Secondary Logo

Journal Logo

The Physical and Athletic Performance Characteristics of Division I Collegiate Female Soccer Players by Position

Lockie, Robert G.1; Moreno, Matthew R.1; Lazar, Adrina1; Orjalo, Ashley J.1; Giuliano, Dominic V.1; Risso, Fabrice G.1; Davis, DeShaun L.1; Crelling, Jeff B.2; Lockwood, John R.2; Jalilvand, Farzad1

The Journal of Strength & Conditioning Research: February 2018 - Volume 32 - Issue 2 - p 334–343
doi: 10.1519/JSC.0000000000001561
Original Research
Free

Lockie, RG, Moreno, MR, Lazar, A, Orjalo, AJ, Giuliano, DV, Risso, FG, Davis, DL, Crelling, JB, Lockwood, JR, and Jalilvand, F. The physical and athletic performance characteristics of Division I collegiate female soccer players by position. J Strength Cond Res 32(2): 334–343, 2018—Playing positions in soccer can exhibit different movement demands during a match, contributing to variations in physical and performance characteristics. National Collegiate Athletic Association (NCAA) soccer features different substitution rules when compared to FIFA-sanctioned matches, which could influence each players' characteristics. Therefore, this study determined the athletic performance characteristics of Division I female soccer players. Twenty-six players (3 goalkeepers; 8 defenders; 10 midfielders; 5 forwards) from the same squad completed assessments of: lower-body power (vertical and standing broad jump); linear (0–5, 0–10, 0–30 meter [m] sprint intervals) and change-of-direction (pro-agility shuttle; arrowhead change-of-direction speed test) speed; and soccer-specific fitness (Yo-Yo Intermittent Recovery Test [YYIRT] levels 1 and 2). Players were split into position groups, and a Kruskal–Wallis H test with post hoc pairwise analyses (p ≤ 0.05) calculated significant between-group differences. There were no differences in age, height, or body mass between the positions. Midfielders had a faster 0–5 m time compared with the defenders (p = 0.017) and the goalkeepers (p = 0.030). The defenders (p = 0.011) and midfielders (p = 0.013) covered a greater YYIRT2 distance compared with the goalkeepers. There were no other significant between-position differences. Overall, Division I collegiate female players from the same squad demonstrated similar characteristics as measured by soccer-specific performance tests, which could allow for flexibility in position assignments. However, a relatively homogenous squad could also indicate commonality in training prescription, particularly regarding acceleration and high-intensity running. Strength and conditioning coaches may have to consider the specific movement demands of individual positions when training these capacities.

1Department of Kinesiology, California State University, Northridge, California; and

2CSUN Sports Performance, California State University, Northridge, California

Address correspondence to Robert Lockie, robert.lockie@csun.edu.

Back to Top | Article Outline

Introduction

Soccer is a high-intensity, intermittent sport requiring both technical and physical capabilities (39) and is one of the most widely investigated team sports within the scientific literature (6,30,39). In most FIFA-sanctioned competitions, between 4 and 7 reserve players are allowed, with 3 substitutions permitted by each team per match. However, in collegiate soccer in the USA, there are less restrictions on the number of substitutions a coach may make during a match. Indeed, National Collegiate Athletic Association (NCAA) laws allow for substituted players to re-enter a match, with an unlimited number of interchanges (7). This difference in substitution rules for matches played under NCAA rules is notable because it could influence the athletic performance characteristics displayed by players. As a result, it is important for soccer and strength and conditioning coaches to know the characteristics of their players, so that they can understand what their capabilities should be on the pitch. Although there is a large volume of research that has been conducted on male soccer players, only recently research has been conducted on the physical characteristics of collegiate female players (42), however soccer has been considered one of the most popular sports for female athletes in the USA (25). Thus, greater analysis of the capacities of collegiate female soccer players is required, especially as it relates to the positions they play.

With regard to the different positions, elite male (3) and female (26) midfield players have been found to cover the greatest distances during a soccer match and also complete more high-intensity activities. Furthermore, previous research has shown elite midfielders to have greater aerobic capacity and repeated-sprint ability (RSA) as shown by better performance in assessments such as the Yo-Yo intermittent recovery test (YYIRT) (18,27,30). Elite female forwards tend to complete more sprints during a match when compared to defenders (26), and male forwards are generally faster in tests of linear speed when compared to midfielders and defenders (36). Elite male (27) and female (26) defenders may cover less distance and complete less high-intensity efforts during a match when compared to midfielders and attackers. Nonetheless, defenders still require high levels of physical fitness (30,42) and have been found to be taller and heavier when compared to midfielders and forwards (36,42). Goalkeepers are generally the tallest and heaviest players on the team (11,36) and also can demonstrate greater lower-body power as measured by maximal jump tests (4,11,36). However, because goalkeepers do not cover as much distance or complete as many high-intensity actions when compared to field position players (39), they also may be slower in sprint tests (11,12,36) and perform worse in maximal aerobic and RSA assessments (4,11,18). Whether these characteristics hold true for collegiate female soccer players is currently unknown. As result, further scientific analysis of this specific athletic population is required.

