Sport Training – Page 2 – The Sport Journal

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, vVO_2max: Velocity at VO_2max

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).

	CB	WB	MF	FW
TD	8549 ± 1106 (6467 – 11066)	8860 ± 1216# (5443 – 10854)	10743 ± 1520* (7060 – 12864)	8069 ± 1286# (6204 – 10537)
7.2 – 10.8 km·h-1	2497 ± 276 (1827 – 2972)	2324 ± 344 (1389 – 2842)	3444 ± 423* (2180 – 3916)	2301 ± 400 (1668 – 2942)
10.8 – 14.4 km·h-1	1574 ± 214 ǂ (1191 – 1959)	1814 ± 258 (1068 – 2218)	2515 ± 382# ǂ (1771 – 3129)	1270 ± 281# (759 – 1688)
14.4 – 18.0 km·h-1	607 ± 113 (449 – 769)	878 ± 135 (639 – 1124)	1092 ± 211 (792 – 1453)	587 ± 109 (395 – 734)
18.0 – 21.6 km·h-1	246 ± 58 (155 – 342)	404 ± 86 (252 – 552)	381 ± 79 (241 – 533)	272 ± 60 (149 – 357)
>21.6 km·h-1	96 ± 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).

	CB	WB	MF	FW
TD	96 ± 8 (88 – 123)	101 ± 7 (85 – 117)	119 ± 20 * (88 – 167)	101 ± 24 (72 – 156)
7.2 – 10.8 km·h^-1	28 ± 2 (25 – 33)	26 ± 3 (21 – 35)	36 ± 3 (29 – 40)	27 ± 5 (19 – 35)
10.8 – 14.4 km·h^-1	18 ± 2 (14 – 21)	21 ± 2 (18 – 26)	27 ± 3 # (21 – 32)	16 ± 4 # (8 – 21)
14.4 – 18.0 km·h^-1	7 ± 1 (5 – 10)	10 ± 1 (8 – 12)	12 ± 3 (9 – 19)	8 ± 3 (4 – 14)
18.0 – 21.6 km·h^-1	3 ± 1 (2 – 4)	5 ± 1 (4 – 6)	4 ± 1 (2 – 7)	4 ± 2 (2 – 9)
>21.6 km·h-1	1.3 ± 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 Level	Reps	Time	Work Rate	Accumulated Distance
8.0 km·h^-1	22	45s	89 m/min	2200
12.0 km·h^-1	10	30s	36 m/min	1000
15.0 km·h^-1	5	24s	20 m/min	500
20.0 km·h^-1	2	18s	8 m/min	200
>21.6 km·h^-1	1	<16s	4 m/min	100

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

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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 sciences, 29(8), 821-830.

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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.

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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 Research, 22(2), 341-349..

18. Parpa, K., & Michaelides, M. A. (2025). Ventilatory thresholds in professional female soccer players. International Journal of Sports Medicine, 46(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 Research, 33(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 Kinesiology, 4(4), 73.

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Troy Palmer2025-09-30T16:08:05-05:00March 4th, 2026|Research, Sport Education, Sport Training, Sports Coaching, Women and Sports|Comments Off

Supplemental lessons to the Peak Health and Performance curriculum: Nutritional considerations for injury, energy management, and gastrointestinal issues

Authors: Tyler B. Becker¹², Ronald L. Gibbs, Jr²

¹Department of Food Science and Human Nutrition, Michigan State University, East Lansing, MI, USA

²Michigan State University Extension, Health and Nutrition Institute, Michigan State University, East Lansing, Michigan, USA

Corresponding Author:

Tyler B. Becker, PhD, CSCS

469 Wilson Road, Room 125

East Lansing, MI 48824

[email protected]

517-353-3338

Tyler B. Becker, PhD, CSCS is an Associate Professor of Nutritional Sciences at Michigan State University in East Lansing, MI. His research interests focus on sports nutrition practices and strategies in youth athletes and higher education andragogy.

Ronald L. Gibbs, Jr, PhD, MCHES is currently a Program Evaluation Specialist for Michigan State University in East Lansing, MI. His research interests focus on coach and athlete education, long-term athlete development (LTAD), psychosocial aspects of sports and physical activity, adolescent nutrition and physical activity behavior change through sport participation, sports performance, and reducing childhood obesity.

ABSTRACT

Youth sports injuries are quite common in sport and have several negative consequences, including healthcare costs, loss of playing time, and producing mental stress. Nutritional strategies have been suggested to improve recovery from sports-related injuries. The Peak Health and Performance (PHP) youth-sports curriculum was developed to use sport to promote healthy eating behaviors. Six additional lessons on nutrition for recovery from injury, energy management, and gastrointestinal issues have been added as addendums to PHP. Lesson A discusses the importance of key nutrients (eg., protein, complex carbohydrates, unsaturated fatty acids, water) for promoting tissue healing following an injury. Lesson B describes several micronutrients and the possible role of nitrates for aiding in injury recovery. Lesson C discusses the implications of low energy availability, including how to identify and prevent it. In Lesson D, several nutritional strategies for addressing mild traumatic brain injuries are explored. Lesson E discusses the importance of sleep for injury recovery and describes nutritional strategies for improving sleep quality. The final lesson (Lesson F) describes various gastrointestinal issues encountered in sport and how to prevent them. Future research will examine youth athlete knowledge of nutritional strategies for recovering from a sports-related injury following these lessons.

KEYWORDS: adolescent sports; sports nutrition; injury management

INTRODUCTION

Sports-related injuries are a significant concern among adolescent athletes, with prevalence rates ranging from 34.1% to 65% (2). Certain groups, including female athletes, obese athletes, and those participating in contact sports, are at particularly high risk. In the US, the rate of injuries in sports, recreation, and leisure activities is 117.1 per 1000 children and adolescents aged 12-17 years of age (57). These injuries impose substantial financial burdens; for example, over a 5-year period in Florida, inpatient care costs for pediatric sports injuries totaled $24.55 million, while emergency care expenses reached $87 million (61). Beyond the economic impact, sports-related injuries also incur both physical and mental challenges to the athlete, including lost playing time, with female athletes averaging 10 days of missed competition per injury (5). This contributes to social isolation and depressive symptoms in adolescent athletes during recovery (63). In addition, gastrointestinal (GI) problems, including diarrhea, vomiting, and abdominal injuries are common place among athletes (12,73), and can contribute to decreases in performance and a loss of playing time (39). Given these multifaceted challenges, there is a critical need to optimize injury prevention and rehabilitation strategies to support young athletes’ physical and psychological well-being.

Proper nutritional intake plays a critical role in injury prevention and rehabilitation among youth athletes (3). In addition to supporting overall health and well-being, adequate nutrition is essential during adolescence–a period marked by rapid growth and development–and contributes to athletic performance and post-workout recovery (15, 66). Despite its importance, many adolescent athletes demonstrate a lack of knowledge regarding both general and sport-specific nutritional practices (6). A recent systematic review by Hulland et al. (2023) revealed that adolescent athletes are more familiar with general than sport-specific dietary strategies (32), while Gibbs and Becker (2025) found that both male and female adolescent athletes scored below 50% on assessments covering both areas (24). These findings underscore a significant gap in nutritional literacy among youth athletes, indicating the need for targeted education to optimize their health development and athletic outcomes.

Several nutritional strategies have emerged highlighting the importance of it for injury rehabilitation primarily in adult athletes (26, 54, 65). For example, kilocaloric and protein needs often increase following injury due to a need for recovery and maintenance of lean body mass resulting from disuse (58, 65). However, the application of nutritional strategies for recovering from injury for youth athletes remains understudied. Alcock et al. (2024) offered a comprehensive overview of injury rehabilitation strategies for youth, indicating practical applications; however there remains a critical gap in understanding how adolescent athletes perceive and apply nutrition during recovery (3). To date, no research has directly examined youth athletes’ knowledge of nutrition for injury rehabilitation, but existing evidence suggests they are likely deficient in this area as well (46). Research suggests that poor food literacy and nutrition knowledge could theoretically contribute to increased injury risk (3, 15). This reinforces the urgency of developing age-appropriate interventions that address both performance and recovery nutrition, particularly in the context of injury.

The Peak Health and Performance (PHP) curriculum was designed from a collaboration by faculty and staff at Michigan State University, Division of Sports and Cardiovascular Nutrition, College of Osteopathic Medicine, East Lansing, MI and Spartan Performance Training, East Lansing, MI (25). This curriculum incorporates various sports nutrition best practices from several areas of literature providing sports nutrition recommendations (17, 66, 69). Fruit and vegetable intake significantly increased in 290 children and adolescents who completed the PHP curriculum (4). Due to the success of the program in modifying nutrition behaviors, additional lessons were created to educate youth on nutritional strategies for injury recovery, energy management, and managing GI issues. These topics include nutritional strategies for musculoskeletal and mild traumatic brain injury (mTBI) recovery, and other nutritional considerations around injury risk and recovery including sleep, low energy availability (LEA), and GI issues. This manuscript describes the rationality and creation of these addendum lessons for the PHP curriculum.

LESSON CONTENT

The original PHP curriculum consists of six lessons labeled as: Lesson 1- Nutrition Basics; Lesson 2- Athletes Performance Plates; Lesson 3- Timing of Intake; Lesson 4- Hydration, Energy Drinks, and Sugary Beverages; Lesson 5- Convenience Foods; and Lesson 6- More Than a Game (25). Further information on PHP learning objectives and topics inclusion can be found in Gibbs & Becker (25). The new additional lessons and their learning objectives can be found in Table 1. These additional lessons are meant to serve as their own lesson series, a single lesson session, or as supplemental lessons to the original PHP lessons.

Table 1.
Additional Lessons for the Peak Health and Performance Curriculum: Learning Objectives
Lesson	Learning Objectives
A: Macronutrients for Injury Rehabilitation	• Explain the four phases of an injury • Understand the importance of consuming enough calories following an injury • Explain why protein is needed during the health process and recall amounts needed • Explain the role that carbohydrates have during the healing process • Describe what role unsaturated fatty acids, such as omega-3s, have while healing an injury. • Understand the importance of water during the healing process
B: Micronutrients for Injury Rehabilitation	• Explain the importance of choosing food sources of vitamins and minerals over dietary supplements • List and understand the roles that vitamins A, C, D, and E have in injury healing • Identify good food sources of vitamins A, C, D, and E • List and understand the roles that calcium, zinc, and iron have in injury healing • Identify good food sources of calcium, zine, and iron • Explain why foods high in nitrates may promote injury healing and identify good food sources of them
C: Low Energy Availability	• Explain what low energy availability is • Identify what causes low energy availability • Understand how low energy availability negatively impacts performance and recovery • Explain how low energy availability may lead to other negative health outcomes • Recognize the symptoms of low energy availability • Describe prevention and treatment strategies for low energy availability
D: Nutrition for Head Injuries	• Explain what happens during a head injury in sport • List the different phases of concussion recovery • Explain the benefits of creatine, magnesium, and flavonoids for head injury recovery • Identify good food sources of creatine, magnesium, and flavonoids • Identify other nutritional considerations to have when recovering from a head injury
E: Nutrition and Sleep for Injury Reduction and Recovery	• Explain why sleep is important for performance and reducing and healing injuries • Identify how much sleep an athlete should be getting each night • Explain the benefits of melatonin and serotonin rich foods for improving sleep quality • Identify other nutrients of interest that are related to sleep quality • Identify foods to avoid prior to sleep • List strategies to set up an ideal bedtime routine
F: Gastrointestinal Issues and Sport	• Understand how vomiting and nausea symptoms may appear during practice and sport • Provide strategies to reduce vomiting and nausea symptoms during practice and sport • Explain how diarrhea can happen during practice and sport • Identify strategies to prevent diarrhea during practice and sport • Explain how probiotics and prebiotics are important for gut health

Each of these six lessons will be discussed in detail in the next section. These supplemental lessons were created in a manner to instruct participants to refer back to the original lessons for further information.

Lesson A: Macronutrients for Injury Prevention

This lesson begins by describing how musculoskeletal injuries heal and the importance of proper caloric intake and macronutrients during recovery from sports-related injuries. Each macronutrient is then highlighted to show its main role in providing both energy and nutritional needs to promote recovery. Macronutrient roles and responsibilities are described in detail in PHP Lesson 1 of the original curriculum (25).

Caloric Intake: The following section of the lesson describes the importance of meeting kilocalorie (kcal) needs to help heal an injury. Research on adult athletes suggest increasing kcal consumption by 10-15% during injury and recovery (58). Additionally, to offset sarcopenia in adults resulting from injury and disuse, energy intake should be between 25-40 kcal/kg of bodyweight per day (54). Independent of injury status, growth and development demands of children aged 9 and up typically require 60-65 kcal/kg of bodyweight per day (21). Taking energy needs during injury into account, coupled with normal demands for growth and development (21), an injured adolescent would need slightly more than the recommended 60-65 kcal/kg of bodyweight per day.

Protein: Following injury, protein requirements are significantly elevated to offset bodily stress incurred from the injury (65). Additionally, protein intake helps offset muscle atrophy due to disuse (47). Protein requirements for adult athletes and recreationally active adults is between 1.2 to 2.0 g/kg of bodyweight per day (69), with protein recommendations for adolescent athletes being in a similar range (15, 41). Following injury, it is suggested to increase daily intake of protein to 2.0 to 3.0 g/kg of bodyweight in athletic adults (65), which likely suffices for protein requirements for adolescent athletes.

Carbohydrates: Carbohydrates can provide a source of energy while healing through an injury (65), and aid in muscle adaptations and recovery (69). Due to a decrease in the amount of high-intensity exercise that can be performed while injured, carbohydrate needs are not as large as what is needed in an uninjured athlete (65). Thus, to meet demand while recovering from an injury, up to 60% of daily kcals should come from carbohydrates (65), with an emphasis on complex carbohydrates. Additionally, fatty acids are important in the recovery process as they synthesize several hormones and aid in the absorption of several vitamins (3, 27). Unsaturated fatty acids, such as omega-3 fatty acids may reduce inflammation, thereby making their need instrumental during the recovery process (27). It is recommended to consume good sources of omega-3 fatty acids including fatty fish, walnuts, flaxseed, and avocado, which this lessons includes as suggested food sources (27, 65).

Fluid Intake: Hydration for performance is covered in Lesson 4 of the original PHP, but in this lesson, it is explored in more detail pertaining to injury risk and recovery. Over half of US children are inadequately hydrated (37), and being in this state can increase risk of injury and prolong recovery (10). Muscles on average are 75% water with bones comprising 25% of it, suggesting that a lowered consumption of it could further exacerbate healing of injuries to these structures (27). Males aged 9 to 13 years need at least 8 cups of fluid per day, while females of the same age need at least 7 cups per day (34). Adolescent males aged 14 to 18 years of age, need at least 11 cups of fluid per day, while females of the same age need 8 cups. Thus, it could be hypothesized that an injured youth athlete should strive to meet and exceed these recommendations for fluid consumption.

Lesson B: Micronutrients for Injury Rehabilitation

Lesson B highlights the importance of specific micronutrients that provide a key role in injury rehabilitation (3, 26). Consuming adequate nutrients, including micronutrients, from whole food sources, is a major goal of the PHP curriculum (21). This lesson begins with a discussion on the concerns with the use of dietary supplements to meet micronutrient recommendations such as issues with regulation (20), and possible contamination (40). Each section of the lesson describes how the micronutrient of interest is implicated in the recovery process, how much is needed, other important functions it provides in the body, and suggested foods that are good sources for the micronutrient of interest.

Vitamin D and Calcium: As summarized in Alcock et al. (2024) micronutrients of interest for bone injury rehabilitation include vitamin D and calcium (3). Calcium is needed to increase bone mineral density and bone remodeling such as when following an injury (27). Vitamin D is needed for calcium absorption and maintenance. Children and adolescents between 9 and 18 years old, need 1,300 mg of calcium every day (23). Adolescents between 14- and 18-years old need at least 15 mcg (600 IUs) of vitamin D daily. Food sources of calcium listed in the lesson include milk, yogurt, salmon, fortified fruit juice, and collard greens (27). Good food sources of vitamin D suggested in the lesson includes salmon, fortified milk, tuna, and cashews.

Zinc and Iron: Other micronutrients of interest for muscle injury also include zinc and iron (3). Zinc and iron are both trace minerals that have several important functions in the human body (27). Zinc is involved in hundreds of functions in the body, such as involvement in DNA synthesis and wound healing, and immune system function (27). Zinc is needed for protein synthesis and iron is needed for the transport of oxygen to several tissues in the body which would increase healing (27). Youth aged 9 to 13 years, need 8 mg of zinc per day (23). Male adolescents aged 14-18 years of age need 11 mg of zinc per day, while females of the same age require 9 mg each day. Children aged 9-13 years of age need 8 mg of iron per day (23). Males aged 14-18 years of age need 11 mg of iron per day, and females of the same age need 15 mg per day. Good sources of zinc include dark meat, legumes, shrimp, and nuts (27). Good food sources of iron includes dark meat, and also spinach and cashews.

Vitamins A, C, and E: Vitamin C plays a pivotal role in the synthesis of collagen (3). Similar to vitamin C, vitamin A aids in collagen formation, specifically the laying down of new collagen (65). Vitamin E can reduce muscle breakdown and promote muscle repair (27). Each of these vitamins can reduce oxidative stress and inflammation and improve tissue healing (27). Children aged 9 to 13 years old need 1,200 mg of vitamin C every day, and adolescents aged 14 to 18 years old, need 1,800 mg per day (23). Good food sources of vitamin C include kiwis, green peppers, strawberries, and cantaloupe (27). Youth aged 9-13 years need 600 mcg of retinol activity equivalents (vitamin A) per day, while adolescents aged 14-18 years need 600 mcg of retinol activity equivalents each day (23). Youth aged 9-13 years of age need 11 mg of vitamin E per day, while adolescents over the age of 14 need 15 mg per day (23). Dietary sources of vitamin A include sweet potatoes, pumpkins, spinach, and squash, while good sources of vitamin E include sunflower seeds, apricots, avocados, and almonds (65).

Although not a micronutrient, eating foods high in nitrates, like beets, could theoretically help heal an injury (76). About 20% of the nitrates consumed in food is converted to nitrite by bacteria found in the oral cavity (76). In turn, the stomach transforms this nitrite into nitrous oxide which can cause vasodilation. Thus, more oxygen and nutrients are transported to the injured area, supporting the healing process. A recent systematic review examined nine studies and concluded that short-term consumption of beetroot may accelerate the recovery of muscle soreness and various functional markers due to its antioxidant and inflammatory properties likely exerted by its nitrate content and several phenolic compounds (60). Therefore, it could be assumed that consuming foods high in nitrates and phenolic compounds could expedite the injury healing process. Aside from beets, good food sources of nitrates include spinach, radishes, celery, and rhubarb (36).

Lesson C: Low Energy Availability

Energy availability is the amount of energy available after energy expenditure, that is used for bodily functions (9). Thus, LEA is the state of inadequate energy intake relative to energy expenditure (9) and the prevalence for LEA in athletes ranges from 22% to 58% in a given sport (44). LEA can lead to several negative impacts on performance including decreased muscular strength, decreased endurance performance, and decreased responses to training responses and adaptations (50, 70). Additionally, there is an increased injury risk with LEA (29, 56).

The next section of this lesson discusses how LEA can negatively impact the growth and development of a child or adolescent, potentially resulting in poor bone health, delayed puberty, short stature, and menstrual irregularities (15). It also highlights several signs and symptoms felt by an athlete that could indicate LEA (9, 70).

LEA, with or without the presence of an eating disorder, is a characteristic of the Female Athlete Triad, which is a condition that also includes decreased bone mineral density, and menstrual dysfunction (53, 59). The concept of Relative energy deficiency in sport (RED-S) expands upon the Female Athlete Triad by recognizing a broader range of health consequences including disruptions to the endocrine system, immune system, and cardiovascular health (9). Raising awareness of these signs and symptoms is essential, especially given that knowledge of LEA remains low among both athletes and coaches (44). The lesson concludes with evidence-based strategies to prevent LEA, as well as treatment options to address its underlying causes (9).

Lesson D: Nutrition for Head Injuries

This lesson discusses various nutritional considerations to assist in the healing process for someone who has had a concussion, or other types of mTBI (22, 62). Current concussion rates in youth sports are 4.17 cases per 10,000 athlete exposures (38). There are several nutritional aspects that may support brain health among those recovering from mTBIs (22, 62). Although several macronutrients are considered nutrients of interest during this process (22, 62), this lesson discusses other nutrients and micronutrients (aside from those discussed in previous lessons) that may have a place while recovering from a mTBI, including creatine, magnesium, and flavonoids.

Creatine: Creatine is a compound that is formed in protein metabolism and works to recycle adenosine triphosphate (ATP) for energy metabolism (42). It has been shown that creatine content in the brain is diminished after a mTBI, and increasing its intake could maintain ATP levels in the brain (1, 65). This could help offset injury sustained from the mTBI, such as decreasing protease activation that degrades axon structures (1). Good food sources of creatine listed in this lesson includes lean red meats, fatty fish, pork, and wild game (72).

Magnesium: Magnesium is a trace mineral that has several functions within the body (27). In the brain, magnesium is involved in efficient nerve signaling and maintaining the blood brain barrier (45). Following a mTBI, magnesium levels decrease in the brain (67), and low magnesium levels have been associated with neuroinflammation and neurodegeneration, including several diseases such as Alzheimer’s and Parkinson’s diseases (67). Research has revealed that magnesium supplementation can reduce concussion symptoms in adolescents following injury (67). Youth aged 9 to 13 years of age need 240 mg of magnesium per day (23). Older adolescent, males aged 14-18 years of age need 410 mg or magnesium per day while their female counterparts need 360 mg per day. Good food sources of magnesium include almonds, cashews, peanut butter, and spinach (27).

Flavonoids: Lastly, flavonoids are phytochemicals found in many fruits and vegetables, that have anti-inflammatory and antioxidant effects, which may reduce swelling after a mTBI (28). Blueberries contain high amounts of flavonoids including anthocyanins, which contribute to the blueberry’s dark color (11). Anthocyanins could lower brain inflammation and stress caused by mTBI (30). Laboratory studies have shown beneficial effects from blueberry supplementation on various cognitive performance outcomes and symptoms following a mTBI (43, 68). Therefore, consuming foods high in flavonoids, including blueberries, could offer a benefit for healing from a head injury.

This lesson concludes with additional nutritional considerations for those recovering from a mTBI. For example, it is suggested to eliminate the consumption of caffeine following a mTBI (65). Other suggestions include taking note of any foods or drinks that cause vomiting or feelings of nausea, and reducing their consumption for a period of time while mTBI symptoms decrease (72).

Lesson E: Nutrition and Sleep for Injury Reduction and Recovery

This lesson highlights the importance of sleep for performance and injury recovery (19, 49). Youth athletes not getting enough sleep are 1.7 times more likely to get injured (52). School-aged children need 9-11 hours of sleep each night, while teenagers need 8-10 hours of sleep per night (31). It is likely an injured athlete should aim for the upper amount of sleep needed per day. Currently, adolescents aged 13-18 years of age are getting on average 7.7 hours of sleep per night, slightly less than the minimum amount needed (48). Several nutrients have been identified that can naturally aid in hormone regulation associated with sleep (55).

Melatonin: Melatonin is a hormone secreted by the pineal gland that is involved in circadian rhythm and increases total sleep time and may reduce time to fall asleep (13, 55). It is found naturally in several foods including tart cherries (18, 51). In addition, tart cherries include other constituents that have anti-inflammatory and antioxidant effects, which may aid in sleep and recovery (8). Other foods with a high melatonin content include milk, pineapples, oranges, and bananas (18, 55).

Serotonin: Serotonin is another hormone involved in sleep by synthesizing hypogenic substances that influence sleep quality (7, 55). