Positional Differences and Workload Requirements of a 3-5-2 Formation in Women’s Soccer

Authors: Asher L. Flynn1, Joanne Spalding2, and Sellena Dixon3

1Department of Sport & Exercise Science, Lincoln Memorial University, Harrogate, TN, USA

2Department of Health Sciences, Georgia College & State University, Milledgeville, GA, USA

3Athletics Department, Lincoln Memorial University, Harrogate, TN, USA

 

Corresponding Author:

Asher L. Flynn, PhD, CSCS

6965 Cumberland Gap Parkway

[email protected]

423.869.6828

Asher L Flynn, PhD, CSCS is an Assistant Professor of Sport and Exercise Science at Lincoln Memorial University, TN. His research interests focus on fatigue and athlete monitoring in colligate athletes, and aspects of women’s soccer performance.

Joanne Spalding, PhD, is an Assistant Professor in Exercise Science at Georgia College & State University, GA. Her research interests include athlete monitoring and long term athlete development in female athletes.

Sellena Dixon, BS, is the graduate assistant for the women’s soccer team at Lincoln Memorial University, TN.

ABSTRACT 

The purpose of this research was to investigated the match demands of 24 female soccer players over one season (15 conference matches) playing in a 3-5-2 formation to determine the match demands and work rates of each position. In order to determine formation specific workload, positions were grouped as center-backs (CB), wingbacks (WB), midfielders (MF), and forwards (FW). Velocity bands used to compare distances and work rates were total distance (TD), 2-3 m/s, 3-4 m/s, 4-5 m/s, 5-6 m/s, and >6 m/s. Results revealed that MF covered significantly more total distance (TD; 10743 ±1520 m) and distance between 2-3 m/s (3444 ± 423 m) than all other positions (CB TD: 8549 ± 1106 m, 2-3: 2497 ± 276 m; WB TD: 8860 ± 1216 m, 2-3: 2324 ± 344 m; FW TD: 8069 ± 1286 m) and greater distance between 3-4 m/s (2515 ± 382m) compared to CB (1574 ± 214 m) and FW (1270 ± 281 m), but not WB (1814 ± 258 m). There were no significant differences between any of the higher velocity bands (>4 m/s). These results can be useful for the coaching staff as descriptive data for the expected distances covered and work rates of Division 2 Women’s soccer teams playing a 3-5-2 formation. These data can be used to determine practice plans in season and for off-season training plans, to prepare athletes for reporting for preseason in appropriate condition.

KEYWORDS: GPS, Sport Science, Athlete Monitoring, Fitness, NCAA

Abbreviations: CB: Center-back, WB: Wingback, MF: Midfield, FW: Forward, GPS: Global Positioning System, MD: Match Day, vVO2max: Velocity at VO2max

INTRODUCTION 

There is a growing interest in the physical demands of women’s soccer, but the majority of research has focused on the top levels of competition (International and Professional; 23). Although this information is important, it is likely to have limited use for lower levels of competition. It has been reported that “top class” females perform more high intensity running compared to “high-level” females (16, 17, 19). Currently, there is a lack of research investigating match demands at other levels of women’s soccer, especially at lower levels of collegiate soccer in the USA.

The majority of the literature investigating the demands of lower levels of women’s soccer has focused on the match demands of NCAA Division I (2, 5, 12, 20, 21), two articles focused on NCAA Division II athletes (9, 11), and one article focused on NCAA DIII (22), with no studies investigating the match demands of women’s NAIA soccer. Gentles et al (2018) observed that NCAA DII female players covered approximately 5480 m in 45 minutes of match play, while NCAA Division I players covered between 9486m and 9930 m in 90 minutes (20, 22). With little evidence exploring the activity profiles of the lower divisions of collegiate women’s soccer, further investigation is needed.

Many of the studies to date, at any level, have been conducted using only a few matches (3, 17), which, due to the high standard deviations (approximately 10 – 40%; 3, 11, 13, 20, 21-23), raise the question of whether a small number of matches truly reflects the average match demands. Previous studies have also shown differences in match demands based on position (20, 21). On average, defenders covered less distance than midfielders and attackers (forwards), and forwards covered more distance than midfielders (20, 21). Another complication when extrapolating information from current research is that the formation type may also alter the match demands (4, 6, 7). These limitations can lead to complications when inferring information from current research for use in a practical setting with different teams.

Factors that alter expected match demands, level of play and formation used, imply that it would be improper for the coaching staff to use data from a different level of play and unknown formation to determine the expected demands for their specific situation; that is, a high school coach should not be implementing a training plan based on data from college, professional, or international level teams. As such, the purpose of this research was to observe the match demands (distances and work rates) of an NCAA Division II women’s soccer team playing in a 3-5-2 formation, and to determine if there are significant differences in distances covered and/or work rates between positions.

METHODS 

Participants  

Retrospective data from 24 field players (age: 19.90 ± 1.56 years old; height: 163.43 ± 6.18 cm, weight: 59.35 ± 7.20 kg,) on the same team were included in this study. A total of 194 observations were included in the analysis (center back (CB), n = 49; wingback (WB), n = 36; midfield (MF), n = 61; and forward (FW), n = 48). This study was approved by the institutional review board of Lincoln Memorial University.

Procedures

Match data from an NCAA division II women’s soccer team playing a 3-5-2 formation were collected during a single competitive season. Only conference regular season matches, conference tournament, and national tournament matches were included, with 15 matches used for analysis.

Global Positioning System (GPS) devices (TITAN sports, Houston, TX, USA), sampling at 10 Hz, were used to track player movement duringcompetition. GPS units were activated at least 20-minutes prior to kick-off and were worn in a provided chest halter that secured the device between the shoulder blades under their game uniform. GPS devices were provided to all athletes (starters and substitutes) during the 10-minute window after the team warm-up and before the start of the match, and were collected again after the final whistle. All data from the duration of the match (substitute warm-up and half-time warm-up) were included in the analysis.

For positional analysis, distances accumulated by all athletes who played in a specific position for a match were summed and then divided by the number of positions in the formation. For example, in the forward position, if one athlete was substituted for a portion of the match, the total distance covered by all three athletes playing in the forward position was summed and then divided by two for the two forward positions in the 3-5-2 system. For the work rate analysis, meters covered per minute at each threshold (distances divided by total match time) were averaged for all players in that position (20). Due to the different substitution rules in college soccer, this analysis was deemed optimal to determine the distances and work rate of each position, instead of specific players. Variables of interest included total distance and distances covered in velocity thresholds; 2 – 3 m/s (7.2 – 10.8 km·h-1), 3 – 4 m/s (10.8 – 14.4 km·h-1), 4 – 5 m/s (14.4 – 18.0 km·h-1), 5 – 6 m/s (18 – 21.6 km·h-1), and >6 m/s (>21.6 km·h-1).

