A Methodological Report: Adapting the 505 Change-of-Direction Speed Test Specific to American Football : The Journal of Strength & Conditioning Research

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Research Note

A Methodological Report: Adapting the 505 Change-of-Direction Speed Test Specific to American Football

Lockie, Robert G.1; Farzad, Jalilvand1; Orjalo, Ashley J.1; Giuliano, Dominic V.1; Moreno, Matthew R.1; Wright, Glenn A.2

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Journal of Strength and Conditioning Research 31(2):p 539-547, February 2017. | DOI: 10.1519/JSC.0000000000001490
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American football is a high-intensity, high-impact collision sport that has very specific physiological requirements. Typical game-play involves short periods (approximately 5 seconds) of very intense activity, followed by longer bouts (approximately 30 seconds) of recovery (34). Hoffman (14) affirmed that the phosphagen energy system is the dominant energy system for football, providing up to 90% of the energy requirements for a game. As a result, most of the physiological testing for football focuses on high-intensity and power-based activities, such as linear and change-of-direction (COD) speed and agility. Change-of-direction speed and agility are essential physical components for football, as these qualities allow an offensive player to elude defenders or defenders to react to their offensive counterparts to cover or tackle them during a game.

It is important to differentiate between COD speed and agility. Sheppard and Young (38) defined agility as the initiation of body movement, change of direction, or rapid acceleration or deceleration, often in response to a stimulus. Thus, agility requires a cognitive and decision-making component. The physical component of agility is COD speed, and incorporates factors such as mechanical skill during a COD, sprint technique, and leg muscle qualities (38). Change-of-direction speed forms the foundation of agility, and this is commonly assessed in team sport athletes, including football players. There are 2 COD tests often used in football combine testing—the proagility shuttle and 3-cone drill (or L-run) (8,12,24,40). Although these tests have value for football, they are not without their limitations. The movement patterns inherent to each drill contain actions that are not necessarily specific to the COD movements in football (i.e., the proagility shuttle involves 3 CODs within a 10-yd boundary; the 3-cone drill involves 5 CODs in the shape of an “L”). In addition to this, the duration of the proagility shuttle when completed by collegiate players who were drafted into professional football was 4–5 seconds; for the 3-cone drill, the duration was 7–8 seconds (40). Metabolic limitations could influence performance in these tests, as opposed to COD ability (30,45). If a coach wishes to purely assess a player's COD ability, an assessment such as the 505 may be more applicable.

The 505 is a COD speed test that typically involves a 10-m sprint past a timing gate, a further 5-m sprint to a turning line where 1 leg needs to reach and plant at this line, before the athlete completes a 180° cut and sprints back through the timing gate (Figure 1). Test time is recorded in the 5-m up-and-back COD. The 505 is a popular assessment because it can isolate horizontal plane agility (7) and COD ability for each leg (6,21,22,26–28,32,33). As a result, this test has been administered for a range of athletes from sports such as rugby league (6,10,11), soccer (28), netball (9), basketball (41,42,44), cricket (21,30), and softball (32,33). In a physically similar population to football players, elite rugby league players completed the 505 from either leg in approximately 2.2–2.4 seconds (6,11). This test duration may reduce the influence of metabolic limitations that could be present in the proagility shuttle or 3-cone drill. Furthermore, the relatively simple up-and-back cut in the 505 could serve better isolate COD ability in football players, and represent a specific action completed within a football game. Indeed, this type of cut features in the training drills for positions such as running backs and receivers within pass patterns (e.g., a comeback route), and linebackers and defensive backs when they need to reposition and defend the run or pass (1). Sierer et al. (40) detailed the importance of COD ability in space for skill positions such running backs, wide receivers, and defensive backs. Furthermore, big skill position players including linebackers, defensive ends, fullbacks, and tight ends need to move explosively within COD actions to converge on the line of scrimmage during match play (40).

Figure 1.:
Structure and dimensions of the traditional 505 change-of-direction speed test.

