2 B. Gibson,3 M. Lebron,1 and A. Jajtner1

1Kent State University;2Florida State University; and3University of Oregon

Purpose: To compare the leukocyte response to a bout of resistance exercise between resistance trained men and women. Methods: Resistance-trained men (n = 7; 22 ± 3 years; 177.5 ± 6.5 cm; 86.1 ± 20.4 kg; squat 1RM: 155.2 ± 26.3 kg) and women (n = 5; 21 ± 2 years; 162.7 ± 6.1 cm; 58.7.1 ± 6.9 kg; squat 1RM: 73.2 ± 16.9 kg) completed a 1-repetition max (1RM) test of the back squat, a high-volume bout of back squats, and 2 days of follow-up testing. Inclusion criteria required men to squat ≥1.5× their body mass and women to squat ≥1.0× their body mass. Women were tested during the follicular phase of their menstrual cycle (days 2–5). The exercise bout consisted of 8 sets of 10 repetitions of the back squat at 70% 1RM, with 2 minute rest between sets. If participants failed to complete 10 repetitions, spotters assisted with each repetition until the set was complete, and weight was reduced for subsequent sets. Blood was collected before exercise (PRE), immediately (IP), 1 hour (1H), 24 hours (24H), and 48 hours (48) post-exercise. Leukocyte count (WBC), lymphocyte number and ratio (LY# and LY %), monocyte number and ratio (MO# and MO%) and granulocyte number and ratio (GR# and GR%) were analyzed by a hematology analyzer. Changes were assessed using a group × time between-subjects repeated measures ANOVA. Results: A main effect of time was noted for changes in WBC (F = 59.84, p = 0.013, ηp2 = 0.857), with increases in WBC from PRE to IP (p < 0.001) and a return to pre-exercise values at 1H (p = 0.075). Significant interactions were observed for LY% (F = 4.93, p = 0.013, ηp2 = 0.330) and GR% (F = 4.30, p = 0.026, ηp2 = 0.301). LY% increased in men from PRE to IP (p = 0.001) and decreased below pre-exercise ratios at 1H (p < 0.001) before returning to pre-exercise ratios at 24H (p = 0.089). LY% did not change from PRE to IP (p = 0.510) in women but decreased below pre-exercise ratios at 1H (p = 0.004) before returning to pre-exercise ratios at 24H (p = 0.089). No differences in LY% were observed between sex at any timepoint. GR% decreased in men from PRE to IP (p = 0.005), increased relative to PRE at 1H (p < 0.001), remained elevated at 24H (p = 0.050), and returned to pre-exercise ratios at 48H (p = 0.189). GR% did not change in women from PRE to IP (p = 0.463), increased relative to PRE at 1H (p = 0.006) and returned to pre-exercise ratios at 24H (p = 0.943). No differences in GR% were observed between sex at any timepoint. No sex-related differences were observed for WBC, LY#, GR#, MO%, or MO#. Conclusions: While changes in WBC were similar between sexes, men and women exhibited dissimilar LY% and GR% responses to an acute high-volume resistance exercise bout. In men, the immediate rise in WBC after exercise was driven primarily by lymphocyte mobilization, while the rise in women consisted of increases in all leukocyte subsets. Moreover, while GR% returned to pre-exercise ratios at 24H in women, men exhibited elevated GR% until 48H. Practical Applications: Despite testing women during the follicular phase, when estrogen is at its lowest concentration, sex-related differences in the immune response to resistance exercise are evident. The prolonged elevation in GR% exhibited in men may indicate a delayed recovery compared to women, as these cells are mobilized in response to exercise-induced muscle damage. Therefore, coaching staff may consider additional recovery strategies with male athletes compared to female athletes.

(12) Activity Profiling in NCAA Division I Women's Lacrosse

J. Kilian1 and K. Snyman2

1Liberty University; and2Concordia University Chicago

External load is a metric increasing in popularity for team sports, both during practice and competition. Wearable technology has become more accurate and accessible, allowing coaches to measure the load experienced by their athletes in different conditions. Purpose: The purpose of this study was to measure the external load of NCAA Division I female lacrosse players during in-season competition to make comparisons among positions (attack, midfield, and defense) and between halves. Methods: External load was recorded using wearable GPS and accelerometer pods (Catapult Sports, Melbourne, Australia) during the first 5 games of the 2020 regular season (the rest of the season was canceled due to COVID-19) for all athletes competing in at least 50% of both halves (n = 11). External load variables included total distance, sprint distance (>19 km·h−1), number of power plays (>3 m·s−2), top speed, and PlayerLoad. A 2 × 3 mixed model analysis of variance (ANOVA) with repeated measures was used to compare between halves and among positions. Statistical significance was set a priori at p ≤ 0.05. To reduce type I error, Bonferonni corrections were used. Partial eta squared and Cohen's d effect sizes were calculated for practical meaningfulness. Results: Game data averages are presented in Table 1. No significant between-group effect was calculated for any of the variables but a main effect for time was apparent for both sprint distance (p < 0.001, ηp2 = 0.27) and power plays (p < 0.001, ηp2 = 0.468). In the second half, midfielders experienced a significant decrease in sprint distance (p < 0.001, d = 1.34) and power plays (p < 0.001, d = 0.99). Defenders also had a significant decrease in power plays (p = 0.004, d = 1.23). No significant differences were observed between positions for whole game data. A moderate effect was calculated between attack and defense for total distance (d = 0.51). A moderate effect was apparent between midfield and attack (d = 0.56) and midfield and defense (d = 0.73) for sprint distance. Conclusions: There were more similarities than differences in external load metrics during competition across positions and between halves. There was an apparent influence of time for high-intensity efforts (power plays and sprint distance), likely owing to the influence of fatigue. Practical Applications: Coaches can use normative data for external loads to influence strength and conditioning programs to ensure the athletes are adequately prepared for the specific demands of in-game performance. Due to the reduction in high-intensity efforts, in-game load monitoring may be necessary to try to preserve intensity late in the game through methods such as strategic substitutions or time-outs.

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Table 1:
Game data comparison between halves and among positions.

(13) Effects of a Progressive 6 Week High-Intensity Interval Training Intervention on Maximal Oxygen Consumption

A. Coleman,1 J. Mota,2 K. Wohlgemuth,1 L. Arieta,1 H. Giuliani,1 T. Blackburn,1 B. Pietrosimone,1 A. Smith-Ryan,1 D. Couper,1 and E. Ryan1

1University of North Carolina at Chapel Hill; and2University of Alabama

High-intensity interval training (HIIT) is a mode of exercise characterized by short, intermittent bouts of exercise interspersed with recovery periods. This exercise modality may serve as an alternative to traditional steady-state endurance training with lower overall training time requirements. There are various HITT prescriptions for dose, volume, and intensity that require further study. Purpose: The purpose of this study was to investigate the influence of a progressive short-term (6 weeks), bi-weekly, cycle based HIIT program on maximal oxygen consumption. Methods: Thirty-five healthy, previously untrained, young adults (mean ± SD, age = 24 ± 6 years; BMI = 23.39 ± 3.36 kg·m−2; 57% female) were randomized into a HIIT (n = 17) or control (n = 18) Maximal oxygen consumption (V̇o2 max; ml·kg−1·min−1) was obtained prior to and following the 6-week HIIT protocol were all subjects underwent a cycle based, ramped V̇o2 max assessment. Peak power was also obtained from the V̇o2 max assessment, which was used to program the HIIT intervention. Participants in the HIIT group performed 12 training sessions over 6-weeks, each including 9 sets of 1 × 1 minute exercise at 90% peak power, with a 10th set performed until volitional failure. The control group was not prescribed any training protocol and were asked to continue their current physical activity habits. Subsequent training session wattage was increased by 7% if the participant could cycle for ≥75 seconds on the 10th set. To examine the effects of the progressive intervention on the change in peak relative V̇o2 (ml·kg−1·min−1), an analysis of covariance (ANCOVA) was used to examine group (HIIT, control) effects on the outcome variable (change score), while covarying for pre-test values. The alpha level was set at p ≤ 0.05, and 95% confidence intervals (CI), estimated marginal means, and the partial eta squared (η2) effect size statistic are also reported. Results: After adjusting for pre-test values (mean ± SD, 34.5 ± 7.1), there was a significant group effect (F = 22.16; p < 0.001; η2 = 0.409) on the post-pre change score. Specifically, the change in V̇o2max was significantly higher for the HIIT (4.53 ml·kg−1·min−1; 95% CI = 2.93–6.13) compared to the control (−0.64 ml·kg−1·min−1; 95% CI = −2.20 to 0.92) group. Discussion: Our findings suggest that 6 weeks of a progressive 10 − 1 × 1 bi-weekly HIIT may substantially improve maximal aerobic capacity in healthy, previously untrained adults. These data add to the growing body of literature which support the notion of cycle based HIIT for rapid improvements in aerobic capacity. Future studies may wish to explore minimal training intensities and durations needed to improve V̇o2 max. Practical Applications: HIIT was shown improve to aerobic function with relatively low training time requirements, whereas traditional training protocols may require a greater intervention length to achieve similar results (e.g., 12+ weeks). This exercise modality may be an attractive strategy to many populations who report lack of time as a primary barrier to exercise. Furthermore, cycle based HIIT has minimal equipment requirements and may be easily implemented in group settings.

(13) The Effects of an Acute Bout of Foam Rolling on Parameters of Running Economy

L. Biscardi, D. Vukovic, and D. Stroiney

George Mason University

Changes in running mechanics, particularly during ground contact, are associated with changes in running economy and performance. Better running economy is related to shorter ground contact times, lower vertical oscillation, and greater leg stiffness. Studies suggest that foam rolling reduces muscle and tissue stiffness both directly, by influencing mechanical properties, and indirectly, by impacting running mechanics via increases in flexibility and range of motion. However, muscle-tendon stiffness is positively related to force production during running. In addition, foam rolling may relieve unilateral restrictions in connective tissue and muscle, reducing existing running asymmetries. Symmetrical running mechanics benefit running economy and reduce risk of non-contact injury. Purpose: To determine whether foam rolling prior to a treadmill run impacts running economy, vertical oscillation, leg stiffness, ground contact time, ground contact asymmetry, or leg stiffness asymmetry. Methods: Nine trained endurance runners (5 males; 35.0 ± 14.2 years; 169.6 ± 7.9 cm; 68.3 ± 7.2 kg; 19.9 ± 8.6% body fat; 49.9 ± 10.1 V̇o2max) volunteered. Anthropometric measures and maximal oxygen uptake were assessed in session one. To assess physiological and biomechanical variables, participants completed a 4-minute treadmill run at self-selected 5-kilometer pace. Variables for analysis were collected in the fourth minute of the run. In session one, participants had a controlled rest period prior to the run. In session 2, foam rolling was applied bilaterally to the hamstrings, calves, gluteal, and quadriceps muscles for 90 seconds prior to the run. Running economy was calculated as ml·kg−1·km−1 to allow for comparison between self-selected speeds. The validated Runmatic app v8.0.2 was used with iOS 13.2.3 to record biomechanical parameters during the treadmill run in both sessions. Mean scores were used for analysis. For leg asymmetry calculations, symmetry angle was calculated for ground contact time and leg stiffness. Values of 0% indicate perfect symmetry while 100% indicates values are opposite. Paired t-tests were used to compare baseline to foam rolling measures for all variables. Alpha was set at 0.05. Results: Average running speed was 13.2 ± 3.8 kph. No significant differences were found between conditions for running economy, leg stiffness, ground contact time, vertical oscillation, ground contact asymmetry or leg stiffness asymmetry (p > 0.05). Conclusions: Following an acute bout of foam rolling, no changes in running economy or biomechanical parameters were observed. Our findings support prior literature that shows no acute improvements, yet no detriments, in performance variables after a single bout of foam rolling. The lack of change in leg asymmetry values may have been due to relatively symmetrical baseline values (stiffness 3.4 ± 3.1%, contact time 1.7 ± 1.6%). Practical Applications: Foam rolling prior to a run does not appear to impact running economy, biomechanical variables, or their symmetry in trained endurance runners. Of particular importance is that foam rolling did not reduce active leg stiffness, contrary to concerns of earlier literature. These findings suggest that foam rolling is a viable warmup tool that can be used prior to a high intensity run without adverse effects to running mechanics or physiological parameters.

(14) Characterizing the Effect of the Menopause Transition on Muscle Size and Muscle Quality

A. Hoyle, L. Gould, H. Cabre, A. Gordon, and A. Smith-Ryan

University of North Carolina at Chapel Hill

As women advance through the menopause transition, there is a progressive loss in bone mineral density, muscle mass, and strength, partially due to the decline in estrogen. This shift in endocrine function may augment age-related risk of sarcopenia and osteoporosis. The impact of menopause on muscle size and quality via ultrasound has not previously been explored. Purpose: The purpose of this study was to compare vastus lateralis (VL) muscle size and muscle quality between pre-, peri-, and post-menopausal women. Methods: Seventy-two healthy women (Mean ± Standard Deviation [SD]; Age: 48.2 ± 7.2 years; Height: 163.0 ± 6.3 cm; Weight: 69.2 ± 14.2 cm), stratified by menopause stage (PRE: n = 24; PERI: n = 24; POST: n = 24) underwent panoramic B-mode ultrasound scans of the VL on the dominant leg. Pre-menopausal (PRE) women were ≥35 year old and eumenorrheic for ≥12 months; peri-menopausal women (PERI) were ≥38 year old, experiencing irregular menstrual cycles, and post-menopausal women (POST) were amenorrheic for ≥12 months. Scans were analyzed offline using Image J software to quantify muscle cross-sectional area (mCSA; cm2) and echo intensity (EI; arbitrary units, a.u). Separate one-way ANOVA with Bonferroni post-hoc analyses were used to compare muscle size and quality between groups. Results: There was a significant difference in both mCSA (p = 0.045) and EI (p = 0.024) between menopause stages. Bonferroni post-hoc comparisons revealed that mCSA was significantly lower in POST (mean ± SD = 15.69 ± 3.69 cm2, p = 0.040) when compared to PRE (mean ± SD = 18.69 ± 3.79 cm2, p = 0.040). Similarly, EI was significantly higher in PERI (mean ± SD = 124.81 ± 28.15 a.u., p = 0.043) when compared with PRE (mean ± SD = 107.05 ± 23.10 a.u). Conclusions: The current findings suggest that both muscle size and muscle quality are negatively influenced by the menopause transition. The transition from PRE to PERI may be the most important to account for muscle loss and potential metabolic changes associated with muscle quality. Practical Applications: Lifestyle and dietary interventions may be required to attenuate the average 1.5 cm2 loss in muscle size through peri- and post-menopause. Decrements in muscle quality appear to begin during peri-menopause, warranting intervention during this critical time to prevent further metabolic disruption related to menopause.

(15) Validity of Dual Energy X-Ray Absorptiometry-Derived 4-Compartment Model in a Multi-Ethnic Sample

H. Cabre,1 M. Blue,2 L. Gould,1 K. Hirsch,3 A. Nelson,1 C. Greenwalt,4 G. Brewer,5 and A. Smith-Ryan1

1University of North Carolina at Chapel Hill;2High Point University;3University of Arkansas for Medical Sciences;4Florida State University; and5University of Connecticut

Body composition assessment provides vital information regarding health status and sport performance. A modified four-compartment (4C) model utilizing dual energy x-ray absorptiometry (DXA) for body volume is a valid method for body composition measurement, but the validity of the DXA-derived 4C model in ethnic minority groups has not yet been evaluated. Purpose: To assess the validity of 4C-DXA derived estimates of percent body fat (%BF), fat mass (FM), and fat free mass (FFM) in a multi-ethnic sample of African American (AA), Asian (A), and Hispanic (H) men and women. Methods: Eighty-eight healthy adults (55% female; 26.5 ± 6.7 years; 168.7 ± 9.3 cm; 72.0 ± 14.5 kg) participated in a single body composition assessment visit. An equal number of AA (n = 22), A (n = 22), H (n = 22) and a Caucasian (C) comparator (n = 22) were measured. Participants were asked to arrive euhydrated having fasted for 12-hours and having refrained from vigorous exercise for 24-hours prior to testing. Body composition was measured via 2 methods: a 4C model criterion and a DXA-derived body volume (BV) 4C model. For both models, bioelectrical impedance spectroscopy was used to estimate total body water; a DXA scan was used to measure total bone mineral content. For the 4C model criterion, air displacement plethysmography was used to measure BV. Paired t-tests were used to compare the 2 models within each minority group. Validity statistics including total error (TE) and standard error of the estimate (SEE) were calculated to assess the prediction error of %BF, FM, and FFM between the 2 models for each race and were classified using Heyward and Wagner standards. Results: For C, there were no significant differences between the 4C model and the DXA-derived BV 4C model for %BF (p = 0.513), FM (p = 0.240), or FFM (p = 0.240). For AA, there were significant differences between the 2 models for FM and FFM (p = 0.014), but not for %BF (p = 0.065). For A, there was a significant difference between the 2 models for %BF (p = 0.025), but not for FM or FFM (p = 0.077). For H, there were no significant differences between the 2 models for %BF (p = 0.647), FM (p = 0.713), or FFM (p = 0.713). The measurement of %BF resulted in the greatest prediction error for each race ([C; TE: 1.33%; SEE: 2.55%], [AA; TE: 1.39%; SEE: 2.61%], [H; TE: 1.71%; SEE: 3.31%], [A; TE: 1.52%; SEE: 2.63%]). The measurement of FM produced good prediction error for each race except for A, which had ideal prediction error ([C; TE: 1.04 kg; SEE: 2.04 kg], [AA; TE: 1.19 kg; SEE: 2.68 kg], [H; TE: 1.15 kg; SEE: 2.29 kg], [A; TE: 0.89 kg; SEE: 1.69 kg]). The measurement of FFM produced ideal prediction error for each race ([C; TE: 1.04 kg; SEE: 1.04 kg], [AA; TE: 1.19 kg; SEE: 1.12 kg], [H; TE: 1.15 kg; SEE: 0.96 kg], [A; TE: 0.89 kg; SEE: 0.90 kg]). Conclusions: The DXA-derived BV 4C model may be a valid method for measuring body composition in all races. Compared to the C comparator, there may be significant error in FM and FFM measurements for AA and %BF measurements of A. Practical Applications: The measurement values of FM and FFM in AA may be significantly overestimated by 1 kg, and the measurement values of %BF in A may be significantly overestimated by 1.4%. If the 4C model cannot be used, the DXA-derived BV 4C model may be acceptable.

(16) Associations of Body Composition Measures With Performance Fitness Tests in Air Force Men

G. Leahy,1 T. Crowder,2 and J. Mayhew3

1Kirtland Air Force Base;2United States Military Academy; and3Truman State University

The military continues to evaluate various methods of estimating body composition to assess their effects on readiness for combat operations. In lieu of simulated combat maneuvers, basic military training physical fitness tests (PFT) consists of one-minute sit-ups, one-minute push-ups, and 1.5-mile run. Association of various body composition factors with physical performance capabilities of military personnel has received varying degrees of attention. A need remains to identify simple yet accurate estimations of body composition and assess their relationship to physical performance. Purpose: To evaluate associations of various body composition assessments with physical fitness test (PFT) performance in Air Force personnel. Methods: Air Force men (n = 123, age = 28.4 ± 6.0 years, height = 178.7 ± 7.0 cm, weight = 85.6 ± 12.3 kg) were evaluated using air displacement plethysmography (ADP) for fat mass (FM), fat-free mass (FFM), and percent fat (%fat). Body mass index (BMI) was calculated by the standard weight-to-height ratio. Waist circumferences (WC) was measured at the level of the umbilicus and adjusted for height (WC·Ht−2). PFT was administered per military instructions. Results: FMI/FFMI (r= −0.51), %fat (r = −0.50), BMI (r = −0.49), WC·Ht−2 (r = −0.41), and weight (r −0.32) were significantly and negatively correlated with PFT score, although none accounted for more than 10% of the variance between test items and PFT. Age was significantly correlated with weight (r = 0.30), %fat (r = 0.37), and WC·Ht−2 (r = 0.47), suggesting gains in each component over service time. However, increases in age accounted for no more than 22% of the variance in any body composition alterations. Furthermore, lack of correlation between age and PFT performance (r = −0.02) suggests increasing age had little influence on PFT. Conclusions: The results of this study suggest that body size measurements may influence military PFT scores but are not likely to be major limiting factors. Practical Applications: Simple fitness tests do not appear to be negatively influenced by variations in body composition measurements. Additional research should be done comparing simple PTF test items to more rigorous combat-oriented test items. This could help identify the influence of different body composition factors on performance in a real-world situation.

(17) Ultrasound Analysis of Quadriceps Femoris Muscle Thickness Following Knee Arthroscopy

C. Cleary,1 T. Smiley,2 K. Martin,2 K. Veazey,2 B. Vopat,2 and A. Herda1

1The University of Kansas; and2The University of Kansas Health System

It is vital to assess the time course of architectural changes of lower extremity skeletal muscle following knee arthroscopy. Purpose: The purpose of this investigation was to assess changes of quadriceps femoris skeletal muscle thickness following knee arthroscopy. Methods: Seven males (Mean ± SD: age (y): 18.3 ± 1.3; height (cm): 185.1 ± 6.6; body mass (kg) 83.2 ± 8.7) were observed 2-, 6-, and 12- weeks after knee arthroscopy. Patients received standard of care treatment through twice weekly physical therapy sessions. If necessary, blood flow restriction (BFR) therapy was utilized during resistance training treatment. Panoramic ultrasound images of the vastus lateralis (VL), vastus medialis (VM), and rectus femoris (RF) were collected at 2-, 6-, and 12-weeks of the operative (OP) and non-operative (NO) legs. Images were analyzed for skeletal muscle thickness (MT) in ImageJ. Data were analyzed through 3 (2×3) two-way repeated measures ANOVAs (leg: OP v. NO) X (time: 2-W v. 6-W v. 12-W) for each MT. Level of significance was set at an alpha of 0.05 for all analyses. Results: The two-way ANOVAs resulted in no significant interactions for VL, VM, and RF muscle thickness (p = 0.43, p = 0.49, and p = 0.69; respectively). However, there was a main effect of leg for each muscle and a main effect of time for VL (p = 0.013) and the VM (p = 0.037). The OP leg was smaller than the NO leg at all time points (VL: p = 0.03, mean difference = 0.19 cm; VM: p = 0.05, mean difference = 0.41 cm; RF: p = 0.01, mean difference = 0.36 cm). Follow-up analyses indicated that the VL muscle thickness at 6-W was less than the muscle thickness at 12-W (p = 0.005, mean difference = 0.19). There was no main effect of time for the RF (p = 0.52). Conclusions: As expected following knee arthroscopy, the OP leg had decreased muscle thickness of the VM, VL, and RF compared to the NO leg across the post-surgical period. However, the muscle thickness of the VL increased from the 6-W to 12-W follow-up, indicating that the standard of care treatment involving BFR resistance training may assist in retaining muscle thickness of the quadriceps femoris. Practical Applications: In the 12-week period after knee arthroscopy, skeletal muscle thickness of the quadriceps femoris significantly decreases in the operative leg. Training protocols that include BFR resistance training should be utilized by physical therapists and coaches to attenuate atrophy after surgery.

(18) Cardiovascular Disease Risk Factors Stratified by Aerobic Capacity in Rural Firefighters

E. Langford,1 M. Abel,1 R. Snarr,2 B. Melton,2 and G. Ryan3

1University of Kentucky;2Georgia Southern University; and3Piedmont University

Sudden cardiac death is consistently the leading cause of on-duty fatality among firefighters. While the National Fire Protection Association (NFPA) recommends firefighters maintain an aerobic capacity (V̇o2max) of 42 ml·kg−1·min−1 for occupational readiness, it is less clear whether this threshold is associated with a reduced risk of cardiovascular disease (CVD). Purpose: To examine differences in modifiable CVD risk factors (RF) between firefighters with a V̇o2max above and below the NFPA's recommendation. Methods: Thirty-one structural firefighters completed a submaximal treadmill test to estimate V̇o2max and were subsequently stratified into 2 groups (≥42 ml·kg−1·min−1: FF≥42; <42 ml·kg−1·min−1: FF<42). Questionnaires were used to determine health history, smoking status, medication use, and weekly physical activity. Blood pressure was recorded on 2 occasions and the average was included in analyses. Measures of waist circumference were obtained to determine obesity status. Furthermore, a blood panel was conducted to determine blood glucose concentrations and cholesterol. Subjects were considered inactive if self-reported physical activity was ≤150 min·wk−1 of moderate or ≤75 min·wk−1 of vigorous intensity. Additional RF classifications were made according to the American College of Sports Medicine guidelines and compared between groups using independent samples t-tests and effect sizes (Cohen's d). An alpha level of p < 0.05 was used to determine significance. Odds ratios were used to determine the likelihood of RF occurrence. Results: Table 1 displays the modifiable CVD RF for each group. The group mean ages were 31.7 ± 10.0 and 34.0 ± 7.4 years (d = 0.26, p = 0.48) for FF≥42 and FF<42, respectively. Furthermore, 33% of FF≥42 subjects and 25% of FF<42 indicated a positive smoking status. Odds ratios revealed that FF<42 were 2 times more likely to have ≥2 RF than FF≥42. Forty percent of FF≥42 exhibited zero RF, 27% had one RF, and 33% had 2 RF. Among FF<42, 13% had zero RF, 38% had one RF, 31% had 2 RF, and 19% had 3 RF. Moreover, FF≥42 had a significantly smaller waist circumference (16% difference), lower blood glucose concentration (8%), and lower systolic blood pressure (5%). Zero FF≥42 had a systolic blood pressure indicative of hypertension, in contrast to 13% of FF<42. Additionally, HDL concentration was 17% greater among FF≥42, with 13% of the group exhibiting HDL as a negative RF. Conclusions: FF≥42 demonstrated more favorable health outcomes and fewer CVD RF than FF<42. Practical Applications: Achieving the NFPA's aerobic capacity recommendation for occupational readiness appears to confer relevant health benefits. Aerobic endurance exercise should be prescribed as part of a comprehensive fitness and wellness program to enhance firefighter readiness and health outcomes. In addition to improving V̇o2max, emphasis should be placed on smoking cessation. Collectively, a reduction in CVD RF may attenuate the high rate of sudden cardiac death in this population.

T7
Table 1:
Comparison of modifiable cardiovascular disease risk factors between firefighters with an estimated aerobic capacity of ≥42 ml·kg−1·min−1 (FF ≥ 42) and firefighters below (FF < 42).

(19) Tactical Vests Worn by Law Enforcement: Is This Improving Stability for Job Performance?

A. Shim,1 D. Shannon,2 M. Waller,3 R. Townsend,4 and M. Ross1

1College of Saint Mary;2Auburn University;3Arkansas Tech University; and4Bardavon Health Innovations

The purpose of this study was to determine the impact on stability of wearing a kevlar tactical vest vs a bulletproof vest with duty belt. Results has been inconclusive from past investigations. A 3 × 8 factorial design MANOVA was selected. All subjects were LEOs (22 males, 3 females; age, 42.4 ± 3.2 years; wt., 101.65 ± 19.4 kg; ht., 178.92 ± 8.2 cm; body mass index 31.5 ± 4.2 kg−2). A Bertec Posturography Plate (Bertec Inc. Columbus, OH) was used to determine 4 Center of Pressure (CoP) scores consisting of eyes open stable surface (EOSS), eyes closed stable surface (ECSS), eyes open perturbed surface (EOPS), eyes closed on perturbed surface (ECPS), and 4 Limit of Stability (LoS) scores in 4 body planes—frontal plane (LoSF), posterior plane (LoSP), left sagittal plane (LoSL), and right sagittal plane (LoSR). Each subject was assessed with the tactical vest, no vest, and with utility belt. The standard A utility belt group showed significance with ECSS (p = 0.001) and with LoSF (p = 0.006), LoSP (p = 0.029), LoSL (p = 0.005), LoSR (p < 0.001). In conclusion, kevlar tactical vests did not provide additional stability when compared to a non-equipment group, or the bulletproof vest standard utility belt group.

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Table 1:
LoSR for standard utility belt group.

(20) Get Up and Go: Performance Elements of a Simulated Tactical Rush

J. Ross,1 J. Winters,1 S. Royer,1 M. Hoch,1 R. Bergin,1 N. Morelli,1 C. Conley,1 R. Sheppard,2 and N. Heebner1

1University of Kentucky, Sports Medicine Research Institute; and2Marine Forces Special Operations Command

The Rush is primary individual movement technique in modern infantry combat. The Rush consists of rising from a prone fighting position followed by a 3–5 seconds sprint toward the enemy to assume a new fighting position. Tactical Strength and Conditioning (TSAC) coaches and researchers have suggested various training methods, especially speed training, to improve performance of the Rush. Our previous research has identified correlations of performance in a variety of explosive lower body tests as they relate to a simulated Rush, but a deeper analysis may help identify priorities for performance training specific to the Rush movement. Purpose: Determine the level of contribution toward total performance for 2 phases of a rush movement. Methods: One hundred forty-eight male personnel (29.5 ± 4.9 years, 1.8 ± 0.07 m, 87.7 ± 11.2 kg, 9.1 ± 4.2 years of service) assigned to deploy within the following 30 days as part of Marine Forces Special Operations Command (MARSOC) completed a physical preparedness assessment which included a simulated, unloaded Rush, designed as a 30 yd sprint with a split time measured at 10 yds (acceleration phase, AP) and a separate variable (speed phase, SP) defined as the difference in times between 10 and 30 yds. Pearson Product-Moment correlations were performed for all variables. Fisher Z transformation was used to compare correlations. An alpha level of p < 0.05 was used to determine statistical significance. Results: Rush correlation with AP (r = 0.900) was significantly stronger than with SP (r = 0.756, p ≤ 0.01). AP and SP demonstrated a weak correlation with each other (r = 0.394, p ≤ 0.01). Likewise, the coefficient of determination for Rush times was stronger for AP (r2 = 0.810, p ≤ 0.01) than for SP (r2 = 0.571, p ≤ 0.01). Conclusions: Our results suggest that the AP may be a more influential phase to the overall performance of the Rush. 81% of the variance of the Rush was explained by the AP performance alone whereas only 57.1% of the variance of Rush was explained by SP. Explosive lower body power movements are typically associated with both acceleration and top speed in athletes. However, in a short acceleration-dominant task from the prone position a person's ability to come up and accelerate is critical. Furthermore, there is likely a significant contribution of the technique of rising from the prone position that cannot be overlooked in Rush performance. Practical Applications: TSAC professionals should prioritize training acceleration into the rush (especially from the prone) over traditional speed training when the goal is to prepare tactical athletes for a Rush under fire scenario. This training may be a combination of technique-based and ability-based training.

(21) The Effect of Exercise-Induced Fatigue on Occupational Performance in Structural Firefighters

M. Mason,1 J. Abt,2 R. Shapiro,1 N. Heebner,3 H. Bergstrom,1 and M. Abel1

1University of Kentucky;2Children's Health Andrews Institute for Orthopaedics and Sports Medicine; and3University of Kentucky, Sports Medicine Research Institute

High intensity resistance training (HIRT) is commonly performed by structural firefighters to enhance preparedness for occupational demands. Despite the potential for HIRT to induce adaptations over time, it is important to determine if a single on-duty HIRT session is detrimental to subsequent occupational physical ability due to exercise-induced fatigue. Purpose: This study evaluated the acute effect of HIRT on occupational physical ability in structural firefighters and assessed the time course of recovery. Methods: Physical ability of 7 male resistance trained career firefighters (35.8 ± 4 years; 181.6 ± 6 cm; 90.6 ± 8 kg) was evaluated based on timed completion of a maximal effort simulated fireground test (SFGT). The SFGT consisted of standardized tasks in personal protective equipment (PPE) while using a self-contained breathing apparatus (SCBA): Stair climb, hoseline advance, equipment carry, ladder raise, forcible entry, victim search, and rescue. Heart rate (HR), blood lactate (BL), rating of perceived exertion (RPE), thermal sensation (TS), air depletion (AD), and work efficiency (WE; (1/(Air depletion x SFGT completion time)) × 10,000) were assessed before, during, and after the SFGT. The timed HIRT session consisted of a standardized set of exercises and absolute training loads. Firefighters performed the SFGT in 3 randomized conditions, separated by at least 48 hours: baseline (SFGTbaseline), 10 minutes post-HIRT (SFGT10min), and 60 minutes post-HIRT (SFGT60min). Repeated measures ANOVAs were used to identify differences in SFGT completion time, AD, WE, HR, BL, RPE, and TS among conditions. Individual differences in SFGT time were assessed using ICC2,1 and minimal difference (MD) scores calculated from a SFGT familiarization trial and SFGTbaseline. Results: There was no difference in HIRT completion time between SFGT10min and SFGT60min conditions (p = 0.078). SFGT10min completion time was greater than SFGTbaseline (430.4 ± 136.5 vs. 296.9 ± 69.3 s, p = 0.008), with no difference between SFGTbaseline and SFGT60min (296.9 ± 69.3 vs. 326.1 ± 88.79 s, p = 0.080). The MD analysis of SFGT time indicated that all firefighters' SFGT10min times exceeded the MD (±26.4 s), whereas 43% (3 of 7) of firefighters exceeded the MD at SFGT60min. AD during SFGT10min was greater than SFGTbaseline (2786.0 ± 488.0 vs. 2186.0 ± 276.0 lb·in−2, p = 0.020), with no difference between SFGTbaseline and SFGT60min (p = 0.253). WE during SFGT10min was less than SFGTbaseline ((0.59 ± 0.32 vs. 0.99 ± 0.29 ((lb·in−2·min)−1)104, p < 0.001)), with no difference between SFGTbaseline and SFGT60min (p = 0.247). SFGT10min pretest RPE (p < 0.001), pretest TS (p < 0.001), pretest BL (p < 0.001) and post-test TS (p = 0.004) were greater than SFGTbaseline. Conclusions: These findings indicate that an acute bout of HIRT decreases firefighters' occupational performance 10 minutes post-exercise with varied responses at 60 minutes post-exercise. Practical Applications: Performing on-duty exercise is recommended by the National Fire Protection Association and is important to enhance chronic occupational readiness. However, firefighters and tactical strength and conditioning practitioners should be aware of the acute deleterious effects associated with performing HIRT on-duty. Factors that may influence the decision to use HIRT on-duty may include firefighters' fitness level, acclimation to HIRT, the magnitude of HIRT loading parameters, and performing HIRT during low volume call times or just prior to the end of a shift.

(22) Time-Restricted Feeding and Aerobic Performance in Elite Runners: Ramadan Fasting as a Model

L. Judge,1 A. Al-Nawaiseh,2 M. Bataineh,2 D. Bellar,3 and H. Kiliani4

1Ball State University;2Hashemite University;3University of North Carolina at Charlotte; and4Jordan University

A distance runner's performance is often limited by energy availability when training or competing. Modifying the frequency and timing of meals by abstaining from eating or drinking, from dawn to dusk, during Ramadan fasting is hypothesized to induce hypohydration and reduced caloric and nutrient intake. Purpose: The purpose of this study was to investigate the impact of Ramadan fasting on distance runners' performances. Methods: Fifteen highly trained male distance runners who observed Ramadan participated in this study (Age = 23.9 ± 3.1 years; Body mass index = 20.8 ± 1.3; Peak V̇o2 = 71.1 ± 3.4 ml·kg−1·min−1). Each participant reported to the human performance lab on 2 testing occasions (pre-Ramadan and the last week of Ramadan). In each visit, participants performed a graded exercise test on the treadmill (Conconi protocol) and their V̇o2, Heart Rate, time to exhaustion, RPE, and running speed were recorded. Detailed anthropometrics, food records, and exercise logs were kept for the entire period of the study. Repeated measures ANOVA, paired t-test, and Cohn's effect size analysis were carried out. Results: Results indicated no significant influence for Ramadan fasting on body mass (p = 0.201), body fat (p = 0.488), lean body mass (p = 0.525), V̇o2max (p = 0.960), energy availability (p = 0.137), and protein intake (p = 0.124). However, carbohydrate (p = 0.026), lipid (p = 0.009), water (p < 0.001), and caloric intakes (p = 0.002) were significantly reduced during Ramadan Fasting. Daily training duration (p < 0.001) and exercise energy expenditure (p = 0.001) were also reduced during Ramadan. Time to exhaustion (p = 0.049), and maximal running speed (p = 0.048) were improved. Conclusions: Overall, time to exhaustion and maximal running speed of the distance runners was improved during Ramadan fasting, independent of changes in nutrients intake observed during the current study. Practical Applications: A strategy of adjusting training intensity and duration may be considered to help maintain quality training during times of fasting.

(23) Relationship Between Energy Balance and Cardiovascular Disease in African American Division I Athletes

A. Williams,1 T. Purdom,1 M. Cook,1 H. Colleran,1 P. Stewart,2 and L. San Diego1

1North Carolina A&T State University; and2University of North Carolina at Chapel Hill

Collegiate athletes have been shown to have nutritional deficiencies that perpetuate additive physiological stress that when chronic, can create deleterious systematic effects. Additionally, athletes who perform at the highest levels undergo cardiovascular remodeling that in some cases can become pathological. Energy intake should equate to energy needs as well as maintain dietary quality to maintain ideal body composition and fulfill the needs to maintain optimal performance. Therefore, energy balance and micronutrients may be influential to an athlete's performance as well as disrupt hemodynamic function. Micronutrients that play a role in cardiovascular health include poly-unsaturated fatty acids, omega-3 fatty acids, iron, and calcium. Deficiencies in these micronutrients may lead to cardiovascular dysfunction and therefore morbidity in high-performing athletes. Purpose: The purpose of this study was to investigate the relationship between energy balance and nutritional content associated with cardiovascular morbidity in African American Division I Athletes. Methods: Using a cross-sectional study design, 23 pre-season athletes were recruited while 18 athletes met objective criterion to classify into 2 groups for comparative purposes normotensive energy balanced (NTEB) n = 7; hypertensive energy deficient (HTED) n = 11). Athletes self-reported nutritional intake using a non-consecutive 3-day food recall with one weekend day using the Nutrition Data System for Research from the University of Minnesota. After the recall, athletes reported to the lab for a follow-up interview with a registered dietitian having fasted for >4 hours refrained from supplements including caffeine for >8 hours and drank water ad libitum. At this time, blood pressure (BP) was taken twice in the supine position 5 min apart after resting for >5 min. High BP was defined as (>120 Systolic BP/< 80 Diastolic BP). Body composition was measured using multi-frequency bioelectric impedance and daily energy expenditure was estimated using a proprietary algorithm reported from the BIA device. Statistical analysis included Spearman correlation and confidence intervals. Correlation values were defined as (0.20–0.39 = weak; 0.40–0.69 = moderate; 0.70–1.0 = strong, (X ± SD). Results: The relationship between high blood pressure and energy deficiency was defined as moderate (R = 0.56) with 11/23 reporting hypertensive and energy deficient. Of the hypertensive athletes, 78.5% (11/14) were calorically deficient with an average deficiency of −1294.6 ± 1362.9 kilocalories. All micronutrient measures for HTED were lacking when compared with NTEB: poly-unsaturated fatty acid - 35.8%; omega-3 -53.74%; iron −55.8%; and calcium −25.0%. Conclusions: A moderate relationship between hypertension and caloric deficiency during the pre-season was observed while research shows an 80% chance of resting BP increasing further during the competitive season. Furthermore, micronutrients were resoundingly deficient in those with caloric deficiencies and hypertensive. The relationship between caloric deficiencies and cardiovascular disease risk can be prevented with adequate nutritional education for collegiate athletes while having regular access to dietitians. Practical Applications: Athletes' nutrition and hemodynamic status should be monitored regularly throughout seasonal transitions to prevent the onset of cardiovascular disease which has been shown to be the most common risk factor for sudden death.

(24) The Influence of Age on Torque Steadiness in Career Firefighters

E. Soucie,1 M. Laffan,1 A. Trivisonno,2 G. Gerstner,3 J. Mota,4 H. Giuliani,1 and E. Ryan1

1University of North Carolina at Chapel Hill;2United States Performance Center;3Old Dominion University; and4University of Alabama

Firefighters provide critical emergency services to their communities. Although optimal neuromuscular function is crucial to perform many essential firefighter tasks, we are unaware of any previous studies examining force steadiness, a proxy for movement precision, in firefighters. Given the large age range among firefighters assigned to fire suppression duty, future studies are needed to determine if aging influences steadiness in firefighters. Purpose: The purpose of this study was to examine the influence of age on torque steadiness at low and moderate intensities in career firefighters. Methods: Forty-one healthy male career firefighters (age: 32.3 ± 8.2 years, stature: 178.3 ± 7.9 cm, body mass: 92.3 ± 18.7 kg) performed 3 leg extension maximal voluntary contractions (MVCs) to determine isometric peak torque (PT) (284.4 ± 68.6 N·m). The MVC with the highest PT value was used to calculate submaximal loads at low (10% of PT; Steadiness10%) and moderate (50% of PT; Steadiness50%) intensities. Participants then performed 30-second isometric contractions at each intensity in a randomized order with 2 minutes of rest between attempts. Subjects were instructed to trace a line projected on a computer monitor in real time at each %PT “as steadily as possible” during the torque-matching task. Steadiness values at 10% (1.3 ± 0.4%) and 50% (1.8 ± 0.7%) of PT were calculated from the middle 10 seconds epoch and were expressed as the coefficient of variation (CV) where CV = standard deviation/mean x 100%. Pearson product-moment correlation coefficients (r) were used to determine the association between age and steadiness at each intensity. An alpha level of 0.05 was set to determine statistical significance. Results: There was no association between age and Steadiness10% (p = 0.844), however, increasing age was associated with poorer Steadiness50% (r = −0.415, p ˂ 0.01). Conclusions: These results suggest that increasing age influences steadiness during moderate intensity tasks, but not low-intensity tasks in a group of firefighters that represent an age range (20–50 years) similar to the majority of front-line firefighters. Practical Applications: Although strength and power are key predictors of occupational performance (e.g., stair climb), steadiness may become increasingly more important in firefighters while rapidly negotiating the fireground and/or stairs with a heavy load. Further, previous studies have demonstrated steadiness can be improved with well-designed training programs, which becomes increasingly important in older firefighters.

(V101) A Comparison of Metabolic Power and Energy Cost by GPS With the “Colli Method” of Profiling and Recalculation by EMG Detected

G. Grassadonia

Catholic University of Murcia, Spain

Purpose: The aim of this study was to investigate in linear sprints the metabolic power and energy cost recalculated by GPS (see Minetti A.E. et al. 20021, di Prampero P.E. et al. 20052, Osgnach C. et al. 20103, Savoia C. et al. 20204) and EMG (Colli R. unpublished), in order to study the possible differences. Methods: The data were acquired in 16 elite U17 football players (mass 64.63 kg ± 4.35, height 177.44 cm ± 4.34) with GPS-IMU Spinitalia v2 and EMG Myontec M-Body 2 resampled at 100 Hz. Prior to the sprint analysis, an individual linear profile between the metabolic power of the GPS and the muscle load value of the EMG expressed in µV (with relative slope and intercept) was constructed for each athlete, for recalculate the metabolic power from the EMG, multiplying the latter by the slope and summing the intercept. The profile included the signal in bipodal static, 4 incremental running gaits (constant running over 50 m) and the sprint where only the runs launched were taken for the construction of the individual profile. Results: The detected metabolic power was respectively for W_GPS and W_EMG between 0 and 5 m (54.58 ± 10.80; 46.07 ± 10.15; d = 0.58; p = 0.03), W_GPS and W_EMG between 5 and 10 m (62.77 ± 11.23; 53.81 ± 8.70; d = 0.29; p = 0.02), W_GPS and W_EMG between 10 and 15 m (58.61 ± 11.57; 54.70 ± 9.70; d = 2.30; p = 0.31), W_GPS and W_EMG between 15 and 20 m (56.88 ± 11.83; 54.78 ± 8.91; d = 1.04; p = 0.58), W_GPS and W_EMG between 20 and 25 m (52.73 ± 11.53; 55.89 ± 8.94; d = 1.87; p = 0.39), W_GPS and W_EMG between 25 and 30 m (44.67 ± 8.31; 56.07 ± 7.70; d = 2.75; p = 0.00), W_GPS and W_EMG between 30 and 35 m (44.25 ± 6.97; 54.51 ± 10.04; d = 1.51; p = 0.00), W_GPS and W_EMG between 35 and 40 m (44.08 ± 9.17; 52.79 ± 8.56; d = 1.31; p = 0.01), W_GPS and W_EMG between 40 and 45 m (44.53 ± 9.17; 49.58 ± 9.46; d = 0.28; p = 0.14), W_GPS and W_EMG between 45 and 50 m (41.35 ± 11.20; 39.02 ± 9.54; d = 0.48; p = 0.53). The detected energy cost was respectively for C_GPS and C_EMG between 0 and 5 m (17.76 ± 2.85; 16.57 ± 3.46; d = 0.38; p = 0.30), C_GPS and C_EMG between 5 and 10 m (10.54 ± 1.45; 8.64 ± 1.42; d = 6.36; p = 0.00), C_GPS and C_EMG between 10 and 15 m (8.59 ± 1.45; 7.69 ± 1.43; d = 1.98; p = 0.09), C_GPS and C_EMG between 15 and 20 m (7.67 ± 1.33; 7.17 ± 1.16; d = 1.14; p = 0.27), C_GPS and C_EMG between 20 and 25 m (6.72 ± 1.33; 6.95 ± 1.03; d = 0.60; p = 0.58), C_GPS and C_EMG between 25 and 30 m (5.73 ± 0.85; 6.89 ± 0.86; d = 0.20; p = 0.00), C_GPS and C_EMG between 30 and 35 m (5.78 ± 1.00; 6.87 ± 1.29; d = 0.99; p = 0.01), C_GPS and C_EMG between 35 and 40 m (5.76 ± 1.19; 6.64 ± 1.12; d = 0.75; p = 0.04), C_GPS and C_EMG between 40 and 45 m (6.02 ± 1.16; 6.41 ± 0.92; d = 0.62; p = 0.30), C_GPS and C_EMG between 45 and 50 m (5.94 ± 1.28; 5.35 ± 0.77; d = 0.64; p = 0.12). Conclusions: The behaviour of metabolic power and energy cost derived from EMG compared to GPS can be more accurate for the study of actual neuromuscular and metabolic engagement. Practical Applications: This new method can be a valuable aid in the optimization of the mechanical-energetic demands, also could be further an important area of study to be investigated in the near future (Montini M. et al. 20,175), to decipher more correctly the characteristics neuromuscular, metabolic and cognitive commitment (e.g.,: exercises in the presence of the ball).

(V102) The Effects of Postural-Based Chiropractic Care on Pelvic Kinematics and Spatiotemporal Parameters of the Gait Cycle

F. Spaniol, A. Osuna, R. Bonnette, and T. Ajisafe

Texas A&M University-Corpus Christi

Gait abnormalities are common in today's society and they can present a problem to the aging population around the world. Chiropractic care can be effective in reducing pain, improving balance, and has the potential to induce neuroplastic and neurometabolic changes in the brain. Very little research exists studying the effects of chiropractic care in gait parameters. Purpose: The purpose of this study was to investigate the effect of postural-based chiropractic care on pelvic kinematics and spatiotemporal parameters of the gait cycle as measured by a single Inertial Measurement Unit (IMU) at the level of the first sacral segment. Methods: Gait analysis data from 20 consecutive patients (10 males, 10 females) who sought chiropractic care at a private clinic was utilized for this study (age = 51.6 ± 15.47, height = 166.34 ± 11.63 cm, and body mass = 75.97 ± 16.46 kg). A single IMU was used to obtain gait analysis and pelvic kinematics data. Results: A single IMU placed at the level of S1 was able to detect certain changes in spatiotemporal parameters of the gait cycle and pelvic kinematics. A significant difference between groups was observed in right pelvic rotation during the stance phase (t = −1.87, p = 0.04). No significant differences were observed in any of the other pelvic kinematics parameters or the spatiotemporal parameters. Significant differences in Cohen's d were observed on right pelvic rotation during the stance phase with a medium effect (d = 0.44), right pelvic obliquity during the swing phase with a small effect (d = 0.22) and left pelvic rotation during the stance phase with a small effect (d = −0.25). No other significant effect sizes were observed in the rest of the variables tested. Conclusions: Gait analysis evaluation can be a valuable component in order to assess patient functionality in an objective way. IMU's are a quick, valid and reliable tool to monitor certain parameters of the gait cycle and pelvic kinematics that can be used both in the clinical setting and the sports field. The pre-experimental nature of this study does not allow for conclusions regarding improvements or lack thereof in the parameters investigated, therefore further research in a more controlled environment is needed in order to elucidate the relationship between postural-based chiropractic care and improvements in gait cycle parameters and pelvic kinematics. Practical Applications: The increase in the utilization of chiropractic services by athletes of all levels calls for more objective evaluations to take place in order to effectively deliver interventions that satisfy the needs of each individual patient. It is suggested that strength and conditioning experts, athletic trainers, and coaches be well versed in the subject of gait analysis.