There has been some analysis of the physiological characteristics of collegiate female soccer players (42). Vescovi et al. (42) found that aerobic capacity, as measured by the multistage fitness test, was similar across their analyzed players. However, although RSA is one of the key performance indicators for differences between higher and lower-level soccer players (18,26) and soccer performance success (28), a test that places a greater emphasis on high-intensity running and RSA was not included in their analyses. Vescovi et al. (42) also found that the different positional groups exhibited similar characteristics although defenders tended to be slower in multidirectional speed tests, including a 40-yard sprint and pro-agility shuttle. However, in addition to RSA assessments such as the YYIRT, it would also be valuable to analyze collegiate female players with other, potentially more soccer-specific sprint acceleration and multidirectional speed tests, as opposed to the 40-yard sprint and pro-agility shuttle, which are assessments typically used for American football players (10,19). This would indicate whether collegiate female soccer players also exhibit differences between positions, or whether a strength and conditioning coach should prescribe more position-specific conditioning and speed training within their training programs.

Therefore, this study conducted an analysis of the physical and athletic performance capacities of Division I female soccer players. The first aim of the study was to document whether there were differences in the anthropometric measures, leg power, linear and change-of-direction (COD) speed, and soccer-specific endurance of the different positions (goalkeepers, defenders, midfielders, and forwards) of collegiate female soccer players from within one squad. The second aim was to provide a profile of the squad of collegiate female soccer players used in this study in soccer-specific tests. It was hypothesized that the study results would reflect previous research (4,11,12,18,27,30,36), in that there would be clear differences in the physical and athletic performance capacities of the different position groups.

Back to Top | Article Outline

Methods

Experimental Approach to the Problem

A cross-sectional analysis of a Division I collegiate women's soccer team was conducted using field tests specific to the sport. The testing sessions incorporated measurements of body size and numerous athletic performance tests, including: vertical and standing broad jump; 30-m sprint test; pro-agility shuttle and arrowhead change-of-direction (COD) speed test; and YYIRT1 and YYIRT2. Comparisons were drawn between the players when they were grouped according to their position (goalkeepers vs. defenders vs. midfielders vs. forwards).

Back to Top | Article Outline

Subjects

Twenty-six female soccer players (± SD age: 20.19 ± 1.20 years; height: 1.66 ± 0.07 m; body mass: 61.85 ± 7.36 kg) were recruited from the same Division I college soccer team. This sample size is similar to other research that has profiled characteristics of soccer players (13,26) and included all members from the squad that were currently participating in full training. G*Power software (v3.1.9.2; Universität Kiel, Kiel, Germany) was used to confirm that the sample size of 26 was sufficient for a between factors analysis with multiple groups and ensured the data could be interpreted with a moderate effect level of 0.75 and power level of 0.8 when significance was set at 0.05 (9). Players were defined into positions by the team's coaching staff (36). The positions were classified as: goalkeepers, defenders, midfielders, and forwards. For inclusion, subjects were required to be a member of the playing squad, over 18 years of age, and injury-free at the time of testing. The data used in this study arose as a condition of monitoring in which player activities were measured over the course of the preseason (44). As a result, California State University, Northridge approved the use of pre-existing data. The study still conformed to the recommendations of the Declaration of Helsinki, and all subjects received a clear explanation of the study, including the risks and benefits of participation. Each player had also completed the university-mandated physical examination and read and signed the university consent and medical forms for participation in collegiate athletics.

Back to Top | Article Outline

Procedures

Testing was incorporated within the squad's gym and field sessions across 4 weeks in the noncompetition months of February and March. Because of the timing of testing, subjects may not have reached their optimal physiological level by this point of preparation for the upcoming season. However, this was time made available by the team's head coach. All subjects were familiar with the tests performed in this study because they were consistently used by the team's strength and conditioning staff for general player monitoring. The jump assessments were completed before a gym (weights) session. This was completed within one session, which incorporated the vertical and standing broad jump. The running assessments were completed before field training (running) sessions following the team's usual warm-up. Five field testing sessions were completed, which incorporated the: (a) pro-agility shuttle; (b) 30-m sprint; (c) Arrowhead COD speed test; (d) YYIRT1; and (e) YYIRT2. Each testing session lasted for approximately 20–30 minutes in duration. The testing was conducted so as to fit into the schedule designed by the team's head coach and strength and conditioning staff, which can be seen in Figure 1. The schedule displays what training sessions were scheduled within a typical week. The running and weights sessions were conducted by the strength and conditioning staff; the field practice sessions were run by the head coach and support staff; and study hall were mandated study periods for the players. The jump testing session was conducted in the afternoon. Field testing was conducted in the morning before a running session. At least 48 hours was provided between each test session, which resulted in testing being spaced out over the 4-week period. In the gym-based sessions, subjects wore their own athletic trainers, and testing was conducted on a rubber-matted floor. Field testing was conducted on a grass outdoor soccer pitch, and subjects wore their own cleats.

Figure 1

Figure 1

Before data collection in the first gym testing session, the subject's age, height, and body mass were recorded. Height was measured barefoot using a standard stadiometer (Seca, Hamburg, Germany). Body mass was recorded using a single standard electronic digital scale (Tanita Corporation, Tokyo, Japan). Body mass index (BMI) was calculated via the formula: BMI (kg·m−2) = body mass·(height)−2. The gym-based session was preceded by a standardized warm-up designed by the team's coaching staff, consisting of 10 minutes of jogging, and 10 minutes of dynamic stretching of the lower limbs. Subjects also completed a standardized warm-up before each field session that was designed by the team's coaching staff, which consisted of 10 minutes of jogging, 10 minutes of dynamic stretching of the lower limbs, and linear and lateral runs over 20–30 m that progressively increased in intensity. Examples of the dynamic stretches included walking quadriceps, hamstrings, gluteal, hip flexor, and groin stretches, and other dynamic movements such as running technique drills. This dynamic warm-up followed procedures conducted in previous research that investigated maximal running tests (19–21,34); thus, the subjects were appropriately prepared for the assessment tasks that were to follow. Subjects completed testing in the order stated in this section and rotated alphabetically by surname for each test (19), except for the YYIRT1 and YYIRT2, which was completed as a group. This ensured sufficient recovery periods (i.e., greater than 3 minutes) between efforts. A standard metric tape measure was used to determine all distances.

Back to Top | Article Outline

Vertical Jump

The vertical jump was used to indirectly measure leg power in the vertical plane (19,38,40), and a jump mat (Just Jump; Probotics Inc., Huntsville) measured performance (29). Testing vertical jump using the Just Jump system has been found to have high reliability in active females (intraclass correlation coefficients [ICC] = 0.90–0.93; coefficient of variation [CV] = 4.4–5.2%) (29). The subject initially stood on the jump mat keeping their heels on the floor, before completing a countermovement and jumping as high as possible. No preparatory step was used, and no restrictions were placed on the knee angle attained during the eccentric phase of the jump. Subjects were also free to swing their arms during jump. This is more practical from a sports perspective because the arms would generally always be used when jumping during a match to add angular momentum to the jump. Subjects were instructed to maintain straight legs during the flight, before landing on both feet with flexion of the hips, knees, and ankles. Within the software for the mat, jump height was calculated from flight time via the following equation: (29). Each subject completed 3 trials, and the best trial was used for analysis.

Back to Top | Article Outline

Standing Broad Jump

The standing broad jump was used to measure leg power in the horizontal plane. This test is reliable (ICC = 0.95; CV = 2.4%) (24) and was performed according to established methods (19,21,24). The subject placed the toes of both feet on the back of the starting line, and with a simultaneous arm swing and crouch, then jumped forward as far forward as possible, ensuring a 2-footed landing. Subjects had to “stick” the landing for the trial to be counted. If not, the trial was disregarded and another completed. No restrictions were placed on body angles attained during the preparatory phase of the jump or the degree of arm swing used. Distance was measured using a standard tape measure, which was the perpendicular line from the front of the start line to the posterior surface of the back heel at the landing. Three trials were completed, and the best trial was used.

Back to Top | Article Outline

Pro-Agility Shuttle

The pro-agility shuttle course and running path are shown in Figure 2, and the test was completed as per established methods (19,37,40,42). This test has been shown to be reliable in female team sport athletes (ICC = 0.82; CV = 1.81%) (37). One timing gate (TC Timing System; Brower Timing, UT, USA) was used for this test, set at a height of approximately 1 m (19). Subjects straddled the middle line in a 3-point stance in between the timing gate. As per the timing system set-up, a TC motion start was used where once the subject was stable in their 3-point stance they could begin the test. Timing was initiated by the first movement of the hand. To start the test, the subject turned and ran 4.57 m (5 yards) to one side and touched the line with one hand. The subject then turned and ran 9.14 m (10 yards) to the other side and touched the other line, before turning and finishing by running back through the start/finish line. Researchers were positioned at either end of the pro-agility shuttle to ensure subjects touched the line. If they did not, the trial was disregarded and reattempted. The timing system started when the subject left the light beam and stopped recording when subjects returned through the gate for the last time. Two trials were completed—one with movement initiation to the left and the other with movement initiation to the right (19). The fastest time from the 2 trials was used. Time for was recorded to the nearest 0.001 seconds.

Figure 2

Figure 2

Back to Top | Article Outline

30-m Sprint

30-m sprint time was recorded by a timing lights system (Fusion Sports, Coopers Plains, Australia). Sprint testing using this equipment has presented high levels of reliability (ICC = 0.76–0.96; CV = 1.9–5.1%) (20). Gates were positioned at 0 m, 5 m, 10 m, and 30 m to measure the 0–5, 0–10, and 0–30 m intervals. Sprints over 5 (36), 10 (36), and 30 m (22,41) have been used in the assessment of soccer players. The 0–5 and 0–10 m intervals measured acceleration (21); the 0–30 m time afforded a measure of maximum velocity specific to soccer players (22,41). Gate height was set at 1.2 m, and subjects began the sprint from a standing start 50 cm behind the start line to trigger the first gate (21). Once ready, subjects were allowed to start in their own time and were instructed to run maximally once they initiated their sprint (19–21). Subjects completed 3 trials, and the fastest trial was used for analysis (21). If the subject rocked backwards or forwards before starting, the trial was disregarded and repeated. Time for each interval was recorded to the nearest 0.001 seconds.

Back to Top | Article Outline

Arrowhead COD Speed Test

The Arrowhead COD speed test is an assessment designed specifically for soccer (14) and thus was included in testing. This test has been found to be reliable (ICC = 0.92–0.93; CV = 0.89–1.01%) when used for collegiate women's soccer players (14), so its inclusion in this study provided exploration into its validity. The procedures for this test were completed per established methods (14). The dimensions, marker positions, and running path for this test are shown in Figure 3, with one timing gate (Fusion Sports, Coopers Plains, Australia) positioned at the start line. Subjects used a similar start position as per the 30-m sprint (i.e., 50 cm behind the start line). When ready, subjects sprinted to the middle marker, turned to the left or right (depending on the trial) to sprint around the side marker, sprinted around the top marker, before sprinting back through the start line and timing gate to finish. Subjects were required to step around and not over the markers. If they did not do this, the trial was stopped and reattempted. Six trials in total were completed; 3 with movement initiation to the left, and 3 with movement initiation to the right (14). The order of these trials was randomized among the subjects. As for the other speed tests, time was recorded to the nearest 0.001 seconds.

Figure 3

Figure 3

Back to Top | Article Outline

Yo-Yo Intermittent Recovery Test Levels 1 and 2

YYIRT1 and YYIRT2 were both used in this study and were conducted according to established methods (16–18). Both versions of the YYIRT have been found to be reliable (ICC = 0.78–0.93; CV = 7.1–7.3%) (8), and consist of repeated 2 × 20 m runs at a progressively increased speed. Each test was controlled by audio beeps from an iPad handheld device (Apple Inc., Cupertino, CA, USA) connected via Bluetooth to a potable speaker (QFX, Inc., Vernon, CA, USA) located immediately adjacent to 20-m long running lanes indicated by markers. Between each running bout, the participants had a 10-second rest period in which they were required to move to a cone 5 m away before returning to the start line. As stated in previous research (16,17), the YYIRT1 has 4 running bouts at 10–13 km·h−1 and another 7 runs at 13.5–14 km·h−1. Following this, the YYIRT1 continues with stepwise 0.5 km·h−1 speed increments after every 8 running bouts until exhaustion.

As documented by Karakoç et al. (16), the YYIRT2 test started at a speed of 13 km·h−1, which then increased by 2 km·h−1 after the first stage and 1 km·h−1 after the second stage. The YYIRT2 then continued with stepwise 0.5 km·h−1 speed increments after every stage until exhaustion. As stated, each test was terminated for a subject when they failed to reach the finishing line in time on 2 successive occasions or by volitional exhaustion. This was monitored by the researchers, and the performance value was recorded as the last completed running bout. The YYIRT1 and YYIRT2 were performed in separate sessions, and all players performed the test within the session. Strong verbal encouragement was provided by the researchers and coaching staff throughout the YYIRT1 and YYIRT2.

Back to Top | Article Outline

Statistical Analyses

All statistical analyses were computed using the Statistics Package for Social Sciences (version 22.0; IBM Corporation, NY, USA). Because of the small sample size for each group (n = 3–10), nonparametric statistics were used (5,43). Players were placed in groups corresponding to their position; goalkeepers, defenders, midfielders, and forwards. In accordance with these groups, a Kruskal–Wallis H test, which is the nonparametric equivalent of a 1-way analysis of variance (5), computed any significant differences between the anthropometrical measurements, jump assessments, linear and COD speed tests, YYIRT1, and YYIRT2. Significance was set at p ≤ 0.05. As nonparametric tests were used, data were presented as medians and interquartile ranges (1,34).

Back to Top | Article Outline

Results

There were no significant differences in the age, height, body mass, or BMI between the groups, which can be seen in Table 1. The performance test data are shown in Table 2. There were no significant between-group differences in the vertical and standing broad jump. With regard to linear speed, midfielders were significantly faster over the 0–5 m interval when compared to the defenders (p = 0.017) and the goalkeepers (p = 0.030). There were no other significant between-position differences in the 0–5 m interval, and none for 0–10 and 0–30 m intervals. There were no significant differences between the groups in the pro-agility shuttle or the Arrowhead COD test. There were no significant between-position differences in the YYIRT1. In the YYIRT2, the defenders covered a significantly (p = 0.011) greater distance when compared to the goalkeepers. The midfielders also covered a significantly (p = 0.013) greater YYIRT2 distance when compared to the goalkeepers.

Table 1

Table 1

Table 2

Table 2

Back to Top | Article Outline

Discussion

The results indicated that there were very few significant between-position differences in the athletic performance characteristics of Division I collegiate female soccer players. This was counter to the study hypothesis and to research conducted with experienced soccer players (4,11,12,18,27,30,36) although the findings were in line with a previous investigation of collegiate female soccer players (42). However, the current study also used certain soccer-specific assessments (0–5, 0–10, and 0–30 sprint intervals; Arrowhead COD speed test; YYIRT1 and YYIRT2) that have not been investigated in great detail for female soccer players from NCAA competition. This is notable, given the differences in substitution rules and how this may impact the physiology of players (7). The results from this study could prove useful for women's soccer and strength and conditioning coaches in designing training programs for their players.