In addition to a potentially more specific COD time measurement, a relatively new measure that can be made from the 505 has been referred to as the COD deficit (30,31). Nimphius et al. (31) suggested that the COD deficit could better isolate COD ability independent of an individual's linear sprint ability. This is because most COD speed tests still involve a large degree of linear sprinting, which could limit how much information is actually provided about an athlete's COD ability (31,36). The COD deficit was initially measured by Nimphius et al. (31) in collegiate football players by comparing with the COD during the proagility shuttle. The COD deficit was calculated as the difference between the 10-yd split time during a 40-yd sprint and the 10-yd split with a 180° COD (as assessed during the first half of the proagility shuttle) (31). Nimphius et al. (30) then adapted this to the 505 with cricketers, with the COD deficit calculated as the difference between the average 505 time and 10-m sprint time. Therefore, in addition to 505 time, COD deficit could also be used to explain a football players' ability to quickly and efficiently change direction, although this requires further investigation.

Despite the potential benefits of using the 505 for football, the distances used within the test should also be considered as to their applicability. Even though the metric system is the standard for scientific assessment, football uses yards as its form of measurement. It would seem a relatively simple process to adjust the distances in the test from 10 m and 5 m to 10 yd (9.14 m) and 5 yd (4.57 m), respectively. Nevertheless, it is still important to ensure that an adapted 505 test still measures the same capacities as the traditional version. This study, therefore, investigated an adapted version of the 505 COD speed test (termed the A505), where the dimensions were adjusted from meters to yards to make it more specific to football, in high school varsity players. Subjects also completed the 40-yd sprint (including measurement of the 0 to 5-, 0 to10-, and 0 to 40-yd intervals) to determine relationships between the A505, and 10-yd time was used to calculate the COD deficit. Smaller subsets of the sample completed the A505 again for a reliability analysis, and the traditional 505 to determine any differences in time because of the shorter distances in the A505 and to clarify whether the A505 measured similar qualities. It was hypothesized that A505 time would be reliable, would be completed in a quicker time when compared with the 505, and that there would be strong correlations between the 505 and A505 time. It was further hypothesized that there would be significant relationships between the 40-yd sprint and A505 (11,21,32), but not the COD deficit (30,31), and both the A505 and COD deficit would have discriminative capacities between football position groups.


Experimental Approach to the Problem

A cross-sectional analysis of varsity high school football players was conducted, whereby the players completed the A505 and a 40-yd sprint. Because of time restrictions, select squad members completed the A505 again for a reliability assessment of this test (n = 10), and others completed the traditional 505 for a comparative and correlation analysis (n = 10). In addition to this, A505 and 10-yd times were used to calculate COD deficit, and correlations were drawn between the A505 and COD deficit, and 5-, 10-, and 40-yd sprint times. A 1-way analysis of variance (ANOVA) was also used to compare the players in A505 test performance when they were divided into position groups to identify discriminant validity.


Twenty-five varsity high school players (age = 16.28 ± 0.83 years; height = 1.81 ± 0.08 m; body mass = 89.07 ± 21.74 kg) were recruited for this study to complete the A505. For the between-position analysis, and as high school players often play both offence and defense, players were grouped as: offensive and defensive linemen (LM); quarterbacks, running backs, and linebackers (QB/RB/LB); and receivers and defensive backs (R/DB). In a follow-up testing session, 10 subjects (age = 16.67 ± 0.82 years; height = 1.84 ± 0.07 m; body mass = 100.58 ± 20.43 kg) completed the A505 again for the reliability analysis, and 10 other subjects (age = 15.57 ± 0.79 years; height = 1.75 ± 0.10 m; body mass = 86.95 ± 35.84 kg) completed the traditional 505. The smaller sample numbers used in the follow-up sessions were because of the availability among school and football training commitments. Subjects were recruited if they were a member of the same school's varsity football team, were injury-free, and had permission to participate from their head coach as testing was conducted during the team's preseason in the month of June. Each subject had been a member of the high school's football program for at least 2 years and had resistance training experience commensurate with this time period. The methodology used in this study was approved by the institutional ethics committee. Players and their parents were contacted via e-mail and telephone to have the study procedures explained to them, and a follow-up meeting was conducted to answer any further questions. All subjects received a clear explanation of the study, including the risks and benefits of participation. Written informed consent was obtained before testing from players and parents (if subjects were under 18 years of age).