(V103) Relationship Between Kinetics of Countermovement Jump and Trunk Mechanics of Collegiate Baseball Pitching

M. Sakurai,1 M. Qiao,1 D. Szymanski,1 and R. Crotin2

1Louisiana Tech University; and2ArmCare.com

Purpose: To identify how countermovement jump (CMJ) kinetics influence kinematics and kinetics of the baseball pitching motion with a focus on lower body and proximal movement. Methods: Nineteen Division I collegiate pitchers (age = 19.9 ± 1.5 years; height = 1.86 ± 0.06 m; body mass = 90.7 ± 13.8 kg) performed 3 double-leg CMJs for jump test and threw 5 strike fastballs from the stretch with a slide step on a custom-made pitching mound built for a laboratory setting. A 3D motion capture system (12 cameras, model Miqus M3, Qualisys, Göteborg, Sweden) tracked whole-body kinematics at 240 Hz from 29 reflective markers. Two force plates (600 × 900 mm, model 6090-15, Bertec Corp, Columbus, OH) recorded ground reaction forces (GRFs) from each leg at 1040 Hz during both jump test and pitching captures. A one-way ANOVA was conducted to identify differences in pitching mechanics and jump kinetic variables between 2 groups that included concentric impulse (CI), eccentric rate of force development (E-RFD), peak power (PP), and modified reactive strength index (RSImod) that were split based on throwing velocity (high velocity vs. low velocity). The strength of association between the variables were identified using eta squared effect size with 95% confidence intervals. The same statistical calculations were repeated to identify differences in pitching mechanics and jump kinetic variables between 2 groups, split based on pitchers' total linear momentum in anterior-posterior direction (high momentum group vs. low momentum group). The medians for throwing velocity and total linear momentum of participants were identified to divide them into 2 groups in each analysis. Results: High throwing velocity group showed significantly moderately higher absolute PP (p < 0.01) than low throwing velocity group for CMJ (Table 1). The high momentum group showed significantly weakly higher CI (p < 0.05) than low momentum group. All of pitching mechanics variables except for the momentum profiles did not show significant differences in both ANOVA tests. Conclusions: Key findings suggest that CMJ data may be able to explain a small percentage of variability in pitching performance as pitchers who threw higher velocity fastballs and achieved greater total linear momentum showed a tendency toward greater force output profiles in the CMJ assessment. The findings also highlight the importance of lower body power for pitching performance because the CMJ is a task that mainly relies on lower body function and explosive coordination. Practical Applications: Strength and conditioning coaches should prescribe plyometric activity to improve a pitchers' ability to produce lower body power and CI to encourage better pitching performance in terms of throwing velocity and linear momentum profiles in the pitching cycle.

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Table 1:
Pitching mechanics and jump variables across throwing velocity (Fast vs. Slow).

(V104) Comparison of Vertical Jump Performance in Starters and Reserves of a Collegiate Volleyball Team

J. Rush, M. Rush, M. Stegemoeller, A. Wright, and P. Donahue

University of Southern Mississippi

The vertical jump task is a major component of the sport of volleyball. As performance of this task is important for many of the technical and tactical demands, an athlete's ability to jump may contribute to their standing within the team. Purpose: Thus, this investigation sought to compare vertical jump performance using the countermovement (CMJ) and squat jump (SJ) between starting and reserve players on a collegiate volleyball roster. Methods: Fourteen female Division I collegiate volleyball players participated in this investigation (age 19.79 ± 0.98 years, height 178.62 ± 5.84 cm, body mass 68.94 ± 10.47 kg). Participants completed a general warm up followed by dynamic lower body movements and 5 submaximal CMJ and SJ lasting approximately 10 minutes. Testing was performed on one day during the first week of preseason training. Both CMJ and SJ testing was conducted using a force platform sampling at 1000 Hz. 3 CMJ trials were performed with a PVC dowel (<1.0 kg) placed across the upper back in a high bar squat position. Participants were instructed to maintain contact with the dowel throughout the trial and jump as high possible using a self-selected countermovement depth and foot position. One second of quiet standing was collected prior to trial initiation to establish body mass for post testing analysis. 3 SJ were then performed where participants were instructed to go to a self-selected semi squat position and hold the position for 3 seconds before jumping as high as possible. Again, the dowel was placed across the upper back with similar instructions to the CMJ. Each SJ force –time curve was visually inspected for a countermovement prior to the propulsive phase. If a countermovement was detected the trial was repeated. 30 seconds of rest were given between each trial and 2 minutes between jumping strategies. Post testing analysis were performed using a customized spreadsheet. Jump height, peak net force, peak power and RSIm from both the CMJ and SJ were compared between the starters and reserves. Statistical comparisons were made using an independent t-test for each variable of interest. Results: CMJ jump height was significantly different between groups (p = 0.047). All other variables displayed no significant differences between starters and reserves. Conclusions: Though a significant difference existed between groups with respect to the CMJ jump height, the lack of significant findings between all other variables demonstrates that other variables outside of vertical jump performance are critical for determining the standing on a team. The results of this investigation are limited to Division I collegiate volleyball athletes as vertical jump performance may influence standing on a team at other levels. Practical Applications: The use of the vertical jump as a means to assess volleyball athlete physical capacities meets the need of testing specificity, but as a means of determining an individual player's standing within a team is limited at higher levels of competition.

(V105) Relationships Between Workload Metrics and Neuromuscular Performance in NCAA Women Athletes: Differences in Absolute Measures and Relative Changes

B. Guthrie, F. Brown, G. Cammarano, and M. Jones

George Mason University

Workload efficiency (WLeff), the ratio between external (EL) and internal (IL) load, represents an index of physiological strain. Neuromuscular performance (NMP) decrements can indicate fatigue, and are associated with decreased WLeff. Research investigating relationships between workload (WL), WLeff, and NMP is limited. Further, the time-varying nature of the exposure to WL and NMP outcomes should be considered when evaluating relationships. Purpose: The purpose was to examine relationships between WL, WLeff, and NMP when measuring absolute outcomes in comparison to relative change. Methods: Nine National Collegiate Athletic Association Division I women's basketball athletes participated over a 5-week preseason period (Table 1). Wearable accelerometers with heart rate monitors (Polar Team Pro, Polar Electro) were used to collect EL metrics of total distance (TD) and high-speed running distance >19 km·h−1 (HSR), and the IL metric of training impulse (TRIMP). WLeff metrics were calculated using ratios between TD and TRIMP (TD:TRIMP) and between HSR and TRIMP (HSR:TRIMP). NMP was assessed via squat jump (SJ) and countermovement jump (CMJ) with a contact jump mat (JustJump, Probotics Inc). Following a standardized, supervised dynamic warmup, SJ tests began from a static start as the athlete hovered over a standardized box that elicited ∼90° of knee flexion. Athletes were instructed to jump straight up while avoiding a countermovement. CMJ tests began from a standing position followed by a rapid descent to the height of the standardized box. For all trials, athletes were instructed to give maximal effort and jump fast and high while keeping hands on hips. At least 3 (extra if > 1 inch difference) and up to 5 trials were performed with peak values used for analysis. Descriptive statistics (Mean ± SD) were reported as weekly averages for all variables. Pearson correlation coefficients were reported for variables at a significance of p < 0.05. (Table 1). Variables were evaluated as absolute outcomes and Z-transformed data. Results: Positive relationships were found for CMJ and TD (r = 0.32, p < 0.05), HSR (r = 0.59, p < 0.05), TD:TRIMP (r = 0.37, p < 0.05), and HSR:TRIMP (r = 0.60, p < 0.01). Positive relationships were observed between SJ and TD (r = 0.32, p < 0.05), HSR (r = 0.57, p < 0.01), TD:TRIMP (r = 0.33, p < 0.05), and HSR:TRIMP (r = 0.57, p < 0.01). There were no relationships between any Z-transformed variables. Conclusions: Greater CMJ and SJ are associated with higher metrics of WL (TD, HSR) and WLeff (TD:TRIMP, HSR:TRIMP), with the strongest relationships observed between HSR and HSR:TRIMP. These relationships are not present when assessing time-varying exposure and outcomes. Practical Applications: NMP exhibits stronger associations with distances at higher intensity than total distances. WLeff may be useful to monitor athlete workload. Jump height as a lone measure of NMP may not be a sensitive indicator of fatigue in relation to the time-varying exposure to WL.

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Table 1:
Descriptive statistics with correlation coefficients.

(V106) Utility of Measuring Force Plate Assessed Neuromuscular Performance before and after 10 Weeks of Marine Officer Candidate School Training

M. Bird, M. Lovalekar, B. Martin, K. Koltun, Q. Mi, and B. Nindl

University of Pittsburgh Neuromuscular Research Laboratory

There has been a renewed interest in assessing tactical mobility via force plate technology in the US military. The advantages are that testing can be field expedient and portable. Force plates can reflect influences of multiple physiological status domains within an individual, such as overreaching, detraining, injury risk potential and physical performance enhancements. Purpose: The aim of the study was to evaluate maximal counter movement jump (CMJ) via force plates technology, before and after 10 weeks of Officer Candidate School (OCS), a rigorous graded physical and leadership training course for Marine Officer Candidates (MOC). Additionally, this study investigated the influence of MOC with differing degrees of jump height performance, on changes in braking rate of force development (BRFD) and average propulsive force (APF) from pre to post OCS. Methods: One hundred fifty-nine MOC (25 ± 3 years, 80.5 ± 9.3 kg, 177.0 ± 6.4 cm) performed CMJ force plate testing pre and post 10-weeks of OCS. MOC performed 3 maximal CMJs, which were averaged, on Hawkin Dynamic Force Plates with 15 seconds of rest between each jump. All participants were divided into quartiles based upon pre-OCS jump height (take-off velocity2 ÷ 2a). For analyses, the 2 middle quartiles were combined into one MID group: HIGH (≥0.446 m), MID (0.355–0.443 m), and LOW (<=0.354 m). To meet assumptions of the statistical test, natural logarithmic transformations of BRFD ([force at lowest displacement—force lowest velocity] ÷ time between these 2 points) and APF (average force from start of lowest displacement to take-off) were analyzed as outcome variables in a two-way mixed measures analysis of variance (time: Pre and Post; group: HIGH, MID, LOW). Results: There was no interaction effect of time*group on APF and BRFD. There was a significant main effect of time on APF (p < 0.0001, np2 = 0.206) and BRFD (p < 0.0001, np2 = 0.096); both BRFD and APF were significantly lower following training. There was a significant main effect of group on BRFD (p = 0.007, np2 = 0.062) and APF (p < 0.0001, np2 = 0.232). Pairwise comparisons showed for BRFD that HIGH was significantly higher than LOW (p = 0.006), while MID was not significantly different than HIGH or LOW (p > 0.05). For APF, all groups were significantly different (p < 0.002; Table 1). Conclusions: There was an overall decline in BFRD and APF from pre to post OCS training, with no significant differences among groups. We have demonstrated groups that differ in jump height performance, have similar declines in force plate measurements relating to rate of force development and average force production following military training. Practical Applications: Measurable changes in force plate assessed BRFD and APF can be detected during 10 weeks of OCS training. One application for force plate technologies within military training courses could be in the detection of changes in neuromuscular performance reflecting either adaptations or maladaptations from training.

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Table 1:
Neuromuscular performance characteristics from counter movement jumps before and after 10 weeks of US Marine Corps OCS training.

(V107) Tapering Increases Myosin-Heavy Chain IIA and Maximal Strength in Strength Athletes

S. Travis,1 K. Zwetsloot,2 A. Ishida,1 I. Mujika,3 J. Gentles,1 M. Stone,1 and C. Bazyler1

1East Tennessee State University;2Appalachian State University; and3University of the Basque Country

The duration and manner in which volume is reduced during a taper may result in divergent 1-repetition-maximum (1RM) strength capabilities and myosin-heavy chain (MHC) isoform shifts. Purpose: Therefore, the purpose of this study was to compare 1RM outcomes and MHC isoform changes between a step and exponential taper in strength athletes. Methods: Fifteen strength athletes (24 ± 4 years, 89 ± 22 kg, 174 ± 8 cm) completed a 6-week peaking program. Athletes were randomly assigned to a step-taper (n = 7) or exponential-taper (n = 8). A mock competition was conducted pre-training (T1) and post-taper (T2) using USA Powerlifting regulations. The short taper group completed 4-weeks of “normal training” followed by a 1-week planned overreach (+150% volume increase) prior to a 1-week step taper (−50% volume reduction). The long taper group completed 2-weeks of “normal training” followed by a 1-week planned overreach (+150% volume increase) prior to a 3-week exponential taper (−50% volume reduction). Volume-load was matched between groups over the 6-week peaking program. Vastus lateralis microbiopsies were completed prior to training (T1) and 72 hours after completing the mock competition (T2). After tissue extraction, samples were placed in skinning solution for 4 months in preparation for single fiber phenotyping using a dot blot method (Figure 1). A total of 3,150 single fibers were isolated and placed in 10 μL of buffer and exposed to room temperature for 1–2 hours. After exposure, 1 μL of each 10 μL aliquot containing a single muscle fiber was placed in a well on top of a membrane. Primary and secondary antibodies were used to treat 3 individual membranes for MHC-I, MHC-IIA, and MHC-IIX. Using the dot blot method, it was possible to quantify MHC-I, -IIA, -IIX, and -I/IIA hybrid fibers. We were unable to detect MHC-IIA/IIX hybrids due to MHC-IIX antibody cross-activity. Phenotyping was determined by dot blot cross-elimination. A 2 × 2 (group × time) mixed ANOVA was used to compare changes over time between groups. Significant main effects were followed by post-hoc comparisons. Alpha criterion was set to p < 0.05. Results: 1RM squat and bench press significantly improved following the step (p = 0.006 and p < 0.001, respectively) and exponential (p < 0.001 and p < 0.001, respectively) taper, whereas 1RM deadlift significantly improved following the exponential taper only (p = 0.012). MHC-I significantly decreased (p = 0.038) and MHC-IIA significantly increased (p = 0.023) following the step-taper only. Conclusions: Tapering for maximal strength appears to induce a physiological increase in MHC-IIA in conjunction with 1RM improvements. Practical Applications: Tapering squat and bench press for 1- or 3 weeks can improve performance similarly, whereas a 3-week taper may be necessary to improve deadlift performance. These performance changes may partly be explained by MHC shifts towards a faster muscle phenotype.

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Figure 1.:
Phenotyping output using dot blot method. 1A. Imaging output of individual blots treated for specific myosin heavy-chain (MHC) isoforms. H = hybrid MHC-I/IIA fibers. Circled dots indicate MHC detection. Dark shaded cells denote MHC-IIX cross-activity removed from analysis to prevent misrepresenting MHC composition. 1B. Phenotype output of pooled group pre-taper and post-taper results to demonstrated overall taper effect on MHC composition.

(V108) Improved Physiological and Psychological Relaxation in Novice Floaters: Characterizing the First Float-Exposure

L. Caldwell,1 E. Post,2 J. Volek,3 C. Maresh,3 and W. Kraemer3

1University of North Texas;2Ohio Dominican University; and3The Ohio State University

Floatation therapy provides a reduced sensory experience by minimizing afferent signaling including visual, auditory, thermal, tactile, gravitational, and proprioceptive inputs. Despite limited research, the high salinity environment is often promoted for its ability to induce relaxation with very little practice or instruction. Purpose: The purpose of this investigation was to examine the effect of a 60-minute floatation session on biomarkers of physiological and psychological relaxation in novice floaters. Methods: Fourteen healthy males (age: 21.3 ± 6.3 years; height: 175.2 ± 6.1 cm; weight: 86.1 ± 10.1 kg) completed the study. Participants had no prior exposure to floatation therapy. Upon arriving at the laboratory, participants received a tour of the facilities and an explanation of the study procedures. Participants then underwent a 60-minute floatation session in the absence of light and sound. To further minimize sensory stimulation, participants were instructed to lie in the supine position with arms and legs outstretched, allowing the thermoneutral water to fully surround the body. Measures of relaxation were assessed before (PRE) and after (POST) the float session. Measures included a blood draw to assess circulating stress hormones (epinephrine, norepinephrine, cortisol), Short Form Profile of Moods States Questionnaire, Positive and Negative Affect Schedule, Lee Fatigue Scale, and visual analog scales for pain and soreness. To conclude the visit, participants engaged in a semi-structured interview, providing an opportunity to capture individual experiences with greater depth and detail. Means and standard deviations were calculated for each variable with differences assessed using paired samples t-test (p ≤ 0.05). Cohen's d was calculated to evaluate the magnitude of change. Results: Significant improvements were observed for negative affect (d = 0.88), total mood disturbance (d = 1.08), tension (d = 1.21), confusion (d = 0.93), fatigue (d = 1.33), energy (d = 0.72) and soreness (d = 0.33). Psychometric improvements were accompanied by a significant decrease in circulating stress hormones. Cortisol was reduced 23% (d = 0.62); norepinephrine was reduced 12% (d = 0.46) and epinephrine was reduced 25% (d = 0.49). When asked to describe the session in their own words, participants often recounted a preliminary phase of acclimation before feeling at ease in the tank. The duration of the acclimation period varied by participant, ranging from 5 to 15 minutes. Following the initial adjustment, participants conveyed feelings of contentment and reported general relaxation of both the body and mind, describing the time in the tank as relaxing, calming, and restorative. Conclusions: The effect sizes demonstrated in this study emphasize the utility of flotation therapy in promoting sympathetic relaxation. After a single exposure, marked improvement was seen in stress-related symptomology including mood disturbance, fatigue, and soreness. Practical Applications: Given these findings, floatation therapy may be considered a valuable intervention for quickly promoting relaxation and managing stress in a variety of sport performance contexts including mental preparation and physical recovery.

(V110) Exercise Participation and Subjective Well-Being of Collegiate Athletes During COVID-19 Pandemic

S. Reiner1, G. Smith2, and R. Davis2

1Rocky Mountain University of Health Professions/Saint Peter's University; and2Rocky Mountain University of Health Professions

Purpose: This study aims to assess collegiate athletes' subjective experience of well-being during the COVID-19 quarantine as well as their exercise patterns to understand their perceived current physical and mental status. Coaches may be facing massive levels of detraining or potentially the rest and recovery desperately needed for a rejuvenated return to sport. Results garnered in this study can inform best practices for periods of cessation of training. Methods: Two hundred thirty-seven collegiate athletes (mean age = 19.75, SD = 1.18) completed an online survey measuring exercise participation and well-being. The survey consisted of 26 questions in open- and closed-question response formats. Exercise behaviors were assessed using average frequency, duration, and intensity. Session intensity was assessed using session rate of perceived exertion (sRPE) using a modified Category Ratio (CR) (0–10 scale). Well-being was assessed using a questionnaire reporting fatigue, mood, sleep quality, general muscle soreness, and stress. A paired sample dependent t-test was performed to assess changes in exercise patterns of frequency, duration, and intensity of workouts and a Wilcoxon Signed Ranked test was performed to assess changes in well-being scores of fatigue, sleep, soreness, stress, and mood at the start of quarantine and current well-being scores. MANOVAs were performed for the effects of sex, sport, and academic year on duration, frequency, intensity, and well-being variables. All statistical analyses used an alpha level of p ≤ 0.05, indicating significance. The effect size was provided where appropriate. A priori indicated an adequate sample size of 128 participants. Results: Exercise habits indicate a statistically (p < 0.05) and clinically significant increase in frequency (t (234) = 4.36, p = 0.000, ES = 0.32), intensity (t (235) = 5.31, p = 0.000, ES = 0.47), and duration (t (234) = 6.54, p = 0.000, ES = 0.47) of exercise sessions overtime during the COVID-19 pandemic quarantine. Perceived psychological well-being also increased as time went on during quarantine with an improvement in fatigue (Z = 3.42, p = 0.001, ES = 0.22), sleep quality (Z = 4.59, p = 0.000, ES = 0.30), stress (Z = 6.53, p = 0.000, ES = 0.42), and mood (Z = 5.86, p = 0.000, ES = 0.38). Conclusions: There was a potential adaptation to quarantine that improved athletes' exercise participation through increased frequency, intensity, and duration of exercise sessions and improved perceived well-being, particularly in fatigue, sleep quality, stress and mood. Practical Applications: The pandemic and any other pro-longed cessation of organized sport offer a unique opportunity to improve wellness indicated in well-being ratings increasing over time and a focus on improving mindset, education on nutrition and performance, recovery, and injury prevention. Improved well-being during quarantine cannot be overlooked for future off-season programming. The improvement in sleep quality, stress levels, mood, and fatigue can have lasting implications for improved performance and resilience for the upcoming season. Concerns exist for periodization strategies, motivation, and possibility of detraining remain for strength and conditioning professionals in the transition to the return to sport. In the current circumstances, the improved perceived sleep quality and experience of stress may create a small buffering effect to illness and should continue to be emphasized upon return to training.

(V111) The Effects of Mindful Meditation on Self-Esteem and Self-Compassion in Female Collegiate Dance Majors

R. Whitehead, K. Jankevicius, H. Samuelson, and M. Whitehead

Stephen F. Austin State University

Purpose: Body image and self-esteem is an ever changing mindset that occurs in everyone, and in recent years the idea of positive thinking has become more prevalent. In physical activities such as dance, that focuses on the way the body moves and looks, perceptions of one's body image can become distorted. The purpose of this study was to determine the effects of a mindful meditation intervention on self-esteem and self-compassion in female collegiate dance majors. Methods: A total of 10 female participants (age = 22.1 ± 1.5 years) with an average of 12.6 ± 5.9 years of dance experience were recruited to participate in this study. Each participant's height, weight, body composition by Dual Energy X-Ray Absorptiometry (DEXA) scan, and body image and self-esteem measures Rosenberg Self-Esteem Scale, and the Self-Compassion Scale were collected prior to the mindful meditation intervention. Over a 15-day (3, 5 d·wk−1) period the participant group was led through a 20-minute mindful meditation session and body image and self-esteem measures were collected at the end of the week. Wilcoxon Signed-Ranks test was used to determine significant differences between the assessments over the course of the intervention with p £ 0.05 set for all analyses. Results: There were no significant differences for the Pre-Wk1 assessments for either the Rosenberg or the Self-Compassion Scales. Analysis indicated significant differences for the Rosenburg Pre-Wk2 (14.8 ± 4.6, 18.2 ± 5.9, p = 0.05) and Pre-Wk3 (14.8 ± 4.6, 19.0 ± 5.6, p = 0.02) assessments. Analysis indicated significant differences for the Self-Compassion Scale Pre-Wk2 (60.9 ± 15.6, 71.4 ± 12.8, p < 0.01) and Pre-Wk3 (60.9 ± 71.4, 83.9 ± 6.9, p = 0.01) assessments. Conclusions: The findings of this study support the efficacy of mindful meditation practice for enhancing both self-esteem and self-compassion in female collegiate dance majors. The major limitation of this research is the relatively small cohort from which the data was collected. Practical Applications: A practical implication from this investigation is that the implementation of mindfulness practice could potentially positively impact both self-esteem and self-compassion by enhancing both of these parameters in this at-risk group.

(V113) The Effects of Ability-Based vs. Traditional Physical Training on the Health and Fitness of Custody Assistant Recruits

R. Lockie,1 J. Dawes,2 M. Moreno,1 A. Bloodgood,1 M. McGuire,1 T. Ruvalcaba,1 E. Hernandez,1 J. Dulla,3 R. Orr,3 and K. Rodas1

1California State University, Fullerton;2Oklahoma State University; and3Bond University

Custody assistants (CAs) maintain security in detention facilities, and may need to perform physical tasks such as inmate restraint. Due to this demand and need for general fitness, physical training programs are often used during academy. Traditional training (TT) typically follows a paramilitary, one-size-fits-all model. This approach may not be optimal for the individual recruit. Purpose: To determine the effects of ability-based training (ABT) vs. TT in CA recruits. Methods: Retrospective analysis was conducted on 2 CA recruit classes who completed an 8-week academy. Physical training was completed twice per week, and incorporated circuit training and running. The TT group (18 males, 13 females) followed a model where all recruits completed the same exercises with the same intensity; the ABT group (17 males, 12 females) had exercises tailored towards their ability. In the week before academy, recruits completed the following assessments: body mass (BM); body fat percentage (BF%); resting heart rate (RHR); blood pressure (BP); waist circumference (WC); waist-to-hip ratio (WHR); combined grip strength; push-ups and sit-ups in 60 seconds; and YMCA step test recovery HR. In the first week of academy, recruits completed 201-m (220-yard) and 2.4-km (1.5-mile) runs. Post-testing occurred in the final week of academy. Independent samples t-tests evaluated between-class pre-test differences. Paired samples t-tests detected if pre-to post-training changes occurred within groups. Change scores were calculated for each variable for each group; independent samples t-tests compared the change scores between the groups. Alpha levels were set at p ≤ 0.05. Results: The TT group had lower BF%, BP, and WC; completed more sit-ups; and were faster in the 2.4-km run before training (p ≤ 0.04). After academy, the TT recruits decreased WHR, and improved grip strength, YMCA recovery HR, and 201-m and 2.4-km run times (p ≤ 0.03). However, the TT also increased diastolic BP (p < 0.01). The ABT recruits decreased BM, BF%, RHR, and WC following academy (p ≤ 0.01). These recruits also improved push-ups, sit-ups, YMCA recovery HR, and 201-m and 2.4-km run times (p ≤ 0.03). Compared to the TT recruits, ABT recruits had greater positive changes in BF%, RHR, diastolic BP, and sit-ups (p ≤ 0.02). The TT recruits had more favorable changes in WHR and grip strength (p ≤ 0.02). Conclusions: Recruits who completed TT and ABT during academy generally experienced favorable changes to health and fitness. The degree of positive change in variables such as BF%, RHR, and sit-ups was greater for ABT recruits. Further, the TT recruits experienced an increase in diastolic BP. This could have been due to the overall stress of academy, which incorporated physical training that was not ability-based. It should be noted that TT recruits generally displayed better health and fitness prior to academy, so their ceiling for improvement may have been lower. However, when coupled with the diastolic BP increase, this may provide evidence for ABT. Fitter recruits may require a more individualized training stimulus. Practical Applications: TT and ABT training can improve the health and fitness of CA recruits. However, TT may have contributed to a diastolic BP increase in recruits, indicative of poorer recovery or systemic fatigue. ABT training also led to a greater range of favorable recruit health and fitness changes. Given the job demands experienced by CAs, training staff should explore the use of ABT.

(V115) Does a Ketone Supplement Enhance Performance and Body Composition in Resistance Training Women?

K. Skemp1 and M. Christy2

1University Wisconsin La Crosse; and2Carroll University

Introduction: Ketone supplements purportedly enhance energy availability by increasing ketones in the blood, which are then used for fueling exercise instead of carbohydrates. Very few studies have examined what effects exogenous ketones can have on body composition and strength performance in women who participate in resistance training. Purpose: The purpose of this study was to examine if a supplement containing exogenous ketones would produce a more positive effect on body composition and various performance measures in comparison to following a healthy diet. Methods: A sample of 13 women (mean age 20.9 ± 2.08) were randomly assigned to either the supplement group (n = 5) who consumed an exogenous ketone supplement twice a day, or a control group (healthy diet group) who were told to use the Harvard Healthy Eating Plate as a reference to healthy eating. Both groups participated in resistance training 3 times a week for 6 weeks. Those in the supplement group had their blood ketone levels monitored via finger stick 3 times per week, 45 minutes after consumption of the supplement and prior to exercise. Body fat and lean body mass were measured using air displacement plethysmography. Strength performance was measured using a 1-RM test in the back squat and bench press, a flexed arm hang for time, and the vertical jump. Delayed onset muscle soreness was also assessed using a visual analogue scale. All measurements were taken at week 0 and at the end of week 6. Results: Both the supplement group and the control group saw positive increases in their strength performance as well as favorable changes in their body composition (See Table 1). Between group differences in body composition and performance measures were not statistically significant at α = 0.05 [p-value ranges 0.338–0.942]. Conclusions: We are unable to conclude that consuming a ketone supplement provides increased benefits to improvements in body composition and performance when compared to a healthy diet in combination with resistance training. Further studies with larger numbers of participants are needed to truly evaluate the impact of exogenous ketones on body composition and performance in resistance training women. Practical Applications: Athletes look to supplements to enhance body composition as well as to improve strength. Ketone supplements are marketed as ergogenic aids that enhance workouts by increasing energy availability through increased levels of blood ketones. In the current study, we did not find any additional benefit to using this type of supplement when compared to following a healthy diet along with a properly designed resistance-training program among female athletes.

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(V116) Heart Rate Response of Special Weapons and Tactics Team Operators During Active Shooter Training Scenarios

Q. Johnson,1 J. Zaragoza,1 R. Orr,2 R. Lockie,3 N. McSpadden,4 C. Manuel,4 D. Smith,1 and J. Dawes1

1Oklahoma State University;2Bond University;3California State University, Fullerton; and4SPD

Simulated active shooter scenarios (SASS) provide special operations teams (SOT) with an opportunity to maintain their skills and receive team feedback in order to optimize their performance. Although research on heart rate (HR) changes in the law enforcement officer (LEO) population is novel, there is virtually no information available examining these differences within SOT groups during these types of scenarios. Purpose: Utilizing HR analysis to identify and quantify the physical demands of SASS among SOT members through HR analysis. Methods: 7 male (age: 38.97 ± 9.17; ht: 177.99 ± 6.45 cm. wt: 88.83 ± 13.55 kg) SOT members volunteered to participate in this research. SOT members performed 3 SASS involving breaching, casualty extraction, and seeking cover while wearing personal protective equipment (PPE). Participants were outfitted with heart rate (HR) monitors and average heart rate (HRavg) as well as maximum heart rate (HRmax) data were collected and recorded for the scenario performed. Results: During SASS it was discovered that HRavg ranged between 45—60% of APMHR and average HRmax ranged between 68–94% of APMHR. Conclusions: SASS can be very physically demanding events that may elicit maximal or near maximal heart rate responses. Practical Applications: Based on the metabolic demands of these events and the individual SOT members capabilities, this information can be used to develop strength training and conditioning programs to optimize performance during active shooter scenarios.

(1) Correlation Between Medicine Ball Throws and Bat Swing Characteristics in College Baseball Players

M. Heinecke,1 J. Mayhew,2 R. Woodall,3 and N. Williams3

1Forsyth Country Day School;2Truman State University; and3Winston-Salem State University

Rotational medicine ball throws (RMBT) have been used as a specific training technique for developing trunk rotation strength in baseball players. It has been assumed that training with different sides with RMBT will strengthen muscles and facilitate bat velocity. However, some concern exists over the effect of RMBT for altering the kinetic sequence of bat swing. Purpose: To examine the relationship between RMBT velocity (RMBT-V), bat swing velocity, and ball exit velocity. Methods: College players (n = 40, height = 180.3 ± 8.1 cm, weight = 84.8 ± 10.4 kg) completed standardized warm-up routines prior to RMBT testing with 3.6- and 9.1-kg medicine balls. RMBT velocity was recorded from a velocity band on the player's forearm over a series of 5 throws with each weight. Following adequate recovery (>10 minutes), each player performed 5 maximum velocity swings hitting a ball off a tee. Ball exit velocity was determined using a standard radar gun. Results: Neither 3.6-kg RMBT-V nor 9.1-kg RMBT-V was not significantly correlated (p > 0.11) with height (r = 0.02 and 0.38, respectively) or weight (r = 0.39 and 0.49, respectively). There was also no significant correlation of 3.6-kg RMBT-V nor 9.1-kg RMBT-V with bat swing velocity (r = −0.33 and −0.21, respectively) or ball exit velocity (r = 0.28 and 0.31, respectively). Bat swing velocity (6.96 ± 0.88 m·s−1) was not significantly correlated (p = 0.17) with ball exit velocity (16.42 ± 0.70 m·s−1). Conclusions: The ability of a player to achieve a higher RMBT-V with differing masses does not appear to be predictive of bat swing velocity nor ball exit velocity. Further, bat swing velocity does not seem to be associated with ball exit velocity under the current measurement system. This research supports previous research on the lack of strong association between trunk rotational velocity as measured by RMBT and bat swing velocity. Practical Applications: A nonspecific trunk rotational power measurement does not appear to have any predictive value for assessing bat swing velocity nor ball exit velocity in college baseball players. Further investigation should explore the relationship between improvement in rotational strength with various training methods and bat swing velocity and ball exit velocity.

(2) The Acute Effects of Low-Load Resistance Training With and Without Blood Flow Restriction on Mean Power

C. Proppe, P. Rivera, and E. Hill

University of Central Florida

Purpose: Low-load resistance training with blood flow restriction (BFR) may result in greater muscle fatigue relative to non-BFR conditions (LL). There is limited available data, however, on the effects of BFR on power output during a fatiguing intervention. Therefore, the purpose of this investigation was to examine the acute effects of BFR on mean power output during fatiguing leg extension muscle actions. Methods: Seven (mean ± SD; 22 ± 3 years) recreationally active females (n = 3) and males (n = 4) were randomly assigned to complete 30 unilateral isotonic submaximal (30% one-repetition maximum [1RM]) leg extension muscle actions with and without BFR on separate days. Mean power was determined for each repetition using a custom-fitted pancake load cell and analyzed offline. Mean power was analyzed between conditions using a paired samples t-test (average power across 30 repetitions) and polynomial regression analyses (first, second, or third order) were performed across the 30 repetitions on the composite mean power responses. An alpha of p ≤ 0.05 was considered statistically significant. Results: There was a significant (p = 0.004, d = 26.45) mean difference between the 2 conditions (LL = 201.72 ± 62.60 W; BFR = 175.34 ± 23.50 W). Mean power increased linearly across the 30 repetitions for the LL condition (p < 0.001, r2 = 0.348), but there was no significant relationship for the BFR condition (p = 0.352, r2 = 0.310). Conclusions: Relative to the LL condition, BFR resulted in lower mean power output during a fatiguing set of isotonic submaximal leg extension muscle actions. Thus, despite performing similar exercise volume between conditions (30 repetitions at 30% 1RM), less mean power was achieved during the BFR condition. That may reflect greater muscle fatigue across the 30 repetitions. Practical Applications: Resistance training to volitional fatigue is a potent stimulus for muscle adaptation. The application of BFR may result in greater muscle fatigue and prior to non-BFR conditions. Thus, applying BFR may be used to increase the efficiency of exercise prescription by reducing the number of repetitions or sets needed to achieve volitional fatigue and induce muscle adaptation.

(3) Load-Dependent Responses in Leg Extension Performance Fatigability Are Sex-Independent Around the Critical Load

T. Dinyer,1 P. Succi,1 C. Voskuil,1 E. Soucie,2 J. Clasey,1 M. Abel,1 T. Butterfield,1 and H. Bergstrom1

1University of Kentucky; and2University of North Carolina at Chapel Hill

The range in responses for men and women to the number of repetitions completed to failure and performance fatigability (PF = %Δ from pre-to post-exercise maximal voluntary contraction [MVC] force) during resistance exercises (RE) has been reported to be sex- and load-dependent. The critical load (CL) has been identified as an individual fatigue threshold that demarcates sustainable from unsustainable RE loads. Purpose: This study aimed to determine if there are load- and sex-dependent responses in the number of repetitions completed to failure and PF during the leg extension (LE) exercise performed below (CL-10%, CL-20%) and above (50, 60, 70, and 80% one-repetition maximum [1RM]) the CL. Methods: Ten men and 11 women completed a 1RM on Day 1, repetitions to failure at 50, 60, 70, and 80% 1RM on Days 2–5 (used to determine the CL from the total work [kg x repetitions] vs repetitions relationship), and repetitions to failure at CL-10% and CL-20% on Days 6–7, for the LE. The MVC was measured immediately before and after the repetitions to failure to determine pF. Statistical analyses (p ≤ 0.05) included intra-class correlation coefficient (ICC2,1), standard error of the measurement (SEM), and coefficient of variation (CoV) to determine the test-retest reliability of pre-exercise MVC (Days 2–7). Separate, 6 (load [50, 60, 70, 80% 1RM, CL-10%, CL-20%]) x 2 (sex [men, women]) mixed model ANOVAs were used to examine repetitions completed and pF. Results: The ICC demonstrated “excellent” reliability (ICC = 0.911; SEM = 29.0 N; CoV = 7.8%). There was no load × sex interaction (F (1.174, 22.315) = 2.636, p = 0.114, pη2 = 0.122) or main effect for sex (F (1, 19) = 3.937, p = 0.062, pη2 = 0.172) for repetitions completed. There was a main effect for load (F (1.174, 22.315) = 81.989, p < 0.001, pη2 = 0.812) and pairwise comparisons indicated the repetitions completed were different from one another across all loads (80% 1RM < 70% 1RM < 60% 1RM < 50% 1RM < CL-10% < CL-20%; p ≤ 0.001). For PF, there was no load × sex interaction (F (2.288, 43.467) = 3.056, p = 0.051, pη2 = 0.139). There was a main effect for load (F (2.288, 43.467) = 38.924, p < 0.001, pη2 = 0.672). Follow-up one-way repeated measures ANOVAs with Bonferroni pairwise comparisons indicated the percent change from pre-to post-exercise MVC for 50% (−21.0 ± 11.4%, p < 0.001), 60% (−15.1 ± 12.8, p < 0.001), 70% (−11.8 ± 12.3%, p < 0.001), and 80% 1RM (−11.0 ± 13.3%, p < 0.001) were less than CL-10% (−53.4 ± 30.1%) and CL-20% (−60.8 ± 25.0%). The percent change for CL-10% and CL-20% were not different from one another (p = 1.000). In addition, the percent change from pre-to post-exercise MVC for 80% 1RM was less than 50% 1RM (p = 0.048). Conclusions: There were no differences in the number of repetitions completed to failure or PF between the men and the women. However, the degree of PF was greater when repetitions were performed to failure below compared to above the CL. These findings support the CL as a demarcation to examine mechanisms of fatigue during high- and low-load resistance exercise. Practical Applications: Load-dependent manifestations of fatigue may dictate the nature and magnitude of responses to resistance training. This may help coaches and practitioners design effective resistance training programs that consider individual fatigue characteristics.

(4) The Effect of the Follicular and Luteal Phases on Power and the Rate of Force Development after Acute Heavy Volume Resistance Exercise

E. Tagesen,1 E. Arroyo,1 M. Lebron,1 B. Miller,2 and A. Jajtner1

1Kent State University; and2Case Western Reserve University

Purpose: To compare the role of follicular (FOL) and luteal (LUT) phases on recovery from resistance exercise in resistance trained women through various performance measures. Methods: Ten resistance trained women (FOL: n = 5; LUT: n = 5; Age: 21 ± 2 years; weight: 62.4 ± 6.6 kg; squat 1RM: 78.86 ± 14.77 kg) performed a high-volume resistance exercise protocol that consisted of 8 sets of 10 repetitions of the back squat with 70% of their one-repetition max (1RM). Women were included if they were taking an oral contraceptive for at least one-year, experienced regular menstrual cycles for at least 6 months, and could perform a back squat 1RM of at least their body weight. Visit One included a review and collection of written informed consent, a criterion 1RM test, and randomization into either the FOL (Days 2–5) or LUT (Days 18–20) groups. Visit 2 was scheduled >72 hours before Visit 3 and consisted of body composition measures, a confirmation 1-RM, and performance test familiarization of the vertical jump (VJ), isometric midthigh pull (IMTP), and isometric squat (ISQT). Performance was quantified through VJ height (cm), rate of force development (RFD) at 100 and 200ms, peak force (PF), and force at 100 and 200ms. Women were scheduled for subsequent visits (3–5) during their assigned phase. On Visit 3, participants reported to the strength lab having abstained from exercise for at least 72 hours, caffeine for 24 hours, alcohol and nicotine for 16 hours, and food for 10 hours. During Visit 3 participants completed the squat protocol and performance measures, which including VJ, IMTP and ISQT, before (PRE), immediately (IP), 1- (1H), 24- (24H), and 48- (48H) hours after exercise. All performance tests were completed 3 times with the average used for analysis. Data were analyzed using a Mixed Model Regression with group and time as fixed factors. Results: There was an interaction in IMTP PF (F = 4.06, p = 0.034). In FOL, IMTP PF decreased from PRE (811 ± 221 N), to IP (p = 0.008, 753 ± 215 N), 1H (p = 0.013, 745 ± 225 N), and 24H (p = 0.043, 709 ± 203 N). In LUT, IMTP PF decreased from PRE (779 ± 70 N) to IP (p = 0.039, 708 ± 92 N) but was recovered by 1H after exercise (p = 0.969, 777 ± 117 N). There was an interaction observed in IMTP force at 100 ms (F = 3.92, p = 0.040). In FOL, IMTP at 100 ms decreased from PRE (800 ± 218) to IP (p = 0.009, 743 ± 211 N) and 1H (p = 0.008, 735 ± 220 N). In LUT, IMTP force at 100 ms decreased from PRE (766 ± 75 N) to IP (p = 0.040, 699 ± 93 N) but was recovered by 1H after exercise (p = 0.981, 767 ± 121 N). There was an observed inaction in IMTP force at 200 ms (F = 3.87, p = 0.041). In FOL IMTP force at 200ms decreased from PRE (797 ± 218 N) to IP (p = 0.010, 739 ± 210 N) and 1H (p = 0.009, 732 ± 220 N). In LUT IMTP force at 200ms decreased from PRE (763 ± 76 N) to IP (p = 0.040, 694 ± 94 N), but was recovered by 1H (p = 0.985, 739 ± 122 N). No differences were observed in VJ, IMTP or ISQT RFD at 100 or 200 ms, or ISQT PF, force at 100 ms, or force at 200 ms. Conclusions: Women appear to recover force production capacity within one hour after exercise in the luteal phase but not until 24 hours after exercise during the follicular phase of the menstrual cycle. Practical Applications: Strength coaches should consider the possible effects of menstrual phase on recovery of force production after high volume resistance exercise.

(5) Contraction Type Does Not Influence Muscle Activation or Force Perception of the Elbow Flexors

K. Kennedy,1 R. Colquhoun,1 M. Magrini,2 S. Fleming,1 N. Banks,3 and E. Rogers3

1University of South Alabama;2Creighton University; and3University of Iowa

Purpose: The purpose of the present study was to examine the effects of maximal concentric (CON) and eccentric (ECC) contractions of the elbow flexors on force perception, strength, and muscle activation. Methods: Nineteen young, resistance-trained males (Age: 24 ± 3 years) completed 6 sets of 10 repetitions of maximal CON and ECC contractions of the elbow flexors across 2 separate experimental visits. The order of the exercise conditions, as well as arm utilized, were randomized and counterbalanced. Visits were separated by 6 ± 1 day. Testing was completed prior to each exercise bout, as well as 24-, 48-, and 72-hours following exercise. At each testing session, subjects were instructed to perform 3 submaximal contractions of the elbow flexors at 75% of their perceived maximal voluntary isometric contraction (MVIC) strength, which was recorded following the submaximal contractions. No feedback was provided to the subjects during the submaximal contractions. During all contractions, electromyographic signals were recorded in the biceps brachii, and the root mean square (RMS) amplitude was calculated offline. Force (nF) and RMS (nRMS) from all perceived 75% contractions were normalized to MVIC from that visit. Separate 2 (Condition) × 4 (Time) × 3 (Repetition) repeated measures ANOVAs were run to examine nF and nRMS, while a 2 (Condition) × 4 (Time) repeated measures ANOVA was run to examine MVIC. Appropriate lower order ANOVAs and t-tests were run to decompose significant interaction and main effects. Results: No significant three-way (p = 0.102–0.252) or two-way (p = 0.056–0.755) interaction effects were uncovered for nF or nRMS. However, a significant main effect for repetition was uncovered for nRMS (p = 0.016). Post-hoc analyses revealed significantly greater nRMS during the second (p = 0.036; 67.3 ± 19.8% MVIC) and third (p = 0.035; 68.7 ± 19.3% MVIC) repetitions when compared to the first repetition (64.3 ± 22.1%) of the 75% contractions. No other main effects (p = 0.104–0.878) were revealed for nF or nRMS. MVIC decreased from PRE (425.6 ± 66.6 N) to POST24 (p = 0.025; 394.2 ± 85.3 N), non-significantly recovered at POST48 (p = 0.097; 408.1 ± 69.1 N), but remained depressed from PRE at POST72 (p = 0.028; 406.5 ± 70.1 N) in CON. In ECC, MVIC decreased from PRE (420.6 ± 97.5 N) to POST24 (p < 0.001; 310.1 ± 96.9 N), before progressively recovering at POST48 (p < 0.001; 339.1 ± 106.1 N) and POST72 (p = 0.03; 356.0 ± 109.7 N) but remaining depressed from PRE (p < 0.001). ECC MVIC was lower at POST24 (p = 0.007) and POST48 (p = 0.023) when compared to their respective CON timepoints. Conclusions: These findings suggest that contraction type does not appear to affect perceptions of force and muscle activation during submaximal contractions of the elbow flexors. While force output was similar across all timepoints, muscle activation was greater in the second and third repetitions compared to the first. Additionally, it is important to note that both nF (63.3% MVIC) and nRMS (66.8% MVIC) were lower than the targeted effort of 75% when collapsed across all time points and conditions. Practical Applications: Additional warmup repetitions may be warranted to increase muscle activation prior to exercise; however, practitioners must consider a potential for athlete's underestimation of force production during submaximal exercise at higher contraction levels.

(6) Substantial Strength Gains Using Blood Flow Restriction in a Middle-Aged Athlete With Chronic Knee Weakness and Instability

M. Schooley and L. Chase

University of St. Augustine for Health Sciences

There is minimal information reported on the effects of blood flow restriction (BFR) on middle-aged athletes with continued chronic musculoskeletal impairments (decreased muscle strength and size) associated with knee instability. Purpose: The purpose of this study was to determine the effects of BFR training on a middle-aged female athlete with chronic weakness and knee instability despite traditional high-level resistance training. Methods: Single subject, pre/post design was used. Participant performed supervised BFR exercise for 8 weeks, 2 sessions per week. Evaluation was performed pre and 8 weeks post BFR exercise intervention. Outcome measures included girth measurements, strength assessments using hand-held digital dynamometry and isotonic machines (predicted 1 repetition max) and Y Balance Test-Lower Quarter. BFR was set at 80% of their arterial occlusion pressure (AOP), for lower extremity resistance exercise training. The intensity of the low-load resistance exercise was 20–40% of 1 repetition maximum (1RM). The study followed the BFR exercise guidelines published in the 2019 Position Stand for BFR exercise. BFR exercise was the only intervention. Results: All outcome measures demonstrated improvement, as noted by a positive percentage of change (see Table 1). Digital dynamometry strength assessments of the lower extremity demonstrated strength gains between 8.4 and 24.3%. Predicted 1RM assessments of the lower extremity demonstrated the largest gains between 21.3 and 41.5%. Y-Balance assessments revealed an 11.2% improvement in the anterior direction. Finally, percent change in girth was greatest (6.3%) at the gluteal/pelvis region. Conclusions: The results indicate that BFR exercise can produce strength gains in a middle-aged female athlete with chronic knee weakness and instability despite a history of traditional resistance training. Furthermore, this improvement in strength may be associated with improved stability, as demonstrated by the Y-Balance scores. Anecdotally, the positive changes were associated with the subject being able to run without a brace and engage in higher-level functional activities when compared to pre-study. The post evaluation also revealed symmetry in bilateral lower extremity strength for the first time in many years. Practical Applications: Traditional resistance exercise training may not be enough to produce significant strength changes in a middle-aged athlete with a long history of knee weakness and instability. BFR exercise training should be considered for middle-aged clients with chronic weakness that is not responding to traditional resistance exercise training.