All matches analyzed were official NCAA matches consisting of two 45-minute halves with a 15-minute half-time period, with a maximum of two 10-minute extra-time periods with a 2-minute intermission, with extra time being stopped in the event of a goal if the competition was tied at the end of the normal 90-minute match.

Data Analyses

Two Repeated Measures ANOVA analyses with Bonferroni corrections were performed to determine whether there was a significant difference in distances and work rates for each position at each threshold (TD, 2 – 3 m/s, 3 – 4 m/s, 4 – 5 m/s, 5 – 6 m/s, and >6 m/s). Statistical analyses were performed using JASP (Version 0.16.2). The alpha level was set at 0.05.

RESULTS 

The first RM-ANOVA revealed significantly higher distances (F(3.37, 62.82) = 11.96, p < 0.001) covered in the MF position compared to all other positions for TD and 2 – 3 m/s. Midfielders also covered significantly more distances than CBs and FWs, but not WBs, at 3 – 4 m/s. The only other significant difference observed was between the WB and FW positions in TD covered. There were no significant differences between any other positions at any other threshold. Descriptive statistics are provided in Table 1.

Table 1

Mean distance covered by position in each velocity zone (meters).

 CBWBMFFW
TD8549 ± 1106 (6467 – 11066)8860 ± 1216# (5443 – 10854)10743 ± 1520* (7060 – 12864)8069 ± 1286# (6204 – 10537)
7.2 – 10.8 km·h-12497 ± 276 (1827 – 2972)2324 ± 344 (1389 – 2842)3444 ± 423* (2180 – 3916)2301 ± 400 (1668 – 2942)
10.8 – 14.4 km·h-11574 ± 214 ǂ (1191 – 1959)1814 ± 258 (1068 – 2218)2515 ± 382# ǂ (1771 – 3129)1270 ± 281# (759 – 1688)
14.4 – 18.0 km·h-1607 ± 113 (449 – 769)878 ± 135 (639 – 1124)1092 ± 211 (792 – 1453)587 ± 109 (395 – 734)
18.0 – 21.6 km·h-1246 ± 58 (155 – 342)404 ± 86 (252 – 552)381 ± 79 (241 – 533)272 ± 60 (149 – 357)
>21.6 km·h-196 ± 35 (45 – 175)200 ± 102 (68 – 426)120 ± 55 (68 – 295)180 ± 112 (45 – 530)

Note: Data are presented as mean ± Standard Deviation (Range).
TD: Total distance, CB: Center back, WB: Wingback, MF: Midfield, FW: Forward
* = p < 0.05 compared to all other positions in that velocity range
# = p < 0.05 compared to the other indicated positions in that velocity range
ǂ = p < 0.05 compared to the other indicated positions in that velocity range

The RM-ANOVA performed to determine differences in work rates at each threshold revealed significantly higher work rates (F(3.47, 64.82) = 6.05, p < 0.001) over the entire match (TD) for the MF position compared to all other positions, and a significantly higher work rate from the MF position in the 3 – 4 m/s velocity range compared to the FW position. There were no other significant differences between any of the other positions at any other threshold. The results are presented in Table 2.

Table 2

Mean work rate by position in each velocity zone (meters per minute).

 CBWBMFFW
TD96 ± 8 (88 – 123)101 ± 7 (85 – 117)119 ± 20 * (88 – 167)101 ± 24 (72 – 156)
7.2 – 10.8 km·h-128 ± 2 (25 – 33)26 ± 3 (21 – 35)36 ± 3 (29 – 40)27 ± 5 (19 – 35)
10.8 – 14.4 km·h-118 ± 2 (14 – 21)21 ± 2 (18 – 26)27 ± 3 # (21 – 32)16 ± 4 # (8 – 21)
14.4 – 18.0 km·h-17 ± 1 (5 – 10)10 ± 1 (8 – 12)12 ± 3 (9 – 19)8 ± 3 (4 – 14)
18.0 – 21.6 km·h-13 ± 1 (2 – 4)5 ± 1 (4 – 6)4 ± 1 (2 – 7)4 ± 2 (2 – 9)
>21.6 km·h-11.3 ± 1 (1 – 3)2.3 ± 1 (1 – 4)1.3 ± 1 (1 – 3)3.4 ± 4 (1 – 13)

Note. Data are presented as mean ± Standard Deviation (Range).
TD: Total distance, CB: Center back, WB: Wingback, MF: Midfield, FW: Forward

* = p < 0.05 compared to all other positions in that velocity range
# = p < 0.05 compared to the other indicated positions in that velocity range

DISCUSSION 

The purpose of this study was to examine the external demands of NCAA DII women’s college soccer playing in a 3-5-2 formation. The most interesting finding from these data was that the WB position was only significantly higher in total distance covered compared to the FW position (p = 0.044), but there were no other significant differences in distances or work rates compared to other positions. This was interesting, given that the WB position is commonly accepted as the most demanding position. Another interesting result was that the MF position had significantly higher distances at lower speeds (2-3 m/s, p < 0.001; 3-4 m/s, p < 0.001) only when compared to FW position. Other studies have reported that different positions have significantly different total distances covered in a match (1, 14). Abbot et al.(2018) reported that central midfielders covered the greatest distance (11,570 ± 469 m), followed by wide attackers (10,918 ± 353 m), wide defenders (10,747 ± 420 m), strikers (10,320 ± 420 m), and central defenders covering the least amount of distance (9,830 ± 428 m), while Lago-Peñas (2009) reported significant differences between nearly every position for each threshold, except for total distance (11.1 – 14 km·h-1, 14.1 – 19 km·h-1, 19.1 – 23 km·h-1, > 23 km·h-1). Both these studies observed high-level male soccer teams (U23 English Premier League, Professional Spanish Premier League) and as such they would not be expected to mimic the results of this study and highlight the importance of sex- and level-specific research.