Two testing sessions were conducted, each separated by 1 week, and sessions were conducted in the late afternoon. Subjects were split into smaller testing groups according to surname for convenience, and each group reported to the field at the same time of day on each testing occasion. The availability of testing times was dictated by the team's coaching staff and needed to fit within the team's regular training schedule, although no other training was completed immediately before testing. In the first session, 25 subjects completed the A505 and 40-yd sprint, which also allowed for the recording of 10-yd sprint time for COD deficit calculation. In the second session, 20 subjects were available; half (n = 10) completed the A505 again and the other half (n = 10) completed the traditional 505. The subjects within these groups were randomly allocated. All testing was conducted on an outdoor turf field, and subjects wore their own cleats during each test. Similar to procedures from Lockie et al. (24), subjects did not eat for 2–3 hours before the session. Subjects also refrained from intensive exercise in the 24-hour period before testing and consumed water as required throughout the sessions.

Before data collection, the subject's age, height, and mass were recorded. Height was measured barefoot using a portable stadiometer (seca, Hamburg, Germany), and body mass was recorded using electronic digital scales (Tanita Corporation, Tokyo, Japan). Before each testing session, all subjects completed a standardized warm-up, which consisted of approximately 10 minutes of dynamic stretching of the lower limbs and linear and lateral runs over 10–20 yd that progressively increased in intensity. Within their testing group, subjects rotated alphabetically by surname for each assessment (24), which was consistent across all sessions. This ensured sufficient recovery periods of greater than 3 minutes between efforts. All subjects were familiar with the movement patterns required for the COD speed tests used in this study. However, the movement patterns for each test were included as part of the warm-up in each session as a further preparatory method.

Forty-Yard Sprint

Forty-yard sprint times were recorded by a timing lights system (Smartspeed; Fusion Sports, Sumner Park, Australia). Gates were positioned at 0 yd, 5 yd (4.57 m), 10 yd (9.14 m), and 40 yd (36.58 m), at a width of 1.5 m and height of 1.2 m. Subjects began the sprint from a 3-point stance 50 cm behind the start line, so as to trigger the first gate. Subjects were instructed to accelerate from the starting line and sprint through all sets of timing gates. If the subjects moved before starting, the trial was disregarded and repeated. As stated, 10-yd times were needed to calculate the COD deficit (30,31), whereas 5-, 10-, and 40-yd times were all included in the correlation analysis. Subjects completed 2 trials (8,21,24), with the average used for analysis.

Adapted 505 Test

The structure and general instructions for the A505 were the same as that for the traditional 505 (7). However, the dimensions were changed to make the test more specific to football (Figure 2). Rather than 10 m, the initial sprint was conducted over 10 yd (9.14 m). The COD section of the 505 was adjusted to 5 yd (4.57 m), instead of 5 m. This matched distances used in the proagility shuttle (8,12,24,40) and distances marked on football fields as well. During the warm-up, subjects familiarized themselves with the movement patterns required for the A505. Subjects used a 3-point start with the same body position as per the 40-yd sprint, with their hand positioned on the start line. The subjects sprinted through the timing gate (Smartspeed; Fusion Sports) to the turning line, indicated by the line markings on the field and markers. Subjects were to place either the left or right foot, depending on the trial, on the line and turn 180°, before sprinting back through the gate. Two trials were recorded for turns off the left and right foot (8,23,24), the order of which was randomized among the subjects. Gate height was set at 1.2 m, with a width of 1.5 m. A researcher was positioned at the turning line, and if the subject changed direction before hitting the turning point, or turned off the incorrect foot, the trial was disregarded and reattempted after a 3-minute recovery period. The average for the A505 for each leg was used for analysis. The COD deficit for the A505 for each leg was calculated via the formula: mean A505 time − mean 10-yd time (30,31). The mean 10-yd time was taken from the 40-yd sprint.