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(7) Recovery of Rapid and Maximal Force Production Following Maximal Eccentric, Maximal Concentric, and Submaximal Eccentric Resistance-Exercise

F. Carlson,1 R. Colquhoun,2 S. Fleming,2 N. Banks,3 E. Rogers,3 and M. Magrini1

1Creighton University;2University of South Alabama; and3University of Iowa

Purpose: The purpose of this study was to investigate the time-course recovery of rapid and maximal strength characteristics following a maximal eccentric (ECC), maximal concentric (CON), and concentric work-matched eccentric (ECCWM) resistance-exercise of the elbow flexors. Methods: Eighteen strength-trained males (mean ± SD; age: 24 ± 3 years) completed ECC, CON, and ECCWM contractions of the elbow flexor musculature in a quasi-randomized order, with each condition separated by 7 days. Each condition consisted of 6 sets of 10 repetitions with 2 minutes of rest between sets through a 90 range of motion. For the initial bout, participants completed either the ECC or CON condition on their dominant arm, with the second bout consisting of the opposite condition in the non-dominant arm. The ECCWM condition was completed on the final testing session on the same arm as the CON condition. For all of the conditions, participants were seated in an isokinetic dynamometer and force was recorded from a load cell attached to a custom-built handle secured to the dynamometer arm. Peak force (PF) and peak rate of force development (pRFD) were recorded prior to (Pre) and immediately post- (Post), 1-hour (Post1), 24-hours (Post24), 48-hours (Post48), and 72-hours (Post72) post exercise. All visits took place at the same time of day (±1 hour). All variables were calculated offline using custom written LabView software. Separate 3 (Condition) × 6 (Time) repeated measures ANOVAs were run to examine any potential differences in the dependent variables, with appropriate post-hoc t-tests to decompose any significant interaction or main effects. Results: A significant condition × time interaction was found for PF (p ≤ 0.001) but not for pRFD (p = 0.068). However, there was a significant main effect for time for pRFD (p ≤ 0.001). Post-hoc analysis revealed significantly reduced pRFD at Post (p ≤ 0.001; 2501.99 ± 765.67 N·s), Post1 (p ≤ 0.001; 2589.74 ± 792.50 N·s), Post24 (p ≤ 0.001; 2911.46 ± 796.61 N·s), and Post72 (p = 0.013; 2986.28 ± 969.10 N·s) when compared to Pre (3625.53 ± 167.11 N·s) and collapsed across groups. Further, PF was significantly reduced at Post (p ≤ 0.001; 249.62 ± 22.33 N), Post1 (p ≤ 0.001; 264.60 ± 24.70 N), Post24 (p ≤ 0.001; 304.31 ± 24.84 N), Post48 (p = 0.005; 332.46 ± 27.67 N), and Post72 (p = 0.012; 350.40 ± 27.40 N) compared to Pre (415.23 ± 21.57 N) in ECC. Significantly reduced PF were shown in ECCWM at Post (p ≤ 0.001, 358.91 ± 71.83 N), Post1 (p ≤ 0.001, 353.63 ± 72.10 N), and Post24 (p = 0.03, 388.12 ± 79.60 N) compared to Pre (435.98 ± 73.75 N). CON showed reduced PF at Post (p ≤ 0.001, 327.78 ± 72.60 N) and Post1 (p ≤ 0.001, 356.10 ± 76.11 N) time points when compared to Pre (416.10 ± 66.10 N). Post-hoc analyses also revealed significantly greater PF for CON and ECCWM compared to ECC at Post (p = 0.016, p ≤ 0.001), Post1 (p = 0.007, p = 0.009), Post24 (p = 0.019, p = 0.021), Post48 (p = 0.043, p = 0.05, respectively). Conclusions: These data suggest that ECC, CON, and ECCWM elicit similar deficits in pRFD for up to 48 hours post-exercise. However, the time-course recovery of PF appears to differ based on contraction-type. Practical Applications: Clinicians, coaches, and practitioners can use these data outlining the recovery of maximal and rapid force production to better structure resistance training protocols, as they appear to have different recovery rates.

(8) The Effects of Hormonal Phase-Based Periodization in Female Collegiate Athletes

A. Placial, K. Lynch, S. Trent, and B. Shaver

William Jessup University

Men and women follow similar periodization programming despite the various differences in training response. Literature supports the relative fatigability of a muscle group (low tolerance to volume) is higher in the Follicular phase (FP), peaking in the late FP and ovulation phase (2,4). Furthermore, it could be hypothesized that utilizing strength training in the FP and utilizing hypertrophy in the LP could result in greater physiological adaptations overall. Purpose: The purpose of this study was to compare the effects of hormonal phase based-training (HPT) vs traditional linear periodization (TRAD) on body composition and strength. In addition, to examine changes in body composition and strength of TRAD against those on birth control following a traditional linear periodization model (TRAD BC). Methods: Nine collegiate women softball players participated in an 8-week training program (age: 20.4 ± 1.51 years, Mass: 70.42 ± 8.756 kg, Height: 164.2 ± 1.87 cm). Based on physiological parameters, the subjects were assigned into: (n = 3) HPT, (n = 3) TRAD, (n = 3) TRAD BC. Pre-post body composition (Fat-free mass vs fat mass) was measured utilizing air displacement plethysmography via Bod Pod. Strength was evaluated through a pre-post 3RM squat, deadlift, and bench press. Each group strength trained 2x/wk in addition to their sport-specific training. Strength phases were at 80–95% of their tested 1RM for 2–6 sets of 6–8 reps; Hypertrophy phases were at 67–85% of their tested 1RM for 3–6 sets of 6–12 reps. HPT Hormonal phases were individually determined for each subject utilizing basal metabolic temperature and Luteinizing Hormone strips. HPT trained in strength from the first day of menses to the day of ovulation; once ovulation had occurred hypertrophy was implemented. TRAD and TRAD BC performed a linear progressive 4-week block of hypertrophy followed by a 4-week block of strength. A T-test was performed to analyze how the change (pre-post) in each variable compared against the sample mean. Based on a 95% confidence interval, above-average x< −1.860, average-1.860 < x< 1.860, below average x < 1.860. Results: HPT had a total of 8 above-average scores surpassing the other 2 groups in the categories of: decrease in body fat percentage (2); increase in fat-free mass (2); decrease in fat mass (2); increase in 3RM squat (1); increase in 3RM deadlift (1). TRAD had a total of 7 above-average scores: decrease in body fat percentage (1); increase in fat-free mass (2); decrease in fat mass (1); increase in 3RM deadlift (2); increase in 3RM bench (1). TRAD BC showed no above-average scores in any of the categories tested. Conclusions: Based on the results of this study, a hormonal phase training model may be more efficient in improving body composition and increasing strength. Additionally, it may appear that birth control attenuates changes in body composition and increasing strength. Practical Applications: Utilizing strength training in the FP and hypertrophy in the LP may elicit greater adaptations. Therefore, both athletes and strength coaches should consider utilizing the HPT model for additional increases in strength and changes in body composition in the long term. Furthermore, athletes and coaches should acknowledge the possible effects of hormonal birth control regarding increases in strength and changes in body composition.

(11) Comparisons of Torque, Power, and Rate of Velocity Development During Isokinetic Muscle Actions in Pre- vs. Post-Pubescent Males and Females

Z. Gillen,1 M. Shoemaker,2 and J. Cramer2

1Mississippi State University; and2The University of Texas at El Paso

Purpose: Examine absolute and normalized peak torque (PT), mean power (MP), and rate of velocity development (RVD) across the isokinetic velocity spectrum in pre-vs. post-pubescent males and females. Methods: Ten pre-pubertal (PRE) males (mean ± 95% confidence interval, age = 9.76 ± 0.49 y), 10 PRE females (age = 9.82 ± 0.60 y), 10 post-pubertal (POST) males (age = 17.58 ± 0.79 y), and 10 POST females (age = 16.88 ± 0.95 y) participated. Ultrasound images quantified forearm flexor muscle cross-sectional area (CSA). Participants completed maximal voluntary isometric contractions (MVICs) and isokinetic forearm flexion muscle actions at 60, 120, 180, 240, and 300°∙s−1. PT was assessed during all muscle actions, while MP and RVD were assessed during isokinetic muscle actions. PT, MP, and RVD were expressed in absolute terms and normalized to CSA and MVIC torque. Mixed factorial ANOVAs (group [PRE vs. POST) × sex [male vs. female] x velocity [60,120,180,240,300°∙s−1]) compared mean values for absolute and normalized PT, MP, RVD. Results: There were differences for CSA, MVIC torque, and absolute isokinetic PT, MP, and RVD such that POST males > POST females > PRE males and females (p < 0.001). Normalizing isokinetic PT to CSA or MVIC eliminated the sex- and group-related differences (p ≥ 0.149), while MP and RVD normalized to CSA or MVIC were greater in the POST than PRE group (p < 0.001), with no sex-related differences (p ≥ 0.359). For all groups, absolute isokinetic PT and isokinetic PT normalized to CSA or MVIC decreased systematically across velocity (p ≤ 0.046). For the PRE group, absolute MP and MP normalized to CSA or MVIC increased from 60 to 180°∙s−1 (p < 0.001), plateaued from 180 to 240°∙s−1 (p = 0.934), and decreased from 240 to 300°∙s−1 (p < 0.001). For the POST group, absolute MP and MP normalized to CSA and MVIC increased from 60 to 240°∙s−1 (p < 0.001) and plateaued from 240 to 300°∙s−1 (p ≥ 0.231). For the PRE group, absolute RVD and RVD normalized to CSA increased from 60 to 240°∙s−1 (p ≤ 0.043) and plateaued from 240 to 300°∙s−1 (p ≥ 0.989), while RVD normalized to MVIC increased from 60 to 180°∙s−1 (p ≤ 0.015) and plateaued from 180 to 300°∙s−1 (p ≥ 0.054). For the POST group, absolute RVD increased systematically across velocity (p ≤ 0.030), while RVD normalized to CSA or MVIC increased from 60 to 120°∙s−1 (p < 0.001), plateaued from 120 to 180°∙s−1 (p ≥ 0.058), and increased from 180 to 300°∙s−1 (p ≤ 0.008). Conclusions: This study demonstrated greater absolute isokinetic PT, MP, and RVD for POST compared to PRE males and females across velocity. Furthermore, normalizing isokinetic PT to CSA or MVIC eliminated the sex- and group-related differences. Interestingly, although normalizing MP and RVD to CSA or MVIC eliminated the sex-related differences, the POST group remained higher than the PRE group. These results suggest that age-related increases in PT were explained by increases in muscle strength and size, while age-related improvements in MP and RVD could not be entirely accounted for by muscle strength and size differences. Practical Applications: In contrast to torque production, growth and development-related increases in power and RVD across the velocity spectrum may be dependent on factors other than maximal muscle strength and size. Therefore, when the goal is to improve performance beyond those observed with growth-related changes in muscle strength and size, training-related activities should be considered across a range of low to high velocities.

(12) Competition Level and Half Differences in External Load and Performance Measures During Matches in American Soccer

G. Ryan,1 D. DeJohn,2 H. Ramirez,2 L. Haaren,2 G. Hogan,2 S. Rossi,2 and R. Herron3

1Piedmont University;2Georgia Southern University; and3United States Sports Academy

Understanding the potential varying external load and physiological demands required across different levels of competition (i.e., collegiate and professional) throughout a match may help coaches, training staffs, and strength and conditioning professionals better design programs to maximize performance and potentially mitigate overuse injury risk. Purpose: The purpose was twofold: (a) To examine the differences of in-game GPS performance metrics between halves and level of competition in soccer players; and (b) To determine if any potential differences in variables of interest were influenced by player position (Goalkeeper [GK], Forward [F], Midfielder [M], Defender [D]). Methods: GPS (STATSport, Newry, North Ireland) match data from a single USL 1 Professional team (p: n = 23) and a single NCAA Division I collegiate team (C: n = 20) were compared. A total of 7 collegiate and 10 pro games were used for analysis. Only complete half data, where players were not substituted off during the half, were included for analysis. Matches were separated into first (H1) and second half (H2) for all analyses. GPS metrics populated by the software included for analysis consisted of: total time (TT); total distance (TD); maximum speed (Smax); explosive distance (ED); high metabolic load distance (HMLD); sprint distance (SD); number of sprints (#S); dynamic stress load (DSL); calories burned (CAL); were used for analyses. A two-way MANOVA was run examining Half and Level (of competition) on all variables of interest on all athletes. Additional MANOVAs were run separating the players by their positions. Post-hoc independent t-tests were used for any significant main effect finding. All significance was set at p ≤ 0.05. Results: Significant main effects were found between Level (F [1, 242] = 23.79, p < 0.01; Wilks' Λ = 0.47) and Half (F [1, 242] = 29.77, p < 0.01; Wilks' Λ = 0.53). Additionally, a significant interaction effect between Level and Half existed (F [1, 242] = 4.40, p < 0.01; Wilks' Λ = 0.15). Post-hoc analysis on the interaction revealed that the only team-wide difference was TT (F [1, 254] = 29.20, p < 0.01; Wilks' Λ = 0.11), with H2 being significantly longer in C (58.1 ± 5.4 min) than p (52.6 ± 1.7 min, p < 0.01). All other variable interactions were deemed statistically insignificant (p > 0.05). When separated by positions, additional significant interactions existed. Conclusions: Results indicate that all players, regardless of level of competition, experienced similar declines in physiological responses and performance measures as the game progressed. Additionally, both C and p players experienced mostly similar physiological stress throughout match play, as determined by minimal significant interactions. However, some positional differences did exist, which is worth further exploring. Lastly, C H2 was longer (∼9.5%) in TT, which may have influenced other performance variables. Practical Applications: Understanding the differences in load and performance experienced during match play between positions may help strength and conditioning professionals as they work with, or transition across, different competition levels. Staffs should note the potential decreases in physiological stress and performance that happens regardless of position and competition level from H1 to H2.

(13) Influence of Muscle Fatigue on Contractile Twitch Characteristics in Persons With Parkinson's Disease and Older Adults: a Pilot Study

M. Grahek,1 M. Magrini,1 J. Siedlik,1 C. Bickel,2 M. Bamman,3 and K. Hammond1

1Creighton University;2Samford University; and3Florida Institute for Human and Machine Cognition

Introduction: It is widely accepted that pathophysiological changes to the central nervous system of persons with Parkinson's disease (PD) result in negative effects on motor function. However, less information is known regarding the pathology of PD on skeletal muscle. Purpose: The purpose of this study was to determine the effect of a fatiguing isometric knee extension protocol on muscle mechanics using evoked twitch contractions in persons with PD and in non-impaired older adults (OLD). Methods: Thirteen persons with PD (M = 5, F = 3, 66 ± 9 years) and OLD (M = 4, F = 1, 65 ± 10 years) volunteered for this study. Participants performed 5-second maximal isometric voluntary contractions of the quadriceps femoris with 5-second rest for 3-minute. Every 30-second, during the rest intervals, a maximal transcutaneous electrical stimulus was administered to the quadriceps femoris to quantify evoked peak twitch torque (PTT), peak relaxation rate (pRR), and peak rate of torque development (pRTD). The highest torque (N·m) achieved during each evoked contraction was calculated and defined as PTT. The steepest positive 25-ms epoch slope (pRTD) and steepest negative 25-ms epoch slope (pRR) of the torque-time curve (N·m·s−1) were automatically calculated. Additionally, fatigue was calculated as percent decline using the following equation: %decline = 100–100 (PeakTorquefinal/PeakTorqueinitial). Linear regressions were performed on the pRTD, pRR, and PTT changes during the fatigue protocol. Slopes and y-intercepts were calculated for each linear regression model, and independent sample t-tests were used to identify significant differences in slopes and y-intercepts between the 2 groups (OLD vs. PD) in %decline, PTT, pRR, and pRTD. Effect sizes (Hedges' g) were calculated to determine the magnitude of differences between groups using pooled SD adjusted for sample size (g). For all analyses, the level of significance was set at α = 0.05 and were performed using R, version 3.6.0. Results: A large effect of voluntary fatigue (%decline) was observed (g = 1.58). There was no difference in the y-intercepts for pRTD between groups (Meandiff = 160 ± 85, p = 0.09; g = −2.25). However, there was a significant difference in the slopes between groups (Meandiff = −24 ± 9.9, p = 0.03; g = 2.99). The multilevel model was developed for descriptive purposes and also quantified the significant interaction effect (Group x Twitch: β = 24.38, SE = 9.98, p = 0.032) for varying slopes across groups. The multilevel model did not show a significant interaction effect for PTT (Group x Twitch: β = 1.69, SE = 0.9, p = 0.086; g = 2.09) or pRR (Group × Twitch: β = 14.67, SE = 7.86, p = 0.089). Additionally, there were no significant differences between groups for the y-intercepts (PTT: Meandiff = 7.5 ± 5.5, p = 0.2; g = −1.63; pRR: Meandiff = 95 ± 55 p = 0.11; g = −2.07) or slopes (PTT: Meandiff = −1.7 ± 0.89, p = 0.09; g = 2.26; pRR: Meandiff = −14 ± 8, p = 0.11; g = 2.09). Conclusions: These data indicate that skeletal muscle in persons with PD is less fatigable compared to non-impaired older adults. The rate, not the maximum capacity, of force generation of the muscle during a fatiguing knee extension protocol was affected by pD. Practical Applications: Coaches, clinicians, and practitioners may use the reduction in the rate of torque production in older adults following a fatiguing protocol to improve exercise programing.

(14) Relationship Of Pinch and Grip Strengths on Velocity and Spin Variables of Different Pitch Types by Collegiate Baseball Pitchers

D. Szymanski,1 A. Garcia,2 and M. Qiao1

1Louisiana Tech University; and2Baltimore Orioles

Baseball pitchers throw various types of pitches to disrupt the hitter's timing by changing speed, trajectory, and location. Pinching and gripping are fundamentally important to manipulate a thrown ball by a pitcher. Purpose: To measure and evaluate normative data for pinch and grip strength and assess the relationship between these data and pitch velocity and spin variables (spin rate, spin efficiency, and true spin) of different pitch types (four-seam fastball, curveball, slider, and changeup) thrown by collegiate baseball pitchers. Methods: Twenty-one Division I collegiate baseball pitchers (age = 19.9 ± 1.5 years, height = 186.6 ± 6.0 cm, body mass = 90.7 ± 13.8 kg, lean body mass = 77.3 ± 9.3 kg, percent body fat = 14.6 ± 5.2%) volunteered for this study. Tests included dominant (D) and non-dominant (ND) hand grip strength (GS), index finger pinch strength (IPS), middle finger pinch strength (MPS), total pinch (IPS and MPS measured simultaneously) strength (TPS), and combined pinch (IPS + MPS) strength (CPS). Pitch velocity, spin rate, spin efficiency, and true spin of the different pitches were recorded in a lab setting. Pitchers threw from a custom-built pitching mound into a pocket net 18.44 m away. The device used to record velocity and spin variable data was placed 4.72 m in front of the home plate with the camera facing the pitcher. Pitchers randomly threw 5 four-seam fastballs, curveballs, sliders, and changeup pitches from the windup. Paired sample t-tests were run on each of the strength measures. The velocity and spin variables of each pitch were correlated with DGS, DIPS, DMPS, DTPS, and DCPS by using a correlation matrix from raw data scores. Statistical analysis used Pearson product-moment correlation coefficient with an alpha level of 0.05. Correlations were listed as high (±0.800–1.0), moderately high (±0.600–0.799), or moderate (±0.400–0.599). Results: There were no statistical differences between D and ND pinch strengths or grip strength except TPS (p < 0.04). There was a moderately high significant relationship between DTPS and curveball true spin (r = 0.660, p < 0.04) and spin efficiency (r = 0.653, p < 0.04). There was a moderate significant relationship between DTPS and fastball velocity (r = 0.520, p < 0.02) and fastball spin rate (r = 0.509, p < 0.03). There were no other significant correlations found between any of the pinch and grip variables and the velocity, spin rate, spin efficiency, and true spin of the 4 pitches. Conclusions: These data provide normative values for pinch and grip strengths in collegiate baseball pitchers. There were significant relationships between DTPS and curveball true spin and spin efficiency as well as fastball velocity and fastball spin rate. There were no correlations between DIPS, DMPS, DCPS, or DGS on any of the different pitch variables. Practical Applications: For those who train baseball pitchers and would like to improve their pinch strength to potentially enhance the baseball spin variables, it is recommended to have pitchers engage in finger grip training. This may improve the rate of force development and maximal force applied to the baseball. It is recommended that pitching coaches and pitchers work on finding the most effective grip for each pitcher to develop the optimal spin variables for the pitches they throw. These data can help contribute to developing normative data for pinch and grip strength for college baseball pitchers.

(15) Contralateral Repeated Bout Effect of the Elbow Flexors in Untrained Males

A. Alberto,1 N. Coker,2 J. Renziehausen,1 M. Stock,1 D. Fukuda,1 M. Clark,1 and A. Wells1

1University of Central Florida; and2Springfield College

Introduction: Exercise-induced muscle damage (EIMD) develops following an unaccustomed bout of eccentric exercise, typically resolving within 3–7 days. However, damage is reduced after repeated exercise, known as the repeated bout effect (RBE). Protective effects from previous bouts may also transfer to the contralateral, unexercised limb. Purpose: Evaluate the magnitude of transfer of the RBE to the contralateral limb following eccentric exercise in untrained males. Methods: Nine untrained males (height: 173.4 ± 8.4 cm; mass: 76.8 ± 9.1 kg; age: 21.1 ± 2.5 years) volunteered to participate in this study. Untrained was defined as at least 6 months of no upper body exercise. Individuals completed 2 exercise bouts consisting of eccentric elbow flexion separated by 14 days. The exercise protocol consisted of 5 sets of 6 repetitions of the elbow flexors. The initial exercise bout (ECC1) was performed on the dominant limb. The repeated bout was performed on both the ipsilateral (ECC2-IL) and contralateral (ECC2-CL) limb in a random order. Range of motion (ROM), proximal and distal pain-pressure threshold (pPPT/dPPT), perceived soreness via visual analog scale (pVAS/dVAS), and maximal voluntary isometric contraction (MVIC) torque were assessed as EIMD measures at baseline (BL), immediately post- (IP), twenty-four hours post (24H), and 72 hours (72H) postexercise. Range of motion of the elbow was assessed using a manual goniometer. PPT was assessed at 60 and 80% of the distance between the acromion process and cubital fossa using a manual algometer. Pressure was applied until participants reported that the stimulus became painful, at which point PPT and level of soreness was rated using VAS. MVIC was assessed using an isokinetic dynamometer. Changes were interpreted using Hedges g effect size. Results: Across all bouts, large effects were noted for decreases in ROM at IP and 24H relative to BL (g's ≥ −1.180). However, effects for decreases in ROM at 72H compared to BL following ECC2-IL and ECC2-CL were small (g = −0.297) and medium (g = −0.604), respectively. Medium and large effects for greater ROM were observed at 24H (g = 0.503) and 72H (g = 0.950) during ECC2-IL compared to ECC1. Small and medium effects for greater ROM were observed at 24H (g = 0.420) and 72H (g = 0.730) in ECC2-CL compared to ECC1. Large effects were observed for decreased MVIC at IP compared to BL for all 3 bouts (g's ≥ −1.250), and at 24H compared to BL for ECC1 (g = −1.690) and ECC2-CL (g = −1.560). However, a small effect was observed for decreases in MVIC at 24H compared to BL in ECC2-IL (g = −0.481). Medium and small effects were observed for reduced MVIC at 72H compared to BL for ECC1 (g = −0.712) and ECC2-CL (g = −0.473). Greater MVIC was observed at 24H (g = 0.899) during ECC2-IL compared to ECC1. Changes across time or between bouts for all other measures were small or negligible (−0.410 ≤ g's ≤ 0.458). Conclusions: MVIC and ROM data suggested EIMD following each exercise bout. Results indicated a contralateral RBE for ROM while MVIC indicated an ipsilateral RBE, suggesting the importance of an initial mechanical stimulus. Differences in PPT/VAS between bouts were not observed, suggesting limited transfer of RBE to the contralateral arm. Practical Applications: The contralateral RBE may reduce EIMD without prior exercise. This may offer insight into loading strategies in the early stages of rehabilitation following a unilateral limb injury.

(16) Pacing Strategies for Women in a 20-Minute High-Intensity Functional Training Competition Workout Containing Muscle-Ups, Rowing, and Wall Balls

G. Mangine,1 J. Dexheimer,2 E. Zeitz,3 J. Tankersley,1 and B. Kliszczewicz1

1Kennesaw State University;2Therabody; and3Azusa Pacific University

High-intensity function training (HIFT) combines a variety of training modalities, exercises, and volume-loads into a workout where the goal is to minimize workout time to completion or maximize work completed within a set time frame. In the 5-week opening round of the major international competition featuring HIFT, athletes are given 4 days to produce their best score following each workout's release. Although multiple attempts are allotted, selecting an optimal pacing strategy would help delay fatigue during a workout, reduce the number of attempts needed to find their best score, and thus, help preserve performance over the course of the competition. However, because each workout features a unique design and little scientific evidence exists on this topic, athletes must base their strategies on their experience with workout elements that are familiar (e.g., specific exercises, repetition schemes). Purpose: To determine the best repetition and rest interval pacing strategies used by women during a 2020 HIFT competition workout that incorporated ring muscle-ups (MU), rowing, and wall balls. Methods: The best recorded effort in the final workout of the 2020 HIFT competition (20.5) was analyzed for a random sample of 79 women who ranked within the top 10,000 competitors (31.3 ± 6.5 years; 163 ± 5 cm; 60.8 ± 5.1 kg). Briefly, 20.5 required competitors to complete 40 ring muscle-ups, an 80-calorie row, and 120 wall balls within 20 minutes, in any order. Videos of each effort were analyzed to determine the number of sets and repetitions completed, as well as time devoted, for each exercise within each minute. Additionally, the count and duration of breaks, transitions, and failed repetitions were also recorded. These were used to calculate average rate and slope across each minute of the workout, and then related to 20.5 performance, which was quantified as the rate of repetitions completed per workout minute. Results: Significant (p < 0.05) Spearman's rho correlation coefficients were observed between 20.5 performance and several pacing variables. Subsequently, stepwise regression was used to produce two 20.5 performance prediction models from significantly related pacing variables (Model 1: MU workout rate; and Model 2: MU workout rate—Slope in time devoted to MU per minute) in a validation group (n = 40) and then cross-validated against another group (n = 39). As no significant differences were observed between these groups, the data were combined (n = 79) to create the final prediction models (Model 1: R2 = 0.82, SEE = 0.59 repetitions□second−1; Model 2: R2 = 0.86, SEE = 0.53 repetitions□second−1). Conclusions: In this specific workout, MU pacing strategy appears to be the most important consideration. A faster rate in 20.5 was observed when competitors completed more muscle-ups in the time they devoted to the exercise, and performance was further improved when MU's were emphasized earlier in the workout. Practical Applications: Our data suggests that in a workout containing ring muscle-ups, rowing, and wall balls, women should place the highest priority on completing muscle-ups early and at a faster pace. As pace diminishes, competitors should then transfer their focus onto completing the other, less technically demanding exercises to maximize their performance.

(17) In-Season External Load Measures of Men Collegiate Soccer Athletes

J. Fields,1 J. Merrigan,2 F. Brown,3 and M. Jones3

1Springfield College;2West Virginia University; and3George Mason University

Introduction: Periodized training programs manipulate training and recovery strategies to optimize performance and minimize fatigue. Quantitatively monitoring external loads may minimize injury risk and improve physical performance. Therefore, tracking collegiate athlete in-season training load is important to achieving a balance between stress and recovery as athletes are faced with multiple games per week, frequent travel, and academic stressors. Purpose: To describe the external loads of a men's collegiate soccer team during practice and games at the start of in-season play. Methods: In the first 2 weeks of the competitive season, National Collegiate Athletic Association Division I soccer athletes (n = 19; mean ± SD, age: 20.3 ± 0.9 years; body mass: 77.9 ± 6.8 kg; body height: 178.87 ± 7.18 cm; body fat: 10.0 ± 5.0%; V̇o2max: 65.39 ± 7.61 ml·kg−1·min−1) wore a global positional system device (GPS/GNSS) during practices (n = 8) and games (n = 3). Starters were classified as players who maintained a minimum playing time of 45 minutes per game (n = 10); other players were considered non-starters (n = 9). Each game was separated by 4 days of practice and recovery. External load metrics collected were: total distance (TD), player load (PL), high-speed distance (HSD, >13 mph (5.8 m·s−1)), high inertial movement analysis (IMA, >3.5 m·s−2), and repeated high intensity efforts (RHIE). Multivariate analyses of variance assessed differences in external load measures for practices and games in starters and non-starters (p < 0.05). Relative to game loads, practices were quantified as high (>1 SD above the mean), medium (1 SD below the mean), low (2 SD below the mean) and very low (3 SD below the mean). Results: For starters, TD (game, 8064 ± 3133 m; practice, 2922 ± 1234 m; 36% of game load), PL (369 ± 132 AU vs. 923 ± 279 AU, 40% of game load), HSD (63 ± 54 m vs. 287 ± 162 m, 22% of game load), IMA (15 ± 9 vs. 34 ± 16, 45% of game load), and RHIE (8 ± 5 vs. 23 ± 10, 32% of game load) were lower in practices compared to games (Λ = 0.344, F = 39.355, p < 0.001). Non-starters were exposed to significantly lower loads in practice relative to the starters' game loads (TD: 2683 ± 1162 m, 55% of game load; PL: 375 ± 133AU, 40% of game load; HSD: 97 ± 322 m, 38% of game load; IMA: 13 ± 10, 38% of game load; RHIE: 6 ± 4, 26% of game load) (p < 0.001). Eight practices were classified as very low for TD and PL, 7 practices were classified as very low for IMA, and 6 practices were classified as very low for HSD and RHIE. No practices were classified as high or medium. Conclusions: Athletes were exposed to lower external loads in practice sessions compared to games. Non-starters were subjected to 25–55% of game loads during practice. No practices were classified as medium or high loads, with the majority of practices (75–100%) being classified as very low. Therefore, practice did not simulate game volumes or intensities. Practical Applications: An individualized approach to monitoring is recommended to ensure starters receive adequate recovery and non-starters receive exposure to game-load physical stress. Improper periodization can result in fatigued athletes, injuries, and poor-quality training sessions that decrease athlete preparedness. In consideration of the short turnover between games in collegiate soccer, it is recommended short duration, high intensity training sessions be included to prepare athletes for game loads.

(18) Performance and Injury Characteristics in Grappling Sports—A Systematic Review

C. Perez, J. Winchester, K. Pacheco, A. Carrillo, and M. Tugel

University of the Incarnate Word

Grappling is one of the oldest forms of sport, with works of art depicting grappling dated from 3000 BC. The focus for grappling sports encompasses stand up techniques including gripping, takedowns, trips, and throws, along with groundwork consisting of pins, joint locks, control positions, chokeholds, and others. Success in grappling sport requires the use of leverage, power, strength, and conditioning along with tactical decision making and strategy. In the last few decades, participation in these sports has grown rapidly. Despite their worldwide popularity and long history, obtaining clear data on injury rates and predictors is challenging. Purpose: The purpose of this systematic review was to examine the rates and most common types of injuries in the more popular grappling sports (Wrestling, Judo, SAMBO, and Brazilian Jiu-jitsu), as well as parameters which may help to predict the likelihood of injury in persons who participate in them. Methods: Searches of PubMed, SPORTDiscus, and Web of Science were undertaking from Jan 2019 through July of 2020, to identify the most appropriate literature for the review, with secondary search of reference lists used to expand the number of possible articles. The review was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols (PRISMA-P). Inclusion criteria specified original investigations which reported data on injury rates and type along with attribute variables such as strength, range of motion, or conditioning, among others. Results: Eight studies met our inclusion criteria. The most commonly reported musculoskeletal injuries across all grappling sports are injuries to the elbow, knee, or spine. In addition, whole body isometric strength, local muscular endurance, power, and grip strength have been shown to be important attributes for success in grappling sports. However, few, if any, studies were able to draw a clear link between those same attributes and rates or type of injury. Conclusions: Despite clear links in other sports, there is a scarcity of data at this time to determine factors which contribute to injury rates in grappling sports. Future investigations are needed to directly explore injury predictors in grappling sports. Practical Applications: Despite a lack of current research in this area, it seems reasonable that a focus on the strength of the musculature and integrity of the connective tissues in and surrounding the elbow, knee, and spine have the potential to pay positive dividends in injury reduction for persons participating in grappling sports. Furthermore, practitioners looking to improve attributes related to competition success should focus on both dynamic and isometric strength, muscular power, local muscular endurance, and anaerobic conditioning.

(19) Assessment of Two Wearable Sensor Systems During Speed and Agility Tests

F. Brown,1 B. Guthrie,1 J. Fields,2 R. Baker,1 and M. Jones1

1George Mason University; and2Springfield College

Introduction: Team court sports require acceleration, deceleration, and quick directional change movements. The popularity of athlete workload monitoring has increased, and a variety of wearable sensor systems are available, yet little information on comparison of metrics between systems exists. Purpose: To determine the validity and reliability of 2 wearable sensors during speed and agility tests. Methods: Subjects (n = 2; mean ± SD, age: 30.42 ± 2.59 years; body mass: 77.7 ± 2.6 kg.; height: 180.3 ± 3.6 cm) wore 2 sensor units. Unit 1 (U1), a 10 Hz GPS/GNSS system with an integrated accelerometer (Catapult S5), was worn in a supportive harness with the unit positioned between the scapulae. Unit 2 (U2), a strap with a heart rate sensor and a 10 Hz GPS system with an integrated accelerometer (Polar Team Pro), was worn at the level of the xiphoid process with the unit positioned on the center of the chest. Three tests were marked via tape measure and administered: 5-10-5 (20 m; n = 6); 15 m sprint +5 m deceleration zone (20 m; n = 3); arrowhead agility test (35 m; n = 5). Metrics collected for comparision between units included: maximum velocity (MV); total distance (TD); acceleration (AC), AC1 (2.00–2.99 m·s−2), AC2 (3.00–4.99 m·s−2); deceleration (DC), DC1 (−2.00 to −2.99 m·s−2), DC2 (−3.00 to −4.99 m·s−2). Pearson Product-Moment correlations examined the strength of relationship between U1 and U2 metrics (p < 0.05). Further, one-sample t-tests compared TD from each unit to tape-measured distances. Intraclass correlations (ICC) were run to assess reliability of each unit (p < 0.05). Correlation magnitudes were classified: trivial (<0.1), small (0.1–0.29) moderate (0.3–0.49), large (0.5–0.69), very large (0.7–0.89), nearly perfect (0.9–0.99). Results: Large and very large relationships existed between U1 and U2 for AC1 (r = 0.618, p = 0.032), DC1 (r = 0.764, p = 0.004), DC2 (r = 0.651, p = 0.022), and TD (r = 0.804, p = 0.002) for all tests. TD values from U1 and U2 were different from the tape-measured distances for 5-10-5 (U1:9.51 ± 2.34 m vs U2:12.68 ± 1.38, p < 0.001), 15 m sprint + 5 m deceleration (U1: 8.08 ± 6.28 m, p = 0.006) vs U2: 10.05 ± 0.709, p < 0.001), and arrowhead (U1:28.62 ± 6.72 m, p < 0.015 vs U2: 31.60 ± 2.71 m, p = 0.003) tests. The higher ICC values for U1 indicate it is a more reliable device (Table 1). Conclusions: Positive relationships between metrics indicate U1 and U2 sensors to be in good agreement. Both units underestimated the actual tape-measured distances of all speed and agility tests. The stronger reliability of U1 measures of acceleration and deceleration suggest it may be a better system for monitoring agility drills. Practical Applications: While the U1 may be a better sensor for monitoring quick changes of direction and agility movements, caution should be exercised when using either sensor for measuring distance. Although there was good agreement between units, it is recommended one sensor system be selected to enable consistent measures of athlete load.

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Table 1:
Reliability of metrics of unit 1 and unit 2.

(20) Effects of Creatine Loading With a Specific View on Acute Exercise Performance: an Update

B. Wax,1 C. Kerksick,2 J. Mayo,3 A. Jagim,4 B. Lyons,5 and R. Tucker6

1Mississippi State University;2Lindenwood University;3University of Central Arkansas;4Mayo Clinic Health System; and5University of Mississippi,6University of Houston-Victoria

Creatine is one of the most studied and popular ergogenic aids for both athletes and recreational lifters seeking to improve sport and exercise performance, augment training, and mitigate recovery time. Studies consistently revealed that creatine monohydrate has a positive ergogenic effect on muscle performance in short-duration, high-intensity exercise performance, and training adaptations. This encompasses increased strength, increased maximal work output, increased maximal force output, improved fat-free mass, and an enlarged creatine pool to amplify the production of adenosine triphosphate during high-intensity exercise. Purpose: This study conducted a review of the available literature to ascertain the most effective way to ingest creatine monohydrate for maximizing intramuscular creatine stores and augmenting acute exercise performance. Methods: A range of databases, including PubMed, Google Scholar, EBSCO-host, were searched for this study. This was conducted using keywords in conjunction with creatine or creatine supplementation. Designated studies evaluating the effects of creatine supplementation dosage on exercise performance were chosen for inclusion. Further citations were found, evaluated, and incorporated from the bibliographies of the selected literature. Results: A review of the literature revealed the most efficient way to increase muscle creatine and phosphocreatine quickly was by a loading phase of creatine monohydrate for 2–7 days at 20 g·d−1 (4 doses of 5 g·d−1), followed by daily ingestions (1 dose of 3–5 g·d−1 or 5–10 g·d−1 for larger individuals) to maintain amplified intramuscular creatine levels. Creatine stores generally increased between 20 and 40%, depending on the baseline intramuscular creatine stores. Furthermore, performance augmentation was more significant in the 5–7 days of creatine loading, in comparison to 2 days of loading. Other beneficial regimens found in the literature effectively increased creatine stores (2 g·d−1·30 d−1; 3 g·d−1·28 d−1; 6 g·d−1·84 d−1 days) up to similar magnitudes intramuscularly over a more extended time, with efficacious exercise outcomes. Conclusions: Our findings establish that a loading phase of 5–7 days at 20 g·d−1 (4 doses of 5 g·d−1) is the best way to increase intramuscular creatine stores quickly for performance augmentation. Practical Applications: A literature review indicates that individuals seeking immediate ergogenic performance effects from creatine implement a 5–7 days loading phase; however, other creatine loading regimens are productive over a more extended period.

(21) Effects of Fasted vs. Fed-State on Anaerobic Power in NCAA Division III Football Players

P. Prins, J. Abraham, N. Anton, R. Martin, T. Rose, and J. Buxton

Grove City College

Recently, fasting-based interventions such as intermittent fasting (IF) has garnered interest as an alternative dietary strategy for improving metabolic and training adaptations compared to fed exercise. IF is a term that encompasses many definitions involving fasting for varying periods (usually for 12 hours or more). To date few studies have examined the impact of fed vs fasted state anaerobic exercise performance. Purpose: To investigate the effects of IF (12- and 16-hour) vs fed state on anaerobic power performance in NCAA Division III college football players. Methods: Fifteen male college football athletes (age 19.8 ± 0.75, height 183.1 ± 8.1 cm, weight 92.7 ± 19.3 kg) participated in this randomized, crossover design study. Subjects completed 3 anaerobic power tests, 40-yard dash, vertical jump, and the Wingate anaerobic test, in either a fed (2 hours following ingestion of carbohydrate rich meal) or fasted state (12- and 16-hour). Results: There were no significant differences between fed vs fasted state for the 40-yard dash (Fed: 5.21 ± 0.27 seconds; 12-hour: 5.21 ± 0.28 seconds; 16-hour: 5.19 ± 0.30 seconds; p = 0.829) and Wingate anaerobic power test (peak power, mean power, and fatigue index all p's > 0.05). There was a significant difference between the fed vs fasted state for the vertical jump test (p = 0.011). Participants jump height was significantly higher in the fed (67.3 ± 11.7 cm) and 16-hour IF state (66.8 ± 9.9 cm) compared to the 12-hour IF state (63.7 ± 9.1 cm) (p = 0.017 and 0.024, respectively). However, there was no significant difference between fed and 16-hour IF state (p > 0.05). Conclusions: The present study suggests that IF has no adverse effects on anaerobic power compared to a fasted state. However vertical jump performance was reduced after a 12-hour fast compared to a fed state and 16-hour fast. Practical Applications: Performing exercise in the fed state and 16-hour fasted state have analogous effects on anaerobic power. The current findings provide coaches, athletic trainers, and players with a better understanding of exercising in a fasted state and anaerobic power.

(22) Effects of Essential Amino Acids on High-Intensity Interval Training Fatigue Outcomes and Workload Progression

K. Hirsch,1 G. Brewer,2 L. Gould,3 C. Greenwalt,4 A. Nelson,3 H. Cabre,3 M. Blue,5 and A. Smith-Ryan3

1University of Arkansas for Medical Sciences;2University of Connecticut;3University of North Carolina at Chapel Hill;4Florida State University; and5High Point University

Essential amino acid (EAA) intake prior to exercise has been shown to extend incremental exercise time to exhaustion (TTE) and delay central fatigue, but cumulative effects of EAA on workload progression are unknown. Compared to males, females recover more quickly between repeated bouts of high-intensity exercise, suggesting higher fatigue resistance. Protein intake prior to high-intensity interval training (HIIT) has been shown to enhance metabolic and strength outcomes, especially in females, but potential differences in effects of EAA on indices of fatigue between sexes has not been explored. Purpose: To explore the effects of EAA on HIIT fatigue outcomes and the cumulative effects on training workload over 8 weeks in untrained males and females. Methods: Thirty-eight sedentary, overweight and obese adults (50% female; 36.5 ± 6.1 years; 35.4 ± 6.7% body fat) completed 8 weeks of HIIT (2 d·wk−1; 6–10 sets) on an electronically braked cycle ergometer. Nineteen participants consumed 3.6 g of EAA 30 minutes prior to and after HIIT sessions. Heart rate (HR) and rating of perceived exertion (RPE) were recorded throughout each session as indices of within training fatigue. On the final set of each session, participants rode to volitional fatigue and TTE (s) was recorded. If TTE was >75 s, watts were increased at the next session to progress workload. Differences between HIIT groups (with and without EAA) were evaluated at baseline, 4-weeks, and 8-weeks. Differences in TTE and watts were evaluated by repeated measure ANOVAs (2 × 3); differences in HR and RPE were evaluated by separate repeated measure ANOVAs (base: 2 × 6; 4 weeks: 2 × 9; 8 weeks: 2 × 10), in the full sample and in males and females separately. Results: There was no difference in TTE or watts with EAA (mean difference (Δ): 2.2 ± 17.5 s; p = 0.9) at any time point. HR and RPE increased with each set within a HIIT session (p < 0.001), but were not significantly different with EAA at any time point (p > 0.05). Results were similar when evaluating males and females separately, but in females, RPE was lower with EAA throughout the HIIT session at baseline (Δ: 0.7–1.7; p = 0.157) and significantly lower at 4-weeks (Δ: 1.1–2.2; p = 0.016), despite no differences in HR (p > 0.05). At 8-weeks, there were no longer differences in RPE throughout the session (Δ: −0.2–0.6; p = 0.987). Conclusions: Pre-post workout EAA did not extend TTE during exercise or enhance training workload across 8 weeks of HIIT in untrained, overweight and obese adults. Results do suggest that pre-workout EAA may reduce perceived exertion during the first 4 weeks of training in females, but effects were not maintained at week 8. Practical Applications: In the early weeks of a high-intensity exercise program, EAA consumption 30 minutes prior to HIIT may reduce perceived exertion from “very hard” to “hard” in females, which could have implications for overall exercise enjoyment and long-term adherence. Effects of EAA on perceived exertion may not be maintained once a certain level of intensity and/or fitness level is achieved.

(23) Differences Between Males and Females on the Same High-Intensity Functional Training Competition Workout With Different Prescribed Loads

J. Dexheimer,1 G. Mangine,2 B. Kliszczewicz,2 E. Zeitz,3 and J. Tankersley2

1Therabody;2Kennesaw State University; and3Azusa Pacific University

High Intensity Functional Training (HIFT) has evolved from a training program with workouts emphasizing metabolic conditioning, weightlifting, and gymnastic movements into the “sport of fitness”. Each year, athletes from all over the world participate in a global HIFT competition, aiming to complete workouts for the fastest time to completion (TTC), for as many rounds or repetitions as possible in a set time, or for maximal weight lifted. Each workout has prescribed load and movement standards, with males typically being assigned heavier loads than females. While this takes into consideration the known strength differences, workouts are not amended for the known aerobic differences between sexes. Previously, different acute physiological responses have been noted between men and women following HIFT workouts. However, no study has examined whether these prescription differences affect workout performance. Purpose: To determine if differences in workout performance existed between males and females on the same workout with different prescribed loads. Methods: A randomized selection of the top 3,000 males and top 3,000 females from the global HIFT competition were analyzed. Data was extracted for one workout (20.1) from a freely accessible online database. Final analysis was conducted on 34 males (28.9 ± 4.6 years; 177 ± 6.6 cm; 86.3 ± 7.7 kg) and 34 females (29.8 ± 5.5 years; 163.6 ± 5.9 cm; 62.9 ± 4.4 kg). The analyzed consisted of 10 rounds of 8 ground to overhead (Males: 95 lbs.; Females: 65 lbs), completed by either a snatch or clean and jerk, and 10 bar facing burpees. Workout performance was measured as TTC and rate per minute (R·min−1). Rate per minute was calculated by dividing the number of rounds by TTC. An independent t-test was used to determine significant differences between males and females for TTC and R·min−1. Results: No significant difference was displayed between males and females for age (p = 0.459) nor ranking (p = 0.720) and all participants completed all 10 rounds. A significant difference was revealed between males and females for TTC (p = 0.002) and R·min−1 (p = 0.002). Males (TTC: 11.3 ± 1.1 minutes) had an 8% faster completion rate than females (TTC: 12.3 ± 1.4 minutes) and males (Rate: 0.892 ± 0.094 R·min−1) displayed approximately a 9% faster R·min−1 than females (Rate: 0.820 ± 0.090 R·min−1). Conclusions: For similarly ranked male and female HIFT athletes, males completed more repetitions per minute resulting in a faster TTC. Practical Applications: Findings revealed that although the same workout was performed at different prescribed loads, males completed the workout faster and completed repetitions at a faster rate than females. This suggests that either the load prescribed was too light for males or too heavy for females. Given the cardiovascular component to a workout like this, it may be advisable to have differing repetitions on other movements. Future investigation should further examine which physiological variable is the best indicator of performance for a workout of this nature, distinctly for males and females, as this may aid an equitable workout prescription.