Field players in elite soccer teams have been characterized by relative heterogeneity in body size (13,30). This was not the case in the current study, where there were no significant differences between the position groups. In addition to this, although previous research has found elite male goalkeepers to be taller and heavier when compared to field players (36), the stature and body mass of the female goalkeepers from the current study was not significantly different to that of the field players. A soccer squad that is relatively homogenous in physical stature could allow for greater flexibility in tactics and formation during a match (13), given that all position groups have a relatively similar stature and size. The results could be reflective of the small sample size of this study, where there were only 3 goalkeepers within that position group. However, what these results may also be reflective of is that some schools may be limited in the players that they can recruit. Traditionally stronger schools in athletics can recruit players that are physically different from their counterparts (10). In soccer, this may mean that taller goalkeepers may be more inclined to go to schools that have been historically strong in soccer. Future research in female collegiate soccer should follow the work of Ghigiarelli (10) for American football, with the analysis of the characteristics of highly recruited players from high school within their positional groups.

Maximal jump performance has been shown to delineate between elite and nonelite female soccer players (35). However, there were no significant differences between the positions in the vertical or standing broad jump. The players from this study appeared to have a relatively equivalent vertical jump (median = 0.51 m) when compared to other collegiate female soccer players, who had a mean vertical jump of approximately 0.40 m (38,40). Vescovi and McGuigan (40) used a protocol that eliminated arm swing, whereas Stieg et al. (38) used a Vertec device to measure jump performance, which may indicate why there were slight differences to the vertical jump measurements from the current research. Nonetheless, when challenging for possession if the ball is in the air, a good vertical jump is necessary for all players (i.e., goalkeepers, defenders, midfielders, and forwards) (12).

Horizontal jump performance has been linked to faster multidirectional speed in young athletes (19), highlighting its application for soccer as well. As for the vertical jump, there were no significant differences between the playing positions in absolute or relative horizontal jump performance. In addition to this, the median for standing long jump from this study (1.94 m) was superior to that of Division III soccer players (1.85 ± 0.15 m) (15). Collectively, the vertical and standing broad jump results indicate that Division I female soccer players can demonstrate leg power that is congruent with collegiate athletes, and this can occur across a squad and multiple playing positions.

Linear speed is an important factor for all soccer players because in game situations, a faster running speed will allow players to reach the ball before their opponents and to position themselves for involvement in play (31). The results from this study showed that midfielders were significantly faster over the 0–5 m interval when compared to the defenders and goalkeepers. It is important to consider the requirements of each position to contextualize these results. Midfielders from different levels of play have been found to complete a high number of sprints during a match (39), which highlights their need for the ability to accelerate. Players in defensive roles often need to reposition themselves to defend the ball and oncoming attacking players, and this means they could spend a greater percentage of time running backwards (3). This may have contributed to defenders being relatively slower over 5 m, as many of their match sprints may be initiated from a different body position to that from a traditional sprint test. Goalkeepers will also tend to complete the least amount of sprints during a match (39), and previous research has documented that goalkeepers are often slower in sprint tests over various distances when compared to the field position players (11,12,36). It should also be acknowledged, however, that goalkeepers are a completely different position when compared to field players which is reflected in different training programs that tend to focus on jumping more so than running (32). Nevertheless, the results from this study demonstrated that within the analyzed collegiate female soccer squad, the midfielders were faster over a sprint acceleration distance of 5 m when compared to the defenders and goalkeepers.

Despite the findings for the 0–5 m interval, there were no significant differences between the position groups in the 0–10 and 0–30 m intervals. Interestingly, in high-level male soccer players, previous research has shown that forwards and attacking players tend to complete longer distance sprints (i.e., up to 30 m) during a match (27) and were faster than other positional groups over 20 m (36). However, this was not reflected in the data from this study on collegiate female players. The current results could be reflective of the homogeneity of the analyzed squad (13,30), which could be a consequence of the training practices adopted by the team's strength and conditioning staff. The size of the sample, and the fact that only one collegiate team was analyzed, could also have influenced the results. Nevertheless, all soccer players should attempt to maximize their speed. A key component of talent identification for soccer players is the ability to achieve a high sprint velocity (11), and starting players tend to be faster than nonstarters (23). When considering the overall data, subjects from this study were faster over 5 and 10 m when compared to high-level American female soccer players (41), similar to recreational female team sport athletes (soccer, basketball, netball, and softball) over 5 m (21), and slower over the 0–10 and 0–30 m intervals when compared to elite Norwegian female soccer players (12). Improving linear speed across a collegiate female soccer squad should be an emphasis for coaches because faster sprinting speed could be a physical characteristic that delineates a team from their opponents. Furthermore, notwithstanding the influence of fatigue (6,26,27) and the ability to make correct decisions and display appropriate technical skills (34), similarities in linear speed across a squad could afford a coach flexibility to make tactical substitutions during a match knowing that there should not be a drop-off in the maximal speed displayed by players during a match.

During a high-level soccer match, players can complete over 700 turns and swerves at different angles (3), which places great importance on COD speed (11). In elite Belgian male soccer players, forwards were faster in a shuttle-run COD speed test (5 × 10-m sprints) when compared to all other position groups (4). There were, however, no significant differences between positions in the pro-agility shuttle in this study. Even though the pro-agility shuttle has been used to assess female soccer players (40,42), it is more commonly perceived as a test that is specific for American football players (10,19). Indeed, the actions of the test (starting from a 3-point stance and maximally sprinting from side-to-side) are not typical for soccer. In contrast, the Arrowhead COD test was designed and stated to be specific to soccer because it incorporates linear sprint acceleration efforts in combination with direction changes that occur after 5–10 m sprint efforts (14). Despite its design, there were no significant differences in Arrowhead COD test performance between the position groups. The results seem to suggest that Division I female soccer players from the same team can demonstrate similar COD speed capacities. A homogenous squad, however, could also indicate that relatively limited position-specific COD speed training being prescribed by the strength and conditioning staff. A further, perhaps more important, consideration is that certain COD assessments, including the pro-agility shuttle and Arrowhead test, still incorporate a large degree of linear sprinting. Sayers (33) asserts that this may limit how much these tests actually indicate COD ability. Using a test that limits the linear sprint distance involved, or measuring the time or velocity immediately following a COD within a test, has been suggested as a better method for assessing COD ability (33). Future research on collegiate soccer players should consider using this approach, potentially with an assessment such as the 505 that limits sprint distances to less than 10 m (21,33) and can isolate direction changes from each leg (21).

Krustrup et al. (17) stated that the YYIRT1 heavily taxes both the aerobic and anaerobic capacities of test subjects and is closely related to match performance in soccer. Interestingly, there were no significant between-position differences in YYIRT1 performance in this study. Collectively, this squad exhibited superior aerobic and anaerobic capacity as it pertains to the YYIRT1. To provide a context for the performance of the squad from the current study, Bangsbo et al. (2) described data where elite female soccer players covered a mean distance of 1,600 m. Mujika et al. (28) suggested that a YYIRT1 performance of approximately 1,200 m should be the standard for first division female soccer players. The overall median YYIRT1 score obtained from the players in this research (1,700 m) suggests that players from this squad would be commensurate with elite female soccer players. Furthermore, given the nature of NCAA competition where there are more relaxed substitution rules (7), a soccer squad that is relatively homogenous in aerobic and anaerobic capacities could allow for greater flexibility in tactics and formations during a match (13). Notwithstanding differences in skill levels, soccer coaches could interchange players into different positions with the expectation that high work-rates should be achieved if they are all appropriately conditioned.

Despite the value of the YYIRT1 (2,17,28), Karakoç et al. (16) suggested that the YYIRT2 is the most valid test for assessing the high-intensity effort requirements of soccer match-play. Despite this, there has been no research documenting YYIRT2 performance in collegiate female soccer players. From the results of this study, both the defenders and midfielders covered a significantly greater YYIRT2 distance when compared to the goalkeepers. These differences would be expected given the differences in positional demands for defenders and midfielders when compared to goalkeepers (39), the different training demands for goalkeepers (32), and the importance of high-intensity running for the field position groups (3,18,26,27,30,42). Indeed, there were no significant differences in YYIRT2 performance between the defenders, midfielders, and forwards. Given the importance of high-intensity running and RSA for soccer (26,39), and that the YYIRT2 is a valid indicator of this (16), these data can be interpreted in several ways. Withers et al. (45) illustrated similarities in RSA work-to-rest ratios for different positions during match-play. As has been stated, similarities across positions could allow the coach to freely substitute players with the knowledge that each has similar high-intensity running and RSA capacities (13). However, there is currently no data that documents the YYIRT2 performance of elite and subelite female soccer players. The issue with this is that even though a squad may demonstrate similar high-intensity running capacities as measured by the YYIRT2, it would not be beneficial if these capacities are lower than their opponents. Future research should assess elite female soccer players in the YYIRT2 because this would better contextualize YYIRT2 data as it relates to Division I collegiate female soccer players.

There are certain study limitations that should be acknowledged. The sample for this study was relatively small (n = 26) although it was similar in size to other soccer research (13,26) and demonstrated appropriate power (9). There was also a lack heterogeneity as only one collegiate squad was tested. It would be of benefit for future research to measure the athletic performance characteristics of female soccer players from a range of programs and across the different levels of play (i.e., Divisions I, II, and II). As the sample was drawn from the one Division I school, this also meant that the distribution of subjects between the position groups was not equal, and this may have influenced the lack of significant differences found between position groups. Indeed, the low number of goalkeepers analyzed (n = 3) could have affected the lack of significant differences found when comparing the different position groups in the physical and athletic performance tests. Nonetheless, the size of the squad analyzed is indicative of collegiate female soccer teams, and even with unequal distributions between the position groups, the interindividual variation can still be informative (13).

The results showed few differences in physical or physiological characteristics between position groups in a Division I female soccer squad. There were some differences found in sprint acceleration over 5 m (midfielders were faster than goalkeepers and defenders) and YYIRT2 (defenders and midfielders were faster than goalkeepers) performance. Nonetheless, as there are differences in the substitution rules for NCAA soccer, similarities in player characteristics could allow for greater flexibility in tactical substitutions for the coach during a match. The results from this research have implications for the training practices of strength and conditioning coaches for collegiate women's soccer.

Back to Top | Article Outline

Practical Applications

There are several practical applications for the strength and conditioning coach that can be drawn from this study. The players from the Division I collegiate female soccer squad analyzed in this study demonstrated similar physical and athletic performance characteristics across different positions. This could be influenced by the conditioning practices of the strength and conditioning staff of the squad tested and may also be a by-product of the more flexible substitution requirements in NCAA-sanctioned matches. Similarities in physical and athletic performance characteristics across a playing squad could allow a coach the freedom to make more tactical substitutions during a NCAA match. However, the importance of speed over 5 m for collegiate female soccer players was highlighted because midfielders from the analyzed squad were faster than both defenders and goalkeepers. Strength and conditioning coaches may have to ensure their players can effectively accelerate over short distances because this could directly affect the players' ability to become involved during match-play. Additionally, the importance of high-intensity running was highlighted because both midfielders and defenders from this collegiate squad were superior to the goalkeepers in the YYIRT2. Strength and conditioning coaches of collegiate female players may need to be cognizant of the high-intensity running and RSA demands for soccer and ensure this is reflected in training. Indeed, for those athletes who play the positions that complete more high-intensity running during a match (i.e., midfielders and defenders), they may need to complete more position-specific high-intensity running training to ensure they can maintain a high work rate within a soccer game.

Back to Top | Article Outline

Acknowledgments

This research project received no external financial assistance. None of the authors have any conflict of interest. The authors would like to acknowledge the subjects for their contribution to the study. Thanks to coach Keith West for his assistance and support of this research and Sarah Mock for assisting with data collection.