Figure 2.:
Structure and dimensions of the adapted 505 change-of-direction speed test.

Traditional 505 Test

The traditional 505 was structured and completed per established methods (7). The same procedures for the A505 were also used for the 505, with the only differences being the distances used within the test (Figures 1 and 2). As for the A505, the average 505 trial for each leg was used for analysis.

Statistical Analyses

Statistical analyses were processed using the Statistical Package for Social Sciences (version 22.0; IBM Corporation, Armonk, NY, USA). Means and SDs were calculated for each variable in addition to 95% confidence intervals. Several statistical approaches were used in this study for different parts of the analysis. First, stem-and-leaf plots confirmed there were no outliers in the data for each variable. To investigate the reliability of the A505, intraclass correlation coefficients (ICCs) were calculated. An ICC equal to or above 0.70 was considered acceptable (2,25). Absolute reliability was assessed by paired samples t-tests (p ≤ 0.05), which were used to determine any significant differences between the sessions for the A505 (25,39) and typical error (TE) (15). The spreadsheet of Hopkins (17) was used to determine the TE (s), expressed as a coefficient of variation (CV; %). A CV of less than 5% was set as the criterion for reliability. The usefulness of the test was determined by comparing the TE with the smallest worthwhile change (SWC) in time for each test (16). The SWC was determined by multiplying the between-subject SD by either 0.2 (SWC0.2) (16), which is the typical small effect, or 0.5 (SWC0.5) (5,25), which is an alternate moderate effect. If the TE was below the SWC, the test was rated as “good”; if the TE was similar to the SWC, the test was rated as “OK”; and if the TE was higher than the SWC, the test was rated as “marginal” (16).

To investigate validity (25,35,39), Pearson’s product-moment correlations (p ≤ 0.05) were used to define relationships between the A505 and 505, as this would provide an indication of whether each version of the 505 measured similar physical qualities. The strength of the correlation coefficient (r) was designated a descriptor as per Hopkins (18). An r value between 0 and 0.3, or 0 and −0.3, was considered small; 0.31 to 0.49, or −0.31 to −0.49, moderate; 0.5 to 0.69, or −0.5 to −0.69, large; 0.7 to 0.89, or −0.7 to −0.89, very large; and 0.9 to 1, or −0.9 to −1, near perfect for predicting relationships. Additionally, paired samples t-tests (p ≤ 0.05) were used to compare the left-leg A505 and 505 and right-leg A505 and 505 times. This was done to ascertain whether the reduction in distance in the A505 had a significant effect on the time to complete the test. Effect sizes (Cohen's d) were also calculated by dividing the means by the pooled SDs (5). In this study, 0.19 or less was considered a trivial effect; 0.20 to 0.59 a small effect; 0.60 to 1.19 a moderate effect; 1.20 to 1.99 a large effect; 2.00 to 3.99 a very large effect; and 4.00 and above an extremely large effect (16).

Pearson’s product-moment correlations (p ≤ 0.05) were also drawn between the A505 and COD deficit with 5-, 10-, and 40-yd sprint times, on the pooled data of all subjects. To provide a further measure of construct and discriminant validity, a 1-way ANOVA determined if any significant differences existed between the defined position groups (LM, QB/RB/LB, and R/DB) in A505 time and COD deficit for each leg. In the event of a significant F-ratio, post hoc analysis was conducted using least significant difference for pairwise comparisons to establish the extent of any significant findings (8,24). An alpha level of p ≤ 0.05 was chosen as the criterion for significance, and effect sizes were calculated for selected comparisons.