(V201) Changes in Lactate and Peak Velocity in Response to Loaded Jumps With Different Structures

Y. Chen,1 H. Wei,1 J. Pádecký,2 D. Omcirk,2 J. Maleček,2 M. Jonáš,2 and J. Tufano2

1Beijing Sport University; and2Charles University, Czech Republic

Purpose: The purpose of this study was to explain how different set structures influence peak velocity (PV) and lactate during and after loaded countermovement jumps (CMJs). Methods: Fifteen resistance-trained university-aged men (20.6 ± 2.06 years, 178.3 ± 5.33 cm, 77.0 ± 5.78 kg, 1RM back squat ≥150% body weight) participated in 4 protocols on 4 separate days separated by a minimum of 48 hours of rest. The protocols all included 30 CMJs with a load of 30% 1RM and 240 seconds of total rest, but the duration and frequency of the rest periods were different: (a) Traditional sets (TS) included 3 sets of 10 repetitions with 120 seconds rest; (b) rest-redistribution 5 (RR5) included 6 sets of 5 repetitions with 48 seconds rest; (c) RR2 included 15 sets of 2 repetitions with ∼17.14 seconds rest; and 4) RR1 included 30 sets of 1 repetition with ∼8.27 seconds rest. Before each protocol, subjects sat for 10 minutes and their baseline blood lactate (Pre) was measured. Then, subjects performed a standardized general warm-up, followed by the assigned protocol for the day. A linear position transducer GymAware collected the PV of the barbell. The ability to maintain PV (PV maintenance) was then calculated as: PV maintenance = mean of all repetitions/fastest PV of the first 10 repetitions. Lactate was measured again immediately (P0) and 5 minutes (P5) after the final repetition. Results: There was a significant difference between the protocols for PV maintenance (p < 0.05). RR5 (96.26% ± 1.79%) better maintained PV than TS (94.91% ± 1.82%; p < 0.05, d = 0.75 [95% CI 0.4%–2.3%]), RR2 (94.96% ± 1.88%; p < 0.05, d = 0.71 [0.1–2.5%]), and RR1 (94.24% ± 2.12%; p < 0.01, d = 1.03 [0.7–3.3%]). For lactate, there was a significant (p < 0.001) main effect for protocol, TS (6.06 ± 3.45 mmol·L−1) was significantly higher than RR5 (4.39 ± 2.34 mmol·L−1; p < 0.01, d = 0.57 [0.58–2.76]), RR2 (3.85 ± 2.09 mmol·L−1; p < 0.001, d = 0.60 [1.28–3.13]) and RR1 (3.89 ± 1.85 mmol·L−1; p < 0.01, d = 0.78 [1.06–3.29]). There was a significant (p < 0.001) main effect for time, with P0 (6.01 ± 2.37 mmol·L−1; p < 0.001, d = 2.19 [2.94–4.75]) and P5 (5.48 ± 2.49 mmol·L−1; p < 0.001, d = 1.81 [2.35–4.28]) were significantly higher than Pre (2.16 ± 0.74). P0 was significantly higher than P5 (p < 0.01, d = 0.22 [0.23–0.82]). And there was a protocol*time interaction, TS (7.96 ± 2.66 mmol·L−1) was significantly higher than RR2 (5.24 ± 2.05 mmol·L−1; p < 0.05, d = 1.15 [0.59–4.86]) and RR1 (5.05 ± 1.55 mmol·L−1; p < 0.01, d = 1.34 [0.66–5.16]) in P0, and TS (7.85 ± 2.70 mmol·L−1) was higher than RR5 (5.30 ± 2.03 mmol·L−1; p < 0.05, d = 1.07 [0.36–4.74]), RR2 (4.22 ± 1.89 mmol·L−1; p < 0.001, d = 1.56 [1.92–5.35])and RR1 (4.53 ± 1.60 mmol·L−1; p < 0.01, d = 1.50 [1.23–5.41]) in P5. Each protocol's P0 and P5 were all significantly higher than their Pre (all p < 0.001). RR2 and RR1's P0 were significantly higher than P5 (p < 0.05, d = 0.52 [0.15–1.88] and 4.45 ± 1.45 mmol·L−1; p < 0.05, d = 0.33 [0.02–1.01]). Conclusions: RR5 maintained PV better than the other protocols, indicating that performing somewhere between 2 and 10 repetitions in a row may be ideal for maintaining PV during loaded CMJs. TS induced the greatest lactate response, indicating that it may have been more fatiguing than the RR protocols despite having the same total rest time. Practical Applications: When performing loaded CMJs during training, RR protocols are likely beneficial for maintaining PV and decreasing metabolic stress. Furthermore, performing 1 or 2 repetitions in a row may be less metabolically taxing than performing 5 repetitions in a row.

(V202) The Effects of Moderate Intensity Strength Training Coupled With Blood Flow Restriction: A 12 Week Intervention

K. Barrett

Western University

Blood flow restriction training (BFRT) has been suggested to increase muscle size and strength in trained and untrained individuals when using light load intensities at approximately 30 percent 1- rep maximum (RM). However, there is little data to support its use when working with moderate load intensities, specifically, above 50 percent of an individual's 1-RM. Purpose: The purpose of this study was to evaluate the effects of moderate load intensity BFRT on muscle size and strength of the biceps brachii after a 12-week strength training intervention. Methods: Nine, previously strength trained, participants performed an elbow flexion exercise at 70 percent of their individualized 1-RM, twice per week, while blood flow of the brachial artery was reduced by 50 percent in the dominant (right) arm. Biceps brachii muscle mass, and maximal isometric voluntary contractions were assessed before and after 12 weeks of training. Results: Using dual-energy x-ray absorptiometry, Biceps brachii muscle mass did not significantly increase after the 12-week training period in either arm, (BFRT arm = 1.85%, non-BFRT arm 3.01%), (p = 0.249). There were no significant differences in isometric arm strength between pre- and post-training, BFRT arm: (pre: 88.5 ± 16.6, vs. post: 87.2 ± 16 N·m), non-BFRT arm: (pre: 87.8 ± 18.8, vs. post: 85.6 ± 20.2 N·m), (p = 0.407). Practical Implications: We conclude that unlike low load intensity BFRT, performing BFRT at higher load intensities does not augment muscle growth or muscular strength in trained, young, men when compared to normal strength training alone.

(V203) Differences in Performance Recovery Between Men and Women Following a High-Volume Resistance Exercise Bout

M. Lebron,1 E. Tagesen,1 B. Gibson,2 J. Laudato,3 E. Arroyo,1 and A. Jajtner1

1Kent State University;2University of Oregon; and3Florida State University

Purpose: To assess changes in performance between men and women after a high-volume resistance exercise bout. Methods: Twelve resistance trained men (n = 7, 22.4 ± 3.3 years, 177.5 ± 6.5 cm, 86.1 ± 20.4 kg, 1RM: 1.83 ± 0.29xBW) and women (n = 5, 21.4 ± 1.5 years, 162.7 ± 6.2 cm, 58.7 ± 6.9 kg, 1RM:1.24 ± 0.19xBW) completed a high-volume resistance exercise bout consisting of 8 sets of 10 repetitions of the back squat at 70% of their predetermined 1RM (HVRE). During visit 1 (V1), participants completed a standardized warm-up followed by a one repetition maximum (1RM) of the barbell back squat. Following the 1RM, qualifying participants were fitted for the isometric mid-thigh pull (110° hip angle) and the isometric squat (75% standing stature). To accommodate completing the HVRE and follow-up visits during the follicular phase (Days 2–5), women were asked to return for a confirmation 1-RM (V2) 96-72 hours prior to the HVRE session. During Visit 3 (V3), participants completed the same standardized warm-up, and the HVRE protocol. Performance tests consisted of the vertical jump (VJ), isometric mid-thigh pull (IMTP) and isometric squat (ISQT). Tests were completed before (PRE), as well as immediately (IP), one hour (1H), 24 hours (24H), and 48 hours (48H) after exercise. Three maximal effort attempts were completed for each performance test and averaged prior to data analysis. Both the rate of force development (RFD) over the first 100ms and isometric force (IF) at 100ms were analyzed for the IMTP and ISQT. A Mixed Model Regression with group and time as fixed factors were used to analyze data. Results: An interaction was observed for VJ (F = 7.161, p = 0.001), with men demonstrating significant decreases in jump height from PRE to IP (p < 0.001) and 1H (p = 0.005) before returning to baseline performance at 24H (p = 0.055) following the HVRE. No difference was observed for women between PRE and all other time points (p ≥ 0.151). A significant interaction was also observed for IMTP IF (F = 3.282, p = 0.032). In men, force decreased from PRE to 1H (p = 0.036) and 24H (p = 0.005), whereas force decreased in women from PRE to IP (p = 0.008), 1H (p = 0.013), and 24H (p = 0.043). A main effect of time was observed for ISQT IF (F = 0.0868, p = 0.009), with a significant decrease from PRE to IP (p = 0.010) and 1H (p = 0.032) and a return to baseline performance at 24H (p = 0.215) and 48H (p = 0.434). A main effect of group was observed for VJH (F = 49.431, p = 0.000), IMTP RFD (F = 11.464, p = 0.009), IMTP PEAK (F = 10.785, p = 0.011), and ISQT PEAK (F = 11.464, p = 0.020). Conclusions: Women appear to be more resilient to muscle damage, as shown through a lessened decrease in force and power production following a high-volume resistance exercise bout. Additionally, men are observed to produce greater overall force and power compared to women. Practical Applications: During their follicular phase, women may be able to complete a greater relative volume of work, in comparison to men, before a decline in performance is observed.

(V204) Gender Differences in LAT Pulldown Exercise Performance and Fatigue

K. Beyer,1 E. Zsido,1 S. Mookerjee,1 B. Comstock,1 and E. Lindermuth2

1Bloomsburg University; and2East Tennessee State University

The LAT pulldown is an upper body pull exercise that targets muscles of the back and elbow flexors. Handgrip strength may be a limiting factor in lat pulldown performance as well. Gender may influence lat pulldown performance and fatigue due to differences in body composition and handgrip strength. Purpose: To assess the differences in lat pulldown exercise performance and fatigue between genders. Methods: Thirty-two college-aged, recreationally trained men (n = 16; 23.32 ± 1.69 years; 1.80 ± 0.06 m; 88.22 ± 8.69 kg) and women (n = 16; 22.06 ± 1.11 years; 1.65 ± 0.06 m, 66.71 ± 12.47 kg) were recruited for this study. The testing protocol was completed on a single day and required the performance of the LAT pulldown exercise using a standardized neutral grip handle. Participants performed a general warmup on a rowing machine and a specific warmup including, dynamic movements, isometrics, and banded exercise. Following the warmup, participants completed an isometric handgrip (HG) test in the dominant hand and a 1-repetition maximum (1RM) test for the lat pulldown. Following a 15-minute recovery, participants completed 3 sets of the LAT pulldown exercise at 80% 1RM completed to failure with a 2-minute rest interval between sets. The number of repetitions completed per set was recorded and the total number of repetitions calculated. The average velocity (AV) and peak velocity (PV) of each completed repetition was recorded with a PUSH Band 2.0 attached to the handle, and a set average calculated for each participant. After the completion of the 3 sets, a post HG test was completed to determine grip fatigue. Differences in the repetitions completed per set, AV, PV, and HG fatigue were analyzed with mixed factorial ANOVA with Bonferroni adjusted post hoc tests. The alpha level was set a p ≤ 0.05, and all data are presented as mean ± standard deviation. Results: ANOVA revealed a trend for a gender × set interaction (p = 0.057) and a significant main effect of set (p < 0.001). Post hoc tests revealed that number of repetitions completed did not significantly change for women from set 1 (7.0 ± 1.9 reps) to set 2 (5.9 ± 1.3 reps) to set 3 (6.0 ± 1.4 reps). However, men had a significant change in repetitions completed from set 1 (7.5 ± 2.5 reps) to set 2 (p = 0.005; 5.6 ± 1.6 reps) and set 3 (p < 0.001; 4.8 ± 1.8 reps). No significant gender × set interaction was noted for AV (p = 0.955) or PV (p = 0.879); however, a significant main effect of gender was noted for AV (p = 0.013) and PV (p = 0.017). Men had a significantly faster average AV and PV (0.46 ± 0.13 and 0.73 ± 0.21 m/s, respectively) than women (0.35 ± 0.2 and 0.56 ± 0.18 m/s, respectively). Furthermore, no gender × time interaction was observed for HG (p = 0.278), but there was a significant main effect of time (p < 0.001). Across genders, HG decreased from pre (42.1 ± 14.2 kg) to post (39.0 ± 13.6 kg). Conclusions: Despite completing lat pulldowns at the same relative intensity, only men experienced a significant decline in repetitions completed, while women were able to maintain repetitions across sets. However, men completed repetitions at a higher AV and PV than women. While HG fatigue did occur across the sets of exercise, there was no difference between genders. Practical Applications: When prescribing upper body pull exercises, such as the lat pulldown, it is important to consider these gender differences in performance and fatigue. More research is needed to understand the underlying physiology of these differences.

(V205) Correlation Between Force- and Various Impulse-Based Dynamic Strength Indices

M. Haischer,1 J. Krzyszkowski,2 S. Roche,1 and K. Kipp1

1Marquette University; and2Texas Tech University

The dynamic strength index (DSI) is the ratio between dynamic and isometric peak forces, and is used to inform training recommendations for athletes. However, given that the ability to express force over time (i.e., impulse) is a better predictor of performance than peak force, recent work proposed using impulse, rather than peak force, to calculate DSI and better evaluate an athlete's capacity to express maximal strength during dynamic tasks. Currently, it remains to be determined if impulse DSI calculations should include the total eccentric and concentric impulse or only the concentric impulse. Purpose: The purpose of this study was to investigate the correlations between force-based DSI (fDSI) and (a) total impulse (TiDSI), and (b) and concentric impulse (iDSI). Methods: Nineteen female collegiate lacrosse players performed countermovement jumps (CMJ) and isometric mid-thigh pulls (IMTP) during preseason testing. Peak forces were extracted from CMJ and IMTP force-time traces, and phase-specific impulse times of CMJ trials were recorded. IMTP impulse was then calculated by integrating force-time traces over the specific CMJ-matched impulse times (TiDSI: eccentric + concentric; iDSI: concentric only). DSI values were calculated as ratios between CMJ and IMTP force (fDSI) and impulse (TiDSI, iDSI), respectively, and Spearman rho correlations were used to assess the relationship between metrics. Results: A strong correlation (ρ = 0.770 [0.557, 0.878], p < 0.001) was found between fDSI and TiDSI, while a moderate correlation was found between fDSI and iDSI (ρ = 0.644 [0.283, 0.840], p = 0.003). An almost perfect relationship linked the 2 impulse-based DSI metrics (ρ = 0.954 [0.906, 0.966], p < 0.001). Conclusion: fDSI exhibits strong and moderate positive correlations with total impulse and concentric impulse based indices, respectively. Due to the importance of time-dependent force output in dynamic performance, contextualizing fDSI with impulse-based metrics may be valuable to practitioners looking to inform training foci among their athletes in a more ecologically valid manner. Practical Applications: If using previously established fDSI thresholds (i.e., <0.6 should train force expression during dynamic tasks; >0.8 should train maximal force production), a concerning number of athletes would receive training recommendations from impulse-based metrics that were in conflict with those from fDSI (TiDSI: 14 of 19 athletes; iDSI: 7 of 19 athletes) (Table 1). Thus, alternative thresholds for TiDSI and iDSI may need to be explored. Nevertheless, evaluating DSI using phase-specific impulse times from the CMJ and time-matched impulse from IMTP is a way that practitioners can incorporate an individual athlete's movement signature into strength evaluations.

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Table 1:
Dynamic strength indices for each athlete.

(V206) Effects of a 12-Week Resistance Training Program on Stretch-Shortening Cycle Function in Young Male Athletes

N. Tumkur Anil Kumar,1 J. Radnor,1 J. Oliver,1 R. Lloyd,1 J. Pedley,1 I. Dobbs,1 and M. Wong2

1Cardiff Metropolitan University; and2Cardiff Met University

Purpose: The purpose of this study was to examine the effects of a 12-week training intervention on SSC function in pre- and post-peak height velocity (PHV) males. Methods: Forty male athletes, aged 9–17 years, were categorized into pre-PHV (maturity offset: <0 years) or post-PHV (maturity offset: >0 years), assessed using anthropometric measures. Athletes within each maturity group were sub-divided into experimental (EXP) or control (CON) groups. The EXP groups participated in a twice-weekly, 1-hour, combined traditional resistance and plyometric training program for 12-weeks. The drop jump, performed from a 30 cm box on to portable force plates, was used to assess SSC function. Performance variables (jump height, ground contact time and reactive strength index [RSI]), and absolute and relative kinetic variables (peak forces, impulse, power and work done) during the braking and propulsive phases were assessed at pre- and post-intervention. To determine the effect of the training intervention, differences in all variables were analyzed using separate 2 × 2 × 2 (maturity × group × time) repeated measures analysis of variance. Effect sizes were calculated to interpret magnitude of within group effects using the Hedge's g statistic. Results: Significant maturity × group × time interactions were observed for jump height, RSI, force at peak COM displacement, take-off peak force, net impulse, mean braking power and mean propulsive power (p < 0.05). The post-PHV EXP group showed small to moderate significant improvements (p < 0.05) from baseline to post-intervention for jump height (g = 0.67) and RSI (g = 0.38). Increases in the performance metrics in this cohort were caused by small to moderate significant improvements in the majority of kinetic variables assessed (see Table 1). No other groups made any significant changes following the 12 weeks (p > 0.05). Conclusions: The results suggest that a 12-week, combined training intervention can elicit small improvements in impulse, and moderate improvements in power output in post-PHV athletes. Furthermore, these changes underpin improvements in jump height and RSI in the more mature youths. However, the combined training program failed to elicit a significant change in pre-PHV children, and these findings may be explained by synergistic adaptation, where the combined training acted as a potent stimulus in addition to the natural, adaptive processes the post-PHV EXP participants were experiencing. Practical Applications: The novel findings of the study suggest that when prescribing training programs to develop the underpinning kinetics of SSC function in youth, practitioners need to consider maturity status. While post-PHV children display a positive responsiveness to a 12-week combined traditional resistance and plyometric training program, pre-PHV children may require a longer intervention, or a greater focus on plyometric training.

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Table 1:
Changes observed from baseline to post-intervention in post-PHV EXP boys.

(V207) Validity of a Sex-Neutral Repetition Prediction Equation to Estimate 1RM Bench Press

J. Mayhew,1 W. Brechue,2 A. Oligschiaeger,1 and M. Hunter3

1Truman State University;2A. T. Still University; and3University of Alabama at Birmingham

A number of repetition equations exist for estimating 1-repetition maximum (1RM) bench press performance. Many were generated on sex-specific samples with limited cross-validation. It would be convenient if a single prediction equation was applicable to both sexes with acceptable accuracy. Purpose: To develop a repetition-to-fatigue (RTF) equation with universal accuracy for predicting 1RM bench press in men and women. Methods: College men (n = 166, age = 19.9 ± 1.7 years, height = 178.6 ± 6.4 cm, weight = 73.8 ± 11.6 kg) and women (n = 135, age = 19.0 ± 1.0 years, height = 165.8 ± 6.4 cm, weight = 60.8 ± 9.6 kg) were measured at the conclusion of 12 weeks of periodized resistance training. Each participant performed a 1RM using the standard touch-and-go method and repetition weight (RepWt; 2-10RM range) RTF on separate days. A 20% cross-validation sample was randomly selected to assess the accuracy of prediction equations. Results: Women performed significantly more RTF (6.9 ± 2.5) at 81.5 ± 9.3% of 1RM than men (6.1 ± 2.2 and 83.4 ± 7.4%, respectively). The prediction equation produced from the validation sample (1RM [kg] = 1.07 RepWt + 0.993 RTF + 5.51 Sex [M = 1, W = 0] − 3.46; n = 236) had a strong correlation (R = 0.98), small standard error (SEE = 4.9 kg) and acceptable coefficient of variation (CV = 9.1%). Removing sex as a variable did not diminish the effectiveness of the equation (1RM [kg] = 1.17 RepWt + 0.88 RTF − 4.0, R = 0.98, SEE = 5.1 kg, CV = 9.5%). Cross-validation (n = 66, 38 M, 28 F) produced a significant correlation (r = 0.98) and nonsignificant difference between predicted (53.4 ± 25.3 kg) and actual 1RM (54.0 ± 27.1 kg) for equation 1 and equation 2 (Eg 1: 53.1 ± 25.3 vs. Eq 2: 54.0 ± 27.1 kg, respectively) with combined sexes. This new sex-neutral equation had a small negative bias (−1.2 kg) and a 95% LoA = −8.0 to 5.7 kg in women, while in men, this sex-neutral equation had no bias (0.0 kg) and a 95% LoA = −11.8 to 11.7 kg. Conclusion: A simple sex-neutral equation can be used to predict 1RM bench press with acceptable accuracy in both men and women. Practical Applications: Exploration of the accuracy of the sex-neutral equation in untrained participants and athletes should be done. If universal accuracy is confirmed, it would simplify the prediction of 1RM as a useful tool in resistance training.

(V208) Association Between Reactive Strength Index and Anthropometric Characteristics in Baseball Players

J. Martínez-Rodríguez, and F. Ramirez-Marrero

University of Puerto Rico, Rio Piedras Campus

Although vertical jump height significantly predicts baseball-specific performance; reactive strength is a more specific power evaluation because it considers the time in contact with the ground right before the jump. Evidence of the association between anthropometric characteristics and ground contact time in vertical jump performance among baseball players is sparse. Purpose: To evaluate the association between anthropometric variables and ground contact time during a reactive strength vertical jump test in baseball players. Methods: Twenty-one baseball athletes who had no physical injuries participated in the study. Athletes completed a modified jump test protocol in which the first jump was initiated outside the mat, immediately followed by 4 rebound-continuous jumps. The protocol was repeated 3 times with 2-minute rest periods in between. Body weight, standing height, trunk length, leg length, waist circumference, and waist-to-height ratio were also determined. Correlation and regression analyses were conducted to evaluate the associations between anthropometric variables and ground contact time before the vertical jump. Results: Standing height was the only anthropometric variable significantly associated with ground contact time (r = 0.44, p = 0.046). Leg length was the standing height component close to significant association with ground contact time (r = 0.39, p = 0.08). Conclusions: Our results suggest that taller baseball players, particularly those with longer legs, tend to have higher ground contact time; and, therefore, lower reactive strength that might potentially influence baseball-specific performance. Practical Applications: Standing height and leg length are anthropometric characteristics to consider when determining baseball-specific performance based on reactive strength evaluations.

(V209) Differences in Sprint Profile and Squat Jump Performance Between Collegiate Sprinters and Non-sprinters

M. Dietze-Hermosa,1 S. Montalvo,2 M. Gonzalez,2 N. Cubillos,2 S. Rodriguez,2 E. Martinez,2 and S. Dorgo2

1The University of Texas at El Paso; and2University of Texas at El Paso

Sprint profile measures have become popular to examine and monitor sprint performance of various athletic populations. This adds to the battery of tests already used by strength and conditioning practitioners to assess athletic performance, such as the vertical squat jump (SJ). However, it is unclear how these measures differ between trained sprinters and other non-sprinter power-based athletes (jumpers and throwers). Purpose: To determine the differences in sprint profile measures and SJ performance between sprinter and non-sprinter athletes. Methods: Twenty-five Division I track and field athletes (sprinters = 12; non-sprinters = 13) participated in this study. Subjects completed 2 SJ trials with a linear encoder attached to a 20 kg bar placed on the subject's upper back. SJ measures of interest during the concentric phase of the jump were jump height, maximum force, maximum velocity, maximum power, and rate of force development. Lastly, subjects completed two 30-meter acceleration sprints. The MySprint mobile application was used to assess subjects' sprint profile including maximal theoretical horizontal force, maximal theoretical velocity, optimal velocity, maximal theoretical power, maximal speed, maximal ratio of force, force-velocity slope, and decrease in ratio of force. The best trial of each test was used for statistical analysis. Mann-Whitney U or Independent samples t-tests were used to determine group differences and corresponding effect sizes (Cohen's d) were calculated. Results: Maximal theoretical horizontal force (t[24] = 1.81; p = 0.08) and maximal theoretical power (t[24)]= 1.78; p = 0.08) during the 30-m acceleration sprint presented marginal differences between sprinters and non-sprinters. The effect sizes for group differences for maximal theoretical force and maximal power were moderate (Cohen's d = 0.72 and 0.69, respectively). No other variables presented marginal significant differences. Conclusion: There are differences in maximal horizontal force and maximal power attained during sprinting between sprinter and non-sprinter athletes. There appears to be no difference in SJ performance between sprinter and power-based non-sprinter athletes. Practical Applications: While non-sprinter power-based athletes appear to perform similarly to sprinters in a vertical SJ, differences in horizontal force ground application and maximal power during sprinting suggest that these performance components must be specifically targeted for athletes seeking to improve their sprint performance.

(V210) The Backwards Overhead Medicine Ball Throw Compared to the Bilateral Broad Jump as Predictors of Acceleration Sprint Completion Times

A. Martinez Ruiz,1 S. Montalvo,1 M. Gonzalez,1 N. Cubillos,1 M. Dietze-Hermosa,2 and S. Dorgo1

1University of Texas at El Paso; and2The University of Texas at El Paso

The bilateral broad jump (BJ) has often been used to monitor and predict sprint performance. Similarly, the backwards overhead medicine ball throw (BOMBT) is used in track and field training to monitor power output in athletes. Purpose: To compare the predictive ability of the BJ and BOMBT test on acceleration sprint completion times. Methods: A convenience sample of 27 male and female Division I collegiate Track and Field athletes were recruited for this study. Subjects performed 3 trials of the BJ and 3 trials of the BOMBT test while standing on 2 dual-axis force platforms with data being collected at 1,000 Hz. BJ distance was measured from the athlete's take-off to the landing heel and the BOMBT distance was measured from the standing position of the athlete to the first point where the medicine ball landed after being released. This was followed by three 30-m sprints with timing gates used to record completion times. The best trial of BJ and BOMBT (as measured by distance), and the sprint (less completion time) were kept for the analysis. Force data were exported into MATLAB, where data was filtered using a Butterworth digital low pass filter with a cutoff at 50 Hz. Thereafter, force data were processed to obtain kinematic variables which included mean and peak velocity, concentric time, and eccentric time and kinetics variables including mean and peak force, power, rate of force development, and rate of power development) of the BJ and BOMBT. Data were then exported into Rstudio for statistical analysis using R programming language. A series of individual stepwise regressions with forward-backward elimination were conducted for all performance, kinematic, and kinetic variables of the BJ and BOMBT to determine which variables were predictive of sprint completion times. Multicollinearity was also assessed via the variance inflation factor (VIF) when 2 or more variables enter the predicting model; if collinearity was present (VIF >5), then variables were removed (backward-elimination) and the model was adjusted. Results: A simplified model of the BJ using only jump distance was able to predict 65% of the variance of the 30-meter sprint completion time (R2 = 0.65; p < 0.01). In addition, adding more kinetic or kinematic variables did not improve the prediction model for the BJ. The best predictor model for the BOMBT was composed of throw distance, peak force, and peak power, and was able to predict 37% of the variance of the 30-meter sprint completion time (R2adjusted = 0.68; p < 0.05). A simplified model of the BOMBT test using throw distance was not able to predict 30-meter sprint completion time (R2 = −0.04; p > 0.05). Conclusion: Based on the results the BJ can be used to accurately predict acceleration sprint completion times. Practical Applications: Strength and conditioning professionals and track and field athletes might opt to monitor the BJ given its predictive ability of sprint completion times. On the other hand, the BOMBT test may not be the best test for predicting sprint completion times.

(V211) Relationships Between Internal and External Training Load Over a Full Season With Collegiate Female Soccer Players

A. Ishida, S. Travis, and M. Stone

East Tennessee State University

Session ratings of perceived exertion (sRPE) and global navigation satellite systems (GNSS) are common athlete monitoring measures to quantify internal and external training load (TL) in soccer. Division I (DI) female soccer players spend 2–3-weeks in pre-season followed by 12–16 weeks of in-season including conference (C) and non-conference (NC) match-play. Due to the short pre-season, the players accumulate higher external TL during NC than C, which could alter the relationship between internal and external TLs over a season. Additionally, individual variability could confound internal and external TL data due to players' match external TL and playing status. However, few investigations have been conducted to examine how in-season individual variability alters the relationship between internal and external TL. Purpose: The purpose of this study was to examine the relationship between internal and external TL during the in-season with DI female soccer players. Methods: Sixteen players (19.8 ± 1.4 years; 165.7 ± 6.0 cm; 62.6 ± 7.8 kg) participated. Data included sRPE and GNSS TL from 19 matches (10 NC and 9 C) during the 2019 in-season. The sPRE was calculated by multiplying a modified Borg rating of perceived exertion by session duration per minutes. Match external TL was assessed using 10 Hz GNSS and 100 Hz accelerometry units (Optimeye S5, Catapult Innovation, Melbourne, Australia). Variables of interest included total distance covered (m) and high speed running distance (HSR; m). HSR was considered as running velocity above 15 km·hour−1. All statistical procedures were performed using RStudio (version 1.1.463) with the packages of nlme (3.1-142) and lme4 (1.1-21). Linear mixed model (LMM) was loaded with fixed effect of total distance, HSR, and in-season phase (NC or C) and random effect of player. The final model of LMM met the assumptions for homoscedasticity, normal distribution of residuals, random intercept, and multicollinearity. A 95% confidence interval was calculated for the fixed and random effect of the final model. Statistical significance was set at p ≤ 0.05. Results: Total distance (coefficient = 0.07 [0.05, 0.10], t = 6.04, p < 0.001) and HSR (coefficient = 0.25 [0.04, 0.46]), t = 2.34, p = 0.02) were significant predictors of sRPE. However, in-season predictions of sRPE were not statistically significant. (coefficient = −24.9 [−92.3, 42.4], t = −0.72, p = 0.47). Significant random effect was observed for intercept (p < 0.001) while the random effect was not statistically significant for total distance and HSR (p = 0.14 and 0.07). Thus, the final model only included the fixed effect of total distance, HSR and the random intercept of player. Fixed effects of total distance and HSR accounted for 54% of the variance in sRPE (R2 = 0.54). The random effect of intercept explained 12% of the variance (R2 = 0.12). Conclusions: Total distance and HSR were predictors of sRPE during match-play with DI female soccer. However, in-season individual variability appeared to have only a small effect on altering the relationship between internal and external TL. Practical Applications: Group assessment can provide a better understanding of the relationship between internal and external TL by providing more accurate representation for overall team preparedness. Individual variability may not substantially affect this relationship.

(V212) Efficacy of 6-Week Suspension Training Exercises on Fitness Components in Older Adults

C. Pierle,1 A. McDaniel,2 L. Schroeder,2 M. Heijnen,2 and W. Tseh2

1Plantation Village; and2UNC Wilmington

Purpose: To determine the efficacy of a 6-week suspension training exercises on fitness components in older adults. Methods: Three male and 8 female volunteers (Age = 80.0 ± 4.9 years; Height = 166.3 ± 9.5 cm; Body Mass = 71.2 ± 4.9 kg; Body Fat = 34.2 ± 2.6%) participated in the 6-week suspension training program. Pre- and post-fitness assessments comprised of handgrip dynamometer, functional reach, and overall balance. The 6-week suspension training intervention required individuals to perform a variety of exercises on the suspension training system for 45 minutes, twice per week. Results: Data revealed no significant difference between pre- and post-body fat (34.2 ± 2.6% vs. 34.3 ± 2.8%) or handgrip dynamometer (22.4 ± 1.9 kg vs. 22.8 ± 1.8 kg). There was, however, a significant difference between pre- and post-functional reach (57.2 ± 6.4 in vs. 68.6 ± 4.3 cm; p = 0.02) and overall balance (67.5 ± 2.4 in vs. 72.2 ± 2.2 UNITS; p = 0.02). Conclusions: From a practical perspective, a specifically-designed 12-session suspension training exercise program was adequate to enhance core stability and overall balance amongst older adult participants.

(V213) Effects of Physical Fitness Measures on Physical and Mental Quality of Life in Professional Firefighters: An Exploratory Study

M. Toczko, M. Fyock-Martin, and J. Martin

George Mason University

Due to occupational demands professional firefighters (FF) require high levels of physical fitness. Common FF occupational tasks include carrying equipment, pushing and pulling objects, climbing ladders and moving continuously for long durations under load. It has been reported that multiple components of physical fitness are associated with the ability to perform FF occupational tasks. While for many populations higher levels of physical fitness are associated with greater physical and mental health it is not clear if this is true for FF. Repetitive work-related stress due to both physical and mental demands placed on FF can be detrimental to health. Health related quality of life (HRQoL) is a measure that includes physical and mental determinants of health. Purpose: To explore the effects of physical fitness on physical and mental health in professional FF. Methods: Twenty-three FF (21 males, 2 females, age: 36.8 ± 7.1 years, years of service: 8.7 ± 6.6 years, height: 177.0 ± 5.7 cm, mass: 88.2 ± 16.0 kg) participated in the study. The physical fitness assessment included the following tests: body composition, sit and reach, vertical jump, 1-repetition maximum bench press, maximum repetitions of pull-ups, maximum repetitions of push-ups, maximal plank hold, Y-balance test, and a 1-mile run. HRQoL was measured using the Short-Form (SF) 36 Questionnaire. Physical and mental health composite scores were then computed. Using the median value FF were divided in into groups for high and low physical and mental health. Group differences in each of the components of fitness were assessed using an ANCOVA with gender, age, years of service, height and weight as co-variates. Descriptive statistics were calculated for each variable. Statistical significance was set to p < 0.05. Results: The mental and physical health composite scores were 55.0 ± 4.3 and 46.5 ± 7.5, respectively. A negative association was found between mental and physical health (r = −0.419, p = 0.046). The high physical health group had significantly greater fat-free mass and less fat mass than the low group (Table 1). FF who reported lower mental health scores had superior results for many of the fitness variables (Table 1). Conclusions: Our findings suggest that self-reported physical health is affected more by body composition measures of fat-mass and fat-free mass than other physical fitness measures. Unexpectedly, for many of the physical measures greater performances were found in the group with lower self-reported mental health. We believe this finding may indicate that fitter FF may be exposed to greater mental stressors which in turn negatively impacts mental health. Practical Applications: Practitioners working with FF to improve physical fitness needed for occupational performance should be aware non-fitness factors may ultimately determine the HRQoL of FF. A holistic approach that includes a focus on overall wellbeing rather than fitness only may be most appropriate.

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Table 1:
Effects of fitness on professional firefighter physical and mental quality of life.

(V214) Analysing the Impact of Active vs. Passive Recovery on Broad Jump Performance in Collegiate Males

A. Bosak,1 M. Shanahan,2 B. Ziebell,3 M. de Moors,4 H. Nelson,5 A. Blackley,6 R. Lowell,7 and A. Frech8

1Liberty University;2Beach Body;3Team Rehab;4Amazon;5University of Mississippi;6Western Carolina University;7Mississippi State University; and8Palmer Chiropractic College

The broad jump (BJ) test is used to assess an individual's horizontal power ability. Traditionally, the recovery period between each BJ is of the passive nature, yet prior studies utilizing other modes of power assessment have evaluated the impact of active recovery (AR) vs. passive recovery (PR) on subsequent power production. Also, previous research with AR vs. PR on BJ performance in active females suggested that PR may contribute to a further jumping distance vs. AR. However, this recovery protocol and the impact on BJ performance has not been evaluated with active males. Purpose: to investigate the potential differences between active vs. passive recovery (AR vs. PR) on BJ performance in no less than averagely fit college-age males. Methods: After having descriptive data (Ht. = 177.67 ± 7.10 cm, Wt. = 85.02 ± 14.35 kg, BF% = 15.44 ± 7.02, age = 22.62 ± 2.67 years) recorded, 32 no less than averagely fit college-age males participated in an 8 minute dynamic warm-up. Subjects were then given a 4 minute PR period after the warm up and then completed 4 familiarization jumps (i.e., trials). After another 4 minute PR period, subjects completed 2 series of jumps (i.e., four trials apiece) in a counterbalanced order with either AR or PR between each jump. The AR period consisted of subjects completing stepping exercises for 60 seconds utilizing a 20 cm step height, while PR had subjects stand still until their next jump. The AR and PR jump series were separated by a standardized 4 minutes PR period. Excluding the first jump of each series, the farthest jump for AR vs. PR was compared using a Paired-Samples t-test with significant differences occurring at p ≤ 0.05. Results: No significant differences (p = 0.472) occurred between AR (237.09 ± 27.54 cm) and PR (236.85 ± 26.73 cm). Conclusions: The results suggest that AR has no significant impact on BJ performance when using no less than averagely fit college-age males. However, 62.5% of the subjects did benefit from PR vs. AR. Future research may be required to assess the impact of sports specific training status and self-selected recovery protocol types on broad jumping performance in male and female athletes. Practical Applications: The mean results of the present study suggest that when assessing the broad jump performance of no less than above averagely fit males, the type of recovery protocol utilized during the recovery period between jumps may not have a significant impact on immediate subsequent jumping performance. However, individual variability may exist between subjects and it may be best to determine the characteristics of those individuals who benefit from AR vs. those who benefit from PR as it pertains to their broad jumping performance.

(V215) Investigation of Functional Weight Bearing Internal and External Rotations Measurements in Various HIP Positions

V. Arbel,1 and T. Amasay2

1University of Illinois at Chicago; and2Barry University

Range of motion (ROM) of the hips is an essential element in sports that is associated with rate of injuries and performance. Decreased hip ROM is associated with higher risk of groin, hamstrings, and shoulder injuries in baseball players as well as decreased pitching biomechanics. Hip ROM deficits in soccer and ice hockey players is associated with increased risk of hip, groin, and non-contact ACL injuries. Decrease in hip internal rotation (IR) and external rotation (ER) ROM have been identified as injury risk factors and an element that may affect performance. Most of hip IR and ER tests were performed in a non-weight bearing positions. Purpose: To investigate the effects of functional weight bearing IR and ER ROM in different hip positions, which may assist in better understanding factors that might affect the prevalence of injury and performance in athletes. Methods: Nineteen participants (10 men and 9 women; 23.2 ± 3.8 years) lower extremity IR and ER ROM were tested in 8 randomized hip positions, on Standing Firm rotational device. The hip positions were flexion IR (FIR), flexion ER (FER), extension IR (EIR), extension ER (EER), abduction IR (ABDIR), abduction ER (ABDER), adduction IR (ADDIR), and adduction ER (ADDER). Each position was repeated 3 times for both right and left sides. Participants max IR and max ER ROM and the sum of max IR plus ER (IRER ARC) were measured in each hip position and recorded using a video camera. Test-retest reliability for each hip position, side, intrarater, and interrater were between good to excellent, ICC 3,1 0.802-0.997. Hence, the highest score of IR and ER ROM, and IRER ARC were used for further analyses. Repeated measure ANOVA was performed to determine the influence of different hip positions on hip max IR and ER ROM, followed by Bonferroni post-hoc analyses, α < 0.05. One-way MANOVAs were used to compare the influence of body side and gender on the max IRER ARC, α < 0.05. Results: Repeated measure ANOVA found significant main effects in hip max IR and ER (p < 0.0001). Post-hoc analyses found that FIR (41.4° ± 8.9°) was significantly smaller than FER (51.1° ± 15.2°), p = 0.001; smaller than ABER (48.1° ± 12.2°), p = 0.01; and larger than EIR (32.0° ± 7.5°), p < 0.0001. FER was found to be significantly larger than EIR, p< 0.0001; ADIR (42.2° ± 10.1°), p = 0.006; ADER (43.7° ± 16.2°), p = 0.001; ABIR (39.4° ± 9.8°), p < 0.0001. EIR was significantly smaller than EER (47.7° ± 14.1°), p < 0.0001; smaller than ADIR, ADER, ABIR, and ABER (p< 0.0001). Lastly, EER was significantly larger than ABIR (p = 0.025) and ABER was significantly larger than ABIR (p = 0.001). No significant differences were identified by the 1-way MANOVAs between body side and between gender for IRER ARC in each hip position, p > 0.3. Mean and standard deviation for IRER ARC were as follow: in hip flexion was 92.5° ± 21.2°; in hip extension was 79.6° ± 18.7°; in hip adduction was 85.9° ± 22.8°; in hip abduction was 87.4° ± 19.3°. Conclusions: Hip starting position was found to influence lower extremity max IR and ER ROM. No significant differences were observed between body side and gender for IRER ARC. Practical Applications: Practitioners need to take into consideration that measuring functional max IR and ER ROM in different weight bearing hip positions may influence the measurements outcome. These findings provide important information to consider when developing injury prevention, performance programs, rehabilitation interventions, and performance testing protocols.

(V216) Nutritional Practices and Use of Ergogenic Resources by Amateur University Bodybuilding Athletes in Pre-competition

O. Machado, and F. Gianolla

Physical Education Faculty of Sorocaba's YMCA

Bodybuilding is a sport where muscular volume, appearance and proportion are important and, in order to achieve the muscle size and quality that allow you to participate in a competition, many athletes use supplements and anabolic steroids. The University Bodybuilding competition is growing. Thus, is important to know how university athletes handle with the use of dietary supplements and anabolic steroids. Purpose: This research aimed to identify the behavior behind the use of nutritional supplements and anabolic steroids in university bodybuilding practitioners. Methods: An online questionnaire was applied in order to collect data from a group of 20 Bodybuilding athletes who participated in a university competition in Physical Education Faculty of Sorocaba's YMCA (6 women and 14 men) aged between 20 and 34 years old. Results: Of the 20 athletes, 55% reported not using dietary supplements before starting the preparation and the other 45% already did. Of the athletes who used the supplements, 60% did it on their own and 40% followed the recommendations of health professionals. Twelve supplements were mentioned as used before starting the preparation, with creatine (32%), whey protein (10%), glutamine (10%) and multivitamins (7%) as the most used. During the preparation for the event, 70% of the athletes used dietary supplements and 30% did not. In the preparation phase, 42% of athletes supplemented themselves and 58% turned to health professionals. The supplements most used during preparation were creatine (30%), whey protein (27%) and BCAA (8%). Regarding the use of anabolic steroids before preparing for the competition, 85% reported not having used it and only 15% reported having used it, which represented 3 athletes. The 3 users reported having been guided by a medical professional. During the preparation, 80% did not use it and 20% did it, representing a total of 4 competitors, where 2 mentioned having done it with medical guidance, 1 did it alone and the other with the help of a friend. The substances used were: stanozolol, testosterone enanthate and oxandrolone. Conclusions: This research indicates that athletes practicing university bodybuilding, before competing, just over half of them used dietary supplements and when they started preparing for a competition the use of supplements increased by 15%. Most of them do their self-management regarding the use of supplements, both before and during preparation. Both before and during preparation, the most widely used supplement was creatine and most university competitors do not use anabolic steroids. Practical Applications: As university bodybuilding is not widespread in the world, with few reports of competitions like this, this research shows that it is possible to prepare without the use of steroids and that food supplements seem to be important during competition, being creatine and whey protein the most used and of the existing supplements, the ones that have higher levels of evidence of its effectiveness.

(V217) Kinetic Differences Between Maximal Countermovement, Hurdle, and Box Jumps

M. Janikov,1 J. Pádecký,1 V. Doguet,2 and J. Tufano1

1Charles University, Czech Republic; and2Atelier Maker

Purpose: The purpose of this study was to explain how different jumping tasks influence key kinetic parameters of the jump. Methods: Recreationally trained university-aged men (n = 20, 25.2 ± 3.5 years, 180.2 ± 4.4 cm, 80.0 ± 7.8 kg, 11.5 ± 2.7% body fat) participated in 3 testing days separated by a minimum of 48 hours of rest. The subjects performed a standardized general warm-up at the beginning of each testing day, followed by 10 warm-up jumps, and 3 maximal jumps. Every subject performed countermovement jumps (CMJ) on the first testing day and then hurdle jumps (HJ) or box jumps (BJ) in randomized order on the second and the third testing day, respectively. The jumping task used during warm-up jumps matched the maximal jumps on every testing day. The height of the hurdle and the box was 50 cm. Ten seconds inter-repetition rest interval was used for all jumps. All subjects were instructed to jump as high as possible and to land softly, regardless of the jump type. The ground reaction forces during take-off and landing were measured by a force plate (Kistler 9286BA; Kistler Instruments Inc., Winterthur, Switzerland) with sampling frequency of 1,000 Hz. A linear position transducer (GymAware Power Tool; Kinetic Performance Technology Pty. Ltd., Canberra, Australia) was attached to a wooden dowel which was held across the shoulders behind the base of the neck by the subjects. Peak take-off force (PF), total impulsion time (TIT), and peak impact force (IF) were calculated from the force plate data and jump height (JH), peak take-off velocity (PV), and countermovement depth (CMD) were calculated from the linear position transducer data. Results: JH was higher during CMJ than HJ and BJ (p < 0.001, d = 2.02 [95% CI 1.22–2.73] and p < 0.001, d = 1.27 [0.57–2.73], respectively). Furthermore, JH was higher during BJ compared to HJ (p < 0.05, d = 0.54 [−0.10 to 1.16]). CMD was significantly deeper (p < 0.05) during CMJ than HJ and BJ with a moderate effect size (d = 0.56 [−0.08 to 1.18] and 0.31 [-0.32 to 0.93], respectively). For PF, PV, and TIT, there were no differences. However, there was a moderate effect for shorter TIT during HJ and BJ than CMJ (d = 0.54 [−0.10 to 1.16] and d = 0.31 [−0.32 to 0.93]). IF was less during BJ than CMJ and HJ (p < 0.001, d = 2.53 [1.70–3.36] and p < 0.001, d = 3.00 [2.10–3.91], respectively). Conclusions: The subjects used deeper countermovement and reached greater jump height when performing CMJ compared to HJ and BJ. Simultaneously, BJ resulted in greater jump height than HJ and lower impact forces than CMJ and HJ. Practical Applications: The present study showed that exercise selection influences vertical jump kinetics. CMJ produced the highest jump, probably as a result of deeper countermovement, but this may not be desired for sports including faster stretch-shortening cycle movements, in which case the HJ may be more appropriate. On the other hand, athletes who may want to decrease eccentric loading might benefit from BJ as it produces similar take-off force and velocity as the other variations but decreases impact forces. Coaches can use these results to better match plyometric exercises to the needs of specific populations.