Back to Top | Article Outline

References

1. Altman DG, Gore SM, Gardner MJ, Pocock SJ. Statistical guidelines for contributors to medical journals. Br Med J (Clin Res Ed) 286: 1489–1493, 1983.
2. Bangsbo J, Iaia FM, Krustrup P. The Yo-Yo intermittent recovery test. Sports Med 38: 37–51, 2008.
3. Bloomfield J, Polman R, O'Donoghue P. Physical demands of different positions in FA Premier League soccer. J Sports Sci Med 6: 63–70, 2007.
4. Boone J, Vaeyens R, Steyaert A, Vanden Bossche L, Bourgois J. Physical fitness of elite Belgian soccer players by player position. J Strength Cond Res 26: 2051–2057, 2012.
5. Cronk BC. How to Use SPSS: A Step-by-Step Guide to Analysis and Interpretation. (8th ed.). Glendale, CA: Pyrczak Publishing, 2014.
6. Datson N, Hulton A, Andersson H, Lewis T, Weston M, Drust B, Gregson W. Applied physiology of female soccer: An update. Sports Med 44: 1225–1240, 2014.
7. Dennison D. 2012 Soccer Guide: A Comparative Study of Rules and Laws. Indianapolis, IN: NCAA, 2012. pp. 1–16.
8. Fanchini M, Castagna C, Coutts AJ, Schena F, McCall A, Impellizzeri FM. Are the Yo-Yo intermittent recovery test levels 1 and 2 both useful? Reliability, responsiveness and interchangeability in young soccer players. J Sports Sci 32: 1950–1957, 2014.
9. Faul F, Erdfelder E, Lang AG, Buchner A. G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behav Res Methods 39: 175–191, 2007.
10. Ghigiarelli JJ. Combine performance descriptors and predictors of recruit ranking for the top high school football recruits from 2001 to 2009: Differences between position groups. J Strength Cond Res 25: 1193–1203, 2011.
11. Gil SM, Zabala-Lili J, Bidaurrazaga-Letona I, Aduna B, Lekue JA, Santos-Concejero J, Granados C. Talent identification and selection process of outfield players and goalkeepers in a professional soccer club. J Sports Sci 32: 1931–1939, 2014.
12. Haugen TA, Tonnessen E, Seiler S. Speed and countermovement-jump characteristics of elite female soccer players, 1995–2010. Int J Sports Physiol Perform 7: 340–349, 2012.
13. Hencken C, White C. Anthropometric assessment of premiership soccer players in relation to playing position. Eur J Sport Sci 6: 205–211, 2006.
14. Jalivand F, Mock SA, Stecyk SD, Crelling JB, Lockwood JR, Lockie RG. The Arrowhead Change-of-Direction Speed Test: Reliability and Relationships to Other Multidirectional Speed Assessments: Presented at 38th National Strength and Conditioning Association National Conference and Exhibition, Orlando, Florida, USA, July 10, 2015.
15. Jones MT, Matthews TD, Murray M, Van Raalte J, Jensen BE. Psychological correlates of performance in female athletes during a 12-week off-season strength and conditioning program. J Strength Cond Res 24: 619–628, 2010.
16. Karakoç B, Akalan C, Alemdaroğlu U, Arslan E. The relationship between the Yo-Yo tests, anaerobic performance and aerobic performance in young soccer players. J Hum Kinet 35: 81–88, 2012.
17. Krustrup P, Mohr M, Amstrup T, Rysgaard T, Johansen J, Steensberg A, Pedersen PK, Bangsbo J. The Yo-Yo intermittent recovery test: Physiological response, reliability, and validity. Med Sci Sports Exerc 35: 697–705, 2003.
18. Krustrup P, Mohr M, Nybo L, Jensen JM, Nielsen JJ, Bangsbo J. The Yo-Yo IR2 test: Physiological response, reliability, and application to elite soccer. Med Sci Sports Exerc 38: 1666–1673, 2006.
19. Lockie RG, Jeffriess MD, Schultz AB, Callaghan SJ. Relationship between absolute and relative power with linear and change-of-direction speed in junior American football players from Australia. J Aust Strength Cond 20: 4–12, 2012.
20. Lockie RG, Schultz AB, Callaghan SJ, Jeffriess MD, Berry SP. Reliability and validity of a new test of change-of-direction speed for field-based sports: The Change-of-Direction and Acceleration Test (CODAT). J Sports Sci Med 12: 88–96, 2013.
21. Lockie RG, Schultz AB, Callaghan SJ, Jordan CA, Luczo TM, Jeffriess MD. A preliminary investigation into the relationship between functional movement screen scores and athletic physical performance in female team sport athletes. Biol Sport 32: 41–51, 2015.
22. Magal M, Smith RT, Dyer JJ, Hoffman JR. Seasonal variation in physical performance-related variables in male NCAA Division III soccer players. J Strength Cond Res 23: 2555–2559, 2009.
23. Manson SA, Brughelli M, Harris NK. Physiological characteristics of international female soccer players. J Strength Cond Res 28: 308–318, 2014.
24. Markovic G, Dizdar D, Jukic I, Cardinale M. Reliability and factorial validity of squat and countermovement jump tests. J Strength Cond Res 18: 551–555, 2004.
25. Markovits AS, Hellerman SL. Women's soccer in the United States: Yet another American “exceptionalism”. Soccer Soc 4: 14–29, 2003.
26. Mohr M, Krustrup P, Andersson H, Kirkendal D, Bangsbo J. Match activities of elite women soccer players at different performance levels. J Strength Cond Res 22: 341–349, 2008.
27. Mohr M, Krustrup P, Bangsbo J. Match performance of high-standard soccer players with special reference to development of fatigue. J Sports Sci 21: 519–528, 2003.
28. Mujika I, Santisteban J, Impellizzeri FM, Castagna C. Fitness determinants of success in men's and women's football. J Sports Sci 27: 107–114, 2009.
29. Nuzzo JL, Anning JH, Scharfenberg JM. The reliability of three devices used for measuring vertical jump height. J Strength Cond Res 25: 2580–2590, 2011.
30. Reilly T, Bangsbo J, Franks A. Anthropometric and physiological predispositions for elite soccer. J Sports Sci 18: 669–683, 2000.
31. Rienzi E, Drust B, Reilly T, Carter JEL, Martin A. Investigation of anthropometric and work-rate profiles of elite South American international soccer players. J Sports Med Phys Fitness 40: 162–169, 2000.
32. Ruas CV, Minozzo F, Pinto MD, Brown LE, Pinto RS. Lower-extremity strength ratios of professional soccer players according to field position. J Strength Cond Res 29: 1220–1226, 2015.
33. Sayers MGL. The influence of test distance on change of direction speed test results. J Strength Cond Res 29: 2412–2416, 2015.
34. Scott BR, Lockie RG, Davies SJG, Clark AC, Lynch DM, Janse de Jonge XAK. The physical demands of professional soccer players during in-season field-based training and match-play. J Aust Strength Cond 22: 7–15, 2014.
35. Sedano S, Vaeyens R, Philippaerts RM, Redondo JC, Cuadrado G. Anthropometric and anaerobic fitness profile of elite and non-elite female soccer players. J Sports Med Phys Fitness 49: 387–394, 2009.
36. Sporis G, Jukic I, Ostojic SM, Milanovic D. Fitness profiling in soccer: Physical and physiologic characteristics of elite players. J Strength Cond Res 23: 1947–1953, 2009.
37. Stewart PF, Turner AN, Miller SC. Reliability, factorial validity, and interrelationships of five commonly used change of direction speed tests. Scand J Med Sci Sports 24: 500–506, 2014.
38. Stieg JL, Faulkinbury KJ, Tran TT, Brown LE, Coburn JW, Judelson DA. Acute effects of depth jump volume on vertical jump performance in collegiate women soccer players. Kines 43: 25–30, 2011.
39. Stolen T, Chamari K, Castagna C, Wisloff U. Physiology of soccer: An update. Sports Med 35: 501–536, 2005.
40. Vescovi JD. Sprint speed characteristics of high-level American female soccer players: Female Athletes in Motion (FAiM) study. J Sci Med Sport 15: 474–478, 2012.
41. Vescovi JD, Brown TD, Murray TM. Positional characteristics of physical performance in division I college female soccer players. J Sports Med Phys Fitness 46: 221–226, 2006.
42. Vescovi JD, McGuigan MR. Relationships between sprinting, agility, and jump ability in female athletes. J Sports Sci 26: 97–107, 2008.
43. Vickers AJ. Parametric versus non-parametric statistics in the analysis of randomized trials with non-normally distributed data. BMC Med Res Methodol 5: 1–12, 2005.
44. Winter EM, Maughan RJ. Requirements for ethics approvals. J Sports Sci 27: 985, 2009.
45. Withers RT, Maricic Z, Wasilewski S, Kelly L. Match analyses of Australian professional soccer players. J Hum Mov Stud 8: 159–176, 1982.
Keywords:

association football; women; sprint acceleration; high-intensity running; Yo-Yo intermittent recovery test level 2

Copyright © 2018 by the National Strength & Conditioning Association.