Table 1 displays the descriptive data for the A505 for both sessions. There were no significant differences between the 2 testing occasions for either the left- or right-leg turns. The ICCs for the left- and right-leg A505 were in excess of 0.70 (0.95 and 0.84, respectively). The measures of absolute reliability (TE and CV) are also shown in Table 1, along with the SWC0.2, SWC0.5, and ratings of usefulness. The CV was less than 5% for the A505 left and right. For the A505 left and right, the TE was either similar to, or exceeded, the SWC0.2. The TE was below the SWC0.5 for each A505 test.

Table 1.:
Descriptive data (mean ± SD; 95% confidence interval) for testing sessions 1 and 2, p value for differences between the sessions, and reliability statistics (intraclass correlation coefficient [ICC], typical error, coefficient of variation, smallest worthwhile change [0.2 × SD = SWC0.2; 0.5 × SD = SWC0.5], and ratings of usefulness) for the adapted 505 (A505) from the left and right legs in varsity high school football players (n = 10).

The correlation data for the comparisons between the A505 and 505 are shown in Table 2, and the descriptive data for these tests are shown in Figure 3. There was a near-perfect correlation between the left-leg A505 and 505, and a very large correlation between the right-leg A505 and 505. The A505 was performed significantly faster than the 505 for both the left-leg (p = 0.04; d = 0.40) and right-leg (p = 0.01; d = 0.67), by 3 and 4%, respectively.

Table 2.:
Correlations between the adapted 505 (A505) and traditional 505 in high school football players (n = 10).
Figure 3.:
Time for the adapted 505 (A505) and traditional 505 when performed with a turn off the left or right leg in varsity high school football players (n = 10). *Significant (p ≤ 0.05) differences between A505 and 505.

The pooled data from 25 subjects was used for the correlation analysis between the A505, COD deficit, and 40-yd sprint (Table 3). The left-leg A505 correlated with the 0 to 5-yd (large), 0 to 10-yd (very large), and 0 to 40-yd (very large) intervals. This was also the case for the right-leg A505, with all relationships being very large. In contrast, the COD deficit from the A505 performed with the left and right leg did not significantly correlate with any 40-yd sprint interval.

Table 3.:
Correlations between the adapted 505 (A505) time from the left and right legs and the change-of-direction (COD) deficit measured from the left- and right-leg A505, with time from the 0 to 5-yd, 0 to 10-yd, and 0 to 40-yd intervals from a 40-yd sprint (n = 25).

Table 4 displays the data for the position groups for the subject characteristics, 40-yd sprint, A505, and COD deficit. There were no significant differences in age between the LM, QB/RB/LB, and R/DB groups. However, the LM were significantly taller than the R/DB (d = 0.99; moderate). The LM were also significantly heavier than the QB/RB/LB (d = 2.66; very large) and R/DB (d = 3.90; very large), whereas the QB/RB/LB were heavier than the R/DB (d = 1.93; large). With regards to the speed tests, the R/DB group were significantly faster in the 0 to 5-yd (d = 1.01; moderate), 0 to 10-yd (d = 1.35; large), and 0 to 40-yd (d = 1.67; large) intervals when compared with LM, by 7, 9, and 12%, respectively. The R/DB were 8 and 12% faster than the LM in the left-leg (d = 1.24; large) and right-leg (d = 1.99; large) A505, respectively. The QB/RB/LB were 7% faster than the LM in the right-leg A505 (d = 1.24; large). The R/DB also had a 19% significantly lower COD deficit for the right leg when compared with the LM (d = 1.41; large).

Table 4.:
Descriptive data (mean ± SD; 95% confidence interval) for age, height, and body mass, 40-yd sprint times (0 to 5-yd, 0 to 10-yd, and 0 to 40-yd intervals), adapted 505 (A505) test times from the left and right legs, and the change-of-direction (COD) deficit measured from the left- and right-leg A505, for offensive and defensive linemen (LM), quarterbacks, running backs, and linebackers (QB/RB/LB), and receivers and defensive backs (R/DB).


This study provided a methodological report as to adapting the 505 COD speed test specific to American football. The 505 was selected as it is a popular COD assessment for athletes from a range of different sports (6,9–11,21,28,30,32,33,41,42,44) and can also be used to isolate COD ability from each leg (6,21,22,26–28,32,33). In addition to this, the 505 features a COD action that is performed by many different position players in football, including running backs, receivers, defensive ends, linebackers, and defensive backs (1,40). The new version of the 505, termed the A505, was shortened to use the Imperial system of measurement to make it more specific to football. The results of this study indicated that the new version of the test was reliable and valid when performed by varsity high school football players. There could be some limitations with interpreting small changes in COD performance with the A505, but this test could detect moderate performance changes in high school athletes. Although further research is needed in collegiate and professional football players, there are still notable applications from the results of this methodological report.

There were no significant differences between the A505 times for the left and right legs recorded in sessions 1 and 2 (Table 1). In addition to this, high ICCs and low CVs were recorded for the left-leg (ICC = 0.95; CV = 2.03%) and right-leg (ICC = 0.84; CV = 4.13%) A505 times. Previous research has shown that the traditional 505 is a reliable COD test when performed by college-aged male and female recreational team sport athletes (ICC = 0.77–0.88; CV = 1.92–2.80%) (43) and experienced rugby league players (ICC = 0.90; TE = 1.90%) (11). The results from this study indicate that when assessed in high school football players, the A505 is as well. Teenage athletes have been previously included to assess the reliability of COD speed tests, as Hachana et al. (13) documented that soccer players under 14 years of age could produce reliable results in a modified version of the Illinois agility test (ICC = 0.94; CV = 1.24%). This provides further support to the results from the current study. Furthermore, although the sample size for the reliability analysis was small (n = 10), Buchheit et al. (3) stated that when good relative reliability is found, changing the sample size may not greatly affect the results.

In addition to ensuring a test is reliable, it is also important to document whether the test is useful. Test usefulness refers to the practicability of the test to confidently monitor the progression of an athlete (4) and can be investigated by comparing the SWC relative to the TE of a test (16). With regards to small changes in performance, the left-leg A505 TE was similar to the SWC0.2, indicating that the usefulness was rated as “OK” (Table 1). For the right-leg A505, the rating was marginal (TE > SWC0.2). However, both the left- and right-leg A505 had good ratings for detecting moderate changes in performance (SWC0.5 > TE; Table 1). It is worth noting that the sample used for this study (teenage varsity football players from the same high school) was relatively homogeneous, and Lockie et al. (25) has suggested that the homogeneity of the group can contribute to a low SWC0.2. A larger, more heterogeneous sample of football players would likely result in a greater SD in the A505, and by extension, the SWC would increase. This could then increase the usefulness of the A505 to assess small changes to “good” (25). Future research could assess a greater range of football players (junior varsity and varsity high school, collegiate, and professional players) to ascertain whether this changes the usefulness of the A505. Nevertheless, football and strength and conditioning coaches can be confident that the A505 could detect moderate changes in COD performance after a training intervention.

The traditional 505 has long been viewed as a valid method for assessing COD performance (7,9,11,21,22,26–28,30,32,33,43,44), and thus, it could be assumed that the A505 would be as well. The correlation analysis indicated that this was the case, as there was 85% explained variance between the left-leg A505 and 505, and 76% explained variance between the right-leg A505 and 505 (Table 2). The reduced distances in the A505, although small, could have influenced the explained variance between the 2 tests. Indeed, the A505 was completed significantly quicker for both the left- and right-legs (Figure 3), with a small and moderate effect, respectively. Nonetheless, these results indicated that the A505 would likely measure similar qualities to the traditional 505.

This is also reflected in the correlations between the A505 and 40-yd sprint intervals (Table 3). The A505 times for both legs positively correlated with sprint times over the 0 to 5-yd, 0 to 10-yd, and 0 to 40-yd intervals, with the explained variance ranging from 58 to 77%. This is similar to research that has investigated the traditional 505 in athletes. For example, Lockie et al. (21) found that performance of 505 significantly correlated with speed over 0–17.68 m in cricketers (r = 0.68–0.83), whereas Nimphius et al. (30) documented significant relationships between the 505 performed from the dominant and nondominant legs with speed over 10–35.8 m in female softball players (r = 0.76–0.99). In professional rugby league players, Gabbett et al. (11) also found positive relationships between the 505 and linear speed (r = 0.52–0.58), in this instance over 5–20 m. However, these results also highlight issues presented by Nimphius et al. (32) and Sayers (36). Sayers (36) stated that COD tests that feature linear sprinting may influence the ability to assess COD performance. Thus, Nimphius et al. (31) had earlier proposed the COD deficit as an alternate measure of COD ability. The results of this study support the findings of Nimphius et al. (30,31), in that the COD deficit measured from both legs in the A505 did not correlate with linear speed as measured by the 40-yd sprint (Table 3). In line with the results from an analysis of cricketers by Nimphius et al. (30), these results would suggest that a different measure of COD ability is provided by the COD deficit when compared with A505 time. It would be worth investigating this further in football players, and whether the COD deficit measured from the A505 changes with specific training.

To further analyze the validity of the A505, a between-position comparison was also conducted. The LM were taller and heavier than the R/DB, and heavier than the QB/RB/LB (Table 4). Additionally, the QB/RB/LB were also heavier than the R/DB (Table 4). This is typical for players from these positions (12,19,20,24,37,40), so it can be assumed that the groups from this study were representative of typical football players from this age group. This is also reflected in the differences in 40-yd times. Receivers and defensive backs tend to be the fastest players (8,12,19), and the R/DB group in this study were significantly faster in all 40-yd intervals when compared with the LM and QB/RB/LB groups (Table 4). The R/DB were also faster than the LM for both the left- and right-leg A505, whereas the QB/RB/LB were faster than the LM in the right-leg A505. As a result, it can be inferred that the A505 does have discriminatory capabilities in the assessment COD ability in varsity high school football players. Additionally, the R/DB had a smaller right-leg COD deficit when compared with the LM, which provides some support to the suppositions of Nimphius et al. (30,31). Therefore, the A505 does have construct validity for the assessment of COD ability in high school football players. It could be surmised that this would extend to collegiate and professional football players, although this needs to be confirmed. In accordance with the findings from this study, forthcoming investigations should measure the A505 test, and the COD deficit derived from this test, in collegiate and professional football players to determine in applicability to these populations.

There are certain limitations in this A505 methodological report that should be acknowledged. The subjects in this study were varsity high school football players, and the results may not directly translate to players from college or professional football. Future research should investigate the A505 in these players. A larger sample of subjects, potentially providing a more heterogeneous sample of football players, could also be beneficial in future investigations as this may influence the data regarding the usefulness of the test (25). The A505 only provides an assessment of one 180° cut, and football features many directional changes through different planes of movement. The ability to move effectively in different movement planes can be directionally specific (29), so the coach must be aware of this before administering a test such as the A505. Nevertheless, this study does provide an initial indication of the potential value of this new modified test. The results suggest that the A505 is reliable, can detect moderate changes in COD performance, has construct validity, and can discriminate between different positional groups in football that should conceivably have different COD abilities.

Practical Applications

The A505 seems to provide a reliable and valid assessment of COD ability in varsity high school football players. The practical application of this is that strength and conditioning coaches could use this test to measure this COD ability in their athletes, as it can discriminate between players across different positions and potentially detect moderate changes in performance with training. Coaches could use the A505 as an alternate, and potentially more specific, COD assessment in lieu of the proagility shuttle or 3-cone drill. Consistent with previous research (30,31), the COD deficit derived from the A505 also seems to provide a different measure of COD ability, given that it does not correlate with linear speed, but can discriminate between high school football players from different positions.


We acknowledge our subjects for their contribution to the study. Thanks to Granada Hills Charter High School for helping facilitate this research and Dr. Shane Stecyk for assisting with data collection. This research project received no external financial assistance. None of the authors have any conflict of interest.


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performance testing; agility; profiling; change-of-direction deficit; high school athletes

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