(1) The Effects of Exercise while Suspended on Low Back Pain and Daily Step Activity Following an 8-Week Training Protocol: An Exploratory Study

R. Alasmar, and S. Stevens

Middle Tennessee State University

Numerous modalities have been used as strategies for rehabilitation and management of low back pain (LBP). Many research studies have explored these modalities to understand their effect on mitigating LBP. Core stability training is 1 of the most commonly used rehabilitation strategies for improving lumbopelvic hip control and the dynamic stability of the lumbar spine in people with LBP. However, no study has explored the effect of exercising while suspended on mitigating LBP. A device has been developed allowing people with LBP to exercise while suspended in a harness apparatus. This device has been reported by a handful of users that there were benefits for mitigating LBP and improving health related quality of life without medication or surgical intervention. Purpose: The purpose of this randomized exploratory study was to evaluate an 8-week strength training program using this device in adults with LBP and its implication on (a) reducing LBP and (b) increasing daily step activity (DSA) and quantifying changes following an 8-week training protocol when comparing the experimental (EXP) group (n = 4; 45.5 ± 10.38 years) to the controlled (CON) group (n = 6; 45.5 ± 14.02 years). Methods: A total of 10 male and female adults (BMI = 27.2 ± 4.22; 45.5 ± 12.05 years) with LBP and pain intensity equal to or less than 40% in the Oswestry Low Back Pain Disability Questionnaire (OLBPQ) were qualified for inclusion in the study and were recruited from Middle Tennessee State University and the surrounding areas of Murfreesboro, TN to participate in an 8-week strength training program (3 visits per week, 1 hour per visit) using the PENDL (exercise suspension device). The OLBPQ perceived pain scales was used to measure changes in back pain intensity; while the Modus StepWatch3 Activity Monitor system was used to measure DSA across 3 consecutive days pre and post 8-week strength training program. Baseline difference between the 2 groups on the primary and secondary outcome variables were assessed using a “2-way repeated measure ANOVA.” All statistical significance was established at alpha level of p < 0.05. Results: Mean values were: OLBPQ pre-training (EXP17.00 ± 10.39%; CON 4.33 ± 5.85%), post-training (EXP 4.00 ± 4.89%; CON 9.00 ± 10.41%); while DSA pre-training (EXP 3252 ± 2,430.92 Steps; CON 4357.83 ± 1823.90 Steps), post-training (EXP 3560.5 ± 3,186 Steps; CON 3953 ± 1931.62 Steps). Reduction in LBP was related to the 8-week training protocol using the PENDL F(1,8) = 11.86, p = 0.009, η2 = 0.59, power = 0.85; while 8-week training protocol had no effect on DSA F(1,8) = 0.23, p = 0.642, η2 = 0.28, power = 0.07. Conclusions: The 8-week strength training protocol showed a statistically significant difference in reducing LBP in the EXP group when compared to the CON group. However, the study demonstrated no statistical significant difference in increasing the average number of DSA between the 2 groups. Practical Applications: Benefits for evaluating this new fitness machine in this trial would enhance our understanding to its impact on reducing LBP and ultimately improving overall health and well-being. Secondary benefit could provide a new tool and an alternative choice to reduce LBP. Lastly, this work could be an extension to potential research studies to explore therapeutic uses within the rehabilitation and fitness industries (e.g., its effect on sports specific skills, autism, ADHD and PTSD); which adds to the research body of knowledge.

(2) Internal but Not External Workload Measures Are Related to Indices of Heart Rate Variability in Collegiate Women's Basketball Players

H. Cintineo, A. Chandler, B. McFadden, T. Cardaci, M. Binetti, and S. Arent

University of South Carolina

The autonomic nervous system (ANS) is comprised of the sympathetic and parasympathetic branches. Together, these systems regulate many bodily systems including the cardiovascular system and, more specifically, heart rate (HR). At rest, parasympathetic activity should predominate while the sympathetic system is withdrawn. Accumulated stress, including training stress, can augment parasympathetic and sympathetic drive at rest, resulting in increased resting HR and decreased HR variability (HRV) which is a measure of the variance in times between heart beats. Purpose: The purpose of this analysis was to assess relationships between measures of ANS activity measured during film sessions and workload metrics in a highly ranked Division I women's collegiate basketball program. Methods: Ten female basketball players were included in this analysis. All methods were approved by the IRB, and informed consent was waived. Athletes wore heart rate monitors with accelerometry during team activities, which included weekly film sessions and on-court practices. During film, data from a 10-minute interval in which heart rate was lowest and most stable were sampled, and average heart rate and HRV metrics (standard deviation of R-R intervals [SDRR] and root-mean-square of successive differences between R-R intervals [RMSSD]) were calculated. Internal (Bannister's training impulse [TRIMP] and summated heart rate zones [SHRZ]) and external (total distance covered) workload measures were determined for practices and games, and acute (7-day) and chronic (28-day) sums of each measure were calculated. Relationships between ANS and workload variables were analyzed using linear mixed effects models in R with an alpha level of 0.05. Results: No workload measures were related to average HR during film (P > 0.07). SDRR was inversely related to acute TRIMP (P = 0.0421) but not acute SHRZ (P = 0.0505) or chronic TRIMP or SHRZ (P > 0.42). RMSSD was inversely related to chronic SHRZ (P = 0.0479) but not chronic TRIMP (P = 0.0671) or acute TRIMP or SHRZ (P > 0.13). Total distance covered was not associated with ANS measures (P > 0.1). Conclusions: These findings show that different measures of ANS activity are differentially affected by and related to measures of workload, which may be due to differential sensitivity in the measurements. The relationship between acute internal workload and SDRR shows that this HRV measure may be more sensitive to short-term workloads, while the relationship between chronic internal workload and RMSSD shows that this HRV measure may be more sensitive to accumulated workloads over a longer period. These findings show the close relationship between workloads, specifically internal workloads, and HRV. Though high internal workloads were associated with lower HRV, the effect of chronic training and subsequent adaptations on changes in HRV remain unclear. Despite the fact that ANS measures were collected during film sessions and not during true rest, these results show promise that HRV measured during this time may be useful for monitoring athletes throughout a competitive season. Practical Applications: Coaches and sport scientists can collect HRV data using common team-based HR monitoring systems during non-training team activities to assess recovery from training and readiness to perform. Future investigations should assess the relationships between HRV and in-game performance metrics to further elucidate the predictive utility of these metrics.

(3) Differences in Internal and External Workloads During Consecutive Collegiate Volleyball Matches

A. Chandler, H. Cintineo, B. McFadden, T. Cardaci, G. Hickman, C. Vincenty, B. Byrd, S. Scruggs, and S. Arent

University of South Carolina

Due to the COVID-19 pandemic, collegiate volleyball teams in the Southeastern Conference are scheduled to play 2 matches within 24 hours against the same team. Therefore, recovery between these match sets is essential to maintain optimal performance. However, the cumulative effects of the matches may lead to increased internal workloads during the latter match, even when external workloads remain constant. Purpose: The purpose of this analysis was to assess differences in both internal and external workload metrics between 2 matches separated by <24 hours. Methods: National Collegiate Athletic Association Division I female volleyball players (n = 11; age = 20.0 ± 1.3 years; BMI = 23.6 ± 2.8 kg/m2) were monitored using heart rate (HR) and accelerometry during 8 competitive matches. Internal workload was calculated as summated heart rate zones (SHRZ; AU) by determining time spent between 50 and 100% of maximum HR, with higher HRs accounting for greater point accumulation. Average HR was calculated for each Match. External workloads were quantified as total distance covered per match and distance covered in speed zones 4 (4.2–5.3 m/s) and 5 (>5.3 m/s). Paired t-tests were used to determine differences in between-day workload metrics (Match 1 and Match 2) with an alpha level of 0.05. Pearson's correlations were used to assess relationships between internal and external workloads. Results: There were no differences in SHRZ between Match 1 and Match 2 (P = 0.29), but average HR was significantly lower during Match 2 compared to Match 1 (P = 0.01). Additionally, total distance covered was significantly higher during Match 2 compared to Match 1 (+280.6 m; P = 0.04), total distance covered in speed zones 4 and 5 did not differ between matches (P > 0.05). SHRZ was strongly correlated with total distance covered for Match 1 (r = 0.73) and Match 2 (r = 0.72) and moderately correlated with distance covered in speed zone 5 (Match 1: r = 0.53; Match 2: r = 0.52). SHRZ was weakly correlated with combined distance covered in speed zones 4 + 5 (Match 1: r = 0.36; Match 2: 0.40) and was not associated with distance covered in speed zone 4 alone (r < 0.20). Average HR moderately correlated with total distance (Match 1: r = 0.67; Match 2: r = 0.51) and distance in speed zone 5 (Match 1: r = 0.51; Match 2: r = 0.45) but was weakly associated with distance in speed zone 4 and combined zones 4 + 5 for both matches (speed zone 4: r = 0.14; speed zone 4 + 5: r = 0.31; Match 2: speed zone 4: r = 0.21; speed zone 4 + 5: r = 0.31). Conclusions: Internal workloads were not elevated during Match 2 when fatigue is likely accumulating among athletes. In fact, total distance covered was higher in Match 2, suggesting an overall lower intensity as more external work was completed without an increase in internal workloads. Additionally, stronger associations were seen between internal workload and total distance covered compared to high-speed running. Practical Applications: Despite being played on a small court, monitoring total distance covered in indoor volleyball players rather than high-speed running may provide a more useful measure of external workload demands and provide further insight into stress, physical readiness, and overall performance. Additionally, increased internal workloads without increased external workloads between Match 1 and Match 2 may indicate impaired recovery between days, although this was not shown in the current analysis.

(4) Reserve Officer Training Corps (ROTC) Cadet Military Performance and Fitness Responses to a COVID Modified Training Semester

T. Cardaci,1 H. Cintineo,1 B. McFadden,1 A. Chandler,1 B. Bozzini,2 M. Kirkland,1 D. Dillman,1 B. Lambros,1 J. Mahal,1 and S. Arent1

1University of South Carolina; and2USARIEM

Reserve Officers' Training Corps (ROTC) cadets are required to partake in field-based, group training targeted to improve general and military-specific fitness and performance. Purpose: The purpose of this analysis was 3-fold: (a) to assess differences in baseline performance characteristics between military branches, (b) to investigate Navy and Marines ROTC cadets' changes in body mass in addition to aerobic and anaerobic performance responses and, (3) to assess changes in their respective military-specific fitness assessments following a collegiate semester long training period. Methods: ROTC cadets (N = 82; M: 73, F: 9; Navy: 54, Marines: 26) were evaluated at the beginning (T1) and end (T2) of an atypical covid modified semester long training period. Body mass (BM) was assessed during the athletes ROTC mandated physical assessments. Cadets underwent maximal countermovement vertical jump height following the hands-on-hips method via digital contact mat to determine peak anerobic power and a field-based graded exercise test to determine aerobic capacity. Cadets also performed their respective military-specific tests, which included the Navy Physical Readiness Test (PRT) or Marine Corps Physical Fitness Test (PFT). Baseline performance metrics between military branches were analyzed using a T-test. To determine changes in performance variables and military-specific assessments over time, a mixed-effects model was utilized with significance set at P < 0.05. The magnitude of change was assessed by Cohen's d (d) effect size. Results: Baseline peak anaerobic power (p = 0.012) and aerobic capacity (p = 0.018) were significantly greater in Marines compared to Navy cadets. All cadets significantly increased BM (p = 0.0024; d = 0.014), peak anaerobic power (p < 0.0132; d = 0.137), and aerobic capacity (p < 0.001; d = 0.164) from T1 to T2. In Marines, no significant changes were observed for PFT scores (p = 0.84; d = −0.140) while Navy cadets significantly increased PRT scores (p < 0.001; d = 0.777) from T1 to T2. Conclusions: These findings suggest that the current ROTC training model appears to increase BM and effectively improve metrics of anaerobic and aerobic performance. However, military-specific fitness assessments improved in the Navy but not Marine cadets indicating the current Marine ROTC training model may not be effective at improving this military-specific metric. However, this discrepancy may also be attributed to differences in baseline fitness levels between branches. Practical Applications: Despite improvements in performance metrics, emphasis should be placed on bolstering the marginal changes that were observed particularly in peak anaerobic power as this metric is an important predictor of military task performance and combat readiness. Future research should investigate novel and effective approaches to improve ROTC cadet and military performance.

(5) Institutional Approach of Legitimacy in the Strength and Conditioning Field

B. Altiner, C. Nite, and M. Dixon

Texas A&M University

The strength and conditioning (S&C) profession is a young field and has been caught between the convergence of health, sport performance, technology, and popular culture, creating a complex and varied network with several agendas and non-convergent interests amongst the public and private sector (e.g., certifying organizations, sport organizations, and for-profit entities). Overwhelming variance and self-regulation of organization standards, practices, education, and certifications distort the value of strength and conditioning coaches (Hartshorn, 2016; Read et al., 2017; Duehring & Ebben, 2010). Purpose: The purpose of this study was to do an extensive review of issues experienced in S&C literature concerning the legitimacy of the S&C field. Methods: A literature review was done to investigate issues that may be a result of field-level legitimacy or lack thereof. Furthermore, tenets of an institutional perspective were used to provide insightful diagnostics and strategies for addressing field-level legitimacy issues. Results: Literature demonstrated trending and existing issues concerning athlete injury and negligence (Waryasz et al., 2016; Eichner, 2018), S&C employment equity and diversity (Sartore-Baldwin, 2013, O'Malley & Greenwood, 2018), meritocracy (Read et al., 2017, Pye et al., 2013; Jefferys & Close, 2013), and monetary compensation (Read et al., 2017, Hartshorn, 2016; Duerhing & Ebben, 2010; Massey, 2013) in the S&C field. An institutional perspective dictates that trending dynamics of the S&C field are pluralistic, with organizations (i.e., certifying, sport programs, and for-profit) vying legitimacy (e.g., authority) and self-regulating standards of competencies and practices. Moreover, institutional research (Khanna & Palepu, 1997) asserts the field lacks macro-level regulatory systems (e.g., institutional void). Conclusions: Attaining legitimacy is considered a vital resource for organizations and is directly related to its' acceptability, credibility, approval, and support among the public and various other stakeholders (Meyer & Rowan, 1977; Suchman, 1995). As multiple interests emerge in a pluralistic field, numerous organizational identities and subcultures begin to fragment as individual organizations respond (e.g., self-regulation) to shifting, competing, or even contradictory environmental demands (Jarzabkowski & Fenton, 2006). Consequently, the field's legitimacy is negatively affected by the various and contending authorities (e.g., certifying organizations, sport organizations, and for-profit entities), contributing to the inconsistencies of field actions (Meyer & Scott, 1983; Scott, 2001).Practical Applications: Literature recognizes that certifying organizations are taking steps towards increasing the field's professionalization and legitimacy. Nonetheless, the existence or encouragement of higher-level credentials and education has yet to provide solutions for standardized policy and practice amongst organizations in the field (LaPlaca & Schempp, 2020; Hartshorn, 2016; Duehring & Ebben, 2010; Read et al., 2017). Strategies are available in managing pluralism, organizational and field legitimacy, and overcoming an institutional void. Moreover, promoting constituent collaboration embodying multiple purposes and values, upholding professional standards, and quality service corresponding with legitimacy.

(6) Moving Less but Working More: a Prospective Evaluation of Load and Recovery in American Collegiate Football Players, Across a Competitive Season

V. Smith,1 R. Mendoza,2 C. Vargo,2 M. VanSumeren,2 J. Sabourin,2 W. Moore,2 and T. Hew-Butler2

1Wayne State Universiy; and2Wayne State University

American college football players experience extreme bursts of internal and external stress loads, which vary widely according to the position they play. Global positioning systems and heart rate variability (HRV) studies suggest players at the linemen position undergo the least amount of external load and are slower to recover compared to other positions. Due to the predominant isometric movement requirements of linemen, external load data may not adequately capture linemen's total load. Purpose: This study evaluated collegiate American football players' positional internal workload and recovery using heart rate (HR) monitors over a 10-week season. Methods: On Tuesdays and Wednesdays (first practices of the week), NCAA Division II football players' (N = 28; age = 20.04 ± 1.72 years; height = 1.76 ± 0.04 meters; weight = 116.23 ± 19.32 kilograms; %bodyfat [%BF] = 27.42 ± 6.08) wore a chest strap HR monitor (Firstbeat, Jyväskylä Finland) for 3-minutes before practice while in the supine position to obtain a HRV score using root-mean square of successive difference and for the duration of field practice to capture internal training load (TRIMP). During practice both temperature and humidity were recorded. Pre-season body composition measurements that included %BF and bone mineral density (BMD) were also collected using dual energy x-ray absorptiometry. All analyses were conducted across position group: receivers, defensive backs, and running backs (SKILL, n = 5); quarterbacks, linebackers, and tight ends (COMBO, n = 3) and linemen (BIG, n = 20). Statistical significance was set a priori as p ≤ 0.05. Results: Across all 20 practices there was large intra- and inter-player variability in their TRIMP (MBIG = 135.37 ± 59.66; MCOMBO = 123.35 ± 50.77; MSKILL = 102.60 ± 52.14) and HRV (MBIG = 54.12 ± 25.46; MCOMBO = 57.12 ± 10.79; MSKILL = 74.63 ± 29.91). A Wilcoxon signed-rank test found practice intensity for Tuesday and Wednesday significantly differed overall (z = 4.46, p < 0.001); based on follow-up, differences were found for BIGs (MdnTuesday = 154.00; MdnWednesday = 110.52), z = −3.77, p < 0.001 and SKILLs (MdnTuesday= 105.74; MdnWednesday = 88.83), z = −2.02, p = 0.04. Tuesday and Wednesday HRV scores differed significantly overall (p = 0.027); follow-up revealed no group specific differences. To determine factors associated with players' load and recovery values, Pearson correlations were conducted by group with all observations across the 10 weeks. TRIMP was only significantly correlated with height (rBIG = 0.12), weight (rBIG = −0.14), BMI (rBIG = −0.18), and BMD (rBIG = −0.26; rSKILL = 0.28), temp (rBIG = 0.30; rSKILL = 0.27), and humidity (rBIG = −0.22; rSKILL = −0.28). HRV was only significantly correlated with height (rBIG = −0.23; rSKILL = −0.64), weight (rBIG = −0.25; rSKILL = −0.25), %BF (rBIG = −0.21; rSKILL = −0.60), BMI (rBIG = −0.13; rSKILL = 0.38), and BMD (rBIG = 0.24). Conclusion: On average the BIGs positional group demonstrated the greatest amount of internal workload and the lowest overall HRV scores compared to the COMBO and SKILL groups. Additionally, small relationships were found between internal load temp, humidity, and BMD for BIGs and SKILLs. Practical Applications: These findings add support to the importance of internal load monitoring for linemen. Linemen reached the highest internal loads of all 3 groups and varied the most in their internal loads. Factors such has body composition and temperature should be considered when planning practice structure and recovery time.

(7) Monitoring Training Load in American Football: an Examination of Integrated Microtechnology Metrics

M. Lewis

Virginia Tech

Integrated microtechnology—a combination of a global positioning system, accelerometer, gyroscope, and magnetometer—is widely utilized as a tool to quantify athlete training load. Purpose: The purpose of this investigation was to explore the relationship between different training load data collected via integrated microtechnology devices and heart rate monitors with the aim to find the most appropriate subset of metrics that describe athlete training load for collegiate American football athletes. Methods: To determine the most appropriate subset of metrics that describe athlete training load for collegiate American football athletes, a principal component analysis (PCA) was conducted. Practice data for 25 division I American collegiate football players (496 observations) from the 2020 season was utilized. Results: Based on the PCA, there were 5 components that explained 81% of the variance in the data (see Table 1). These 5 components can be described as representing 5 distinct training load constructs within the sport: high intensity change of direction based loading, linear running based loading, whole body mechanical loading, low intensity change of direction based loading, and internal loading. Conclusions: This examination identified a set of training load constructs that may be most appropriate for monitoring athlete training load in American football. Practical Applications: The findings from this examination will assist practitioners in monitoring athlete training load in American football.

T18
Table 1:
Pattern matrix.

(8) Performance and Body Composition Changes Across Academic Years in Collegiate Division I Women Soccer Players

B. McFadden,1 B. Bozzini,2 S. Hills,3 H. Cintineo,1 A. Chandler,1 T. Cardaci,1 A. Walker,4 M. Arent,1 M. Russell,5 and S. Arent1

1University of South Carolina;2USARIEM;3Bournemouth University;4Lebanon Valley College; and5Leeds Trinity University

Collegiate athletes have 4 years of eligibility to play their respective sport, giving coaches and training staff a limited period to optimize player performance. Entering college, freshman (∼18 years) are expected to compete at the same high level as their senior teammates (∼22 years); however, unlike seniors, freshman often have limited familiarity with the training demands associated with collegiate sports. Purpose: To determine changes in performance and body composition measures across freshman, sophomore, junior, and senior academic years in National Collegiate Athletic Association (NCAA) Division I (DI) women's soccer players. Methods: Performance testing and body composition data were collected over a 4-year period in NCAA DI women soccer athletes. A total of 58 players (age = 19 ± 1 years, height = 168 ± 6 cm; Mean ± SD) competing in the same soccer program were included in analysis. Testing occurred at 4 time points throughout the academic year (pre & postseason, pre & post spring training). Athletes arrived for testing ≥2 hours fasted, ≥4-hour abstention from caffeine, and having refrained from exercise ≥24 hours. Body composition was assessed via air displacement plethysmography to determine percent body fat (%BF), fat free mass (FFM) and body mass (BM). Maximal countermovement vertical jump height was assessed via contact mat using both arm swing (CMJ) and hands-on-hips (CMJHOH) methods. Aerobic capacity (V̇o2max) and ventilatory threshold (VT) were assessed by indirect calorimetry during a maximal graded-exercise test on a treadmill. To account for the unbalanced nature of data through repeated measurements of the same individuals, linear mixed models were used to assess differences in performance and body composition across time periods with standardized effect sizes (d) calculated in R (p < 0.05). Results: Over the 4 years, 116 freshman, 90 sophomore, 80 junior, and 45 senior tests were performed. No differences were seen in V̇o2max or VT across academic years. Juniors and seniors had greater FFM than freshman (p = 0.001, d = 0.62; p = 0.001, d = 0.71, respectively) and sophomores (p = 0.02, d = 0.46; p = 0.01, d = 0.58; respectively). Seniors demonstrated greater BM than freshman (p = 0.04, d = 0.36). Sophomores, juniors, and seniors exhibited lower %BF compared with freshman (p = 0.03, d = 0.32; p = 0.04, d = 0.30; & p = 0.02, d = 0.41). Sophomores, juniors, and seniors exhibited greater CMJ compared to freshman (p = 0.049, d = 0.28; p = 0.001, d = 0.64; p = 0.001, d = 0.58; respectively), while juniors also showed greater CMJ compared to sophomores (p = 0.03, d = 0.28). Sophomores, juniors, and seniors displayed greater CMJHOH compared to freshman (p = 0.001, d = 0.78; p = 0.001, d = 1.19; p = 0.001, d = 1.32, respectively), and upperclassmen showed greater CMJHOH compared to sophomores (p = 0.003, d = 0.54; & p = 0.001, d = 0.75). Conclusions: Freshman exhibited the lowest BM, FFM, CMJ, and CMJHOH compared to all other classman indicating a need for improved conditioning programs prior to entering college. Practical Applications: Soccer is a power endurance sports and requires high levels of aerobic capacity and power capabilities to be successful. Maximizing these attributes in each athlete becomes critical to long-term team success. Determining normative fitness profiles across academic years can help to guide performance goals for coaches and training staff at both the collegiate level as well as the high school level, where players are aiming to transition and secure a role on a NCAA team.

(9) The Acute Effects of High-Intensity Resistance Exercise on Measures of Cognitive Function

J. Anders,1 W. Kraemer,2 E. Post,3 L. Caldwell,4 M. Beeler,5 E. Martini,2 J. Volek,2 C. Maresh,2 and S. Hayes2

1University of Nebraska- Lincoln;2The Ohio State University;3Ohio Dominican University;4University of North Texas; and5Hastings College

A preponderance of evidence suggests that acute bouts of moderate-intensity exercise facilitate cognitive function. The relationship between exercise intensity and cognitive function has been hypothesized to exhibit an inverted-U pattern, however, few studies have examined the effects of high-intensity exercise on cognitive function. Furthermore, these studies have reported equivocal findings and have primarily utilized an aerobic exercise modality. Heavy barbell back squats (80% of 1 repetition maximum [1RM]) have been demonstrated to elicit significant increases in indices of physiological stress. The Automated Neuropsychological Assessment Metrics (ANAM) was developed by the Department of Defense and has been demonstrated to be a reliable and valid measure of cognitive function. Purpose: The purpose of this study was to examine the influence of an acute bout of high-intensity barbell back squats on measures of cognitive function. Methods: Ten men (age = 24.4 ± 3.2 years; body mass = 85.7 ± 11.8 kg; height = 168.3 ± 28.8 cm; back squat 1RM = 139.0 ± 24.1 kg) performed 6 sets of 10 repetitions of barbell back squats at 80% 1RM. The participants completed the ANAM during the familiarization visit, immediately before, and immediately after the high-intensity resistance exercise bout. The ANAM was comprised of 7 tasks that assess various cognitive domains. The throughput scores (r·m−1) and reaction times (ms) for each task were examined with separate 1-way repeated measures ANOVAs. Results: The repeated measures ANOVAs for throughput scores demonstrated significant mean differences for the Mathematical Processing task (p < 0.001, ηp2 = 0.625). Post hoc pairwise comparisons demonstrated that the post-fatigue throughput (32.0 ± 8.8 r·m−1) was significantly greater than the pre-fatigue (23.8 ± 7.4 r·m−1, p = 0.003, d = 1.01) and the familiarization throughputs (26.4 ± 5.3 r·m−1, p = 0.024, d = 0.77). The Coded Substitution-Delay task throughput also demonstrated significant mean differences (p = 0.027, η2p = 0.394). Post hoc pairwise comparisons demonstrated that the post-fatigue throughput (49.3 ± 14.4 r·m−1) was significantly less than the pre-fatigue throughput (63.2 ± 9.6 r·m−1, p = 0.011, d = 1.14). The repeated measures ANOVAs for reaction time demonstrated significant mean differences for MTH (p < 0.001, η2p = 0.624). Post hoc pairwise comparisons demonstrated that the post-fatigue reaction time (1885.2 ± 582.8 ms) was significantly less than the pre-fatigue (2,518.2 ± 884.8 ms, p = 0.005, d = 0.85) and familiarization reaction times (2,253.7 ± 567.6 ms, p = 0.009, d = 0.64). The Go/No-Go task reaction times demonstrated significant mean differences (p = 0.031, ηp2 = 0.320). Post hoc pairwise comparisons demonstrated that the post-fatigue reaction time (285.9 ± 16.3 ms) was significantly less than the pre-fatigue reaction time (298.5 ± 12.1 ms, p = 0.006, d = 0.88). Conclusions: High-intensity resistance exercise may elicit domain-specific influences on cognitive function characterized by the facilitation of simple cognitive tasks, such as information processing and response inhibition, as well as impairments of complex cognitive tasks, such as memory and information recall. Practical Applications: Service people and athletes are commonly placed under highly stressful situations and are forced to make decisions that can determine the success of the mission or the game. This study provides insight into what type of decisions might be impacted and how these decisions may be influenced by highly stressful conditions.

(10) Effects of Lower Extremity Muscular Power on Gait Speed During Single and Dual-Task Conditions in Adults

S. Paulson,1 M. Gray,1 J. Gills,1 J. Glenn,2 E. Madero,2 J. Myers,2 J. Vincenzo,3 C. Walter,3 A. Campitelli,1 and M. Jones,1 J. Sanders4

1University of Arkansas;2Neurotrack Technologies;3University of Arkansas for Medical Sciences; and4Shippensburg University of PA

Previous research suggests muscular power plays a significant role in physical functioning. Thus, a decrease in muscular power may be related to reduced physical function. One prominent physical function assessment is gait speed. More recently, dual-task (DT), a motor task (gait task) coupled with a cognitive task has been identified as a negative predictor of physical function to a greater extent than the motor task independently. However, it is unclear if muscular power influences DT performance. Purpose: The purpose of this study was to compare lower extremity muscular power (PWR) on gait speed (GS) under single and DT conditions. Methods: Adults (N = 149) over the age of 45 completed 2 trials of each walking condition at their habitual (HAB) and fast (FAST) walking speed. Average GS was calculated during the single (walking) and DT (cognitive task and walking) conditions for each speed (HAB and FAST). Relative power, from a sample of younger adults (ages 18–29 years), calculated from the average of 5 power chair stands was used to create 3 PWR groups: Below average (LOW; n = 59, M±SD: age: 74.56 ± 10.69 years; mass: 76.49 ± 15.54 kg, height: 162.24 ± 9.38 cm), average (AVE; n = 57, age: 75.25 ± 9.03 years; mass: 78.02 ± 15.07 kg, height: 166.65 ± 10.47 cm), and above average (HIGH; n = 33, age: 74.24 ± 6.90 years; mass: 76.85 ± 15.56 kg, height: 164.48 ± 10.13 cm). Data were analyzed using a 1-way ANOVA. Results: There was a significant difference in HAB GS (p < 0.01) and FAST GS (p = 0.04) between the PWR groups. Gait speed in the LOW PWR group was 9 and 11% slower when compare to the AVE group for HAB and FAST speeds, respectively. Results were similar when comparing the LOW and HIGH PWR groups; GS was 13 and 11% slower among the LOW group during the HAB and FAST conditions, respectively. However, no significant difference was found between the groups during the DT conditions, HAB DT GS (p = 0.64) and FAST GS (p = 0.84). Conclusions: Lower extremity muscular power significantly affected habitual and fast single-task gait speeds. The LOW power group walked significantly slower than the AVE and HIGH power groups during both habitual and fast single-task gait speed tests. Further, power did not affect dual-task gait speed. Practical Applications: The preservation of lower extremity muscular power is important factor for maintaining physical functioning as 1 ages. Therefore, the implementation of exercise programs with muscular power exercises may improve, or at the very least maintain, single-task gait speeds.

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Table 1:
Descriptive statistics of power groups and gait speeds (N = 149).

(11) Isokinetic Squat Performance Is Associated With Leg Press One-Repetition Maximum but Not Repetitions to Fatigue

P. Harty,1 M. Stratton,1 G. Escalante,2 M. Siedler,1 C. Rodriguez,1 J. Dellinger,1 A. Williams,1 S. White,1 R. Smith,1 B. Johnson,1 and G. Tinsley1

1Texas Tech University; and2California State University, San Bernardino

Muscular strength is a vital athletic attribute that is targeted by many training programs. One-repetition maximum (1RM) tests are typically used to assess changes in muscular strength but may not be ideal in certain situations due to technique deficiencies, time constraints, and potential injury risks from maximal exertion under fixed load. In contrast, isokinetic strength tests provide accommodating resistance throughout the entire range of motion, generally increasing the precision of strength estimates and potentially improving safety. Thus, these tests may prove useful for assessing muscular strength on a more frequent basis than traditional 1RM testing. Purpose: To determine relationships between isokinetic squat performance, leg press 1-repetition maximum results, and leg press muscular endurance testing. Methods: Healthy, resistance-trained males and females (n = 15; Mean ± SD; Age: 23.6 ± 4.9 years; Height: 171.3 ± 8.2 cm; Body mass: 74.1 ± 13.8 kg) participated in this investigation. Following a standardized body weight warmup, participants performed a 3-repetition isokinetic squat protocol, with an initial trial repetition at approximately 50% effort followed by 2 maximal repetitions, which were averaged prior to analysis. Each repetition consisted of a 4-second eccentric phase and a 4-second concentric phase, with brief pauses at the top and bottom of the movement. Next, participants performed up to 5 1RM attempts on a 45° leg press, adhering to the warm-up protocol set forth by the National Strength and Conditioning Association. After a 3-minute rest, maximal leg press repetitions to fatigue (RTF) were completed using a load equivalent to 2× body mass (males) or 1.5× body mass (females). Spearman correlations were computed, with a manual Bonferroni correction applied to control for multiple comparisons, setting the corrected threshold of significance at p < 0.0125 (0.05/4 comparisons). Additionally, surprisal values (S) were generated by computing the -log2 of each test statistic. These values can be intuitively interpreted as the number of consecutive fair coin tosses required to equal the level of surprise of obtaining the p-value in question. For example, a p-value of 0.001 (S = 9.97) is as surprising as getting all heads on 10 consecutive coin tosses. Results: A significant correlation was identified between peak isokinetic concentric force and leg press 1RM (rs= 0.85, p < 0.001, S = 13.8) but not between peak isokinetic eccentric force and 1RM (rs= 0.61, p = 0.015, S = 6.1). No significant relationships were identified between isokinetic concentric peak force (rs= 0.28, p = 0.320, S = 1.6) or eccentric peak force (rs= 0.34, p = 0.212, S = 2.2) and leg press repetitions to fatigue. Conclusions: This investigation identified a strong relationship between peak isokinetic concentric force production and leg press 1RM performance, but not repetitions to fatigue. Eccentric force production during the isokinetic test displayed a weaker relationship with 1RM and no relationship with RTF performance. Practical Applications: The present investigation suggests that isokinetic testing may serve as an acceptable surrogate for leg press 1RM when assessing strength. These tests could prove useful for strength and conditioning professionals who implement frequent strength assessments or wish to maximize athlete safety during periods of peaking or overreaching.

(1) The Effects of Fatiguing Leg Extension Muscle Actions With and Without Blood Flow Restriction on Neuromuscular Patterns of Responses

P. Rivera, C. Proppe, and E. Hill

University of Central Florida

Purpose: The mechanisms underlying muscle adaptation in response to low-load blood flow restriction (BFR) might be due to greater muscle activation and/or to metabolite buildup which slows action potential conduction velocity. Therefore, the purpose of this investigation was to examine the acute effects of fatiguing unilateral leg extension muscle actions with and without BFR on muscle activation and action potential conduction velocity. Methods: Ten (mean ± SD; 21 ± 3 years) recreationally trained men (n = 5) and women (n = 5) randomly performed, on separate days, 30 unilateral submaximal (30% 1-repetition maximum) leg extension muscle actions with and without BFR. Across the 30 reps, electromyographic (EMG) amplitude and EMG mean power frequency were recorded from the vastus lateralis and examined using polynomial regression analyses (first, second, or third order). The individual and composite EMG amplitude and EMG mean power frequency responses were normalized to the second rep (first rep was excluded from all analyses) and an alpha of p ≤ 0.05 was considered statistically significant. Results: For the composite normalized EMG amplitude responses, there were significant quadratic increases for both the BFR (p = 0.021, R2 = 0.855) and non-BFR conditions (p < 0.001, R2 = 0.875). For the composite normalized EMG mean power frequency responses, there was a significant quadratic decrease for the BFR condition (p = 0.032, R2 = −0.968) and a significant linear decrease for the non-BFR condition (p < 0.001, r2 = −0.915). Conclusions: As a result of the fatiguing unilateral leg extension muscle actions, there were similar increases in muscle activation (EMG amplitude) but decreases in action potential conduction velocity (EMG mean power frequency) for both the BFR and non-BFR conditions. These data suggested that the application of BFR does not elicit greater acute changes in muscle activation or metabolite buildup as inferred by the EMG amplitude and EMG mean power frequency responses, respectively. Practical Applications: One set of fatiguing unilateral submaximal leg extension muscle actions was sufficient to increase muscle activation and possibly induce metabolic accumulation with and without BFR. Thus, acute fatiguing intervention utilizing submaximal load can be used to elicit acute neuromuscular changes that may facilitate chronic training-induced adaptations to skeletal muscle. The application of BFR may be used to add variety to exercise but it does not appear to elicit a superior response relative to non-BFR conditions.

(2) Peak Yank Is Not Predictive of Countermovement Jump Height in Recreationally Trained Males

M. Hermes,1 E. Mosier,2 and A. Fry1

1The University of Kansas; and2Northwest Missouri State University

The vertical jump (VJ) is often used to assess lower body performance through force-time data analysis. However, kinetic and kinematic events are not always easily explained through force-time data alone. Yank is the time-derivative of force and represents instantaneous rate of force development (RFD). The analysis of yank-time data may be a viable option to understand kinematic and kinetic events during jumping. However, the relationship between yank-time characteristics and VJ performance is less clear. Purpose: The purpose of this study was to assess the relationship between yank-time characteristics and VJ performance in recreationally active males. Methods: Recreationally active males (x̄ ± SD, n = 15, age = 23.0 ± 3.8 years, height = 170.7 ± 28.8 cm, mass = 81.8 ± 14.2 kg, mean jump height = 52.7 ± 10.4 cm) participated in this study. Participants completed 9 maximal countermovement jumps without arm swing. To remove arm swing, participants held onto a stretching stick placed on the upper back. Participants rested for 1–2 minutes between jumps and the best jump, as determined by jump height, was used for analysis. All jumps were performed on a uniaxial force plate sampling at 1,000 Hz. Force-time data was collected from the force plate. Jump height was determined from force-time data. Yank-time data was derived from force-time data using a low-pass Hamming filter with a cutoff frequency of 10 Hz. Five yank events were defined as follows: 1 = jump initiation, 2 = first yank trough, 3 = bottom of the force curve, 4 = peak force, 5 = toe off. Time duration between events was analyzed. Dependent variables included yank phase (YP) duration, jump height (JH), peak yank (PY), time to PY, and total jump time (JT). Pearson product-moment correlations were used to analyze the relationships between yank-time characteristics and JH (p < 0.05). Results: No significant relationships were observed between JH and PY (r = −0.033, p = 0.907), time to PY (r = −0.146, p = 0.604), JT (r = −0.035, p = 0.9), or any YP duration (r = −0.443 to 0.229, p = 0.098–0.989). PY was moderately correlated with YP 3–4 (r = −0.527, p = 0.043) and YP 4–5 (r = 0.643, p = 0.01), accounting for 28 and 41% of the variance in PY, respectively. Conclusion: Yank-time characteristics were not predictive of JH in recreationally active males. RFD has previously been identified as a significant predictor of jump performance. Subject heterogeneity and lack of jumping proficiency may have influenced this. However, YPs 3–4 and 4–5 were moderately correlated with PY. Practical Applications: As YP 3–4 represents lowest force to peak force, shorter phase duration indicates shorter time to peak force. Further, YP 4–5 was positively correlated with PY. This may be related to impulse. As impulse is the product of force and time, an increased time to apply force may lead to a higher impulse and influence PY. Further work should analyze how PY is related to impulse and other VJ characteristics.

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(3) Quadriceps Fatiguability Is Not Related to Muscle Cross Sectional Area, Echo Intensity, or Muscle Strength

S. Fleming,1 R. Colquhoun,1 M. Magrini,2 M. Ferrell,3 and N. Banks4

1University of South Alabama;2Creighton University;3Oklahoma State University Center for Health Sciences; and4University of Iowa

Purpose: The purpose of this investigation was to examine the relationship between fatiguability of the right quadriceps muscles and quadriceps muscle size, echo intensity, and strength in healthy college-aged males. Methods: Twenty-five recreationally active males (Age: 23 ± 3 years) volunteered for this investigation. Following an overnight fast, panoramic b-mode ultrasound images were taken of the right vastus lateralis (VL) and rectus femoris (RF) to determine cross-sectional area (CSA) and echo intensity (EI) at 50% of the length of the femur in the transverse plane. For all exercise testing, participants were seated in an isokinetic dynamometer with the knee joint set at 90° of flexion. Participants then completed 2 maximal voluntary isometric contractions (MVIC) of the right quadriceps with 1 minute of rest between attempts. Fatiguability was assessed via repeated 50% MVIC trapezoidal ramp contractions until the participant could no longer accurately follow the force trajectory. The ramp contractions consisted of a 3-second quiescent period, 5-second ramp to the target torque, a 10-second hold at the target torque, followed by a 5-second descending ramp back down to baseline, and subsequent 3-second quiescent period, allowing for approximately 6-second between contractions. CSA and EI were assessed offline via ImageJ by the same experienced investigator. CSA of the VL and RF were summed to get establish quadriceps CSA (QCSA). Weighted EI ([VL CSA/QCSA]*VL EI) + ([RF CSA/QCSA]*RF EI) was summed for quadriceps EI (QEI). Bivariate correlations and stepwise multiple linear regressions were used to examine the relationship between fatiguability (i.e., number of repetitions completed) and of QCSA, QEI, and MVIC strength. Results: There were no significant relationships between fatiguability and QCSA (p = 0.088; r = −0.345), QEI (p = 0.169; r = 0.151), or MVIC (p = 0.104; r = −0.333). Stepwise linear regression analyses uncovered no significant predictors of fatiguability. However, there was a significant positive relationship between MVIC and QCSA (p=< 0.001; r = 0.656) and negative relationship for QCSA and QEI (p = 0.044; r = −0.407). Conclusions: The results of this investigation suggest that QCSA, QEI, and voluntary strength of the quadriceps do not significantly predict fatiguability of the quadriceps. However, our data show that there is a positive relationship between muscle size and voluntary strength of the quadriceps. Furthermore, a negative relationship was observed between muscle size and EI of the quadriceps. Thus, the interplay between ultrasonographic measures (particularly EI), muscular strength, and fatiguability remains unclear. Practical Applications: Coaches and practitioners cannot presently rely on ultrasonographic measures or muscular strength to predict fatiguability of the quadriceps musculature. Additional research is needed to understand the relationship between non-invasive measures of skeletal muscle properties and fatiguability.

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Figure 1.:
Visual depiction of significant relationships between quadriceps cross-sectional area (QCSA) and maximal voluntary isometric contraction (MVIC) strength (panel A) and QCSA and weighted quadriceps echo intensity (EI; panel B).

(4) Sprint Momentum: an Alternative Metric to Sprint Evaluation in American Football

B. Mann,1 J. Mayhew,2 J. Dawes,3 M. heinecke,4 and J. Signorile1

1University of Miami;2Truman State University;3Oklahoma State University; and4Forsyth Country Day School

Three of the most talked about metrics for the sport of American Football are height, weight, and 40 time. In the collegiate environment, there is a conundrum as athletes are typically still physically maturing during their competitive years, and weight gain is prevalent. As has been noted in research, there tends to be an increase in body mass and no improvement in sprint times after the first year of engagement in a S&C program. Purpose: To assess a novel metric of sprint momentum over the course of a career to examine changes that have occurred. Methods: During their participation in a S&C program at a Division 1 BCS Power 5 conference team, the athletes ran a 40 yard dash every spring. Over the course of a 15 year period, 78 athletes who completed 4 off-seasons were selected to examine the changes that occurred in sprint momentum (body mass × sprint velocity) and compared them against the changes in sprint times. The 40 was tested by sprinting 40 yards from a 3 point stance, using an electronic timing system with a push pad start and recorded to the nearest 100th of a second. Body mass was collected using a calibrated scale. Sprint momentum was calculated by dividing 36.6 m by their sprint time and then multiplying by their weight in kg. Results: Repeated measures analysis for 40 sprint times revealed a significant difference for years (F(3,75) = 3.981, p = 0.008, ηp2 = 0.044, observed power 0.832). Post hoc analysis showed that year 2 was significantly faster than year 1 (Mean difference [Mdiff] ± SE = −0.05 ± 0.01 s, p = 0.001, Cohen's d [d] = −0.13), while year 3 was not significantly different from year 1, but was slower than year 2 (Mdiff ± SE = −0.02 ± 0.010 s, p = 0.087, d = 0.03). Year 4 was not significantly different from year 3, but was slower, (Mdiff ± SE = 0.01 ± 0.01 s, p = 0.512, d = 0.00). Repeated measure analysis of the 40 yd dash momentums also showed a significant difference between years (F(3,75) = 39.95, p = 0.000, ηp2 = 0.348, observed power = 1.000). Pairwise comparisons found that year 2 was significantly greater than year 1 (Mdiff ± SE = 23.55 ± 3.46 kg·second−1, p = 0.000, d = 0.26), year 3 was significantly greater than year 2 (Mdiff ± SE = 9.33 ± 3.21 kg·second−1, p = 0.005, d = 0.10) year 4 trended towards significant difference as compared to year 3, (mean difference [SE] = 6.99 ± 3.52 kg·second−1, p = 0.051, d = 0.06). Conclusions: The combined effects of 40 yard sprint time and body mass is evidenced by the significant increases seen between all playing years and the significant improvement and substantial effect size seen between years 1 and 4 (p < 0.0001; d = 0.43). Practical Applications: By utilizing sprint momentum, the coach will be better able to evaluate the changes in the entire athlete across the course of their career.

(5) A Temporal and Kinetic Comparison of Traditional Elastic Band Squats and Reverse Elastic Band Squats: Implications for Specificity of Training

S. Rogers, S. Henderson, and M. Mache

California State University, Chico

Elastic band squats are commonly used in strength and conditioning programs. Researchers have examined traditional elastic band squats but have neglected to study reverse elastic band squats, though both methods are employed. Purpose: The purpose of this study was to compare the force-time characteristics of traditional, traditional elastic band, and reverse elastic band back squats. Methods: Ten experienced men weightlifters (22.8 ± 0.92 years, 80.4 ± 8.82 kg, 1.81 ± 0.01 m) participated in 2 testing sessions. Both sessions included a general warm-up, followed by a back squat specific warm-up. A 6RM back squat assessment was completed during the first testing session. In the second session participants performed 3 randomized blocks of trials at 70% of their 6RM load. Blocks of trials consisted of 6 traditional, 6 traditional elastic band (i.e., bands anchored to the bottom of the squat rack), and 6 reverse elastic band back squats (i.e., bands anchored to the top of the squat rack). The load used during elastic band squats was equal to the sum of the forces applied by the barbell, the load on the barbell, and the maximum resistance provided by the elastic bands. To compare the force-time characteristics of the squats vertical ground reaction force data were collected at 1,000 Hz during each block of trials. The late descending phase (last 150 ms) and early ascending phase (first 150 ms) were analyzed. Dependent variables were averaged across trials of the same type and Friedman's test was used to compare the squat variations. Post-hoc analyses were used as needed. Significance was set at p < 0.0016 for all comparisons. Results: Traditional back squats had greater values of peak force when compared to traditional elastic band squats (p = 0.008), differences in peak force were not observed for the other comparisons (all p > 0.016) (Table 1). Traditional back squats also had greater values of mean force compared to traditional and reverse elastic band squats during the descending (both p = 0.008) and ascending phase (both p = 0.008). Differences in mean forces were not observed between elastic band squat types (all p > 0.016). Differences in rate of force development between squat types were not observed for the late descending or early ascending phase (all p > 0.016). Conclusions: Elastic band squats were different from traditional back squats with regards to peak and mean force. Rate of force development for traditional back squats and those performed with bands were statistically similar; however, the present values should be considered when determining which squat variation might be most specific for a given athlete and desired outcomes. Practical Applications: Elastic band squat loads should be modified as needed to address the observed differences in peak and mean forces. Further, it is possible that over the course of a training program the rates of force development noted here could be meaningful.

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Table 1:
Vertical ground reaction forces (VGRF) and rate of force development (RFD) during 3 back squat variations (Mean + SD).

(6) Agonist-Antagonist Muscle Interactions During Dynamic and Static Contractions

C. Mackey,1 A. Barrera-Curiel,2 R. Thiele,3 and J. DeFreitas4

1Loyola University Chicago;2California State University;3Kansas State University; and4Oklahoma State University

The coordinated interactions between agonist and antagonist muscle groups can be exceptionally complex. This coordination between opposing muscles depends on the combination of various shared inputs, which can be central or peripheral in origin. Due to this complexity, efforts to provide insight between agonist and antagonist muscle interactions have utilized various assessment modalities. Purpose: Examine agonist-antagonist muscle interactions during dynamic and static contractions. Methods: Twenty-six resistance-trained men (age = 23.32 ± 3.17 years, height = 178.76 ± 6.17 cm, mass = 89.20 ± 13.82 kg) participated in this study. Participants completed maximal voluntary contractions (MVCs) (0°·second−1; 180°·second−1; 500°·second−1) of the elbow flexors (EF), elbow extensors (EE), knee flexors (KF), and knee extensors (KE). Surface EMG recordings were examined from the biceps brachii (BB), triceps brachii (TB), vastus lateralis (VL), and biceps femoris (BF) muscles as to be representative of the EF, EE, KE, and KF muscle groups, respectively. A 4 × 3 (muscle × contraction) repeated measures ANOVA was used to determine the difference in coactivation based on the muscle and contraction type (dynamic or static) utilized. Results: A significant muscle × contraction interaction (p = 0.002) was observed in which the change in coactivation depended on contraction type and on which muscle was assessed. There were significant main effects for both muscle (p < 0.001) and for contraction (p < 0.001). Pairwise comparisons (muscle) revealed that the VL presented with significantly less (p < 0.001) co-activation compared to both the BF and TB. Coactivation of the BF was significantly more (p < 0.001) than the BB, while the BB coactivated significantly less (p < 0.001) than the TB. Pairwise comparisons (contraction) revealed that the static contraction (0°·second−1) (p < 0.001–0.003) produced significantly greater coactivation compared to the dynamic (180°·second−1 and 500°·second−1) contractions. Additionally, the dynamic 500°·second−1 contraction produced a significantly higher amount of coactivation when compared to the 180°·second−1 contraction (p < 0.001). Conclusions: The results of the present investigation revealed that antagonist coactivation differs not only based on muscle group but on the type of contraction being assessed. Since a commonly proposed purpose of antagonist coactivation is to provide joint stability, it is possible that measurements examining maximal force (isometric/static) and velocity (500°·second−1) would require more coactivation to stabilize the joint. Practical Applications: These findings may be useful for clinicians and practitioners who would like to incorporate maximal effort static contractions as a part of their training or reconditioning programs in combination with high velocity movements.

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(7) Changes in Rate of Force Development Cause Compensatory Alterations in Motor Unit Firing Rate and Recruitment

C. Macarilla,1 R. Colquhoun,1 E. Rogers,2 and N. Banks2

1University of South Alabama; and2University of Iowa

Purpose: To examine the effects of differing rate of force development on motor unit (MU) recruitment and firing behavior of the biceps brachii. Methods: Thirteen strength-trained males (Age: 24 ± 2 years) completed an experimental session in which maximal voluntary isometric contraction (MVIC) strength and MU behavior of the biceps brachii were recorded during 3 isometric ramp contractions with a target force of 70% MVIC. Subjects were asked to complete trapezoidal ramp contractions with differing rates of force development, in which the target trajectory increased linearly at a rate of 20% MVIC per second (FAST), 10% MVIC per second (MOD), or 5% MVIC per second (SLOW) to a 10-second plateau at the target force before returning to baseline at the same rate. Two minutes of rest were given between each contraction and the order was randomized for each participant. All testing took place with the subject seated and restrained in an isokinetic dynamometer and their dominant arm fixed at 90° of shoulder and elbow flexion. A cuff was placed around the subject's wrist and attached to a load cell that was fixed to the arm of the dynamometer to record the subject's force output. Surface electromyographic signals were recorded from the biceps brachii and decomposed offline into their constituent MU firing behavior. Individual subject's MUs were plotted to obtain a slope and y-intercept of the Recruitment Threshold (RT) vs. Mean Firing Rate (MFR) and RT vs. MU Action Potential Amplitude (MUAP) for each ramp contraction. Slopes and y-intercepts were the averaged across each condition to make a composite line for each relationship during each ramp contraction. Regression analyses utilized to examine potential difference in slopes and/or y-intercepts of the composite lines across contractions for each relationship using GraphPad. Results: Analyses found significantly different slopes of the RT vs. MFR relationship between all ramp contractions (p < 0.001 for all). Specifically, there was a progressive increase in the slope of the RT vs. MFR relationship with increasing RFD of the ramp contraction (SLOW -0.73 ± 0.28 pps/MVIC vs. MOD: −0.70 ± 0.29 pps/MVIC vs. FAST: −0.63 ± 0.29 pps/MVIC). Analyses also revealed significant differences in the slopes of the RT vs. MUAP relationship across all ramp contractions (p < 0.001 for all), with FAST exhibiting the slowest slope (27.7 ± 16.4 µV) followed by SLOW (38.60 ± 24.8 µV) and MOD exhibiting the most rapid increase (41.4 ± 31.4 µV). Conclusions: Altering contraction RFD alters the recruitment and firing patterns of MUs, with the most rapid RFD resulting in the shallowest slope of both the RT vs. MUAP and RT vs. MFR relationships. Practical Applications: It appears differences in RFD alter both MU recruitment and firing rates. Thus, strength and conditioning professionals should aim to vary RFD when prescribing exercise to maximize MU adaptation. Future studies should determine this relationship in other muscle groups.

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Figure 1.:
Composite regression lines for the recruitment threshold (RT) vs. motor unit action potential amplitude (MUAP; panel A) and RT vs. mean firing rate (MFR; panel B).

(8) Hamstring:Quadriceps Co-activation Ratio Across Different Training Loads in the Barbell Back Squat

S. Martinez,1 J. Coons,1 and K. Mehls2

1Middle Tennessee State University; and2Walsh University

Simultaneous activation of the hamstrings and quadriceps during knee extension is thought to counteract shearing of the tibia, increase joint stability, and prevent injury to the anterior cruciate ligament (ACL). Muscle activation hamstring:quadriceps (H:Q) ratios closer to 1.0 indicate balanced co-activation to generate absolute strength and stabilize the knee. Closed kinetic chain exercises have been emphasized to facilitate co-activation of the leg muscles to provide stability at the knee during movement. However, H:Q co-activation ratio in the barbell back squat (BBS) has yet to be investigated across training loads. Purpose: The purpose of this study was quantify and compare hamstring:quadriceps (H:Q) co-activation ratio across training loads in the BBS in resistance trained females. Methods: Surface electromyography (EMG) was used to measure muscle activity of the vastus lateralis (VL), vastus medius (VM), biceps femoris (BF), and semitendinosus (ST) during a BBS. Participants (M ± SD: n = 19; age: 21.20 ± 1.50 years; height: 164.48 ± 13.05 cm; body mass: 66.80 ± 17.51 kg; 1RM: 85.68 ± 17.73 kg) completed 3 repetitions of the BBS at 40, 50, 60, 70, 80 and 90% of a 1-repetition maximum (1RM). All EMG data was normalized to the 1RM EMG data collected for each participant. The H:Q co-activation ratio was calculated by dividing the average hamstring activity (BF, ST) by the average quadriceps activity (VL, VM). Twelve separate 1-way repeated-measures ANOVAs with relative load as the within subject factor were run for the H:Q co-activation ratio (ascending and descending phases). Results: During the ascending phase, the H:Q co-activation at 90% 1RM was significantly higher ((F(1, 19) = 56.05, p = 0.009, η2= 0.747) compared to 50% 1RM by 0.270. As relative load increased, there was a general linear increase in H:Q co-activation ratio during the ascending phase (see Figure 1). During the descending phase, H:Q co-activation ratio was the highest at 40%1RM with a marked drop off as load increased to 60%1RM, followed by general linear increase to 90% 1RM. Conclusions: Higher training loads produce a H:Q co-activation ratio closer to 1.0, creating a more balanced H:Q co-activation during the ascending phase of a BBS. Lighter training loads may support a balanced H:Q co-activation ratio during the descending phase of BBS by allowing females to sit back further during the squat and emphasize the hamstrings' muscle action. Practical Applications: Prescribing training loads near 1RM of the BBS can stimulate balanced H:Q co-activation during the ascending phase, thus promoting knee stabilization. As ACL injuries during eccentric actions are common, lower training loads (40% 1RM) may be necessary to emphasize hamstrings muscle activity during the descending phase of the BBS. Coaches and trainers should consider emphasizing H:Q co-activation during training sessions to promote stabilization at the knee joint and prevent injuries.

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Figure 1.:
H:Q Co-activation ratio across loads during barbell back squat.

(9) Time Course of Changes in Physiological and Perceptual Responses During Incremental vs. Constant Power Exercise

P. Succi,1 T. Dinyer,1 C. Voskuil,1 M. Byrd,2 and H. Bergstrom1

1University of Kentucky; and2Mayo Clinic

The patterns of physiological responses, including V̇o2, heart rate (HR), and respiration rate (RR), are typically related to perceptual responses during incremental exercise (i.e., graded exercise test [GXT]). These relationships are often used to infer mechanisms underlying the rating of perceived exertion (RPE). However, these same relationships may not hold during constant power output (PO) exercise. Purpose: This study compared the time course of changes and patterns of responses for V̇o2, HR, RR, and RPE during a GXT and a constant PO trial to exhaustion. Methods: Ten subjects (Mean ± SD, age = 22.8 ± 3.6 years) completed a GXT to determine V̇o2peak and PO at V̇o2peak (PPO). In addition, V̇o2, HR, RR, and RPE responses were recorded during the GXT and a trial to exhaustion at 85% PPO. For the ride at 85% PPO, the first ∼2.5 minutes were removed to account for the adjustment to exercise. Separate 1-way repeated measures ANOVAs with post-hoc Student Newman-Keuls test were used to determine the time course (normalized to time to exhaustion [TLim]) of changes among the repeated measured variables normalized to the maximal values obtained from the GXT. Polynomial regression analyses were used to determine the composite normalized V̇o2, HR, RR, and RPE responses (linear and quadratic) vs. normalized time (10–100%) for each trial. Results: There were quadratic increases in GXT V̇o2 and 85% PPO V̇o2 (R2 = 0.999 and 0.973, respectively) that were significantly greater than baseline at 10% TLim. For the GXT, the V̇o2 at each time point was greater than the previous, but for the 85% PPO trial, the V̇o2 at 100% was not different from the V̇o2 at 60–90% TLim. There was a quadratic increase in 85% PPO HR (R2 = 0.994) and a linear increase in GXT HR (r2 = 0.999) that were both significantly greater than baseline after 10% TLim. For the GXT, the HR at each time point was greater than the previous, but for the 85% PPO trial, the HR at 100% was not different from the HR at 80–90% TLim. The 85% PPO RR demonstrated a linear increase (r2 = 0.931) that was significantly greater than baseline at 30% TLim, but all time points were less than 100% TLim. However, GXT RR demonstrated a quadratic increase (R2 = 0.990) that was significantly different from baseline at 50% TLim, but all time points were less than 100% TLim. The 85% PPO RPE had a quadratic increase (R2 = 0.993) that was significantly greater than baseline after 10% TLim, but the RPE at 100% TLim was not different than the RPE at 70–90% TLim. The GXT RPE had a linear increase (r2 = 0.997) that was greater than baseline after 20% TLim and each time point was greater than the previous. Conclusions: There were distinct patterns of responses and time course of changes for the physiological and perceptual variables during exhaustive exercise at 85% PPO compared to the GXT. The V̇o2, HR, and RPE demonstrated a plateau for the last 20–40% of TLim at 85% PPO, but continuous increases were observed for each of these variables in the GXT. The RR patterns of responses and time course of changes did not track any other variables. Thus, RPE may be most closely related to metabolic and cardiovascular demands during exhaustive incremental and constant PO exercise. Practical Applications: The similar patterns of responses and time course of changes between V̇o2, HR, and RPE support the use of RPE to monitor the metabolic and cardiovascular demands during constant PO or incremental exercise without the need for additional equipment.

(10) Sweat Rate Variability in Endurance-Trained Athletes

M. Bello, B. Shepherd, F. Price, and J. Smith

Mississippi State University

Adequate fluid replacement following exercise is an important consideration for athletes, however similar environmental conditions may not produce consistently similar sweat rates. Understanding and measuring the fluctuations in sweat rate can be a useful indicator for proper hydration strategies. Purpose: The purpose of this study was to investigate variations in sweat rate while performing self-selected exercise sessions to evaluate error in sweat rate calculations in similar temperature conditions. Methods: Endurance-trained males (n = 3) and females (n = 9) completed training sessions once per week for a minimum of 30 minutes of running or biking at a self-selected pace over a period of 24 weeks. Body mass was recorded pre- and post-training, and any fluids and foods consumed during exercise were weighed pre/post. The highest and lowest sweat rates were recorded for each individual in 3 WBGT conditions: Low (<10°C), Moderate (10–20°C), High (>20°C). T-tests were used for comparisons between WBGT, duration, distance, pace, and sweat rate within each temperature range. Significance was set a priori at P < 0.05. Results: Participant sessions were split into temperature ranges for analysis (Low, n = 9; Moderate, n = 6; High, n = 10). There were no significant differences in duration, distance, pace, and WBGT for any of the groups within the grouped temperature (p > 0.07). High and low sweat rates were significantly different in for all groups. Average differences in sweat rates were: ΔLow = 0.15 L/h, p < 0.01; ΔModerate = 0.14 L·h−1, p < 0.05; ΔHigh = 0.13 L·h−1, p < 0.01. Conclusions: The assessment of sweat rate for a training session can provide useful data for determining fluid intake both during and post-exercise. However, the significant differences in sweat rates within each temperature ranges indicates a single timepoint may not accurately represent an individual's typical rate in similar environmental conditions. Practical Applications: Despite similar environmental conditions and training intensity, individuals experienced variation in sweat rate within each temperature range. This indicates the fluid loss during exercise varies, extrapolation for longer periods of exercise can lead to error, and monitoring/measuring fluid loss regularly can help properly implement hydration strategies to optimize training and performance.

(11) Association of Fitness Testing, External Load Metrics, and Hard Endpoints in NCAA Division I Women's Lacrosse

C. Fortney, J. Kilian, A. Schaefer, and J. Glauser

Liberty University

Load monitoring is a popular application of wearables, but less is known about the connection to hard endpoints during gameplay. Purpose: The purpose of this study was to discover correlations between fitness tests, external load measures, and hard endpoints during simulated competition in collegiate women's lacrosse. Methods: Data were collected during 6 off-season intra-squad scrimmages. These officiated scrimmages were designed to replicate games and were played according to regulation. External load metrics were collected using wearable technology (Playertek by Catapult, Melbourne, Australia). The external load metrics were total distance (TD), sprint distance (SD), and power plays (PP). Goals (G), assists (A), shots (S), caused turnovers (CT), and ground balls (GB) were documented for all athletes listed on the starting line-up for both teams. Fitness tests completed were the average of 2 trials of the 300-yard shuttle (300YST), Peak Power (POW) assessed via a pneumatic squat machine (Keiser Corporation, Fresno, CA), and the Beep Test (BT). Pearson correlations were computed for all variables with significance set at p < 0.05. Results: Peak power was significantly correlated with 300YST (r = −0.447, p = 0.01). The 300YST scores were significantly correlated with stage completed for the BT (r = −0.57, p = 0.001). Overall, fitness tests were poorly correlated with in-game external load and hard endpoints (p > 0.05). Significant correlations between external load and hard endpoints are presented in Table 1. No significant correlations were found between external load measures and GB or CT. External load in 1 game was significantly correlated with next-game performance for the TD (range: 0.628 ≤ r ≤ 0.889, p < 0.05), SD (range: 0.554 ≤ r ≤ 0.978, p < 0.05), and PP (range: 0.610 ≤ r ≤ 0.871, p < 0.05). Conclusions: Fitness testing scores tend to be correlated with each other but with limited application in correlating certain fitness tests with certain external load measures. Some correlations were found between external load and hard endpoints, but further research is needed to elucidate a more consistent pattern. This study was not designed to account for technical or tactical aspects of sport performance or other moderating variables such as recovery, so future research should focus on controlling these factors. Practical Applications: Finding associations between external load metrics and hard endpoints during gameplay can be a valuable tool for coaches to understand which physical performances tend to influence the outcome of a game more. While fitness testing and in-game physical performance have their place, there may be limited connection between these variables and hard endpoints. The results of this analysis emphasize the importance of measures not included in external load or fitness testing data, which may include technical and tactical factors.

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Table 1:
Significant correlations between external load and hard endpoints.

(12) Sport Differences in FAT-FREE Mass Index Among a Diverse Sample of Female Collegiate Athletes

A. Jagim,1 J. Luedke,2 and J. Erickson1

1Mayo Clinic Health System; and2University of Wisconsin - La Crosse

Body composition assessment is a valuable tool among applied sports science settings to monitor changes in training and nutrition-focused interventions, while also allowing for the classification of health status among athletic populations. Fat-free mass index (FFMI) in particular, is becoming a popular metric to determine an athletes potential for future fat-free mass accrual or to identify athletes who may be at risk for low FFM, potentially indicative of disordered eating patterns, namely insufficient energy intake. However, limited data are available regarding normative data profiles of FFMI values among female collegiate athletes. Purpose: The aim of the current study was to examine sport-specific differences in FFMI values among a convenience sample of female collegiate athletes. Methods: Ninety-two NCAA Division III female (Age: 19.45 ± 1.1 years, Height: 1.68 ± 0.06 m, Bodyweight: 65.16 ± 11.04 kg, %BF: 22.71 ± 5.9%) athletes completed a body composition assessment using air displacement plethysmography between the 2015–2020 seasons. FFMI was then calculated by dividing FFM by height·m−2. Linear regression was used to calculate a height and sex adjusted FFMI value. Results: Regressing FFMIRaw against height in this subgroup revealed a nonsignificant slope of B = −0.043 (p = 0.285). After adjusting all FFMIRaw data using this slope, 1-way ANOVA revealed that there was no significant difference between FFMIRaw, FFMIAdjfemales or FFMIAdjmales, therefore, FFMIRaw was used to report all results. The results of the 1-way repeated-measures ANOVA indicated that the mean ± SD FFMI for all athletes was 17.54 ± 1.8 kg·m−2. There was a significant main effect for sport category, with post-hoc analysis indicating that throwers had a higher (p < 0.001) FFMI (mean difference, 95% confidence interval) compared to sprinters & soccer athletes (4.17, 2.03–6.32 kg·m−2), endurance & weight sensitive athletes (4.91, 2.67–7.14 kg·m−2), and court sport athletes (4.39, 1.97–6.81 kg·m−2), respectively. A summary of FFMI raw and male adjusted values with percentile rankings by sport are presented in Table 1. Conclusions: The results of the current study indicate that sport-specific differences in FFMI exist among female athletes with strength athletes (throwers) exhibiting higher FFMI values than other sport categories. Practical Applications: The results of the current study can help guide strength training and nutritionl programming decisions by providing sport specific normative data profiles regarding FFMI for female athletes. These profiles can help rank athletes, depending on where they fall within the respective percentile categories and better direct subsequent body composition goals. Further, this information allows for comparisons across sport categories and divisions of competition.

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Table 1:
Descriptive summary of FFMI values and percentile rankings by sport category.

(13) Differences in Lower-Body Strength and Leg Lean Mass in Pre, Peri and Post-menopausal Women

A. Gordon, L. Gould, A. Hoyle, H. Cabre, H. Giuliani, E. Ryan, and A. Smith-Ryan

University of North Carolina at Chapel Hill

Women may spend up to half of their lives in menopause. The menopause transition is characterized by a drop in estrogen levels, and concomitant increase in chronic disease risk. Menopausal changes coupled with the age-related loss of skeletal muscle mass (sarcopenia), can impact functionality and quality of life. It is important to understand the extent to which the menopausal transition impacts measures of lower body strength and functionality. Purpose: To investigate the cross-sectional changes in peak torque (PT) across the menopause transition. A secondary aim was to evaluate differences in total leg lean mass (LMleg) between pre-, peri-, and post-menopausal women. Methods: Seventy-two healthy females (Mean ± Standard Deviation: Age = 48.1 ± 7.1 years, Ht = 163.0 ± 6.4 cm, Wt = 69.2 ± 14.5 kg) were stratified by menopausal status. To be classified as pre-menopausal (PRE), women were ≥35 years old and eumenorrheic for the previous 12 months. Peri-menopausal (PERI) women were ≥38 years old and experiencing irregular menstrual cycles, and post-menopausal (POST) women were amenorrheic for ≥12 consecutive months. Knee extensor strength of the dominant leg was evaluated with a calibrated portable isometric dynamometer. Participants performed 3 warm-up repetitions at 50–75% of maximal effort followed by 3 maximal efforts, separated by 1 minute of rest. Whole-body dual-energy x-ray absorptiometry (DXA) scans were performed to evaluate total LMleg and dominant leg-specific LM (right/left). To account for differences in LM, dominant leg LM was used to calculate adjusted PT (PT/LMleg). A 1-way analysis of covariance (ANCOVA), covaried for age, was used to evaluate the differences in PT, adjusted PT, and LMleg between menopause groups. Results: There were no significant differences in absolute PT between PRE and PERI (Mean Difference [MD] ± Standard Error [SE]: 61.5 ± 26.5 Nm, p = 0.070) or PRE and POST (41.1 ± 26.9 Nm, p = 0.391). No significant differences were found in adjusted PT between PRE and PERI (MD±SE: 1.3 ± 1.4 Nm, p < 0.99) or PRE and POST (−0.2 ± 1.4 Nm, p < 0.99) menopausal groups. LMleg significantly decreased between PRE and POST (MD ± SE: 1.6 ± 0.6 kg, p = 0.055), but was not significantly different between PRE and PERI (1.4 ± 0.6 kg, p = 0.085). Conclusions: The lack of significant differences in PT between menopause groups suggests that despite a decrease in lower body LM, the menopause transition alone is not a main contributing factor to potential declines in lower body strength with age. Practical Applications: When examining increased chronic disease risk and decrease in functionality experienced throughout the menopause transition, the lack of strength decrements found in this study warrant further research into factors that affect functional outcomes. When training and prescribing exercise and nutritional strategies to women in the menopause transition, maintenance of LM should be a primary focus; an average of 1.5 kg lost in the legs may have significant implications for functionality and quality of life.

(14) Relationship Between Work-Related Fatigue and Performance Fatigability in Career Firefighters

H. Giuliani,1 M. Laffan,1 A. Trivisonno,2 G. Gerstner,3 J. Mota,4 and E. Ryan1

1University of North Carolina at Chapel Hill;2United States Performance Center;3Old Dominion University; and4University of Alabama

Due to the unique work characteristics and strenuous demands of their job, firefighters experience work-related fatigue which can influence occupational health and safety. Previous studies have shown that changes in maximal strength across a shift cycle are related to inter-shift recovery in firefighters when quantified using the Occupational Fatigue Exhaustion Recovery (OFER) scale. However, no research has examined the relationship between a lab-based measure of performance fatigability and survey-based perceptual fatigue in this population. Purpose: The purpose of this investigation was to examine the relationship between the 3 dimensions of the OFER (acute fatigue, chronic fatigue, inter-shift recovery) and performance fatigability in career firefighters. Methods: Thirty-nine career firefighters (32.7 ± 8.2 years, 179.0 ± 7.4 cm, 92.7 ± 19.1 kg, 28.9 ± 5.3 kg/m2) visited the laboratory for a single visit. Following a brief warm-up, 3 maximal voluntary contractions (MVC) were performed to determine baseline maximal isometric peak torque (PT). Participants then completed an isotonic leg extension fatigability assessment, which included 30 isotonic concentric contractions at 40% MVC through 80° of range of motion, with 1 contraction every 3 seconds and the limb passively returned to the starting position. Immediately following the fatiguing task, a single isometric MVC was performed. Isometric PT was determined as the highest 500 ms epoch during the 3–4 seconds contractions, and performance fatigability was examined by calculating the percent change in PT from prior to and following the fatiguing task. Participants also completed the OFER scale, which includes a total of 15 questions examining 3 unique components of work-related fatigue—acute fatigue (AF), chronic fatigue (CF), and inter-shift recovery (IR). The OFER scale is a 7-point Likert scale ranging from 0 (strongly disagree) to 6 (strongly agree), with a combination of positively and negatively keyed items. Negatively keyed items were reversed scored (final score = 6-original score). Each subscale score is computed by a formula: (sum [item scores]/30)*100. Higher AF and CF scores indicate greater fatigue, whereas a higher IR score indicates better recovery. Pearson product-moment correlation coefficients were used to determine the relationships between AF, CF, and IR with the percent reduction in PT, with an alpha level set at 0.05. Results: The mean ± SD for the AF, CF, and IR scores and the percent reduction in PT were 13.9 ± 4.1, 33.9 ± 18.3, 75.8 ± 18.4, and 10.9 ± 10.7%, respectively. The reduction in PT was not significantly related to AF (p = 0.51), CF (p = 0.80), or IR (p = 0.67). Conclusions: Although research has shown that changes in strength across a shift cycle may relate to work-related fatigue in firefighters, this lab-based assessment of performance fatigability was not associated with perceived work-related fatigue. Practical Applications: These findings may highlight that a single laboratory assessment of high-intensity performance fatigability may provide little insight into perceived work-related fatigue in firefighters. However, future studies are needed to determine if different fatigability assessments (e.g., long duration, lower intensity) or the timing (e.g., prior to or after their shift cycle) of these assessments may impact these results.

(15) Acute Hypoxic Exposure Does Not Affect Performance on the Army Combat Fitness Test of the 3 Repetition Deadlift, Hand-Release Push-Up, and Leg Tuck

J. Jenkins, O. Salmon, and C. Smith

University of Texas at El Paso

Altitude stress in military operations is defined as terrestrial elevations above 3,937 ft, where the decrease in atmospheric pressure causes a proportional decrease in partial pressure of oxygen. High altitude conditions can be simulated by altering the fraction of inspired oxygen, which reduced the amount of oxygen inhaled. Decreased availability of oxygen (i.e., hypoxia) has been shown to cause functional impairments and altitude illness. The Army Combat Fitness Test (ACFT) is the new physical assessment of the United States Army, with the goal of providing a better indicator of physical performance in a combat environment and reduce physical training related injuries. Military deployments and operations have increased, especially in high mountainous terrain as a result of combat operations against military units or terrorist organizations. Purpose: The purpose of this study was to examine the effect of acute hypoxic exposure at simulated altitude of 7,000 ft (FiO2: 16%) and 10,000 ft (FiO2: 14.3%) during the 3 Repetition Maximum Deadlift (MDL), Hand-Release Push-Up (HRP), and Leg Tuck (LTK) performance of the ACFT. Methods: Fourteen men (10) and women (4) (mean ± SEM; age 27.36 ± 1.12 years, height 1.71 ± 2.79 m, weight 80.60 ± 4.24 kg) performed the MDL, HRP, and LTK events of the ACFT once at Baseline condition (FiO2: 21%) and at simulated elevation of 7,000 ft (FiO2: 16%) and 10,000 ft (FiO2: 14.3%) using a hypoxic generator with an exposure time of around 1 hour. ACFT scores were calculated using regression analysis of FY20 ACFT Standards of the MDL, HRP, and LTK events. Passing was defined as the Army's minimum standard for soldiers in “moderate” physically demanding units and military occupational specialties. Results: The 1-way repeated measures ANOVA was not significant for total ACFT Scores (Baseline: 77.58 ± 4.10, 7,000 ft: 79.24 ± 4.70, 10,000 ft: 77.00 ± 4.47; p = 0.0141, ηp2 = 0.140). Finally, 1-way repeated measures ANOVA indicated no difference in MDL performance (273.30 ± 14.70 lbs, 236.90 ± 29.02 lbs, 246.5 ± 24.26 lbs; p = 0.195, ηp2 = 0.124), the number of HRP (37.64 ± 3.93, 38.00 ± 4.50, 36.64 ± 4.16; p = 0.677, ηp2 = 0.030) and LTK (8.50 ± 2.31, 9.79 ± 2.66, 8.43 ± 2.53; p = 0.136, ηp2 = 0.142) performed at acute hypoxic exposure of Baseline, 7,000 ft, and 10,000 ft. Conclusions: Acute hypoxic exposure had no effect on ACFT scores based on the MDL, HRP, and LTK events. There was also no difference in performance within the 3 events of the ACFT during acute hypoxic exposure. The results of this study indicate soldier-analogs were able to maintain similar physical performance at simulated acute hypoxic exposure during the MDL, HRP, and LTK events of the ACFT. Practical Applications: Acute hypoxic exposure, simulating rapidly ascending to high elevation environments, did not affect performance on the MDL, HRP, and LTK ACFT events. The results of this study can be useful for Army Commanding Officers when faced with rapid deployment to high elevation combat zones, where acclimatization may not be possible.

(16) Muscular Strength Differences in a Nationally Representative Sample of Older Veterans and Non-Veterans

J. Harden, L. Reynolds, P. Wilson, and G. Gerstner

Old Dominion University

Lean mass and muscular strength decrease with age, the consequences of which may lead to further health concerns. Although the veteran population is an at-risk population for physical health risks, little is known about the differences in muscular strength between veteran and non-veteran populations. Partaking in regular physical training as a part of military service, for example, could confer some benefits with respect to strength and lean mass (LM) maintenance, but this has not been examined at the population level in the United States. Purpose: This study examined the difference in absolute and normalized isokinetic muscular strength, LM, and percent fat mass (%BF) between older American male veterans and non-veterans aged 50–64 years. Methods: This study consisted of a cross-sectional, observational analysis of publicly available National Health and Nutrition Examination Survey (NHANES) data, covering 1999–2002. The population-representative estimates generated by NHANES are achieved through stratified, multistage, probability-based sampling technique, and this sampling process consists of 4 stages, including counties, segments, households, and individuals. Muscle strength data was available on 865 male veterans (VET; stature: 177.2 ± 0.58 cm; mass: 90.9 ± 1.23 kg; BMI: 28.9 ± 0.49 kg·m−2) and 1,075 non-veterans (NON; stature: 175.4 ± 0.52 cm; mass: 87.7 kg ± 0.91; BMI: 28.4 ± 0.26 kg·m−2) aged 50–64 years. Measurements were taken in a mobile examination center for height, weight, muscular strength, LM, and %BF. A dual-energy x-ray absorptiometry scan was used to determine LM and %BF. Isokinetic muscular strength was measured as the peak force (PF) of the quadriceps at the speed 60 deg·second−1. Normalized muscular strength (nPF) was determined by dividing PF by LM. Data for each measurement was downloaded from the NHANES website, then combined into a master file for all analyses. NHANES-supplied exam population-weights were used to account for the sampling design and non-response. Means and standard errors of the means were calculated for continuous variables. Four t-tests were used to determine the differences between groups regarding PF, nPF, LM, and %BF. All tests were considered significant at an alpha of 0.05. Results: There were statistically significant differences between groups for PF (VET: 490.1 ± 3.7 N; NON: 476.2 ± 3.3 N; p = 0.002) and nPF (VET: 8.09 ± 0.06 N/kg; NON: 8.03 ± 0.05 N/kg; p = 0.006). However, there were no statistically significant differences between groups for LM (VET: 61.1 ± 0.28 kg; NON: 59.8 ± 0.28 kg; p = 0.793) and %BF (VET: 29.7 ± 0.17; NON: 28.5 ± 0.17; p = 0.615). Conclusions: These findings indicate that, despite having similar levels of LM and %BF, veterans aged 50–64 years have greater absolute and relative isokinetic muscular strength than non-veterans. However, the differences were small and of unknown clinical significance. Practical Applications: As both muscle mass and strength are known to decrease starting in the fifth decade, interventions focusing on maintaining maximal isokinetic strength, not just muscle mass, are needed within the general population. However, interventions focused on decreasing %BF or increasing lean mass would be beneficial to both veteran and non-veteran populations.

(17) Applications of Heart Rate Variability Monitoring in Tactical Police Training

C. Tomes, B. Schram, and R. Orr

Bond University

Purpose: Police work is known to be a physically, mentally, and emotionally demanding profession. Special Emergency Response Teams (SERTs) are tasked with responding to the most high-risk scenarios. Further, many SERT operators serve on teams as a collateral duty beyond their regularly scheduled police work. As such, these personnel often attain very high levels of physical fitness but may be vulnerable to accumulating excessive chronic stress. Heart rate variability (HRV), the analysis of the difference in time between individual beats of the heart, shows promise as a field measurement of holistic load because of its sensitivity to the dynamic regulatory patterns that both intrinsically and extrinsically regulate cardiac activity. However, little HRV research has been conducted to date among SERT personnel. Methods: The aim of this study was to identify potential relationships between a measure of physical fitness (occupational obstacle course completion time) and time-domain HRV (pRR50) in a pilot cohort of SERT personnel. This research was conducted in compliance with the Declarations of Helsinki and with IRB approval. Prospective 3-lead ECGs were captured from 8 male SERT operators prior to and following a firearms training event. HRV was assessed as the within-operator change from baseline to post-training of the percentage R-R intervals varying by 50 ms (∆pRR50). Results: Obstacle course time correlated significantly with ∆pRR50 r(8) = 0.712, p = 0.048. More fit operators (as measured by obstacle course time) were more resilient to HRV changes during training. Conclusions: These results indicate the HRV monitoring is feasible in the field environment and can provide human performance optimization personnel with an additional meaningful tool for the objective measurement of stress in a tactical police environment. Organizations should promote fitness in personnel and may especially consider anaerobic capacity and recovery as a means of mitigating stress vulnerability based on the results of this study. Practical Applications: These results establish precedent for further investigations into HRV monitoring utilization in tactical police units. The findings of this study also indicate that more fit operators were more physiologically resilient to demands imposed by the training exercise. Specifically, anaerobic capacity and recovery may be key performance indicators within this population and warrant further investigation. TSAC practitioners may consider utilizing HRV measurement to support human performance optimization efforts within their organizations.

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Table 1:
HRV Values by training phase.

(18) Relationship Between Stature, Body Composition, and Absolute and Relative Strength and Power to Fastball Velocity Among Collegiate Baseball Pitchers

D. Szymanski,1 J. Szymanski,1 P. Ortiz,1 D. Cloud,1 and R. Crotin2

1Louisiana Tech University; and2ArmCare.com

Purpose: To determine which lab and field tests correlate to mean and best fastball velocity (FBV) for collegiate baseball pitchers. Methods: Twenty-five Division I baseball pitchers (age = 20.4 ± 1.5 years, height = 187.0 ± 6.0 cm, body mass = 91.2 ± 12.4 kg, lean body mass = 75.6 ± 7.5 kg, percent body fat = 15.5 ± 5.9%, body mass index = 26.0 ± 2.7 kg/m2, adjusted BMI = 21.9 ± 1.5 kg lean body mass/m2) volunteered for this study. Tests included anthropometrics and body composition as well as absolute strength tests for 1 repetition maximum (1RM) parallel squat (PS), dumbbell bench press (DBBP), and 1-arm landmine (LM) row, and dominant (D) and non-dominant (ND) hand grip, index finger pinch, and middle finger pinch strengths. Absolute power tests included a 1.8 kg overhead medicine ball throw (OHMBT) for velocity, standing long jump, D and ND leg lateral-to-medial jump, vertical jump, and estimation of peak power (PP). Relative values for all tests were calculated based on the strength and power values divided by the athlete's body mass and lean body mass (LBM). The mean and best FBV from 485 fastballs were recorded during 17 offseason intrasquad games from the wind-up. All of these variables were correlated with 1 another by using a correlation matrix from raw data scores. The critical r value for Pearson product-moment correlation coefficient was 0.396 with an alpha level of 0.05. Results: Mean FBV was 38.8 ± 1.4 m·s−1 while the best FBV was 40.3 ± 1.2 m·s−1. There were significant moderately high correlations between best FBV from the wind-up and total grip strength (r = 0.705), D grip strength (r = 0.667), ND grip strength (r = 0.655), 1-arm LM row (r = 0.620), estimated PP (r = 0.618), and OHMBT (r = 0.604). There were significant moderate correlations between best FBV from the wind-up and LBM (r = 0.559), 1RM PS (r = 0.447), adjusted BMI (r = 0.433), and height (r = 0.429). There were significant moderate correlations between mean FBV from the wind-up and OHMBT (r = 0.544), LBM (r = 0.509), height (r = 0.485), total grip strength (r = 0.466), D grip strength (r = 0.456), estimated PP (r = 0.453), and ND grip strength (r = 0.412). Conclusions: There were significant relationships between mean and best FBV from the wind-up during intrasquad games and various anthropometric, body composition, and absolute strength and power variables. There were no significant relationships between mean and best FBV from the wind-up during intrasquad games and absolute DB BP or various pinch strength, nor any absolute or relative jump tests, or any relative strength or power variables. Practical Applications: Results indicate that strength and conditioning professionals should emphasize the development of absolute strength and power as well as LBM for collegiate baseball pitchers. When addressing the lack of significant relationships between the various absolute and relative jump test results and mean and best FBV, strength coaches must remember that just because they have helped develop strong and powerful pitchers, it does not mean that those outcomes relate to FBV or that those pitchers will improve their FBV. Finally, bilateral and unilateral jump testing in baseball can be used as markers of fitness improvement, maintenance, or decrements; or baseline data used to determine rehabilitation status for when to return-to-play. Perhaps, physical qualities that are unassociated with FBV may be found to improve injury prevention in future studies.

(19) Relationships Between Lower-Body Power and Linear and Change of Direction Speed Among Major League Soccer Combine Participants

J. Zaragoza, Q. Johnson, B. Jacobson, D. Smith, and J. Dawes

Oklahoma State University

Professional sports teams and organizations often evaluate athletic abilities of potential athletes through physical fitness assessments. Especially, in the United States, elite collegiate and international soccer players will complete combine testing prior to entering the Major League Soccer (MLS) draft. The MLS Combine, completed over 4-days, consists of anthropometric measurements and physical fitness assessments (i.e., vertical jump, 30-meter sprint, and 5-10-5 agility) followed by soccer specific field assessments (e.g., scrimmages) from technical and tactical coaches. To date, no research exists examining the Combine performance assessment results in prospective MLS athletes. Purpose: The purpose of this study was to determine if a relationship exists between lower-body power and measures of linear and change of direction speed (CODS) in MLS Combine participants. Methods: Publicly available data from 6 years (2013–2019) of MLS Combine participants (N = 81) was retrieved from an online database. Performance (i.e., 30-meter sprint and 5-10-5 agility) data were assessed. Pearson's correlation coefficient was used to determine if significant relationships exist between lower-body power (absolute (PAPw) and relative power (P:BM)) and the Combine performance tests. All data were analyzed using a free open-source statistical software package (JASP, Version 0.11.1, Amsterdam, NL USA) and statistical significance was set a priori at p ≤ 0.05. Results: A large, significant correlation was found between absolute power and 30-meter sprint time (r = −0.60, p = 0.001), but not 5-10-5 agility (r = −0.20, p = 0.11). Similarly, a significant large correlation was seen between relative power and 30-meter sprint time (r = −0.67, p = 0.001), but not 5-10-5 agility (r = −0.21, p = 0.09). Conclusions: On average, only 0.01% of male collegiate soccer players in the United States are invited to participate in the MLS Combine. As such, optimal performance in fitness testing and field evaluations is necessary to improve an athlete's chance of being selected during the draft. One way to optimize performance is in the ability to generate high amounts of lower-body power, a necessary attribute in high-intensity, and intermittent team sports such as soccer. Specifically, the results of the present study indicate that the development of lower-body power (absolute or relative to body mass) may improve linear speed in elite collegiate MLS Combine prospects. Practical Applications: Research conducted in elite athletes is often limited for various reasons. Moreover, research conducted in prospective MLS athletes is lacking. This study demonstrates the relationships between lower-body power and the selected MLS combine performance tests in elite, prospective MLS athletes. Based on these results it appears that an emphasis on developing lower-body power among elite soccer athletes can positively impact linear and change of direction speed performance. As such, this should be a priority when preparing athletes for the MLS Combine.

(20) Examining the Acute Effect of a Tabata Workout on Executive Function

R. Edmonds, R. Kraft, M. Cantu, E. Meister, P. Huynh, and J. Siedlik

Creighton University

Early research suggests that moderate intensity aerobic exercise has the potential to improve cognitive performance, while high intensity exercise may decrease optimal cognitive performance. Research also shows that individuals with higher aerobic fitness may be able to better maintain sustained attentional, however less is known about the potential impact of anaerobic based exercise on attentional focus and working memory. Purpose: To examine the acute effect of a Tabata workout on executive function, assessed via the paced auditory serial addition task (PASAT). Methods: Participants (N = 20, Age = 21.3 ± 0.9 years, Ht = 1.7 ± 0.1 m, Wt = 67.9 ± 10.1 kg) completed 5 familiarization trials of the PASAT and 2 familiarization trials of the Tabata workout. Following a randomized crossover design, subjects completed 2 trials, an experimental condition in they completed a Tabata workout, with a PASAT was administered while rested (BASE), 10 minutes after the Tabata (POST-10), and 20 minutes after the Tabata (POST-20), and a control condition in which participants did not complete a Tabata workout, but still completing the time-matched PASAT task. During both trials, heart rate and heart rate variability were recorded at rest upon arrival (BASE), and before and after each PASAT was administered (Figure 1). Salivary cortisol was also recorded at rest and upon completion of the last PASAT. Differences across all dependent variables were analyzed by using repeated measures analysis of variances. Results: Significant interactions (p < 0.05) were identified for HR, HRV, RMSSD between conditions. As anticipated, HR was significantly higher post Tabata when compared to the control trial. Likewise, as expected, HRV and RMSSD were significantly reduced following the Tabata workout when compared to the control trial. Salivary cortisol was similar before and after the PASAT in the control trial, while it was significantly higher post Tabata compared to baseline. A significant main effect (p < 0.05) was observed for the PASAT between conditions. Conclusions: The current study suggests that an acute bout of HIIT prior to a cognitive task may offer subtle improvements to working memory as assessed by the PASAT. More importantly, these results suggest an acute high-intensity workout does not have a detrimental impact on short-term cognition. Practical Applications: While the improvement in PASAT scores following the Tabata workout may not offer a meaningful improvement in working memory, it does suggest that a high-intensity workout 10–20 minutes prior to a cognitive task does not appear to hinder working memory. As such, given the overwhelming evidence that supports the cardiovascular benefits of HIIT, college students who are short of time should look to the Tabata as a means to stay in shape.

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Table 1:
Experimental and Control protocol timelines.

(21) Acute Effect of Ankle Joint Mobilization on Hamstring Flexibility

C. Kaplan,1 D. Szymanski,2 and S. Graves3

1James Madison University;2Louisiana Tech University; and3Florida Atlantic University

Non-contact hamstring strain injuries are very common among collegiate level power sport athletes. Common modifiable etiological factors of hamstring strains include, but are not limited to, muscular imbalance, muscle fatigue, and hamstring tightness. Purpose: To investigate the effects of ankle joint mobilization on hamstring flexibility in NCAA Division I athletes. Methods: Eight male (age 20.6 ± 0.68 years, height = 185.73 ± 4.59 cm, body mass = 86.75 ± 4.25 kg) and 10 female (age 20.6 ± 0.34 years, height = 173.23 ± 2.39 cm, weight = 70.31 ± 3.75 kg) Division I athletes from 7 different power sports (baseball, basketball, beach volleyball, football, indoor volleyball, soccer, and softball) volunteered for this study. All subjects completed a health questionnaire and dietary log before participating in the battery of tests. Before completing 2 trials of the weight-bearing lunge test (WBLT) and sit and reach test (SART), all subjects participated in a test familiarization session. Subjects began each trial by removing their shoes and sitting for a 5-minute rest period. Following the rest period, ankle dorsiflexion was measured using the WBLT. Subjects were instructed to place either knee against the wall and move their front foot back as far as they could before their heel lifted off the ground. The distance between the big toe and the wall was measured. Once this was completed, then the other ankle was tested. Following the WBLT, subjects performed a SART. After another 5-minute rest period, subjects were then randomly chosen to receive the intervention. The intervention consisted of 5 posterior to anterior oscillations of each metatarsal, then 10 posterior to anterior mobilizations of the ankle joint. If a subject was not randomly selected to receive the intervention, they would receive it the next trial. Following the intervention, subjects would perform the WBLT and SART again. The difference between the pre-intervention and post-intervention tests was determined. Data were analyzed using a 2-way repeated measures ANOVA. If an interaction or main effect were noted, paired sample t-tests were run. All data are presented as mean ± SD. Alpha levels were established a priori at p < 0.05. Results: A significant main effect was noted for WBLT (p = 0.04) and SART (p = 0.03). There was a statistical differences between the intervention and non-intervention WBLT (p = 0.002). The intervention added 1.30 cm of dorsiflexion to each foot. There were significant statistical differences between the intervention and non-intervention post-test SART (p = 0.0014). When subjects received the intervention, they added an average of 2.60 cm to their SART. Conclusions: The data suggests that an acute intervention of metatarsal oscillations and ankle joint mobilizations is effective in increasing ankle dorsiflexion and hamstring flexibility in NCAA Division I athletes. Practical Applications: Although the sample size was small for this study, the preliminary results show promise for this intervention as an effective acute means to increase ankle dorsiflexion and hamstring flexibility. Clinically, this procedure could be used in addition to various types of traditional stretches and specific exercises as a way to reduce hamstring injury occurrence.

(22) Positional Differences in Performance Among Major League Soccer Combine Participants

J. Prather,1 J. Zaragoza,2 C. Harrison,1 and L. Taylor1

1University of Mary Hardin-Baylor; and2Oklahoma State University

The Major League Soccer (MLS) combine is held every year inviting promising elite collegiate and international soccer players to participate in fitness and field testing. Over the course of 4 days, the MLS combine assesses vertical jump, 30-meter sprint, 5-10-5 agility test, as well as anthropometric measurements. To date, there have been no studies examining the positional differences in fitness assessment results of elite athletes participating in the MLS combine. Purpose: The purpose of this study was to examine positional differences in MLS combine physical fitness assessments. Methods: Publicly available data was obtained from an online database from the 2013 to 2019 MLS combine (n = 81). Players were grouped by their position for testing purposes (defenders [DF] [n = 33; height, 181.95 ± 5.95 cm; weight, 77.66 ± 6.74 kg], forwards [FW] [n = 16; height, 181.92 ± 6.87 cm; weight, 79.71 ± 8.11 kg], and midfielders [MF] [n = 28; height, 177.62 ± 6.03 cm; weight, 72.56 ± 6.66 kg]]. Due to a small sample size (4), goalkeepers were excluded from this analysis. All data were retrospectively analyzed using PASW software version 24.0 (SPSS Inc, Chicago, IL). Descriptive statistics (mean ± standard deviation) were calculated for each variable. One-way analysis of variance (ANOVA) with a Bonferroni post-hoc analysis was used to detect differences between groups. Statistical significance was set a priori at p ≤ 0.05. Results: Anthropometric differences were observed with significant differences in height (DF: 181.95 ± 5.95 cm vs. MF: 177.62 ± 6.03 cm; p = 0.04) and weight (MF: 72.56 ± 6.66 kg vs. DF: 77.66 ± 6.74 kg; p = 0.03) & (MF: 72.56 ± 6.66 kg vs. FW: 79.71 ± 8.11 kg; p = 0.01). Thirty-meter sprint times were significantly different between FW (4.00 ± 0.14 s) and MF (4.14 ± 0.20 s; p = 0.008). Significant differences between (p = 0.019) DF (76.70 ± 8.92 cm) and MF (70.17 ± 9.02 cm) and between (p = 0.013) FW (78.50 ± 6.28) and MF (70.17 ± 9.02 cm) were observed in vertical jump. Significant differences were seen in peak anaerobic power output between DF (6,118.48 ± 634.24 W) and MF (5,491.26 ± 702.10 W; p = 0.002) and FW (6,321.06 ± 539.07 W) and MF (5,491.26 ± 702.10 W; p < 0.001). No other differences were observed between assessments of physical fitness and player position (p > 0.05). Conclusions: The high-intensity, anaerobic nature of soccer requires a great amount of power and agility from the athletes; however, in order to compete at an elite level, it is critical that players are optimally prepared for training and game play based on their positional demands. The results of this study allow for athletes and strength and conditioning professionals to optimize performance by identifying where individual athletes may be lacking in performance compared to their position. Practical Applications: Scant research exists involving physical assessments of aspiring MLS athletes, thus leaving room for potential gaps in knowledge of the importance of position-specific performance and training goals. This study illustrates the positional differences of elite soccer players in MLS combine physical fitness tests. Future research comparing these data to data from professional and international level soccer clubs could add perspective to the differences between key fitness parameters across positions and play a role in using combine type testing to predict future performance.

(V301) Models Predicting Vertical Jump Displacement Using Structural and Kinetic Variables

L. Weiss,1 D. Powell,1 M. Paquette,1 L. Massey,2 and H. Daugherty3

1The University of Memphis;2Wright Medical Technology, Inc; and3University of Tennessee Health Science Center

Vertical jumping performance relies upon assorted variables contributing to the summation of internal forces to overcome body load at take-off. Body part proportions, dimensions and orientations, integrated force capabilities of involved body parts, and loading are all contributors. Purpose: To identify combinations of independent variables significantly contributing to jumping performance. Methods: Healthy recreationally-trained adults (31 men, 29 women), 18–35 years of age, participated in the investigation. Subjects performed 3 countermovement vertical jumps (CMVJ) using a self-selected initial depth and constrained arm swing. Vertical displacement was measured using a Vertec with initial apparatus position based on maximal unilateral overhead arm reach concurrent with maximal bilateral plantar flexion. Numerous body dimension, body composition, and kinetic variables were measured with the latter assortment attained during CMVJ. A maximum of 1 independent variable per 10 subjects was used as a limitation to the number of explanatory variables considered for inclusion in models. For the combined group of men and women, a maximum of 6 was considered. Bivariate correlations were initially used to identify variables most associated with CMVJ displacement. From that group of variables, the 1 most associated with CMVJ displacement was selected for inclusion in the model. Thereafter, other variables from that group were selected only if they were poorly associated with the initial variable selected. Variable selection was terminated based on sample size limitation or if no additional variables met the criteria for selection. Models were constructed using forced-entry multiple linear regression. A Koenker test was used to test for heteroscedasticity. Multicollinearity was examined using Tolerance (<4.00) and Variance Inflation Factor (>0.20). Other than the constant, variables were excluded from models if they did not make significant (p < 0.05) contributions to the respective equations. Results: Models predicting CMVJ displacement are in Table 1. No model contained more than 3 viable independent variables. Neither heteroscedasticity nor multicollinearity were detected in any of the final models. Conclusions: Two- and 3-predictor models may explain between 69 and 75% of CMVJ displacement in healthy young men and women. Practical Applications: For 3-component models, vertical peak power normalized for body mass and center of mass concentric impulse obtained during vertical jumping may be used with relative body fat to provide the best estimate of countermovement vertical jump displacement. Alternatively, static Q-angle or foot length may be substituted for impulse with a small reduction in predictability. For 2-component models, vertical peak power normalized for body mass and either center of mass concentric impulse obtained during vertical jumping or relative body fat may be used to predict CMVJ displacement.

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Table 1:
Viable models predicting CMVJ displacement for men and women combined.

(V302) Bodymass Is Associated With Cross Punch Force, but Not With Cross Punch Velocity in Male Amateur Boxers

J. Pádecký, K. Petr, R. Jebavý, and J. Tufano

Charles University, Czech Republic

Boxers need to sustain a certain body mass (BM) due to weight categories. Evidence suggests that BM is correlated to cross punch force (PF), and therefore improving PF might be limited. However, it is still unclear whether other crucial punch characteristics such as peak velocity (PV) are correlated to a similar degree with BM, and therefore might be increased without affecting BM. Purpose: Therefore, the purpose of this study was to investigate associations between BM and PF and PV during cross punches. Methods: Twelve elite male amateur boxers (BM 80.4 ± 11.1 kg, height 181.6 ± 7.1 cm, boxing experience 8.0 ± 5.9 years) participated in this study, which took place over 2 laboratory visits. During the first familiarization visit, subjects performed a standardized warm-up consisting of 5 minutes of low-intensity rowing, mobility drills, and 3 short boxing sprints with increasing intensity on a heavy bag. After 4 minutes of rest, subjects performed a single cross punch from a self-selected stance, aiming to punch a tri-axial force plate suspended in the air with a cable system at the subject's chin level. During the second experimental visit which occurred approximately 24 hours after the first visit, subjects performed an identical warm-up, and after 4 minutes of rest, performed 1 cross with the instruction to punch the force plate as hard and as fast as possible. A single reflective marker was placed in the center of the 12-ounce boxing gloves, and punch PV was measured with the Qualisys Motion Tracking Manager (500 fps), which was synchronized with the force plate (12,000 Hz) that recorded the peak force of the punches. Pearson's correlation coefficient, 95% lower and upper confidence intervals (LCI, UCI respectively), and linear regression were used to calculate the associations between BM and PV and PF. Results: V was 9.2 ± 8.59 m·s−1, and PF was 848 ± 210 N. The correlation between BM and PF resulted in r = 0.679 (0.172 LCI, 0.901 UCI), r2 = 0.461, and p = 0.015. The correlation between BM and PV resulted in r = 0.327 (−0.304 LCI, 0.759 UCI), r2 = 0.107, and p = 0.299. Individual punch data in shown in Figure 1. Conclusions: BM was highly correlated with PF, but was not correlated with PV, which may be the result of variety of factors. It is possible that other anthropometric or physical characteristics such as arm length, coordination, or rate of force development might be greater contributors to cross PV. Practical Applications: Since BM was associated with PF but not PV, efforts should likely be made to increase PV in ways that do not influence BM. Future researchers should investigate the effects of arm length, coordination, and the rate of force development on punch PV, as those factors likely play a greater role than BM.

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Figure 1.:
Cross punch peak force (PF) and peak velocity (PV), plotted in relation to each subject's body mass.

(V303) Effects of Footwear on Static and Dynamic Balance in Division 1 Collegiate Volleyball Players

L. Basford, K. Barrett, C. Howard-Smith, J. Garner, and J. Mouser

Troy University

Balance is an important component of volleyball actions, such as blocking and landing. Differences in footwear may influence balance performance by altering proprioceptive characteristics, center of pressure (CoP) location, sway velocity, medial-lateral (ML) displacement and anterior-posterior (AP) displacement. Purpose: To examine the effects of footwear on static and dynamic measures of balance in Division 1 collegiate volleyball players. Methods: Fifteen female participants (mean ± SD): age of 19.5 ± 1.09 years, height of 178.15 ± 6.60 cm, weight of 73.93 ± 7.98 kg, BMI of 23.38 ± 2.23, dominant leg length: 101.42 ± 4.19, nondominant leg length: 100.77 ± 4.19, were recruited for this study; 3 were unable to complete the study due to unrelated injury or time constraints. All data analyses were run on the remaining 12 participants. Participants visited the lab on 4 separate occasions with a minimum of 48 hours between each visit. During each visit, either the Adidas Crazyflight X3 high top (HT), Adidas Crazyflight X3 low top (LT), or Adidas Pureboost Trainer (T) were worn. To determine static balance, participants were instructed to stand on the force plate as still as possible with feet hip width apart and arms at their sides and look at a fixed point. Participants repeated 3 10 s trials with 20 s rest in between each trial. Participants then performed a y-balance test. The order of direction and beginning leg (dominant vs. nondominant) were randomized for each participant prior to arrival. Trials were repeated if participants lost balance. Three successful trials on each leg in each direction were recorded. Repeated measures ANOVAs were performed to determine the effect of shoe on balance measures of RMS sway, sway velocity, CoP excursion, ML and AP displacement, and reach length in the y-balance test. Statistical significance was set a priori at α = 0.05. Results: There were no statistically significant effects of shod condition for any of the static balance measures investigated (p > 0.05 for all). Neither a significant interaction (p = 0.169), nor main effects of shoe (p = 0.669) or leg (p = 0.752) were found for the anterior reach. No significant interaction (p = 0.580) or main effects of shoe (p = 0.786) or leg (p = 0.067) were found in the posterolateral reach. There was a significant shoe x leg interaction (p = 0.036) in the posteromedial reach. Follow-up pairwise comparison with Bonferroni adjustment revealed significant differences between dominant and non-dominant legs in the HT condition (−2.78 cm, 95%CI: −5.18 to −0.38 cm, p = 0.027). Conclusions: With the exception of posteromedial reach length when balancing on the dominant leg, it does not appear that choice of footwear influences laboratory measures of static or dynamic balance in Division 1 collegiate volleyball players. Practical Applications: Unless posteromedial reach length is deemed important, it does not appear that shoe choice affects static and dynamic balance in this population. One should consider practicing in the same shoe that they plan to compete in for reasons of specificity.

(V304) A Comparison of Stroke Length and Thoracic Displacement Between Two Types of Rowing Ergometers

T. Lu,1 M. Jones,1 J. White,2 and J. Yom3

1George Mason University;2Ohio University; and3University of Illinois, Springfield

Ergometer rowing, which requires a complex motor learning process, is utilized for indoor training and to evaluate rowers' physical capabilities. Poor rowing technique can lead to injuries primarily in the lower back, but also in the knee, shoulder, and wrist due to incorrect sequencing of body segment motion. Therefore, understanding differences in technique between ergometers is essential to reduce injury, purchase the safest equipment, and develop efficient techniques. Yet, limited research exists that investigates the kinematic differences of rowing ergometers, particularly during maximum effort. Purpose: To compare the differences in kinematics (stroke length, thoracic displacement) between dynamic (DYN) and type D ergometers in experienced rowers during maximal effort. Methods: Eleven collegiate oarswomen (mean ± SD; age, 20.1 ± 1.3 years; height, 172.9 ± 8.1 cm; body mass, 69.2 ± 13.4 kg; 2,000-m erg time, 474.8 ± 26.6 seconds) completed anthropometric measures and were familiarized with the DYN ergometer on their first visit to the laboratory. For the second and third sessions, 2 incremental exercise tests were separated by 48 hours and completed in randomized order (DYN, type D). Participants performed 7-stage (4 minutes per stage), incremental rowing tests, with the starting intensity determined from each athlete's most recent 2,000-m type D erg time. Intensity increased by increments of 10–20 watts each stage, and the last stage was performed with maximal effort during which the athlete was instructed to cover as much distance as possible. Submaximal stage intensities were the same on the 2 ergometers. A 3D motion analysis system (200 Hz, Vicon) and biomechanical modeling software (Visual 3D, C-motion, Inc.) were used to collect and calculate kinematic data. Stroke length and thoracic displacement were compared using pairwise t-tests (p < 0.05). Results: At the maximal stage, rowers had significantly higher stroke length on the type D (1.4 ± 0.1 m) compared with DYN ergometer (0.8 ± 0.1 m) (p < 0.001). There was no significant difference in the thoracic displacement between the 2 ergometers (DYN: 25.2 ± 13.2 vs. type D: 26.5 ± 4.7°). Conclusions: Stroke length was significantly decreased on the DYN compared to the type D ergometer. Although there was no difference in the thoracic displacement between the 2 ergometers at the maximal stage, it is of interest to note the greater variance in thoracic displacement that was observed on the DYN. Practical Applications: Longer stroke lengths are reported to have a relationship with greater mean forces, which could possibly increase the risk of injury. Increased thoracic displacement is associated with a strategy to create more power to deal with intense training demands. The DYN rowing ergometer, from the injury prevention standpoint, may be a better choice than the traditional type D ergometer due to a smaller stroke length. Therefore, athletes, particularly those at risk for injury, should consider utilizing the DYN ergometer.

(V305) Segmental Bioelectrical Impedance Spectroscopy Phase Angle and Characteristic Frequency as Measures of Muscle Quality in Young Men

L. Arieta,1 H. Giuliani,1 G. Gerstner,2 J. Mota,3 and E. Ryan1

1University of North Carolina at Chapel Hill;2Old Dominion University; and3University of Alabama

Various electrical properties of segmental bioelectrical impedance spectroscopy (sBIS), specifically phase angle (PA) and characteristic frequency (CF), have been speculated to reflect muscle quality or muscle tissue composition. However, few studies to date have examined the association between muscle quality and various sBIS values. Purpose: To determine if sBIS derived PA and CF are associated with quadriceps muscle quality in young men. Methods: Twenty-four healthy, normal weight, and recreationally active young men (mean ± SD age: 21.7 ± 2.1 years; body mass index: 22.5 ± 1.2 kg·m−2) refrained from vigorous exercise for 48 hours and fasted for a minimum of 8 hours prior to visiting the laboratory on 1 occasion. Following a 20-minute lying rest period, panoramic brightness mode ultrasound imaging was used to determine subcutaneous fat corrected echo intensity (EI) as a measure of muscle quality. One scan of each superficial quadricep muscle (vastus lateralis, rectus femoris, and vastus medialis) was taken at 50% of femur length, with the right leg propped and supported at 50° of flexion. Echo intensity was averaged across all 3 muscles. Segmental bioelectrical impedance spectroscopy was used to measure PA and CF of the right thigh. The current injecting electrodes were placed 10 cm distal to the anterior superior iliac spine (proximal injecting electrode) and 10 cm proximal to the tibial tuberosity (distal injecting electrode), respectively. The sensing electrodes were placed 5 cm distal from the proximal injecting electrode and 5 cm proximal from the distal injecting electrode, measured center to center of the electrodes. Pearson's product moment correlation coefficients were used to determine the association between EI and PA and CF. Statistical significance was set a priori at an alpha level of p ≤ 0.05. Results: Echo intensity (83.0 ± 11.7 a.u.) was negatively associated with PA (13.7 ± 1.8°) (r = −0.552, p = 0.005), but was not associated with CF (31.3 ± 5.5 kHz) (p = 0.814). Conclusions: Higher EI was associated with lower PA, but not with CF. These findings suggest that sBIS-derived PA may provide an index of muscle quality, even in a homogeneous sample of healthy young men. Practical Applications: Segmental bioelectrical impedance spectroscopy derived PA may be a portable and cost-efficient way to assess muscle quality in field and clinical settings that would require minimal training.

(V306) Examination of the Relationships Between Biomechanical Markers and Endurance Running Performance in Male and Female Division 1 Cross Country Athletes

L. Biscardi, and D. Stroiney

George Mason University

Running economy (RE) and V̇o2max are related to endurance running performance. At similar relative intensities gender differences in running economy are minimal. RE is related to greater leg stiffness and lower vertical oscillation. Shorter ground contact times and greater force production are related to faster running speeds. Prior research shows that men have greater leg stiffness and run at faster speeds than women. Understanding gender differences in factors related to endurance performance may help guide training programs for collegiate cross-country athletes. Purpose: To compare relationships between markers of endurance performance with vertical oscillation, ground contact time, leg stiffness, and maximal relative force for NCAA D1 men and women cross-country athletes at similar relative intensities of running. Methods: Fifteen NCAA D1 cross country runners (7 males; 20.3 ± 1.3 years; 174.7 ± 10.2 cm; 64.2 ± 9.1 kg; 14.6 ± 8.2 %BF; 58.4 ± 8.6 V̇o2max) completed a 4-minute treadmill run with a 1% incline at self-selected 5k pace. Oxygen uptake and body fat percent were estimated. The validated Runmatic app v8.0.2 with iOS 13.2.3 recorded biomechanical parameters during the run. Mean scores were used for analysis. RE (mL·kg−1·km−1) and biomechanical parameters were analyzed in the last minute of the run. Independent t-tests were used to compare variables between genders. Pearson correlations were run separately for men and women to determine relationships between RE, V̇o2max, speed, ground contact time, vertical oscillation, leg stiffness and maximal relative force. Results: Expected gender differences were found for height, body fat, and V̇o2max (M:65.6 ± 6.8; W:52.0 ± 3.6 mL·kg−1·min−1; p < 0.01). There was a difference in speed (M:18.7 ± 2.4; W:16.2 ± 0.4 km·h−1, p < 0.05) but no difference in relative intensity of running (89.7 ± 4.4%V̇o2max) or RE (184.3 ± 12.7 mL·kg−1·km−1) between genders (p > 0.05). For men, there was a strong positive relationship between V̇o2max and speed (r = 0.84) and maximal relative force (r = 0.80); and strong negative relationships for V̇o2max and speed with contact time (r = −0.93; r = −0.94) and vertical oscillation (r = −0.77; r = −0.86). Contact time showed a strong positive correlation with vertical oscillation (r = 0.86) and strong negative correlation with maximal relative force (r = −0.81). In women, a strong positive relationship between V̇o2max and RE (r = 0.72) was found. No other significant relationships were observed. Conclusions: As expected, men ran at faster self-selected 5k speeds than women. Contrary to prior research, no relationships were found between the explored biomechanical variables and running economy. However, in men these variables showed important relationships with other running performance parameters. In collegiate cross-country runners, shorter ground contact times and lower vertical oscillation may differentiate men with faster running speeds and higher V̇o2max, and the ability to apply higher forces may impact ground contact time. Practical Applications: Training interventions to reduce ground contact times, increase maximal relative force during contact, and reduce vertical oscillation may assist collegiate cross-country men in achieving better running performance parameters.

(V307) Relationships Between Body Composition and Bone Mineral Density in Collegiate Athletes and Students via Dexa Scan

M. Lane,1 Y. Vitel,1 D. Stevens,1 J. Wagganer,2 J. Mayhew,3 and J. Barnes2

1Eastern Kentucky University;2Southeast Missouri State University; and3Truman State University

Introduction: Identification of athletic potential is incredibly important to success of athletic programs. Being able to predict which athletes are more likely to make positive changes in lean mass and fat mass is of great importance for coaches. Purpose: to investigate the relationship between body composition, bone mineral density as well as changes in college students. Methods: Eight hundred fifteen collegiate students participating in a variety of sports and activities were scanned initially and 346 tracked in a longitudinal analysis (ht. 1.75 ± 0.11 m, wt. 81.1 ± 36.7 kg, age 20.9 ± 2.5 years, body fat % 24.6 ± 9.2%). After giving consent and completing health history questionnaires each participant completed a Dual-Energy X-Ray Absorptiometry (DXA) scan (Lunar Prodigy, GE). Total fat mass (TFM), total lean mass (TLM), bone mineral content (BMC) and bone mineral density (BMD) values were analyzed for change relative to days between scans and the results were multiplied by 28 for standardization to monthly projections. Correlation matrixes were made to analyze the relationships between age, height, weight, TLM, TFM, BF%, BMD, BMC, and changes in TLM (cTLM), TFM (cTFM), BF% (cBF%), BMC (cBMC), and BMD (cBMD). Results: BMD values were 1.373 ± 0.163 g·cm−2, BMC values were 3.071 ± 0.680 kg, cTLM of 0.007 ± 0.063 kg, cTFM −0.0004 ± 0.0383, cBF% −0.0005 ± 0.0212, cBMD −0.0002 ± 0.0036 g·cm−2, and cBMC −0.677 ± 9.220 g. Several significant correlations were observed (*denotes p < 0.05; ** denotes p < 0.01). The strongest correlations to TLM were observed with BMC (r = 0.877**), height r = 0.799**, BMD r = 0.787**, weight r = 484**, BF% r = −0.298**, and TFM r = 0.166**, age r = 0.143** with no significant relationships with any of the change variables except for cTLM r = −0.195**. Correlations to TFM were observed between weight r = 3,421**, BMC r = 0.140***, BMD r = 0.109**, and cTFM r = −0.127*. Relationships to BF% were as follows TFM r = 0.859**, height r = −0.301**, TLM r = 0.298**, BMC r = −0.283**, BMD r = −0.219**, weight r = −0.173**, cTLM (r = −0.512**) and cTFM (r = 0.792**). BMD relationships were to BMC r = 0.888*, TLM r = 0.787*, height r = 0.579**, weight r = 0.412**, BF% r = −0.219, TFM r = 0.140*. BMC were all previously reported except for height r = 0.774**, weight r = 0.432**, and age r = 0.080**. cTLM was related to age (r = 0.132*), weight (r = −0.137*), and previously reported TLM. cTFM was related to weight (r = −0.135*) and TFM previously reported. No other significant relationships were identified between any of the variables. Conclusions: Several relationships were observed between body comp and anthropometrics. For TLM the most significant relationships, aside from to height, were observed between BMC and BMD. Individuals with denser bones tended to carry greater amounts of lean mass. Individuals with higher TLM tended to experience a decrease in TLM between scans as well as being leaner in terms of BF% but had higher TFM. TFM was higher in athletes that were heavier with higher BF%. Other contributors to TFM were BMC and BMD and athletes with higher TFM tended to experience a decrease in TFM over time. Finally, BF% was inversely related to height, TLM, BMC, and BMD. Whereas BF% had a positive relationship to weight and TFM which was the greatest contributor. Practical Applications: Greater BMD is related to greater amounts of TLM and TFM. Athletes that exhibited greater initial TLM tended to decrease with time whereas the opposite relationship was observed between TFM and BF%. Further examination of trends in body composition over time is required.

(V308) Changes in Body Composition for Collegiate Athletes Over Time Utilizing Air Displacement Plethysmography

Y. Vitel,1 D. Stevens,1 M. Lane,1 J. Wagganer,2 J. Barnes,2 and J. Mayhew3

1Eastern Kentucky University;2Southeast Missouri State University; and3Truman State University

Introduction: Body composition affects sport performance. However, the rate of body composition change over time in athletes has not been thoroughly analyzed. Therefore, the gap of literature exists that evidence may lead coaches to unrealistic expectations of body composition changes for athletes Investigating changes in athlete body composition can better inform coaches, trainers, and other personnel to more feasible changes over time. Purpose: To report ranges of body composition changes in collegiate athletes. Methods: Three hundred tewnty-six Division I athletes (ht. = 1.74 ± 0.12 m, wt. = 78.9 ± 22.5 kg, age 19.5 ± 1.2 years, 183 females, 143 males) participated in this study after filling out an informed consent and health history questionnaire. Air displacement plethysmography scans (Bod Pod, Cosmed) were conducted multiple times throughout each athlete's career utilizing standard testing procedures after proper calibration protocols. Athletes were typically scanned twice per year. Athletes that were scanned at least twice were utilized in the data set. Data was then exported and analyzed for daily change in body composition utilizing SPSS, using initial body composition values divided by days between scans. These results were then multiplied by 28 to represent the relative monthly change for each athlete. Results: Monthly changes were reported as follows, fat percentage was 0.095 ± 1.55% with a 95% CIof 3.197 to −3.007%. Fat mass change was 0.164 ± 1.308 kg with a 95% CI of 2.691 to −2.542 kg. Fat free mass change was −0.138 ± 1.408 kg with a 95% CI of 2.679 to −2.956 kg. Total body mass change was −0.122 ± 2.36 kg with a 95%CI of 4.598 to −4.841 kg. Conclusions: Even though overall changes in body composition for athletes are small, the standard deviations and ranges of those changes are quite large. This data set does give some ideas of potential changes, but caution should be exhibited for only looking at the outliers. Further research should be performed examining typical change patterns over collegiate athletic careers. Practical Applications: Knowing feasible changes in body composition will help guide coaches, trainers and other personnel in improving performance of athletes without compromising their health.

(V309) Comparison of Multiple Methods to Evaluate Body Composition in Collegiate Female Ultimate Frisbee Athletes

J. Casey,1 S. Reddy,1 and L. Colston2

1University of North Georgia; and2Georgia State University

Body fat percentage (BF%) is an important anthropometric measurement that has been shown to influence both performance and health of athletes. As a result, it is of value for practitioners to monitor body composition in athletes and assess trends over time. Multiple techniques of body composition assessment exist, however, practitioners need an assessment method to be valid, accessible, and easy to use. Various field techniques meet the criteria of accessibility and ease of use, however, limited research exists examining these tools in female athletic populations. Further, there are no descriptive body composition data on ultimate frisbee athletes. Purpose: This study was conducted to determine the agreement between 6 body composition assessment methods: 3-site skinfold (3SF); body adiposity index (BAI), and 4 separate BMI-based BF% equations compared to air-displacement plethysmography (AP). Methods: Nine female collegiate ultimate frisbee athletes (Mean ± SD; Age: 21 ± 1 year, Height: 165.7 ± 4.5 cm, body mass = 64.1 ± 7.9 kg, and BMI = 23.3 ± 2.3 kg·m−2) visited the laboratory once to undergo a test battery consisting of height, weight, hip circumference, 3SF, and AP. Additionally, BF% was predicted via body adiposity index (BAI) and 4 previously developed BMI-based equations: Jackson et al. (2002) (JABMI); Deurenberg et al. (1991) (DEBMI); Womersley & Durnin (1977) (WDBMI); and Gallagher et al. (2000) (GABMI). A repeated-measures ANOVA was performed to determine mean differences between BF% assessed via AP compared to the other methods. Pearson product-moment correlation coefficients, constant error, and the 95% limits of agreement via the Bland-Altman method were also calculated. Results: BF%, r-values, and limits of agreement (constant error ±1.96 SD) are depicted in Table 1. There were no significant differences between AP and any other method of body composition assessment (p > 0.05). A strong, positive relationship was identified between body composition estimated by AP and 3SF (r = 0.83, p = 0.0006). All other correlations only had a moderate relationship with AP. Conclusions: This investigation revealed that there were no significant mean differences in the estimation of BF% between the various methods and AP. However, it should be clearly noted that each BMI-Based equation and BAI had large limits of agreement relative to AP. Further, each of these methods only had moderate correlations with AP. In comparison, 3SF provide a strong, positive relationship with AP and much smaller limits of agreement. Practical Applications: Despite the lack of significant group mean differences between AP and any of the comparison methods of body composition assessment, practitioners should be cognizant of the large limits of agreement and moderate correlation coefficients when comparing each BMI-Based equation and BAI to AP. As a result, it is recommended to refrain from the utilization of these field methods to estimate BF% in this population.

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Table 1:
Each body composition method compared to AP. (n = 9) (mean ± SD).

(V310) Can Training Class Completion Enhance Biddle Physical Ability Test Performance in Structural Firefighter Candidates? A Pilot Study

R. Lockie,1 T. Ruvalcaba,1 J. Meloni,2 M. McGuire,1 E. Hernandez,1 R. Orr,3 J. Dawes,4 and J. Dulla3

1California State University, Fullerton;2Santa Ana College;3Bond University; and4Oklahoma State University

The Biddle Physical Ability Test (BPAT) is an entry level test used to identify candidates with the abilities needed to become a structural firefighter. This test simulates firefighting tasks which must be completed in succession in ≤9:34 minutes:s. Based on the demands of the BPAT, some community colleges will offer semester-long training classes for candidates. However, it is not mandatory for candidates to complete any training or practice prior to attempting the BPAT. Purpose: To determine whether completing a physical ability training class improves BPAT performance in structural firefighter candidates. Methods: This pilot study involved retrospective analysis of 32 structural firefighter candidates (30 males, 2 females) who attempted the BPAT in 1 session. All candidates received instruction on how to complete the BPAT, which was performed in the following gear: turnout coat; helmet; gloves; breathing apparatus; athletic clothes; and tennis shoes. Individual BPAT events were timed and collated to provide total time. The events were: dry and charged hose drag; halyard raise, roof walk, and attic crawl; roof ventilation and victim removal; ladder removal and carry; stair climb with hose bundle; crawling search and tower exit; stair climb with air bottles; hose hoist; and return to ground floor with air bottles. Independent samples t-tests (p < 0.05) and effect sizes calculated BPAT differences for individual events and the total time between candidates who completed a training class and those that did not. Candidates who failed (via a slow time or disqualification) were also detailed. Results: Twenty-nine candidates passed the BPAT, of which 6 completed a training class. The 3 candidates (2 males, 1 female) who failed the BPAT did not complete a training class. There were no significant differences in BPAT times between those that completed a training class and those that did not (p = 0.10–0.83). There were moderate effects for the between-group differences in roof ventilation and victim removal (∼57.83 vs. ∼62.48 seconds; d = 0.89), ladder removal and carry (∼33.50 vs. ∼41.35 seconds; d = 0.95), and the hose hoist (∼47.17 vs. ∼54.48 seconds; d = 0.74). Candidates who completed the training class were faster in these events. Conclusions: The results suggest, that while not always the case, those who attend a training class are less likely to fail the BPAT. Although there were no significant between-group differences (possibly influenced by the sample size), it was notable that BPAT tasks that are more physically demanding (victim removal, ladder removal and carry, hose hoist) were finished faster by candidates who had completed a training class. The effect size differences may provide some initial evidence of better skill acquisition for those candidates. Further, training staff have anecdotally noted candidates often struggle with the ladder removal and carry. Candidates who completed the training class were 19% faster in this event, and the female candidate who did not pass the BPAT was disqualified at this event. Practical Applications: This pilot study indicated potential benefits of physical ability training classes for structural firefighter candidates, and a need for more research in this area. Certain candidates may be able to complete the BPAT without specific training. However, for candidates who may find the physicality required for the BPAT difficult, they should consider enhancing their task-specific fitness and skills in a training class.

(V311) Performance in the Role Fitness Test (Entry) and Physical Employment Standards in Recruit Aged Men and Women

P. Peterson,1 K. Krajewski,1 I. Allen,1 N. Sekel,1 M. Lovalekar,2 A. Sterczala,1 N. Ahamed,1 S. Flanagan,1 C. Connaboy,1 and B. Nindl2

1University of Pittsburgh Neuromuscular Research Laboratory/Warrior Human Performance Research Center; and2University of Pittsburgh Neuromuscular Research Laboratory

The UK Ministry of Defence (MoD) gauges occupational readiness through a series of physical tests, specifically, the Role Fitness Test (Entry) (RFT[E]) prior to basic training and the Physical Employment Standards (PES) upon completion. With the ban on women in ground close combat roles (GCC) lifted, further investigation is required to understand sex specific differences in performance of RFT(E) and PES. Purpose: The primary aim of this study is to elucidate the between-sex differences in performance outcomes on the PES. The secondary aim is to assess the association of the 2 km Run portion of the RFT(E) on PES outcomes. Methods: Seventy-five recreationally active recruit-aged men (n = 43) and women (n = 32) participated. Participants completed a 2 km treadmill run to the best of their abilities. PES testing was administered on a separate day wearing 11 kg of body armor/helmet. PES consisted of: (a) 20- m simulated casualty drag (CD) of a 111 kg dummy, (b) max single lift (MSL) in which participants lifted weighted sandbags onto a 1.49 m box, (c) 240 m water can carry (WCC) with a 22 kg water cans in each hand, (d) Repeated lift & carry (RLC) with 20 kg sandbag for 1200 m, and (e) 2 km Ruck March (RM) with 25 kg load. Between-sex differences in PES performance were analyzed using a Chi-squared test or Fisher's exact test where assumptions were not met. Multiple logistic regression was performed for the association of 2 km Run on PES performance based on MoD standards with sex added to the model (α = 0.05). Results: Men passed the PES tests at significantly greater proportions than women (p < 0.05). MSL had the greatest proportion of females (84%) pass relative to males (100%) (p = 0.012), whilst only 1 female (3.1%) passed the RM compared to 21 males (49%) (p < 0.001) and CD saw 6.5% of females (n = 2) and 93% of males (n = 40) pass. WCC and RLC had a similar proportion of females pass (both n = 4, 12%) with disproportionate rates of males passing (n = 37, 88%; p < 0.001 and n = 29, 67%; p < 0.001). Results from the multiple logistic regression are displayed in Table 1. Conclusions: Recruit aged men perform significantly better on PES than women. Investigations should aim to discern what between-sex differences in physical fitness can be addressed in basic training to better prepare women for GCC roles. The odds of positive outcomes in the CD, WCC, RLC, and RM is significantly lower in women when compared to men. However, after adjusting for sex, faster 2 km run times are associated with positive outcomes on the WCC, RLC, and RM. These results suggest that aerobic fitness contributes to WCC, RLC, and RM but not CD and MSL. Practical Applications: The results indicate the need for an emphasis on performance enhancement of women in basic training to develop the requisite strength, power and capacity to perform occupational tasks relevant to GCC. Further, increased aerobic fitness and upper body strength may benefit women in reaching military occupational standards.

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Table 1:
Multiple logistic regression for the association of 2 km Run (min) and sex on PES outcomes.

(V312) Force/Load-Velocity Profiling Methods and Army Combat Fitness Test Performance in Rotc Cadets

D. Boffey, J. DiPrima, A. Straus, C. McAbee, B. Monis, H. Bauta, and D. Fukuda

University of Central Florida

Force-velocity profiles (FVP) and load velocity profiles (LVP) are methods of profiling strength and speed capabilities for different movements. The Army Combat Fitness Test (ACFT) is the US Army's new physical fitness test of record, and includes events testing strength and speed. There have been no investigations into the relevancy of FVP and LVP with regard to ACFT performance. Purpose: The purpose of this study was to determine the relationship between FVP and LVP parameters on individual and total ACFT scores. Methods: Army ROTC cadets performed a FVP of the barbell squat jump (n = 61) and an LVP of the hex bar deadlift (n = 64). Profiles were incrementally evaluated with 3 loads (squat jump) or 5 loads (deadlift), and the ACFT was conducted on a separate day. Simple correlations were run between FVP and LVP variables and ACFT scores. Statistical significance was set at α ≤ 0.05. Results: LVP X-intercept (maximum load; kg) had significant correlations with all events (r = 0.36–0.69) except for the 2-Mile Run (p > 0.05), and had a significant correlation with total ACFT score (r = 0.45, p < 0.001). LVP Y-intercept (maximum velocity; m·s−1) had a significant correlation only with the 2-Mile Run (r = 0.43, p < 0.01) and was not correlated with total ACFT score. LVP slope did not have significant correlations with leg tuck or 2-Mile Run (p > 0 .05) but had a significant correlation with total ACFT score (r = 0.27, p = 0.05). FVP F0 (maximum force; N) had a significant correlation with all 6 individual events (r = 0.38–0.51) and total ACFT score (r = 0.45, p < 0.001). FVP slope and FVP Vo (maximum velocity; m·s−1) were not correlated with any of the 6 events or total ACFT score. FVP Pmax (maximal power; W) had a significant correlation with all 6 ACFT events (r = 0.29–0.42) and total ACFT score (r = 0.41, p < 0.01). Percentage of Optimal Slope at both 90° takeoff angle (vertical jump) and 30° takeoff angle (sprint) had no correlation with individual or total ACFT score. Conclusions: Maximal force production, rather than velocity, during the squat jump and hex bar deadlift may be related to total ACFT performance in ROTC cadets. Maximal power production was also related to ACFT performance, and this may have been driven by higher force production rather than velocity. The optimal slope method of FVP analysis may have limited predictive use for ACFT performance and training. Practical Applications: Maximal force production during both the barbell squat jump and hex bar deadlift may be good indicators of ACFT performance. To maximize performance on the ACFT, maximal absolute strength on the hex bar deadlift and maximal force production during barbell squat jumps should be emphasized during the physical training of ROTC cadets.

(V313) Effects of Firefighter Shift Schedules on Body Composition and Fitness

L. Garrett,1 C. Ayars,2 and A. Harveson1

1California Baptist University; and2A.T. Still University

Previous studies have identified a decline in Americans' health for decades due to increases in the prevalence of obesity, diabetes, cardiovascular disease and other noncommunicable diseases. Firefighters and first responders are the primary line of defense in maintaining and preserving life when medical consequences arise from these diseases. Rises in call volume have added stress and workload to an already unique shift schedule. Common schedules are a minimum of 24-hours and firefighters are on call for the duration of the shift. With such a burden placed on firefighters, it is critical to examine strategies for maintaining their overall wellness. Purpose: The purpose of this study was to examine differences in health and performance when comparing shift schedules of active-duty firefighters. Methods: A causal comparative descriptive research design using secondary data was used to explore differences in subjects' body composition, muscular strength, endurance, and flexibility, and cardiorespiratory endurance. Body composition was assessed using waist circumference (WC), body mass index (BMI), and body fat percentage (BF%) measurements. The estimated 1 repetition maximum (1RM) leg press, maximum cadence push-ups, and trunk flexion were used to examine muscular strength, endurance, and flexibility respectively. Cardiorespiratory endurance was evaluated using participants' V̇o2max. A Mann-Whitney U test was conducted to compare 2 different shift schedules of 887 firefighters. Group 1 worked a 48/96 (2 days on, 4 days off) and Group 2 worked a 4's and 6's (on, off, on off, on, off 4 days/on, off, on, off, on, off 6 days). Results: Although the 48/96 group outperformed the 4's and 6's group in all but 1 category, cadence push-ups, there were no statistically significant results (see Table 1). Additionally, our findings revealed that firefighter body composition is within a healthy range. Conclusions: Firefighters are a unique and specialized group tirelessly serving the public. Because of the physical and time demands, it is critical to preserve their health and wellness to ensure they are able to care for the community and perform while on duty. Practical Applications: Findings from this study suggest that shift schedule alone does not affect body composition or fitness levels among career firefighters.

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Table 1

(V314) Evaluation of a Remote Exercise Training Program Designed for Rotc Army Cadets Preparing for the Army Combat Fitness Test

J. Mintz,1 B. Roberts,2 E. Plaisance,1 K. Rushing,1 G. Jenkins,1 G. Fisher,1 and C. Morris1

1University of Alabama at Birmingham;and2United States Army Research Institute of Environmental Medicine

Before the recent implementation of the Army Combat Fitness Test (ACFT), the Army used the Army Physical Fitness Test (APFT) as a means to evaluate field readiness. The APFT consisted of 2 minutes of push-ups, 2 minutes of sit-ups, and a 2-mile run. The ACFT was designed to more accurately address physical abilities required for incoming military personnel. Purpose: The purpose of this study was to develop and test the effects of a remote exercise training program designed to improve performance on the ACFT by Reserve Officer Training Corps (ROTC) cadets. Methods: Thirty ROTC cadets (Mean Weight = 70.37 ± 13.91) (Mean BMI = 23.83 ± 3.57) performed an 8-week training protocol following baseline ACFT. The protocol focused on movements that were used in the ACFT. Participants were assigned in groups of 5–8 cadets into 1 of 3 stations: resistance training, conditioning, and endurance. Resistance training consisted of: Deadlift, dumbbell row, leg tuck, push-up (3–4 sets of 5–20 repetitions, per exercise), Conditioning: 25-meter sprint, 25-meter sled drag, 40 lb kettlebell carry, 10 lb underhanded power throw. Each event lasted 1 minute with alternating ratios of exercise:rest in seconds (e.g., 30:30, 40:20, 20:40). Endurance: 2-mile run (capped at 20 minutes). Training was conducted 3 days per week for 8 weeks. Each session was either low, moderate, or high effort to ensure that cadets had the proper recovery between sessions. Each session was cadet-led and supervised by ROTC staff. Cadet leaders met with an investigator on a weekly basis with the physical fitness leader of each cohort to provide a summary of training and to answer any questions that arose. Cadets were also provided an exercise library for assistance. This library consisted of examples of each movement. Results: Table 1 presents the scoring of each criterion tested. The 3-repetition maximum deadlift and 2-mile run score improved significantly from baseline (p < 0.05). The total score of the test as well as the total percentage of the test improved significantly (p < 0.05). There were no other significant changes. Conclusions: Following 8 weeks of a remote training program, cadets significantly improved their overall ACFT compared to baseline ACFT. These findings provide evidence that a remotely delivered training program designed for ROTC cadets can be effective for enhancing scores on the ACFT. Practical Applications: If a specified training program can be used to enhance the performance of a cadet on the ACFT, then it could have positive implications on how tactical athletes perform in the field of duty. our initial findings suggest that the remote training program was effective at improving performance on the ACFT, but that fine-tuning will be required to maximize performance enhancements to improve ACFT and physical ability for incoming military personnel.

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Table:
1ACFT scores pre-intervention and post-intervention scores.

(V315) Pacing Strategies in a 9-Minute High Intensity Functional Training Competition Workout including Deadlifts, Handstand Pushups, and Handstand Walks

B. Kliszczewicz,1 G. Mangine,1 E. Zeitz,2 J. Dexheimer,3 and J. Tankersley1

1Kennesaw State University;2Azusa Pacific University; and3Therabody

A 5-week competition that features unknown high-intensity functional training (HIFT) workouts is held annually to find the “Fittest on Earth.” The workouts are prescribed using various modalities, exercise orders, weights, and repetition schemes designed to test the competitor's overall fitness. However, due to their unknown nature, it is difficult for athletes to develop effective training and pacing strategies. Purpose: To observe and determine which pacing strategies best predicted performance in a 9-minute workout consisting of deadlifts, handstand pushups and walks. Methods: Recorded efforts were randomly selected and analyzed from the top 10,000 male competitors of the 2020 competition (n = 31; 29 ± 4.6 years; 176.9 ± 6.8 cm; 85.8 ± 7.9 kg). The selected workout consisted of 2, 3-round parts that needed to be completed within 9 minutes. The first part involved a 21-15-9 repetition scheme that alternated deadlifts (DL) at 225 lbs. and handstand pushups (HSPU), and the second part used the same repetition scheme for DL at 315 lbs. and alternated with a 50-ft handstand walk (HSW). The workout was scored as a rate (repetitions·min−1), while rates for each exercise and round were verified via video analysis. Additionally, breaks, transitions, and failed repetitions were quantified. Results: Significant (p < 0.05) Spearman's rho correlation coefficients were observed between workout performance and several pacing variables. Subsequently, separate stepwise regression analyses were performed to find the best predictors of workout performance from significantly correlated time-to-completion, rate, failed repetitions, breaks, and transition time variables. These resulted in 5 final models that initially included round 4 completion rate (R2 = 0.92, SEE = 0.69 repetitions·min−1) and where variance-explained could be progressively improved with the addition of average round rate (R2 = 0.95; SEE = 0.56 repetitions·min−1), average round transition time (R2 = 0.97; SEE = 0.43 repetitions·min−1), variability HSPU/HSW break time (R2 = 0.98; SEE = 0.34 repetitions·min−1), and average break time in round 6 (R2 = 0.99; SEE = 0.29 repetitions·min−1). Conclusions: The completion rate of round 4 (i.e., when DL load increased to 315 lbs. for 21 repetitions and HSPU's switched to a 50-ft. HSW) was the best predictor of workout performance, followed by average round and transition rates. Performance was further improved in those athletes who varied less in breaks taken during HSW, and overall break time in the final round. Practical Applications: The variables of overall round rate and average round transitions fall under conventional wisdom in performance and pacing, in that faster rounds and shorter rest will yield greater performance. The correlative value of round 4 rate suggests that pacing techniques prior to particularly taxing movements (i.e., Round 4) was vital to the overall workout performance. Furthermore, this suggestion goes beyond the strength required to rapidly move 315 lbs. DL, but the comfort and competence to transition to skilled movements (HSPU/HSW). Therefore, it is recommended that strategic pacing should be performed in easier or lighter rounds to avoid unnecessary fatigue in later rounds, while training strategies should focus on skilled movement technique.

(V316) Associations Between Age and Jump Performance Among Special Weapons and Tactics Team Operators

Q. Johnson,1 M. Lopes Dos Santos,1 C. Stahl,1 M. Uftring,1 M. Abel,2 R. Orr,3 R. Lockie,4 N. McSpadden,5 C. Manuel,5 and J. Dawes1

1Oklahoma State University;2University of Kentucky;3Bond University;4California State University, Fullerton; and5SPD

Lower-body power is essential for Special Weapons and Tactics (SWAT) unit operators when performing many occupational tasks, such as breaching, casualty extraction and seeking cover. In interesting aspect of SWAT teams are sometimes very diverse age demographics. In many instances, there are a very wide range of operators from various age groups who must be able to adequately perform their occupational duties in order to successfully complete their mission. Generally, some if not most of these occupational duties are influenced by an individual's ability to produce muscular strength and power. However, the relationships between age and lower-body power within this population have not been fully explored, especially in tests that require multiple efforts. Purpose: The aim of this study was to examine the relationship between age and vertical jump performance among multi-jurisdictional SWAT team members. Methods: Seventeen (n = 17, age 35.5 ± 5.9 years; HT 181.5 ± 8.4 cm; BM: 96.2 ± 13.1 kg) male police officers belonging to a multi-jurisdictional SWAT unit participated in this study. Multi-jurisdictional SWAT units are generally a collective group of SWAT operators from several smaller departments who combine forces and respond to the needs of all the law enforcement agencies they serve. After anthropometric data and self-reported age were recorded, all officers performed 4 consecutive vertical jumps on a contact mat. Data collected from this assessment included average vertical jump height for the 4 jumps (VJ height) and the average ground contact time between jumps. A Pearson correlation was used to determine if significant relationships (p < 0.05) existed between age, VJ height, and ground contact time. Results: No significant relationship (r = 0.245, r2 = 0.05, p = 0.97) was found between age and VJ height among the officers. However, a strong positive correlation between age and ground contact time (r = 0.712, r2 = 0.50, p = 0.001) was found. Conclusion: The results of this study reveal that while VJ height did not decrease with age. However, the results indicated that increased age was associated with a longer average ground contact time between the consecutive jumps. This suggested that older officers may have spent more time in contact with the ground to maintain the same jump height as their younger counterparts. This may be due to a greater dampening of the stretch-shortening cycle at ground contact among older officers. Practical Applications: Older SWAT officers may utilize different jump strategies and rely more on concentric force production to achieve greater vertical jump heights in contrast to the utilization of stored elastic energy when ground contact time is reduced. Additionally, this may influence job performance by increasing the time to completion of power-based occupational duties. Therefore, it may be in the best interest of tactical strength and conditioning facilitators to identify and apply age-specific strength and conditioning approaches if possible.

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Figure 1.:
Relationship between age (years) and avg. VJ height (cm).

(V317) Pacing Strategies in a 20-Minute High Intensity Functional Training Competition Workout Including Box Jumps, Clean and Jerks, and Single Leg Squats

E. Zeitz,1 G. Mangine,2 J. Dexheimer,3 J. Tankersley,2 and B. Kliszczewicz2

1Azusa Pacific University;2Kennesaw State University; and3Therabody

An annual online fitness competition to find the “Fittest on Earth” includes 5 weekly High Intensity Functional Training (HIFT) workouts that challenge proficiency in various combinations of weightlifting, different cardiovascular exercises, and assorted gymnastic tasks. Because of the variable nature of the prescribed modalities of exercise, set and repetition scheme, as well as the allotted duration of each challenge, it is possible that pacing strategies (e.g., breaks within sets, transition times), may influence time-to completion (TTC) and those strategies might be applied to other workouts of similar design. To date, little research is available to support this theory. Purpose: To determine the effect of pacing strategies on performance in a 20-minute HIFT competition workout involving box jumps, a clean and jerk ladder, and single leg squats. Methods: Recorded efforts of the workout (20.4) were selected and analyzed for a random sample of the top 10,000 male (n = 74; 30.6 ± 5.4 years; 176 ± 6 cm; 84.5 ± 7.6 kg) and female (n = 77; 31.0 ± 6.0 years; 163 ± 5 cm; 60.8 ± 5.1 kg) competitors from the 2020 HIFT competition. The workout allotted 20 minutes to complete a 6-round chipper: Rounds (R)1: 30 box jumps (BJ) (24/20in) and 15 Power Clean (PC) (95/65); R2: 30 BJ/15 CJ (135/85lb); R3: 30 BJ/10 CJ (185/115lb); R4: 30 single leg squats (SLS)/10 CJ (225/145lb); R5: 30 SLS/5 CJ (275/175 lb); 30 SLS/5 CJ (315/205lb). Pacing was quantified by time to complete the entire set of a movement within each round and transition time between movements, and performance was scored by rate of repetitions per minute (repetitions·min−1). Results: Significant (p < 0.05) Spearman's Rho correlation coefficients were observed between 20.4 performance and several pacing variables. Stepwise regression was then used to initially produce 8 predictive models for 20.4 from significantly correlated pacing variables in a validation group (n = 74). These were cross-validated in another group (n = 77), where only 1 model (average CJ rate [rounds 4–6] + average exercise rate [rounds 1–3] + slowest exercise rate [rounds 4–6]–standard deviation in transitions [rounds 4–6]) was found to produce statistically similar estimates of 20.4 performance. The groups were then combined (n = 151) to create the final prediction model (R2 = 0.81, SEE = 0.52 repetitions·min−1). Conclusions: A consistently faster rate of effort over the entire workout produced the better 20.4 scores. The best performances were observed in those athletes who also better maintained their pace specifically in the weightlifting component over the final 3 rounds. Though sex was related, it did not significantly influence 20.4 performance. Practical Applications: Although HIFT competition workouts will vary in their specific design, when a Chipper-style workout combines a progressive increase in weightlifting load with a consistent volume of basic calisthenic movements over several rounds, male and female athletes should place the most attention on averaging a faster weightlifting pace over the final 3 rounds. Their secondary goal should be to focus on maintaining a fast but consistent rate of effort for all other workout components.

(V318) the Influence of Joint Torque on Injury Rates in Soccer Players—A Meta-Analytic Review

H. Capozzella,1 B. Peters,2 J. Heinsohn,1 J. Rochelle,1 J. Winchester,1 and F. Wyatt3

1University of the Incarnate Word;2United Regional Hospital; and3Midwestern State University

With more than 265 million participants, soccer is the most popular sport world-wide. Injury prevention and rehabilitation programs are formed based upon current evidence for injury rates, risk factors, and factors which contribute to re-injury. Purpose: To analyze the relationship between performance variables and injury rates in collegiate soccer players. Methods: A meta-analysis review was conducted to investigate differences in joint torque and range of motion in injured versus uninjured soccer players. Data regarding injury status and joint torque of various muscle groups at different contraction velocities were collected from different studies for the investigation. The data was then analyzed to determine whether there were differences between persons who were injured and not injured in the aforementioned variables. Computerized searches were performed via PubMed, SPORTDiscus, and Web of Science to generate citation lists from the period of August 2018 to December 2019 and were limited to studies involving soccer, where both joint torque and injury status were reported. The review was performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols (PRISMA-P). This developed a retrieval of papers published from 2008 to 2019. Differences between groups were for several joint torque variables (knee flexion at all velocities, assessed with paired samples t-test, and effect size (ES) was determined through Cohen d. Results: No significant differences were determined between injured and uninjured soccer players for Knee Flexion (p = 0.1, ES = 0.12); Hip Flexion (p = 0.42, ES = 0.13), Hip Abduction (p = 0.18, ES = 1.29), Torque at 240 deg·s−1 (p = 0.5, ES = 0.21), Eccentric (p = 0.58, ES = 0.51) Concentric (p = 0.64, ES = 0.01). Conclusions: Even though there were positive effects in some variables, no statistical significance was observed. There are a very small number of studies in this area, making conclusive statements difficult. Additional investigations in this area need to be performed, particularly given the popularity of soccer as a sport. In addition, despite the rates of injury in female soccer players being reported as up to twice as high, a lack of data exists exploring injury predictors in females as compared to males. Practical Applications: Despite a lack of significant findings in this meta-analysis, possibly due to only a few studies directly investigating the link between joint torque and injury in soccer players, previous studies have suggested that weakness can lead to increased risk for some of the more common injuries in soccer such as inversion sprain, hamstrings strain injury, and Achilles tendinopathy. As such, it is prudent at this time for practitioners to consider strengthening as a method of injury prevention, along with performance enhancement. Additional research is needed to explore a potential gender differences which may exist.

(1) Determining the Optimal Load for Maximal Power Production in the Mid-Thigh Power Clean

A. Squillante, B. McCormick, L. Martin, E. Schroeder, and S. Sigward

University of Southern California

Evidence suggests the importance of prescribing optimal load to maximize peak power output in explosive strength training for sport. However, to date conflicting results exist on the effect of loading on peak power output in the mid-thigh power clean (MTPC). Purpose: To determine the optimal load to maximize peak power output in the MTPC based on lower body strength (barbell back squat 1RM). Methods: Twenty-six male and female weightlifters (average: age 25.5 ± 3.8, height 168.2 ± 4.6 cm, body mass 76.7 ± 14.6 kg; men: age 26.3 ± 3.4, height 171.8 ± 4.1 cm, body mass 84.7 ± 16.9 kg; women: age 24.5 ± 4.2, height 164.2 ± 5.1 cm, body mass 68.7 ± 12.4 kg) were tested in the MTPC for incremental loads of 20, 30, 40, and 50% of the barbell back squat 1RM. During testing, all participants performed 4 sets of 3 repetitions standing on a force platform sampling at 1,000 Hz (AccuPower, Advanced Mechanical Technology, Inc., Watertown, MA). Peak vertical bar velocity was measured using a wearable accelerometer placed on the barbell (Push 2.0). Results: Findings from all participants reveal that peak power output in the MTPC (average: 3,625 ± 1,326 W; men: 4,219 ± 1,333 W; women: 3,031 ± 1,059 W) occurs for loads equal to 20–30% of the barbell back squat 1RM with no significant difference between men and women. Peak power output occurs when neither force (average: 3,522 ± 1,285 N; men: 3,893 ± 1,194 N; women: 3,294 ± 1,178 N) nor peak vertical bar velocity (average: 2.19 m·s−1; men: 2.29 ± 0.34 m·s−1; women: 2.09 ± 0.38 m·s−1) is at its peak. A 1-way repeated-measures analysis of variance revealed a significant difference between peak power output at 20 and 30% of the barbell back squat 1RM compared to loads at 50%, F(3,75) = 5.74, p < 0.05. Conclusions: Peak power output in the MTPC occurs for loads equivalent to 20–30% of the barbell squat 1RM with no significant difference between men and women. These findings suggest no additional benefit of training for power at greater intensities.

(2) Unilateral Muscular Fatigue From Handgrip Holds on Ipsilateral and Contralateral Performance Fatigability

C. Voskuil, T. Dinyer, P. Succi, M. Abel, M. Campbell, and H. Bergstrom

University of Kentucky

Performance fatigability (%Δ in maximal voluntary isometric contraction [MVIC]) provides an objective measure of the exercise-induced decline in muscle force. Isometric, unilateral fatigue has been shown to result in no change, decreased, or increased MVIC and/or isometric work in the non-exercised, contralateral limb. Purpose: This study examined the effects of unilateral, isometric handgrip holds to failure for the dominant (Dm) and non-dominant (NDm) limb on ipsilateral ([IPS] exercised side) and contralateral ([CT] non-exercised side) performance fatigability. Methods: Eleven subjects (mean ± SD, Age: 22.5 years ± 2.8) performed 2, 6 seconds MVICs for the Dm and NDm limb during visit 1, followed by a familiarization of the fatigue test. Visits 2 and 3 included an isometric, handgrip hold to failure (HTF) fatigue test at 50% MVIC for either the Dm or NDm limb. Prior to, and immediately after the HTF, a MVIC was performed on the IPS and CT sides. The fatigue test (Dm or NDm) was randomized between visits and the side tested first (IPS and CT) was randomized for pre-and post-tests, within each visit. Reliability was examined separately for the Dm and NDm pre-fatigue MVIC using intra-class correlation coefficients (ICC2,2), standard errors of the measurement (SEM), and coefficients of variation (CoV). A 2(limb [Dm, NDm]) × 3(visit [1–3]) repeated measures (RM) ANOVA was used to examine the pre-fatigue MVICs. Performance fatigability for fatigue tests was examined with a 2(fatigue [Dm, NDm]) × 2(side [IPS, CT]) RM ANOVA. The MVIC at pre-and post-fatigue were compared for the IPS and CT sides for both the Dm and NDm fatigue tests using a priori planned comparisons (p < 0.05). Results: There was no systematic error for the pre-fatigue MVIC on the Dm (p = 0.77; mean ± SD = 40.9 ± 10.8 kg) or NDm (p = 0.82; mean ± SD = 39.6 ± 12.4 kg) limb and the MVIC demonstrated “excellent” reliability (ICC, SEM, and CoV; Dm = 0.948, 2.7 kg, and 6.5%; NDm = 0.945, 3.1 kg, and 7.8%). There were no differences (p = 0.19–0.95) between the Dm or NDm hand for pre-fatigue MVIC (grand mean = 40.2 ± 11.8 kg). The time to task failure for the 50% MVIC HTF was longer (p < 0.001) for the Dm (122.4 ± 29.1 s) than the NDm (108.4 ± 34.2 s) limb. For performance fatigability, there was no 2-way fatigue (Dm, NDm) × side (IPS, CT) interaction (p = 0.62) or main effect (p = 0.67) for the fatigue test. There was a main effect for the side tested (p < 0.001). The performance fatigability for the IPS (25.0 ± 9.7%) side was greater than the CT (−1.1 ± 6.4%) side. There was a significant decrease in force from pre-to post-fatigue on the IPS side for both the Dm (mean diff = 9.6 ± 4.9 kg; p < 0.001) and NDm (difference = 9.7 ± 4.4 kg; p < 0.001) tests, but no differences pre-to post-fatigue on the CT side for the Dm (mean diff = −0.2 ± 4.3 kg; p = 0.867) or NDm (mean diff = −0.8 ± 2.5 kg; p = 0.244) tests. Conclusions: Despite the greater fatigue resistance for the Dm compared to the NDm limb, there were no differences in performance fatigability for the IPS side and no fatigue-induced decrease in force in the non-exercised, CT side. These findings may be attributable to the peripheral threshold of fatigue or sensory tolerance limit theories and did not suggest group III/IV afferent feedback and central fatigue in the CT, non-exercised limb. Practical Applications: Fatiguing, unilateral exercise involving a small amount of muscle mass does not affect force production in the CT limb.

(3) Comparison of Lower Extremity Strength Values in Male Collegiate Ice Hockey and Soccer Players

C. Merkley, G. Potts, M. Riopelle, R. Conners, and P. Whitehead

The University of Alabama in Huntsville

Ice hockey is a sport that requires substantial lower body strength and power. However, it is speculated that the rigid design of the boot of the hockey skate, which limits ankle range of motion (ROM), may compromise ankle strength values compared to other lower extremity dominant sports that do not have similar mobility limitations due to equipment. Deficits in isokinetic strength of the lower body musculature could impede the ability to generate speed and power, and could lead to an increase in the prevalence of lower body injuries or a decrease in performance. Few studies have been performed to investigate differences in lower body strength between athletes that have mobility limitations due to equipment within lower extremity dominant sports. Purpose: To determine differences in ankle and knee strength values between collegiate ice hockey and soccer players. Methods: Ten NCAA Division I male hockey players (age = 21.9 ± 1.1 years; height = 178.0 ± 6.0 cm; weight = 83.3 ± 8.1 kg) and 7 NCAA Division II male soccer players (age = 20.3 ± 1.6 years; height = 175.5 ± 10.3 cm; weight = 80.0 ± 7.1 kg) were compared for isokinetic ankle and knee strength. Following the collection of demographic data and a standardized warm-up, subjects performed tests of ankle inversion and ankle eversion on an isokinetic dynamometer at test speeds of 30°·s−1 and 60°·s−1. Subjects were also tested for knee flexion and knee extension strength at 60°·s−1 and 180°·s−1. Isokinetic strength values of the dominant limb between hockey and soccer players were compared using independent sample t-tests, and an alpha level of 0.05, 2-sided was set a priori as a significance level. Effect sizes were calculated using Cohen's d. Results: Hockey players had significantly greater ankle strength than soccer players at each test speed in both the inversion (t ≥ 2.611, df = 15, p ≤ 0.020) and eversion (t ≥ 2.331, df = 15, p ≤ 0.034) directions. A large effect size was reflected for both inversion (d ≥ 1.26) and eversion (d ≥ 1.21). Strength values for knee flexion and knee extension were not significantly different between the 2 groups (t ≤ 1.431, df = 15, p ≥ 0.173). Conclusions: It was hypothesized that due to the fixed position of the ankle within the boot of the skate, their ankle strength would be lower than that of soccer players. While knee flexion and knee extension values were not different across the 2 lower extremity dominant sports, which was expected, the differences found for ankle strength were surprising. Despite the ROM limitations for hockey players, the results suggest that hockey players have significantly higher ankle inversion and eversion strength than soccer players. Practical Applications: Strength and conditioning coaches who may have a similar mindset to our hypothesis will benefit from this information. Rather than dedicating specific time towards ankle strengthening within hockey players, this data could lead 1 to focus more on ROM or stability exercises during off-ice conditioning. Such an approach may be more beneficial as ankle strength may not be the primary deficiency contributing to ankle injuries in hockey players.

(4) Effect of Subjective Sleep and Recovery Scores on Same-Day Vertical Jump Performance Tracking

R. Herron,1 G. Ryan,2 D. DeJohn,3 H. Ramirez,3 L. Haaren,3 G. Hogan,3 and S. Rossi3

1United States Sports Academy;2Piedmont University; and3Georgia Southern University

Purpose: Subjective data are often used to monitor an athlete's physiological or psychological status in an attempt to track fatigue or readiness to perform. The purpose of this study is to investigate the effect of self-reported sleep quality scores and perceived recovery status on a commonly-used performance indictor–vertical jump height–in professional soccer players. Methods: Data from 22 professional male soccer players (aged 23 ± 1 year), totaling 1,341 observations, were analyzed. Each observation included scores from the Sleep Quality Scale (SQS), Perceived Recovery Scale (PRS), pre-practice vertical jump (PRE-VJ). SQS and PRS are 11-point ordinal scales ranging from “0 = worst” to “10 = best” for their respective metrics. For analysis, the SQS and PRS scores were binned into 3 groups: low = scores 0–3, medium = scores 4–7, and high = scores 8–10. PRE-VJ was recorded as athletes reported to the field for practice. Athletes performed 1, maximal-effort countermovement jump (akimbo style = hands on hips) on an electronic switch mat. A 2-way ANOVA was used to examine the effect of SQS and PRS levels on the performance variable, PRE-VJ. Results: There was no interaction between the effects of SQS and PRS on PRE-VJ [F (4, 1,332) = 1.928, p = 0.103]. Furthermore, there was no main effect of SQS [F (2, 1,332) = 0.987, p = 0.373)] nor PRS [F (2, 1,332) = 1.612, p = 0.200)] on PRE-VJ. Conclusions: These data do not show an effect of SQS and/or PRS on PRE-VJ performance in professional male soccer players. Practical Applications: At the team-level, SQS and PRS scores do not infer changes in PRE-VJ scores, in this study. However, 2 things are important to consider. First, the validity of subjective data and quick-capture performance data is highly important. Athlete/coach buy-in and quality control related to data acquisition and monitoring are extremely important in creating a practical and informative monitoring program. Secondly, within an athlete monitoring program, subjective data are potentially valuable in monitoring stressors that are not captured in performance data of any type. Therefore, all those involved in an organization's sport science team need to work towards creating and optimizing a system that supports athlete health and performance in their program.

(5) Concurrent Activation Potentiation in Handgrip Strength in Sedentary vs. Athletic Populations

V. Cazás-Moreno,1 R. Cochrum,1 M. Overstreet,1 P. Dickson,1 J. Heimdal,1 and L. Brown2

1Tennessee State University; and2California State University, Fullerton

Introduction: Concurrent activation potentiation (CAP) is a neuromuscular phenomenon that utilizes remote voluntary contractions (RVCs) to enhance strength and/or force output in a prime mover(s). The potential training benefits that could be gained through the strategic use of CAP have shown considerable promise, but the majority of research has only utilized trained participants in the study of CAP. Therein, it is unknown if all populations (e.g., untrained, trained) are able to utilize CAP to increase strength in a similar manner or even at all. Purpose: To assess the effect of CAP via jaw clenching on isometric handgrip strength (iHGS) between sedentary and athletically trained groups. Methods: Twenty sedentary male and female participants (age: 21 ± 2 years; wt: 71.4 ± 16.6 kg) and 13 male and female division-1 athletes (age: 21 ± 2 years; wt: 87.2 ± 20.1 kg) performed a grip-based warm-up followed by 2 randomized iHGS trials under jaw clenching (JC), and no jaw clenching (NJC) conditions. A standard handgrip dynamometer was utilized, while the JC was performed with a general use adult form fit mouthguard. Each condition was repeated 3 times with 30-seconds rest between each repetition and 5-minutes rest between each condition. Both the average (AVG) and MAX measures were recorded during each condition and only the dominant hand was analyzed. Results: A 2 × 2 ANOVA revealed no significant (p = 0.791) population × condition interaction for MAX iHGS. There was, however, a main effect for population (p = 0.040) where athletes (x̄: 46.27 ± 12.98 kg) were stronger than sedentary (x̄: 37.77 ± 9.90 kg), and a main effect for condition (p = 0.005), where JC (x̄: 41.12 ± 11.80 kg) was greater than NJC (x̄: 39.08 ± 11.43 kg). A second 2 × 2 ANOVA revealed no significant (p = 0.464) population × condition interaction for AVG iHGS. There was, however, a main effect for population (p = 0.038) where athletes (x̄: 41.99 ± 10.86 kg) were stronger than sedentary (x̄: 34.93 ± 8.80 kg), and a main effect for condition (p = 0.024), where JC (x̄: 37.71 ± 10.12 kg) was greater than NJC (x̄: 36.1161 ± 10.72 kg). Conclusion: This is the first known study to examine the effect of training status on CAP. In line with previous research, it appears both the sedentary and highly athletically trained are susceptible to the usage of CAP (via jaw clenching) during maximal strength efforts. Both populations exhibited greater iHGS during JC in both MAX and AVG measures. Practical Applications: Longitudinal research is needed to determine if greater benefit can be attained through training and/or intentional use of RVC's to enhance CAP. Strength and conditioning and physical training/therapy practitioners should attempt to creatively and strategically utilize jaw clenching and various forms of CAP, to help potentially increase max effort attempts in athletic and sedentary populations.

(6) Effects of Load on the Functional Movement Screen In-Line Lunge and Its Scoring Criteria

B. Leshinske

Saint Xavier University

The Functional Movement System (FMS) is a pre-participation evaluation tool used among physical therapists, strength coaches, personal trainers, and athletic trainers to identify movement deficiencies. The FMS displays both intra-rater and interrater reliability but has been challenged with regards to the validity of the composite score and its use to predict injuries. In addition, several studies have also looked at the impact of a weight vest on the FMS screen in firefighters. A quasi-experimental design will be used to properly assess the impact of resistance may have on the scoring criteria of the FMS. An alpha value of p < 0.05 will be set to determine statistical significance with an associated 95% confidence intervals (CI) being calculated for statistical significance. A Wilcoxin Signed Ranked test will be used to determine sensitivity between the BW, 10 and 20% additional load. Furthermore, a ROC curve will be used to show how sensitive the inline lunge is to load. This was approved by the Institutional Review Boards of Rocky Mountain University of Health Professions and Saint Xavier University. Purpose: The purpose of this study is to investigate how resistance may impact the FMS scoring system and overall movement using a weight vest based on bodyweight in collage aged athletes 18–24 years old. The primary investigator hypothesizes that load will have an impact on the inline lunge with 10 or 20% load. Methods: A convenience sample of 23 student athletes from Saint Xavier University performed the inline lunge from the Functional Movement System (FMS). The subjects performed the FMS inline lunge without load, and if a score of 2 or 3 was attained on each leg they would retest wearing a weighted vest to include 10% of their bodyweight (BW). The subjects would repeat the inline lunge with the weighted vest, and if a score of 2 or 3 was achieved on each leg, additional load would be added to the weight vest equaling 20% of their bodyweight. Results: A load of 10% did not elicit a significant difference (alpha = 0.05, p = 0.317) when compared to the bodyweight inline lunge on the right side, accepting the null hypothesis. A load of 10% on the left side elicited a significant difference when compared to the unloaded left side (A load of 20% resulted in significant difference (alpha = 0.05, p = 0.025) compared to the bodyweight lunge, accepting the hypothesis as stated. When comparing loads of 10 and 20% there was only significance on the left side with regard to load (Right alpha 0.05, p = 0.157, Left side alpha 0.05, p = 0.021). A 2x2 table was analyzed to determine sensitivity. A 10% load was sensitive (R = 89.5%, L = 88.2%) when compared to the bodyweight inline lunge for both right and left side. A load of 20% compared to bodyweight also showed high sensitivity (R = 90.9%, L = 100%). When comparing a 10% load to 20% load it was found to be poor on both the right and left side (R = 0.58, L = 0.53). Conclusions: The results of this study demonstrate that the inline lunge of the FMS is not impacted by a load of 10% but is significantly impacted by a load of 20%. Furthermore, a change of load between 10 and 20% also showed a decrease in scores that was significant. The inline lunge is sensitive to load on both the right side and left side with 10 or 20% loads. It can be concluded that while the inline lunge is sensitive to load across both 10 and 20%, it is only significantly impacted by a 20% load increase on bodyweight.

(7) Muscle Hypertrophy Adaptations in Pectoralis Major and Its Effect on Absolute Strength in Resistance-Trained Males

A. Murphy,1 A. Horwell,1 J. Bradshaw,1 T. Wadhi,1 T. Morrison,2 V. Hollamon,1 S. Zazzo,1 C. Barakat,1 J. Sullivan,1 J. Walters,1 and E. De Souza1

1The University of Tampa; and2University of North Carolina at Chapel Hill

Introduction: There is an ongoing discussion on how muscle hypertrophy contributes to strength gains. However, little is known about the association between changes in muscle thickness and maximal strength in trained individuals. Purpose: Therefore, the purpose is to examine the association between increases in muscle thickness and absolute strength in resistance-trained males. Methods: Twenty-seven resistance-trained males (1 repetition maximum [1RM] to body mass [BM] ratio = 1.20) underwent an 8-week training intervention consisting of barbell bench press, and barbell incline press exercise. Training was performed twice per week with at least 48 hours in between sessions. Muscle thickness of the pectoralis major (belly and lateral portion) was measured using ultrasonography. Maximal strength was assessed via 1RM bench press. The assessments were conducted at pre and post-testing. Results: A Pearson product correlation revealed a moderate association between muscle thickness and bench press 1RM (r = 0.51, 95%-CI: 0.1562–0.7508, p = 0.0074), Figure 1. Conclusions: Our data suggests that there is a moderate association between muscle hypertrophy and maximal strength. Practical Applications: Athletes may consider implementing periods of training prioritizing muscle hypertrophy in order to increase strength adaptations.

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Figure 1.:
Relationship between changes in muscle thickness and 1RM improvements.

(8) The Influence of Fat Free Mass Adaptations on Muscular Strength in Trained Individuals

A. Horwell,1 C. Barakat,1 A. Murphy,1 J. Bradshaw,1 T. Wadhi,1 T. Morrison,2 V. Holloman,1 S. Zazzo,1 J. O'Sullivan,1 E. De Souza,1 and J. Walters1

1The University of Tampa; and2University of North Carolina at Chapel Hill

Little is known in regard to what extent increased muscle mass accrual supports an additional increase in absolute strength. Purpose: This study investigated the relationship between regional fat free mass (FFM) and muscle strength in trained males. Methods: Thirty-five males with previous strength training experience (1 repetition maximum [1RM]: body mass [BM] ratio = 2.09) were stratified based on training volume performed prior to intervention (sets per week for quadriceps muscle), and were then randomly assigned to 1 of 3 experimental groups: low (12 SET per week, n = 13), moderate (18 SET per week, n = 12) or high volume (24 SET per week, n = 10). Subjects underwent an 8-week lower-body RT program, twice a week, consisting of the following exercises: squat, leg-press, and glute-hamstring curls. Fat free mass in the region of interest (ROI) of the thigh muscles was assessed using dual-energy x-ray absorptiometry (DEXA) at pre and post-testing. A 1 repetition maximum (RM) squat was utilized to assess increase in maximum strength. A Pearson product correlation coefficient was used to assess the association between FFM and 1RM. Results: There was a positive association between FFM in the ROI and 1RM strength (r = 0.53, 95%-CI: 0.24–0.73, p = 0.001), Figure 1. Conclusions: Our data suggests that FFM accrual of the lower extremities was moderately correlated to increases in squat 1RM strength. Practical Applications: It may be beneficial for athletes to implement periods of training dedicated to achieving muscle hypertrophy, when aiming to optimize muscular strength.

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Figure 1.:
Relationship between changes in ROI-FFM and 1RM improvements.

(9) Effects of Blood Flow Restriction Training on High Intensity Back Squat Repetition Volume When Training to Failure

K. Saffold, B. Hornikel, T. Adams, K. Oudjit, A. Fleming, M. Jones, and L. Winchester

The University of Alabama

Purpose: The purpose of this study was to examine the effects of blood flow restriction (BFR) exercise on repetition volume when training high-intensity back-squats until failure. Methods: A counter-balanced repeated measures design was utilized in 9 resistance-trained individuals (Age 25.78 ± 4.66 years; Height 183.59 ± 8.33 cm; Mass 92.10 ± 13.58 kg; Body fat 15.04 ± 6.86 %BF; back-squat 1RM 158.08 ± 45.71 kg). A baseline 1-repetition maximum (1RM) test was performed for back-squat during an initial visit. During 2 separate sessions, the participants completed 4 sets of back-squats with 3 minutes rest between sets, each to failure, using a load of 75% of 1RM.Laboratory visits were separated by a minimum of 72 hours and a maximum of 7 days. During the BFR session, personal tourniquet pressure (PTP) was determined for each leg using the Delfi PTSII system. Bilateral occlusion using a pressure of 80% of PTP was used during the BFR squat protocol on the upper thighs. The BFR cuffs were inflated synchronously 30 seconds before the start of the first set and deflated for the rest period immediately following the end of the second set. The cuffs were re-inflated 30 seconds before the start of the third set and deflated 2 minutes following the end of the fourth set. Paired Sample T-tests were utilized to analyze differences between total session repetitions as well as set repetitions. Data are presented as mean ± standard deviation, with p < 0.05 used to determine statistical significance. Results: There was a significant decrease in total session repetitions during the BFR session (24.78 ± 9.91 vs. 42.33 ± 14.59; p = 0.001). There was also a significant decrease in repetitions completed during set 1 (11.67 ± 4.53 vs 13.67 ± 4.80; p = 0.027), set 2 (4.22 ± 2.22 vs. 11.11 ± 3.76; p < 0.001), and set 4 (2.67 ± 2.06 vs. 8.44 ± 3.36; p < 0.001). There was no significant difference in repetitions completed between conditions during set 3 (6.22 ± 3.27 vs 9.11 ± 3.59; p = 0.117). Conclusions: All sets between both conditions were performed until failure. Based on the differences in the number of repetitions performed, as well as differences within individual sets between conditions, it appears that BFR significantly reduces the total volume an individual can perform during high-intensity back-squats. There was no significant difference in the number of repetitions performed during the third set, which was the set after the BFR cuffs were deflated during the rest period. Practical Applications: Utilizing BFR during high-intensity back-squats reduces the total amount of repetitions performed. BFR can induce muscular fatigue at a faster rate than back-squats without BFR. Research on differences in performance adaptations between traditional back-squats and back-squats with BFR would help us to understand how this decrease in training volume plays a role in performance adaptations.

(10) The Effect of Training Loads on Peak Bar Velocity During a Hang Power Clean in Adolescent Males

C. Addie,1 S. Martinez,2 and K. Mehls3

1Middle Tennessee State;2Middle Tennessee State University; and3Walsh University

Olympic weightlifting exercises have been advocated as an effective way to enhance the force-velocity profile. However, the force-velocity characteristics of a given training exercise depend on several variables, 1 of which is training load. While several studies have examined the force-velocity characteristics of more mature, stronger athletes, none have examined these characteristics in youth athletes during Olympic lifts. Purpose: The Purpose of this study is to assess bar velocity on hang power cleans at various training intensities. Methods: Adolescent males who engage in Olympic weightlifting (M ± SD: n = 16; age: 16.90 ± 1.00 years; height: 180.10 ± 8.10 cm; body mass: 81.10 ± 15.05 kg) performed 3 repetitions from the hang power clean position at 30, 40, 50, 60, 70, 80, and 90% of their 1 rep max (1RM). A TENDO Unit (Model V-620, Tendo Sports Machines, Slovak Republic) recorded peak velocity, force, and power. Peak velocity was analyzed using a 1X7 (sex x% of 1RM) repeated measures ANOVA. Results: Training load was found to have a significant effect on peak bar velocity (p = 0.000). Pairwise comparisons revealed that 30% (2.4 ± 0.5 m·s−1), 40% (2.2 ± 0.3 m·s−1), 50% (2.0 ± 0.2 m·s−1), 60% (1.9 ± 0.3 m·s−1), and 70% (1.9 ± 0.2 m·s−1) 1RM were not significantly different from each other, but had significantly faster peak bar velocity than 80% (1.8 ± 0.2 m·s−1) and 90% (1.7 ± 0.2 m·s−1) 1RM. Conclusions: Increasing training loads beyond 70% 1RM significantly reduces peak bar velocity in the hang power clean for adolescent males. Practical Applications: Practitioners designing Olympic lifting training programs for adolescents need to be mindful of the force-velocity curve of individual lifts. If bar velocity is the main goal, keeping training intensity below 70% 1RM will result in the fastest peak bar velocities.

(11) Predicting Sprinting Speed Using Agility and Power Tests in Professional Male Soccer Players

G. Ryan,1 D. DeJohn,2 H. Ramirez,2 L. Haaren,2 G. Hogan,2 and S. Rossi2

1Piedmont University; and2Georgia Southern University

Testing and evaluation of an athlete's physical abilities and readiness to train and compete may be limited either by time, administrator error, or finances. This is particularly true of determining maximum sprint speed, which can either be calculated from time to completion, which can introduce considerable human error or more accurately measured via GPS devices. While GPS systems are more accurate, these devices may be outside the financial means of many sport teams. One solution to this problem may be the implementation of accurate field tests, and the subsequent creation of regression equations, to estimate maximum sprint speed. Purpose: The purpose of this study was to determine potential predictors of maximum sprint speed from a variety of agility and lower body power tests in professional soccer players. Methods: Sixteen professional USL 1 male soccer players (Age: 22.6 ± 2.4 years, Height: 1.80 ± 0.10 m, Weight: 78.2 ± 7.3 kg) participated in the study. All athletes completed a test battery that included: Pro Agility Shuttle (PAS), L-Drill (L-D), akimbo countermovement jump (CMJ), and 30 m maximum effort sprint (Smax). All athletes were allowed to complete each trial twice, and the better effort was included for analyses. Performance on the PAS and L-D were measured via stopwatches, CMJ on a switch mat, and Smax using a GPS device. Prior to all tests, all equipment was calibrated according to manufacturer specifications. Pearson correlations were run on all variables to determine their relationship to Smax. Additionally, a forward multiple linear regression was calculated to predict Smax based on all other variables of interest. Significance of relationships was calculated at p ≤ 0.05. Results: A significant, positive, moderate correlation was found between CMJ (60.7 ± 6.4 cm) and Smax (8.7 ± 1.1 m·s−1, r = 0.55; p = 0.02). No significant correlations were found between PAS (r = −0.19; p = 0.25) or L-D (r = −0.29; p = 0.14) and Smax. A significant regression equation was found (F (1, 15) = 5.923, p = 0.03) with an adjusted R2 of 0.247. CMJ was the only significant predictor of Smax. The prediction equation was Smax = 13.225 + 0.263 (CMJ). 95% CIs were (7.665, 18.784) and (0.031, 0.495) respectively. PAS (p = 0.83) and L-D (p = 0.60) were not significant predictors of Smax in the tested population. Conclusions: CMJ helped explain ∼25% of the variance in Smax among professional USL 1 soccer players. CMJ may be the best predictor of Smax of the tests completed due to the similar nature of lower body explosion required for both tests. Practical Applications: The ability to predict Smax variance based on CMJ performance is key for managing time spent testing to allow adequate time for training other requirements of sport as well as providing a low cost alternative to estimating Smax compared to GPS devices. Appropriate monitoring of athlete ability is important to maximize performance during different phases of training when time or funding is limited due to other team requirements. Lastly, strength and conditioning professionals may look to implement vertical and horizontal plane lower body power development to potentially improve Smax in professional soccer players.

(12) Acute Effects of Complex and Conjugate Training Methods on Upper and Lower Body Power

Y. Figueroa,1 and Z. Tabrani2

1Sam Houston State University; and2University of St. Augustine for Health Sciences

Muscular power is essential for success in various aspects of human performance. There have been many studies that focus on methods for improving power developments, but limited research has compared training methodologies in order to determine which is more effective. Two of these training systems are known as complex and conjugate. The complex training methodology utilizes high-intensity resistance training in combination with plyometric exercises. Meanwhile, the conjugate method incorporates high-intensity resistance training with an overspeed component to yield higher developments in power output. Purpose: The aim of this study was to compare the effects of complex and conjugate training methodologies on upper and lower body power in a trained population. It was hypothesized that the complex training method would have a greater effect on upper and lower body power compared to the conjugate method. Methods: Thirteen participants (9 females, 4 males) were randomly assigned to either a complex or conjugate training group. Ten participants (7 females, 3 males) adhered to the training program until completion of data collection. Participants trained for a total of 6 sessions which occurred 3 times a week over a period of 2 weeks. Upper and lower body strength was assessed using a 1-repetition maximum (1-RM) on the bench press and back squat, respectively. Upper body power was measured using a linear transducer while the participant performed the bench press 1-RM. Lower body power was measured using vertical jump (VJ) height. Each assessment was performed pre- and post-training. Results: There were no significant differences between training conditions for upper body power, lower body power, or vertical jump height. However, both complex and conjugate exercise protocols showed a significant increase for upper body power post-training. Upper body power was found to significantly increase by an average of 57.15 Watts (SE = ± 16.12, p = 0.008) across groups. Conclusions: In a trained population, when resistance exercise is paired with either a plyometric or overspeed exercise, upper body power may increase. Practical Applications: Coaches looking to acutely increase upper body power in their athletes can elect either complex or conjugate training methodologies. A longer training cycle and larger sample size may show significant differences in lower body power. Addressing these limitations in future research can provide coaches and athletes with more definitive training parameters for improving vertical jump and lower body power in athletic populations.

(13) Association Between Jumping Asymmetry and Linear Speed in Division Ii Collegiate Softball Players

K. Everhart, J. Grazer, K. Hunt, and M. Martino

Georgia College & State University

Limb-asymmetry is becoming a more researched topic in recent years due to its expected impact on injury prevalence and performance. Limb-asymmetry has been assessed as a possible indicator of return to play and likelihood of injury. Several studies have investigated the role an asymmetrical profile can have on injury, the method of assessment has ranged from isokinetic assessment of single joint exercises to isometric full body assessments. The role that it plays in sprinting and sport performance has been questioned as limited observations have been made to this date. Due to limited studies and the variations in results regarding the role an asymmetrical profile plays on performance, it is still a largely clouded, but important relationship. Purpose: The purpose of this study was to investigate the relationship between lower body asymmetries during the countermovement jump and their potential impact on linear sprint performance. Methods: Nineteen Division II softball athletes participated in this study. The participants completed a CMJ test on biaxial force plates being sampled at 1,000 Hz and analyzed using a customized Microsoft Excel program. Athletes performed 2 trials and averages were taken from the trials for the following variables: eccentric braking impulse and concentric impulse for left and right legs. From this, net impulse was calculated to determine center of mass displacement based on the impulse-momentum relationship and using the following formula (take-off velocity)2/2*9.81 m·s−2. Participants completed two 20 m sprints with timing gates at 5, 10, and 20 m. Pearson-product moment correlations were performed between all dependent variables. Alpha level was set at p ≤ 0.05 for all statistical analyses. Results: Results indicated that there were not any statistically significant relationships between the asymmetry metrics and sprint times of 0–5, 0–10, or 0–20 m, or asymmetry metrics and jump height in the countermovement jump. Conclusions: The results indicate that sprint performances at the 3 distances as well as jump performance are not related to inter-limb asymmetries. These findings could be due to the average absolute asymmetry not being at a high magnitude in the sample used, (i.e., over 15%), therefore having a low impact on athletic performance. Task-specificity of testing and performance, as well as the variable nature of asymmetry between different athletes and the sport of softball itself could lend a hand to showing irregular or insignificant results as well. In order to ascertain an athlete's asymmetrical profile, multiple tests would need to be conducted on a regular basis. Practical Applications: This highlights that there may be other metrics that need to be evaluated to determine the impact on sprinting performance or as previous literature has reported, asymmetries are likely to be task-specific and highly variable. Professionals may need to determine cost-effective methods of evaluating sprint asymmetries.

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Table 1:
Correlations between sprint time, jump height, and average concentric and eccentric impulses.

(14) The Reliability of and Relationships Between 3 Velocity-Based Training Devices During the Countermovement Shrug

C. Kissick,1 B. Techmanski,1 P. Comfort,2 B. Mann,3 and T. Suchomel1

1Carroll University;2University of Salford; and3University of Miami

Purpose: To examine the reliability of, and relationships between 3 velocity monitoring devices for the countermovement shrug exercise at 3 commonly prescribed loads. Methods: Ten resistance-trained men (age: 24.9 ± 4.0 years, body mass: 89.8 ± 15.0 kg, height: 179.2 ± 8.4 cm, relative 1-repetition maximum [1RM] back squat: 2.0 ± 0.3 kg·kg−1, relative 1RM hang power clean [HPC]: 1.2 ± 0.2 kg·kg−1) with previous the HPC and its variations participated in 2 testing sessions. The first session was used to determine the 1RM HPC for each participant. During the second testing session, each participant performed 3 repetitions of the countermovement shrug (CMS) at loads of 80, 100, and 120% of their 1RM HPC. The Tendo (T), PUSH Band 2.0 (P), and GymAware PowerTool (GA) devices were used to measure mean (MBV) and peak barbell velocity (PBV) during each repetition. Intraclass correlation coefficients (ICC) and typical error expressed as coefficient variation percentages (CV%) were used to determine the relative and absolute reliability of each device, respectively. In addition, Pearson's correlation coefficients were used to examine the relationships between each device for MBV and PBV at each load. No correlations were calculated between T and the other devices at 120% due to the participants not reaching the required displacement threshold of the T device. Results: The mean and standard deviation for MBV and PBV with each device, as well as the correlation magnitudes between devices, are displayed in Table 1. The ICC for the MBV were 0.94–0.95, 0.66–0.84, and 0.88–0.95 for T, P, and GA, respectively. In addition, the ICC for the PBV were 0.91–0.95, 0.80–0.85, and 0.91–0.95 for T, P, and GA, respectively. The CVs for MBV were 2.7–5.6%, 4.2–6.2%, and 3.3–4.4% for T, P, and GA, respectively. In addition, the CVs for PBV were 2.2–4.1%, 3.1–7.0%, and 3.2–6.2% for T, P, and GA, respectively. The relationship between devices for MBV were all very large (r ≥ 0.70) across all loads, except for P and GA at 120% 1RM (r = 0.60). In addition, the relationship between devices at PBV were all very large (r ≥ 0.70) across all loads. Conclusions: The relative reliability between trials was good to excellent. In addition, acceptable within-session variability was displayed across all loads; however, the T device may be limited when measuring MBV and PBV at 120% 1RM. Large to very large relationships existed between the T, P, and GA devices for MBV and PBV across all loads. Practical Applications: The T, P, and GA devices may be used to reliably assess MBV and PBV during CMS repetitions performed with 80, 100, and 120% 1RM HPC; however, recording velocities at supramaximal loads with the T device may be limited due to participants not reaching the required displacement threshold. Despite the large relationships between devices, practitioners should be aware that MBV and PBV are calculated differently and may thus, provide different velocity magnitudes.

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Table 1:
Mean and peak barbell velocity and relationships between the Tendo (T), Push Band 2.0 (P), and GymAware PowerTool (GA).

(15) Differences in Countermovement Jumps by Football Position

N. Despot,1 B. Mann,1 D. Feeley,1 V. Ishmael,1 J. Barber,1 K. Kroboth,1 C. Dodd,1 J. Mayhew,2 J. Dawes,3 and J. Signorile1

1University of Miami;2Truman State University; and3Oklahoma State University

Football is a sport with many positions that have different responsibilities and athletic demands. All football athletes rely heavily on their lower-body power, but the specific interactions of force and velocity may differ. The countermovement jump is a highly reliable test for lower body power, that can be used quickly for large teams. Purpose: To evaluate the differences in discrete variables from the countermovement jumps between the different positional groups of a football team. Methods: During an evaluation, athletes from a Division 1 BCS Power 5 conference team (n = 82, age = 19.89 ± 1.55 years, height = 1.87 ± 0.06 m, body mass = 101.78 ± 22.77 kg) performed a countermovement jump test. The 82 athletes who performed the countermovement jumps were placed into 4 groups (big, middle, skill, specialists), based on positional groups as determined by the coaching staff. There were 20 big position, 26 middle, 31 skilled positions, and 5 specialists. The athletes were instructed to place their hands on their hips for the duration of the test. The athletes then stood on a single axis dual force platform system sampling at 1,000 Hz for 3 seconds. Once their mass was recorded, the athletes jumped on command as high as they could. The best repetition was used for the analysis. The 7 variables evaluated using multiple univariate analysis were Force @ Peak Power (N), Force @ Zero Velocity (N), Jump Height (cm), Velocity @ Peak Power (m·s−1), Concentric Peak Force/BM (N·kg−1), Concentric Mean Power/BM (W/kg), and Concentric Impulse (Ns). Results: The data analysis from the univariate ANOVA's revealed a significant difference when looking at Force @ Peak Power (N) (F = 31.586, p ≤ 0.001, ηp2 = 0.549, observed power = 1.000), Force @ Zero Velocity (N) (F = 20.661, p ≤ 0.001, ηp2 = 0.443, observed power = 1.000), Concentric Impulse (Ns) (F = 8.858, p ≤ 0.001, ηp2 = 0.254, observed power = 0.994), Velocity @ Peak Power (m·s−1) (F = 9.581, p ≤ 0.001, ηp2 = 0.269, observed power = 0.996), Jump Height (cm) (F = 13.718, p ≤ 0.001, ηp2 = 0.345, observed power = 1.000), Concentric Peak Force/BM (N/kg) (F = 4.273, p = 0.008, ηp2 = 0.141, observed power = 0.846), Concentric Mean Power/BM (W·kg−1) (F = 10.235, p ≤ 0.001, ηp2 = 0.282, observed power = 0.998). Conclusions: Post Hoc analysis showed the big group performed significantly better than the middle when total force was calculated (Force @ Peak Power p ≤ 0.001, Force @ Zero Velocity p = 0.001, and Concentric Impulse p = 0.036). The skilled positions performed the best overall at the speed variables, and where body mass was normalized. They performed significantly better than the middle at the Concentric Mean Power/BM (p = 0.008), and Velocity @ Peak Power (p = 0.018). Practical Applications: Linemen produce the most amount of force but are the least efficient at doing so, while skilled positions produce less force but are the most efficient. To optimally train for their responsibilities on the field, the big group should train to produce the most force possible, skilled positions should train to be as efficient as possible, and the middle group should have an even balance.

(16) Muscle Tissue Oxygenation and Muscle Blood Flow Responses to Fatiguing Leg Extension Exercise in Sarcopenic and Non-sarcopenic Older Adults

M. Shoemaker,1 S. Pereira,2 V. Mustad,3 Z. Gillen,4 B. McKay,5 J. Lopez-Pedrosa,2 R. Rueda,2 and J. Cramer1

1The University of Texas at El Paso;2Abbott Nutrition;3Nutrition Science Consulting, LLC;4Mississippi State University; and5Creighton University School of Medicine

Purpose: Examine responses of muscle tissue oxygenation and blood flow with near-infrared spectroscopy (NIRS) during fatiguing, anaerobic leg extension exercise in sarcopenic (S) and non-sarcopenic (NS) older adults. Methods: Twenty-2 older adults (mean age ± SE = 77 ± 2 years) were categorized as NS (n = 11) or S (n = 11) based on grip strength and muscle mass. Maximal leg extension strength was estimated with a unilateral, dynamic constant external resistance 5-repetition maximum (RM) test used to estimate 1RM. For the fatiguing task, participants completed repetitions to failure using 30% of the estimated 1RM at a tempo of 20 bpm. Number of repetitions completed and time to failure was recorded. Muscle tissue oxygenation of the vastus lateralis was measured with NIRS. Relative changes from baseline for total hemoglobin (Hb) + myoglobin (Mb) (Δtotal[heme]) as a reflection of muscle blood flow and measurements of tissue saturation (StO2) (%) were divided into quintiles (%) based on the number of repetitions and time to failure and categorized as 0–20%, 20–40%, 40–60%, 60–80%, and 80–100% time to exhaustion (TTE). Two-way mixed factorial ANOVAs (time x group) were used to examine responses across time and group-related differences. Follow up t-tests were performed. Results: Estimated 5RM was greater for NS than S (14.0 vs. 9.8 kg, p = 0.049). Number or repetitions (NS = 19, S = 14 reps, p = 0.121) and TTE (NS = 1.5 S = 1.2 minutes, p = 0.262) were not significantly different. At 40–60% and 60–80% TTE, Δtotal[heme] was different between groups (p = 0.034–0.043) with NS showing decreases from baseline of −14.66 µM at 40–60% TTE and −18.27 µM at 60–80% TTE, whereas S experienced non-significant changes from baseline of 0.36–0.62 µM (Figure 1). At 20–40% TTE, NS had greater StO2 than S (73 vs. 65%, p = 0.026) and saw significant decreases over the fatiguing exercise bout (p = 0.011–0.049) while StO2 in S remained unchanged (p = 0.322–0.965) (Figure 1). Conclusions: Sarcopenia resulted in lower muscle tissue oxygenation and non-significant changes in muscle blood flow over a fatiguing bout of exercise compared to NS individuals. This indicates that S individuals experience less muscle blood flow during fatiguing exercise, indicating possible endothelial dysfunction and/or reduced muscle capillarization, related to muscle atrophy. Practical Applications: Reduced muscle blood flow, and thus, reduced delivery of nutrients to muscle, may further exacerbate sarcopenia. As individuals age, aerobic exercise together with muscle strengthening programs are vital to delay progression of sarcopenia and help maintain muscle strength and functionality.

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Figure 1.:
Changes from baseline of total[heme] (top) and tissue saturations (StO2) (%) (bottom) during a fatiguing bout of leg extensions in non-sarcopenic (NS) and sarcopenic (S) older adults. *Indicates differences between groups, #indicates less than 20–40% TTE, §indicates less than 40–60% TTE, and † indicates less than 60–80% TTE. p-values are type I errors of independent t-tests. Values are means ± standard errors.

(17) The Influence of Motor Unit Number and Muscle Activation on Early Phase Rate of Torque Development in Younger and Older Men

M. Magrini,1 R. Colquhoun,2 M. Ferrell,3 S. Fleming,2 J. Mota,4 J. Siedlik,1 N. Poidomani,1 N. Jenkins,5 and J. DeFreitas6

1Creighton University;2University of South Alabama;3Oklahoma State University Center for Health Sciences;4University of Alabama;5University of Iowa; and6Oklahoma State University

Purpose: The purpose of this study was to examine the influence of muscle activation and motor unit number estimation on early phase voluntary rate of torque development (RTD) in younger (YM) and older (OM) men. Methods: Thirty-two YM (n = 17; Mean ± SD, Age = 22 ± 3 years) and OM (n = 15; Age = 74 ± 6 years) volunteered to participate in this study. The RTD of the first 50 ms of a rapid maximal isometric contraction (RTD50) following force onset was assessed and analyzed in both age groups. Surface electromyography (sEMG) recorded muscle activation of the right vastus lateralis (VL), rectus femoris (RF), and vastus medialis (VM) during the first 50 ms of muscle excitation prior to RTD50. sEMG signals were normalized to maximal M-wave peak-to-peak amplitude and summed (nEMG50) to provide normalize muscle activation amplitude. Motor unit number estimations (MUNE) were examined using the incremental method from the VL of both age groups. Multiple linear regression analysis was used to develop a model for predicting RTD50 after adjusting for age group (YM vs OM), MUNE, and nEMG50. In order to allow slope coefficients to vary across subgroups, an interaction effect between age group and nEMG50 (age group x nEMG50) was included in the model. Statistical analyses were performed in SPSS v. 22 with significance value set at p ≤ 0.05. Results: A 4-predictor model was able to account for 44% of the variance in RTD50 (F(4,27) = 7.145; p ≤ 0.001; Adjusted R2 = 0.442). nEMG50 (107.46 ± 84.21 mV) had a significant (β = 1.289, p = 0.001) partial effect on RTD50 (555.23 ± 282.63 Nm·s) in the full model with a significant interaction effect observed for age group × nEMG50 (68.55 ± 100.48; β = −1.001, p = 0.037); meaning, the slope coefficient of nEMG50 varies across age group categories (YM vs. OM). MUNE (209.43 ± 71.28 #) had no effect on RTD50 independent of age (β = 0.386, p = 0.12). Because of the trouble visualizing multiple regression analysis, figure 1 presents the interaction of nEMG50 on RTD50 in YM, OM, and combined groups. Conclusions: These data suggest that RTD50 is highly dependent on muscle activation characteristics. Specifically, our data provide evidence that older adults may depend more on muscle activation at contraction onset of early phase RTD when compared to younger adults. Practical Applications: Clinicians, coaches, and practitioners can use these data to effectively program exercise training focused on improving rate of force development in the older adult population.

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Figure 1.:
Effect of nEMG50 on RTD50 in combined (both age groups; black dashed line), younger men (black dotted line), and older men (gray dotted line).

(19) Decision Making and Performance Outcomes in Major League Baseball Batters: Pre- and Post- Injury

I. Gillis,1<