In a more direct comparison with other women’s college soccer research, Sausaman et al(2019) and Alaxander et al (2014) reported significant differences in distances covered by position, whereas Corrales (2020) reported no differences, regardless of position. Sausaman et al (2019) reported that attackers covered more high-speed (> 15 km·h-1) and sprint (> 18 km·h-1) distances than midfielders and defenders, with no difference between midfielders and defenders. Alexander et al (2104) reported that central defenders covered the least amount of total distance (8041.2 ± 371.0 m), followed by central attacking midfielders (9236.1 ± 491.3 m), fullbacks (9306.2 ± 367.8 m), and wide midfielders (9500.4 ± 847.0 m), with central defensive midfielders (9947.4 ± 577.9 m) covering the greatest amount of total distance. Fullbacks (1321.5 ± 173.7 m) and wide midfielders (1208.2 ± 314.1 m) covered significantly more distance at high speed (> 15 km·h-1) compared to central defensive midfielders (847.7 ± 234.9 m), central attacking midfielders (747.64 ± 196.5 m), and central defenders (614.1 ± 98.9 m). The difference in results between these studies and the current investigation could be due to a different level of competition (NCAA Division 1), a possible difference in formation (not reported), or due to the current studies banding velocity zones (i.e. 4 -5 m/s, 5 – 6 m/s) instead of summing distances above thresholds (> 15 km·h-1).

CONCLUSION 

This present study provides information on the expected work and work rates of division 2 women’s soccer. Data analysis revealed minimal differences based on position, with the midfield position being the only position with significant differences and only at low intensity thresholds (TD, 2-3 m/s). All other positions and intensities were not statistically different, highlighting the possibility that training for these positions likely does not need to be modified to fit each position but rather each athlete.

APPLICATIONS IN SPORT

The primary application of this research is to allow the coaching staff to determine the appropriate fitness, conditioning, and practice workloads for their team with respect to their level of competition, formation, and style of play. Using typical tactical periodization plans for match-day preparation (Match day (MD) +1, MD -2, MD -1, etc.), position-specific workloads can be determined and monitored to ensure optimal loading during each practice session. This information can also be used to determine fitness testing requirements. Since there was a significant drop (43.7%) in distance covered and work rate (approximately 43% decrease) at intensities above 4 m/s (14.4 km·h-1) observed from this study, minimum criteria for aerobic fitness tests could be set at 15.5 km·h-1, which would allow players to do the majority of the work expected below their estimated lactate threshold (85% vVO2max; 8, 18)

In addition, these data can be used to determine the appropriate time requirements for different conditioning drills. For example, making a time criterion of 3:40 for an 800 m run would meet the Long Interval definition for an individual with a vVO2max of 15.5 km·h-1, but if a team had higher/lower requirements, adjusting time cut offs would be suggested (15). These data can also be used to create game-specific conditioning drills, such as creating an interval training exercise (100m active running, 100m recovery jog; Table 3) that would provide about 30 – 35% of game distances at the higher end of expected game work rates.

Table 3

Interval conditioning exercise.

Speed LevelRepsTimeWork RateAccumulated Distance
8.0 km·h-12245s89 m/min2200
12.0 km·h-11030s36 m/min1000
15.0 km·h-1524s20 m/min500
20.0 km·h-1218s8 m/min200
>21.6 km·h-11<16s4 m/min100

Note: Work Rate was calculated as the total distance covered in each velocity threshold divided by the total exercise time (24.5 min).

When retroactively analyzing team distances and work rates to create a training plan, it is important to note that since the majority of the total distance covered during a match is at low intensities (<3 m/s; 11), focusing on “running” the observed TD is likely unnecessary. Lower speed distances (<4 m/s) would be expected to be accumulated through daily technical drills and exercises. Higher speed distances (>4 m/s) could be accumulated in any manner chosen by the coach, such as a mixture of soccer technical drills and/or conditioning drills.

When using workload data in this manner, this would allow the coaching staff to create training plans that develop physical characteristics in a manner appropriate to the athletes level and expected match play requirements instead of arbitrarily spending time and effort developing a specific characteristic beyond projected usefulness. For example, since the majority of work is performed below 14.4 kph, spending the time and training effort for a vVO2max above 16 kph would be counterproductive. The extra focus could be better spent on improving other training targets to improve performance (technical, tactical, sprint, acceleration, change of direction)

ACKNOWLEDGMENTS

The authors declare no conflicts of interest, and no funding was received for this research.

REFERENCES 

1.   Abbott, W., Brickley, G., & Smeeton, N. J. (2018). Positional differences in GPS outputs and perceived exertion during soccer training games and competition. The Journal of Strength & Conditioning Research32(11), 3222-3231.

2.   Alexander, RP. (2014) Physical and Technical Demands of Women’s Collegiate Soccer (Publication No. 2421). [Doctoral dissertation, East Tennessee State University], Digital Commons.

3.   Andersson, H. Å., Randers, M. B., Heiner-Møller, A., Krustrup, P., & Mohr, M. (2010). Elite female soccer players perform more high-intensity running when playing in international games compared with domestic league games. The Journal of Strength & Conditioning Research24(4), 912-919.

4.   Aquino, R., Vieira, L. H. P., Carling, C., Martins, G. H., Alves, I. S., & Puggina, E. F. (2017). Effects of competitive standard, team formation and playing position on match running performance of Brazilian professional soccer players. International Journal of Performance Analysis in Sport17(5), 695-705.

5.   Bozzini, B. N., McFadden, B. A., Walker, A. J., & Arent, S. M. (2020). Varying demands and quality of play between in-conference and out-of-conference games in division i collegiate women’s soccer. The Journal of Strength & Conditioning Research34(12), 3364-3368.

6.   Bradley, P. S., Carling, C., Archer, D., Roberts, J., Dodds, A., Di Mascio, M., Paul, D., Gomez Diaz, A., Peart D., & Krustrup, P. (2011). The effect of playing formation on high-intensity running and technical profiles in English FA Premier League soccer matches. Journal of sports sciences29(8), 821-830.

7.   Carling, C., Espié, V., Le Gall, F., Bloomfield, J., & Jullien, H. (2010). Work-rate of substitutes in elite soccer: A preliminary study. Journal of science and medicine in sport13(2), 253-255.

8.   Cerezuela-Espejo, V., Courel-Ibáñez, J., Morán-Navarro, R., Martínez-Cava, A., & Pallarés, J. G. (2018). The relationship between lactate and ventilatory thresholds in runners: validity and reliability of exercise test performance parameters. Frontiers in physiology9, 1320.

9.   Choice, E. E., Tufano, J. J., Jagger, K. L., & Cochrane-Snyman, K. C. (2022). Match-play external load and internal load in NCAA division II women’s soccer. The Journal of Strength & Conditioning Research, 10-1519.

10. Corrales, I. (2020). The Physical Demands of Women’s Collegiate Soccer Matches Assessed Using GPS Devices [master’s thesis, California State University, Fullerton], https://scholarworks.calstate.edu/.

11. Gentles, J. A., Coniglio, C. L., Besemer, M. M., Morgan, J. M., & Mahnken, M. T. (2018). The demands of a women’s college soccer season. Sports6(1), 16.

12. Ishida, A., Travis, S. K., Draper, G., White, J. B., & Stone, M. H. (2022). Player position affects relationship between internal and external training loads during Division I collegiate female soccer season. The Journal of Strength & Conditioning Research36(2), 513-517.

13. Jagim, A. R., Murphy, J., Schaefer, A. Q., Askow, A. T., Luedke, J. A., Erickson, J. L., & Jones, M. T. (2020). Match demands of women’s collegiate soccer. Sports8(6), 87.

14. Lago-Peñas, C., Rey, E., Lago-Ballesteros, J., Casais, L., & Dominguez, E. (2009). Analysis of work-rate in soccer according to playing positions. International Journal of Performance Analysis in Sport9(2), 218-227.

15. Laursen, P., & Buchheit, M. (2019). Science and application of high-intensity interval training. Human kinetics.

16. Martínez-Lagunas, V., Niessen, M., & Hartmann, U. (2014). Women’s football: Player characteristics and demands of the game. Journal of Sport and Health Science3(4), 258-272.

17. Mohr, M., Krustrup, P., Andersson, H., Kirkendal, D., & Bangsbo, J. (2008). Match activities of elite women soccer players at different performance levels. The Journal of Strength & Conditioning Research22(2), 341-349..

18. Parpa, K., & Michaelides, M. A. (2025). Ventilatory thresholds in professional female soccer players. International Journal of Sports Medicine46(02), 97-103.

19. Ramos, G. P., Nakamura, F. Y., Penna, E. M., Wilke, C. F., Pereira, L. A., Loturco, I., Capelli, L., Mahseredjian F., Silami-Garcia E., & Coimbra, C. C. (2019). Activity profiles in U17, U20, and senior women’s Brazilian national soccer teams during international competitions: are there meaningful differences?. The Journal of Strength & Conditioning Research33(12), 3414-3422.

20. Sausaman, R. W., Sams, M. L., Mizuguchi, S., DeWeese, B. H., & Stone, M. H. (2019). The physical demands of NCAA division I women’s college soccer. Journal of Functional Morphology and Kinesiology4(4), 73.

21. Vescovi, J. D. (2014). Motion characteristics of youth women soccer matches: female athletes in motion (FAiM) study. International journal of sports medicine35(02), 110-117.

22. Vescovi, J. D. (2015). Physical demands of regular season and playoff matches in professional women’s soccer: a pilot from the Female Athletes in Motion (FAiM) study. In International research in science and soccer II (pp. 95-106). Routledge.

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2025-09-30T16:08:05-05:00March 4th, 2026|Research, Sport Education, Sport Training, Sports Coaching, Women and Sports|Comments Off on Positional Differences and Workload Requirements of a 3-5-2 Formation in Women’s Soccer

Match Demands and Positional Differences of NCAA Division II Women’s Soccer Players Over a Competitive Season

Authors: Joanne Spalding1, Jacob L. Grazer2

1Department of Health & Human Performance, Georgia College & State University, Milledgeville, GA, USA

2Department of Exercise Science & Sports Management, Kennesaw State University, Kennesaw, GA, USA

 

Corresponding Author:

Joanne Spalding, PhD, CSCS, CPSS, ACSM-EP

231 West Hancock Street

Milledgeville, GA 31061

[email protected]

478-445-2135

Joanne Spalding, PhD is Assistant Professor in Exercise Science at Georgia College and State University. Her research interests include long term athletic development and monitoring at the club, high school, and college level with an emphasis on neuromuscular fatigue.

Jacob L. Grazer, PhD, CSCS, USAW-1, ACSM-EP is currently a faculty member in the Department of Exercise Science and Sport Management at Kennesaw State University. Jacob’s research interests include: accentuated eccentric loading, countermovement jump analysis, and sport technology.

ABSTRACT 

Purpose:  There has been a growing interest in American women’s college soccer with the majority of research focused on the NCAA Division I level.  With 250+ Division II programs competing in 2024, there is an underrepresentation of this group in the literature. The purpose of this study is to examine the physical demands in Division II women’s soccer and analyze whether these physical demands vary by position.

Methods:  Twenty-two Division II female soccer field players from one DII college team were monitored over an 18-match season wearing GPS devices, a technology that is more commonly used at prevalent at Division I universities. Field players were divided into one of four positions: (1) Center Back Defenders; (2) Outside Back Defenders; (3) Midfielders; and (4) Forwards. The GPS devices provided data on: (a) total distance traveled; (b) total distance traveled per minute; (c) high-speed running distance traveled per minute; and (d) sprint distance traveled per minute. Due to NCAA Division II substitution rules, the focus in this study is the relative variables calculated as distance traveled per minute.

Results: Descriptive statistics for each GPS measurement are calculated based on the position played.  Then, Analysis of Variance (ANOVA) is used to identify any differences in player workload physical demands based on the position played. For distance traveled during a match, Center Back Defenders traveled the least distance compared to other positions. Similarly, for high-speed running distance, Center Back Defenders traveled the least distance compared to other positions. Finally, for Sprint Distance per minute, both Forwards and Outside Back Defenders traveled more distance compared to Center Back Defenders and Midfielders.

Conclusions: Findings suggest that the physical demands of Division II women’s soccer differ by position. Center Back Defenders tend to ‘stay at home’ and defend the goal while traveling less distance and sprinting less often. Forwards and Outside Back Defenders tend to spend more time sprinting compared to other players.

Applications in Sport: Coaches and practitioners can use this data when designing training programs to ensure their athletes are well-prepared for the differing physical demands of their sport based on the position played.

KEYWORDS: college soccer, GPS, match demands, women’s soccer, physical match performance

INTRODUCTION 

Over the past several years, there has been an increase in the number of peer-reviewed research articles focusing on the physical demands of women’s soccer. The majority of the research that has been conducted has focused on athletes who compete at the professional and international levels (E. Choice et al., 2022). Recently, there has been a growing interest in American college women’s soccer, with the majority of this research focused on National Collegiate Athletic Association (NCAA) Division I level. This can likely be attributed to the fact that wearable technology has become more prevalent at the collegiate Division I level making it easier to collect information regarding the physical demands experienced by female collegiate athletes. However, with 250+ Division II programs competing in the 2024 season, this significant population has been under-represented in research efforts to examine the physical demands on the athlete when competing.  As such, further analysis is needed to better understand the physical demands on athletes participating in the various levels of collegiate women’s soccer. 

Soccer is a high intensity, intermittent sport that requires running, jogging, walking, repeated sprints, jumping and change of direction (Al-Hazzaa et al., 2001; Bloomfield et al., n.d.; Wisløff et al., 2004). Matches consist of two 45-minute halves with a 15-minute halftime period. For international competition, the Fédération Internationale de Football Association (better known as FIFA) sanctions allow for five substitutions per game with a typical squad size of 26 players. However, NCAA soccer permits an unlimited number of players to be on the official roster during the regular season. Substitutions rules for the NCAA also differ from FIFA in that the number of substitutions is unlimited per game, and players are allowed to re-enter the match once in the second half. This difference is notable because it may influence the physical demands placed on players during match play.

Current literature has explored match play data at various playing levels and reports that there are differences in match-play demands at different levels in women’s soccer (E. Choice et al., 2022). A perspective review by Vescovi et al (2021) reported that there is a linear increase in total distance covered across playing levels ranging from youth (~7,500m), collegiate (~9,500m), to professional levels (~10,200m). A systematic review of women’s soccer also identified that playing demands increase between playing levels, and that there are positional differences in terms of total distance covered, high-speed running distance, and sprint efforts where midfielders covered greater total distances and sprint efforts compared to central defenders (Alexander, 2014; E. E. Choice et al., 2023).

Challenges arise when comparing research due to variations of inclusion criteria and determination of velocity thresholds. In addition to inclusion criteria varying, values are typically reported in total distances rather than relative to time spent playing on the field. As highlighted previously, the unique NCAA substitution rules make it challenging to fully grasp the physical demands that are placed on the athletes since it is uncommon for someone to play a full 90-minute match in women’s collegiate soccer. Due to the potential influence of substitution rules on physical demand, more research is needed to gain a greater understanding of the relative demands with respect to playing time. 

Very few studies have investigated the match demands of NCAA DII women’s soccer (E. E. Choice et al., 2023; Gentles et al., 2018). Gentles et al. (2018) assessed and compared accelerometry data to data collected using GPS signal. Although total distance and distance covered in specific velocity zones were reported, statistical analyses were not made comparing playing positions. Whereas Choice et al., (2023) investigated the external and internal load of players, including positional and time-specific differences.  

Due to the lack of research in women’s soccer in general, and specifically at the lower playing levels, there is a need for more research. The purpose of this study is to examine the physical demands in Division II women’s soccer and analyze whether these physical demands vary by position.

SOCCER TEAM ROLES AND ROLE EXPECTATIONS

Given this study examines the possible differences in physical demands on soccer athletes based on the position played, it is advantageous to clearly outline each position and the expectation of athletes who play that position. Each position carries distinct responsibilities within a team’s formation and can change based on the formation. This study focused on a team that utilized the 4-3-3 formation where positions are separated into center backs, outside backs (right and left), midfielders (center and attacking), and Forwards (central striker and right/left wing) (see Figure 1).

Figure 1 – Visual Presentation of 4-3-3 Soccer Formation

Center Back Defenders

Center back defenders are primarily responsible for defensive organization and central coverage. When in a defensive scenario, center backs are responsible for defending the opposing forwards, intercepting through balls, contesting aerial duels and tackling to gain possession. In possession, center backs initiate playing out from the back, with passes to midfielders or out to forwards, and or switching play across the back line.

Outside Back Defenders

Outside backs (right and left) provide width for the back line and help with transitional play from the defensive half to the attacking half. Out of possession, outside backs typically deal with the opposing forward or winger depending on the opposition’s formation. Similar to center backs, outside backs with attempt to win aerial duels and tackles. In possession, outside backs will look to support the team by overlapping the forward, dribbling the ball up the field, delivering crosses and well as helping maintain possession in the attacking half. 

Midfielders

The center midfielders are composed of two defensive midfielders and one attacking midfielder. The defensive midfielders attempt to shield the back line, break up opposition attacks, and in possession help to maintain and build possession from the defensive to attacking half. The attacking midfielder helps the forward and midfielders with defensive duties and in possession looks to support the forwards, maintain possession as well provide goals and assists. 

Forwards

Forwards help to provide width and are important for stretching the oppositions defense. They will primarily defend the oppositions outside back and recover into midfield positions when out of possession. In possession they will aim to beat defenders one-on-one, deliver crosses and create shooting opportunities. When a player is in the central striker position, they are the focal point of the attacking line and are primarily there to convert scoring opportunities by finishing inside and around the 18-yard box. In possession, the central striker will look to hold the ball up allowing midfielders and other forwards to join the play. They will attempt to make runs to disrupt the defensive lines and apply pressure to the opposition center backs. 

METHODS 

Participants  

A total of 22 NCAA Division II female soccer players participated in this study. Participants were athletes from a team already using a GPS athlete monitoring system. Players were assigned 1 of 4 positions by the team’s coaching staff (Sporis et al., 2009).

  1. Center Backs (CB) (n = 4)
  2. Outside Backs (OB) (n = 5)
  3. Midfielders (MID) (n=6)
  4. Forwards (FWD) (n= 7). 

Procedures  

A total of 18 regular season matches were included in this analysis from a single competitive season. Global Positional System (GPS) devices (TITAN Sports, Titan2, Houston, TX, USA) sampling at 10 Hz were used to track player movement during competition.  Data included 234 observations (n= 79 FWD, n= 70 MID, n= 50 OB, n= 35 CB). The team used for this study played 1-4-3-3 formation (please note 1 = goalkeeper) during all matches included in the analyses. All matches were official NCAA matches with two 45-minute halves and a 15-minute halftime period. All players were informed of the risks and benefits of this study and voluntarily signed an informed consent. This study was approved by the Institutional Review Board.  

Variables for Analysis

Data was collected on the following variables to better understand the physical demands on each player based on position played (see Andersson, 2010).

  • Total Distance – The total distance a player covers during a game. This value is needed to determine the distance covered related to minutes played.
  • Relative Total Distance (TDREL) – The distance covered per unit of time, expressed as meters per minute (m/min).
  • Relative High-Speed Running Distance (HSRREL) – Distance covered per minute while running at high speeds, in this case, over 15 kilometers per hour (km/h), or 9.3 miles per hour.
  • Relative Sprint Distance (SDREL) – Distance covered per minute while sprinting, usually above a higher threshold. In this case, over 18 kilometers per hour (km/h) or 11.2 miles per hour.

Using the Global Navigation Satellite System to Measure Match Load  

GPS units were worn in a harness that secured the device between the scapulae (i.e., shoulder blades). The units were turned on 10 minutes before being placed in the harness to ensure sufficient GPS signal was attained per manufacturer’s instructions. Due to the substitution rules in NCAA college soccer, calculating the variables per minutes played was deemed the optimal solution for comparing workload across playing position.

RESULTS 

Three separate one-way ANOVA analyses with Bonferroni corrections were conducted to determine if there were differences between positions for Total Distance (TDREL), High Speed Running Distance (HSRREL) and Sprint Distance (SDREL). Statistical analyses were performed in SPSS (Version 27.0.1). Alpha level was set at p <0.05. Eta-squared effect sizes were calculated to determine magnitude of differences for each variable. For pairwise comparisons, Cohen’s d effect sizes were calculated to determine magnitude of difference between playing positions (Hopkins, 2002).  Descriptive statistics for match physical performance for this specific team are summarized in Table 1.

Table 1 – Match Performance Data

Variables Midfielders (n=70) Forwards (n=79) Outside Back Defenders (n=50) Center Back Defenders (n=35) Total (n=234) 
Minutes Played per Match 51.6 ± 13.6 52.8 ± 15.1 52.1 ±13.9 68.0 ±19.9 57.1 ± 15.6 
Total Distance (m) 5,643.9 ± 1,435.0 5,507.9 ± 1,214.1 5,506.3 ±1,373.8 6365.1 ± 1884.9  Greatest total distance covered due to greatest minutes played5,855.8 ±1,476.8 
Relative Total Distance (m/min) The distance covered per unit of time, usually expressed as meters per minute (m/min). 110.4 ± 14.2 Significantly greater than Center Back Defender106.8 ± 14.4   Significantly greater than Center Back Defender106.8 ±12.6  Significantly greater than Center Back Defender93.8 ± 11.6 105.9 ± 14.5 
Relative High Speed Running Distance (m/min)  Distance covered per minute while running at high speeds, in this case, over 15 kilometers per hour (km/h), or 9.3 miles per hour.  10.06 ± 3.45  Significantly greater than Center Back Defender12.96 ±4.01 Significantly greater than Center Back Defender 13.18 ± 4.21 Significantly greater than Center Back Defender7.53 ± 2.90   11.33 ± 4.26 
Relative Sprint Distance (m/min)  Distance covered per minute while sprinting, usually above a higher threshold. In this case, over 18 kilometers per hour (km/h) or 11.2 miles per hour3.45 ± 1.98  6.06 ± 2.64 Significantly greater than Center Back Defender  Significantly different than Midfielders5.53 ± 1.85 Significantly greater than Center Back Defender  Significantly different than Midfielders3.05 ± 1.92  4.72 ± 2.53 

 Relative Total Distance (TDREL)

A one-way ANOVA revealed a significant difference in positions for TDREL, F(3, 230) = 11.9, p = <0.001. An effect size (η2=0.135) indicated a medium effect. Post Hoc analysis indicated that there were mean differences between FWD and CB (p = <0.001), MID and CB (p = <0.001), and OB and CB (p = <0.001).  

Relative High-Speed Running Distance (HSRREL)

There were statistically significant difference for HSRREL, F(3, 230) = 23.73 p < 0.001, with a large effect (η2=0.23). Post Hoc analysis showed mean differences between FWD and MID (p = <0.001), FWD and CB (p = <0.001), MID and OB (p = <0.001), MID and CB (p = <0.008) and OB and CB (p = <0.001) as seen in Figure 2. 

Relative Sprint Distance (SDREL)

Finally, there were statistically significant differences for positions in SDREL, F=(3,230), 25.547, p <0.001 with a large effect η2=0.25 Post Hoc analysis revealed mean differences for FWD and MID (p = <0.001), FWD and CB (p = <0.001), MID and OB (p = <0.001), OB and CB (p = <0.001). 

DISCUSSION 

The purpose of this study is to determine the physical demands for NCAA Division II Women’s Soccer and to assess positional differences and physical demands relative to minutes played.  The study’s results include the average demands during match play of each field position as previously shown in Table 1. The main findings of this study indicate that center backs accumulate the greatest total distance, however, this is mainly attributable to extended playing time as they frequently remained on the field 15-17 minutes longer than other positions. When normalized for minutes outside backs, midfielders and forwards covered greater total distance and high-speed running distance than center backs. In addition, outside backs and forwards demonstrated greater sprint distance per minute compared to both center backs and midfielders. 

The average total distance covered for players included in analyses was 5,855 ± 1,476 meters, which differs from prior findings by Choice et al. (2023) who saw starters cover 9,463 ± 2,591 meters. It should be noted that the analysis by Choice et al. (2023) only included players who participated in over 50% of match play. Findings from this study are similar to results reported by Gentles et al. (2018) who reported findings of 5,480 ± 2,350 meters and average minutes played of 45.32 ± 26.01 which are similar to minutes played in this study.  The maximum distance covered by an individual in this study was 9,810 meters, which is much lower than distance covered by the sample in Gentles (13,850 meters) and Choice (12,054 meters), but similar to distances reported in Division I athletes, 9,786 meters (Sausaman, 2019). Both maximum and average distance covered varied across levels may indicate that more research is needed across differing playing levels. Also, from a practical point of view, this should help sport practitioners implement appropriate programs that develop players for both maximum and mean distances, regardless of minutes played.  

To our knowledge, this is the first study to report TDREL (105 ± 14.5 m/min), HSRREL (11.3 ± 4.2 m/min) and SDREL (4.72 ± 2.53) in NCAA Division II athletes. Gentles (2018) reported total distance accumulated at velocity zones 15.00 – 19.99 kph and 20.00-24.99 kph but not relative distances. Due to the substitution rules in NCAA College soccer, there is a high variance in match-to-match playing variables. Other studies have only included players who have played over 50% of the match or the entire match (E. E. Choice et al., 2023), whereas other research only included participants who completed the match in its entirety (Alexander, 2014; Sausaman et al., 2019).  If training programs are only based on average totals, then the whole picture may not be clear when designing training programs for those not participating in 90 minutes. Therefore, reporting data per minute may be more beneficial as reserves need to be trained throughout the season to compensate for minutes not played.  

There was a difference in positional demands for HSRREL, with FWDs covering higher distances than MIDs and CBs. Whereas OBs covered more HSRREL than CBs and MIDs, and MIDs only covered more distance than CBs. Although there was no statistical difference between OBs and FWDs, OBs covered slightly more distance per minute. Although the lack of statistical difference between FWDs and OBs may be due to formation and playing style. In the 4-3-3 OB and FWDs may have similar positional demands as OBs are often part of the attack by providing width higher up the field. Formation on the field was not controlled for in this study so more research is warranted to understand positional differences across a variety of formation styles. 

Results also showed that FWDs covered more SDREL than MIDs and CBs, and OBs covered more than CBs. Although variables are different within this study, results show similar trend within the literature, that forwards cover more HSR distance and sprint distance than midfielders (Sausaman et al., 2019; J. Vescovi, 2013). It should also be noted that CB and OB positions are typically grouped together as a singular position group (commonly reported as defender) (Stolen et al., 2005; J. D. Vescovi, 2012).

This study provides further evidence, particularly in women’s soccer literature, that there is a need to differentiate between central and outside defenders when evaluating physical demands during competition due to the different physical demands during competition (Alexander, 2014; Harkness-Armstrong et al., 2022). It is also important to note that in NCAA Division I studies, players covered more high-speed running and sprint distance on average compared to NCAA division II athletes. This indicates that the Division I game may be played at a faster pace, especially in those critical moments of the game (defensive recovery run, sprinting to goal etc.) As this study reports HSR and sprint distance per minute, it prevents the authors from making additional conclusions or comparisons.  

There are limitations to the study that may have impacted the results.  The data for this study was collected for one team playing one season of competition.  The level of soccer players at all NCAA level can vary greatly across teams and conferences.  Therefore, further research is needed to confirm the current findings. Differences in match demands as well as positional demands may be a result of opposition level, formations, match status, and match location.  As such, additional research is needed to assess these factors to determine their possible influence on the physical demands of Division II women’s soccer.  

CONCLUSION 

This study examined the physical demands of women’s soccer at the NCAA Division II level and analyzed differences among position groups. Unlike previous research, this study assessed Relative total distance (TDREL), relative high-speed running distance (HSRREL), and relative sprint distance (SDREL), providing average values for all players and specific positions to describe match demands. The findings highlight differences in physical demands based on position played. The findings from this study emphasize the importance of evaluating workload relative to minutes played and recognizing the unique demands of each position at the NCAA Division II level. Such insights provide a framework for tailoring training, conditioning and substitution strategies that reflect position-specific requirements rather than relying on team-wide averages.  Future research should continue to examine how positional workloads vary across divisions and competitive levels, as well as how these demands interact with injury risk, recovery and long-term players development. 

APPLICATIONS IN SPORT

These findings provide an insight into general and positional demands of women’s soccer at the NCAA Division II level. These results are particularly valuable to coaches who may strategically utilize the NCAA substitution rules to manage player workloads. Caution should be exercised when applying published findings from other levels of play and relying on total averages as positional differences can substantially influence match demands.

The results emphasize the importance of aligning athlete’s physical attributes with the requirements of their playing positions. Forwards and outsides backs perform the highest sprinting and high-speed running demands per minute and may require players that have higher acceleration and sprint capacities. On the other hand, players that have less high-speed and sprinting demands, but positional awareness may be better suited at center back. 

This may have implications for recruitment. Coaches may want to target athletes with performance profiles that align with the positional demands, rather than relying on general fitness. In regard to player development, training and conditioning programs should be tailored to the requirements of each position moving beyond a one-size-fits-all approach. For example, midfielders may benefit from training designed to sustain higher per-minute workloads, while forwards and outside backs should focus on repeated spring ability as well as increasing top speed. 

Finally, these results may extend to tactical decision making and injury prevention. Coaches may rotate outside backs and forwards more frequently to preserve sprint performance later in matches. These findings provide sport practitioners with evidence-based guidance to optimize recruitment, training and match management in NCAA division II soccer. 


REFERENCES 

  1. Alexander, R. (2014). Physical and Technical Demands of Women’s Collegiate Soccer. Electronic Theses and Dissertations, 2421. https://dc.etsu.edu/etd/2421
  2. Al-Hazzaa, H., Almuzaini, K., Al-Refaee, S., Sulaiman, M., Dafterdar, M., Al-Ghamedi, A., &  Al-Khuraiji, K. (2001). Aeronic and anaerobic power characteristics of Saudi elite soccer players. Journal of Sports Medicine & Physical Fitness, 41(1), 54–61.
  3. Andersson, H. A., Randers, M. B., Heiner-Møller, A., Krustrup, P., & Mohr, M. (2010). Elite female soccer players perform more high-intensity running when playing in international games compared with domestic league games. Journal of Strength & Conditioning Research, 24(4), 912–919. https://doi.org/10.1519/JSC.0b013e3181d09f21
  4. Bloomfield, J., Polman, R., & O’Donoghue, P. (n.d.). Physical demands of different positions in FA Premier League soccer.
  5. Choice, E. E., Tufano, J. J., Jagger, K., L., & Cochrane-Synman, K. C. (2023). Match-Play External Load and Internal Load in NCAA Division II Women’s Soccer. Journal of Strength & Conditioning Research, 37(12), 633–639. https://doi.org/10.1519/JSC.0000000000004578
  6. Choice, E., Tufano, J., Jagger, K., Hooker, K., & Cochrane-Snyman, K. C. (2022). Differences across Playing Levels for Match-Play Physical Demands in Women’s Professional and Collegiate Soccer: A Narrative Review. Sports, 10(10), 141. https://doi.org/10.3390/sports10100141
  7. Gentles, J., Coniglio, C., Besemer, M., Morgan, J., & Mahnken, M. (2018). The Demands of a Women’s College Soccer Season. Sports, 6(1), 16. https://doi.org/10.3390/sports6010016
  8. Harkness-Armstrong, A., Till, K., Datson, N., Myhill, N., & Emmonds, S. (2022). A systematic review of match-play characteristics in women’s soccer. PLOS ONE, 17(6), e0268334. https://doi.org/10.1371/journal.pone.0268334
  9. Hopkins, W. G. (2002). A scale of magnitude for effect statistics. http://www.sportsci.org/resource/stats/effectmag.html.
  10. Sausaman, R. W., Sams, M. L., Mizuguchi, S., DeWeese, B. H., & Stone, M. H. (2019). The Physical Demands of NCAA Division I Women’s College Soccer. Journal of Functional      Morphology and Kinesiology, 4(4), 73. https://doi.org/10.3390/jfmk4040073
  11. Sporis, G., Jukic, I., Ostojic, S., & Milanovic, D. (2009). Fitness profiling in soccer: Physical and physiologic characteristics of elite players. Journal of Strength & Conditioning Research, 23(7), 1947–1953. https://doi.org/10.1519/JSC.0b013e3181b3e141
  12. Stolen, T., Chamari, K., Castagna, C., & Wisl??ff, U. (2005). Physiology of Soccer: An Update. Sports Medicine, 35(6), 501–536. https://doi.org/10.2165/00007256-200535060-00004
  13. Vescovi, J. (2013). Motion Characteristics of Youth Women Soccer Matches: Female Athletes in Motion (FAiM) Study. International Journal of Sports Medicine, 35(02), 110–117. https://doi.org/10.1055/s-0033-1345134
  14. Vescovi, J. D. (2012). Sprint profile of professional female soccer players during competitive matches: Female Athletes in Motion (FAiM) study. Journal of Sports Sciences, 30(12), 1259–1265. https://doi.org/10.1080/02640414.2012.701760
  15. Wisløff, U., Castagna, C., Helgerud, J., Jones, R., & Hoff, J. (2004). Strong correlation of maximal squat strength with sprint performance and vertical jump height in elite soccer players: Figure 1. British Journal of Sports Medicine, 38(3), 285–288. https://doi.org/10.1136/bjsm.2002.002071

2025-09-25T15:33:55-05:00February 4th, 2026|Research, Sport Education, Sport Training, Sports Coaching, Sports Health & Fitness, Women and Sports|Comments Off on Match Demands and Positional Differences of NCAA Division II Women’s Soccer Players Over a Competitive Season

Affective Forecasting and Social Physique Anxiety among Female Athletes: A Pilot Study

Authors: Jessica Wolverton1 & Urska Dobersek2  

1Athletics Department, McDaniel College, Westminster, USA; 2Department of Psychology, University of Southern Indiana, Evansville, IN USA

Corresponding Author:

Jessica Wolverton, M.S.
2 College Hill Westminster, MD 21157
[email protected]
410-857-2566

Jessica Wolverton, MS is a former collegiate volleyball coach and a current collegiate athletics administrator. Her research focus includes well-being, mental health resourcing, and programming for student-athletes.
Urska Dobersek, Ph.D., CMPC is an associate professor of psychology at the University of Southern Indiana. Her research interests include individuals’ identities, objectification of women, sexual and mate selection, and diet and mental health

Affective Forecasting and Social Physique Anxiety among Female Athletes: A Pilot Study

ABSTRACT

While people make affective forecasts every day, they overestimate the impact of future events on their emotional states — displaying an impact bias. Comparatively few studies examined athletes’ accuracy of specific emotions in aesthetic sports. To remedy this gap, we explored predicted social physique anxiety and self-presentational concerns in an experimental analysis of 156 female collegiate volleyball players between 18 and 23 years of age. Athletes completed a Demographic Questionnaire and the Trait Anxiety Inventory before being randomly assigned to one of the four experimental conditions (i.e., control, practice, intersquad scrimmage game, or heavy spectator game). After the manipulation, their social physique anxiety levels and self-presentational concerns in sport were assessed. A one-way Analysis of Variance revealed significant differences among the conditions on social physique anxiety, F(3, 152) = 4.70, p = .004, h2 = .09. Specifically, Tukey HSD post-hoc test revealed that athletes in the control condition scored higher on social physique anxiety (M = 2.74, SD = 0.71) compared with intersquad scrimmage game condition (M = 2.15, SD = 0.70), p < .01, d = .83. No other significant differences were observed. Contrary to prior literature, athletes overestimated their forecasted anxiety in the control group and underestimated their forecasted social physique anxiety levels in a game closed to large crowds. Our study extends previous work on affective forecasting, and more importantly, provides additional information on specific emotions in aesthetic sports. Our findings suggest that coaches and sport psychology consultants could potentially reduce athletes’ social physique anxiety and self-presentational concerns by channeling their attention to the task at hand.

Key Words: affective forecasting, social physique anxiety, self-presentational concerns, pilot study

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2023-09-27T11:50:12-05:00September 29th, 2023|Research, Sports Coaching, Sports Health & Fitness, Women and Sports|Comments Off on Affective Forecasting and Social Physique Anxiety among Female Athletes: A Pilot Study

Increased Exposure to Women in Sport Increases Familiarity and Liking

Authors: Beth Dietz

Department of Psychology, Miami University, Middletown, Ohio, US

Corresponding Author:

Beth Dietz
Department of Psychology, Miami University
Middletown, OH 45044
[email protected]

Dr. Beth Dietz is a professor of psychology at Miami University. Her research interests include social identity, sport fans and spectators, women in sport, and the scholarship of teaching and learning.

Increased Exposure to Women in Sport Increases Familiarity and Liking

ABSTRACT

Purpose: The quantity of media coverage of sports played by females has not achieved parity with coverage of sports played by males. Additionally, coverage of sport played by females is often regarded as boring, uninteresting, and bland. The current study tests the hypothesis that as exposure to sport and gender increases, so will liking. Methods: Participants completed measures of familiarity, liking, and knowledge before and after a course on Sport and Gender. Results: The results showed increases over time in liking-to-watch, frequency-of-watching, knowledge of and familiarity with sport played by women (results also showed increases for neutral sports and sports played by males). Conclusions: These results suggest that repeated exposure to sports played by females leads to greater liking and interest. Applications: Increasing exposure to sports played by females in the media and in classrooms will lead to increased liking of, and likely demand, for sports played by females.

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2023-09-22T13:09:26-05:00September 22nd, 2023|Research, Sports History, Sports Marketing, Women and Sports|Comments Off on Increased Exposure to Women in Sport Increases Familiarity and Liking

Title IX and Its Impact on Opportunities for Women in NCAA Coaching and Administrative Leadership

Authors: Elisa Van Kirk

Department of Education, St. Lawrence University, Canton, NY, US

Corresponding Author:

Elisa Van Kirkl
SLU- 23 Romoda Dr.
Atwood Hall 21
Canton, NY, 13617
[email protected]
860-919-3274

Dr. Elisa Van Kirk is a Visiting Assistant Professor in the Department of Education at St. Lawrence University in Canton, NY. Van Kirk played Division I softball and was a collegiate coach at the Division III level for over a decade. Currently, Van Kirk primarily works with the University’s graduate students who are pursuing a Master of Art in Leadership degree.
Van Kirk’s research focuses on collegiate athletics, athletic leadership, as well as sports and gender.

Title IX and Its Impact on Opportunities for Women in NCAA Coaching and Administrative Leadership

ABSTRACT

Title IX was evolutionary when first enacted, and it provided a framework to address equity in education in many respects; however, it has had limited effects in many other areas, including in NCAA athletic administration. In this commentary, a discussion is offered in regard to the ongoing impacts of Title IX in college athletics and ways in which this legislation has impacted women and their opportunities for leadership. Examples from the literature from women who once held roles in NCAA Division III leadership are considered and their experiences are drawn upon to demonstrate ways in which barriers and sources of inequity continue to exist. Recommendations are offered for women seeking leadership positions based on the experiences of the women in this study.

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2023-03-13T09:35:26-05:00March 13th, 2023|Commentary, Sport Education, Sports History, Women and Sports|Comments Off on Title IX and Its Impact on Opportunities for Women in NCAA Coaching and Administrative Leadership
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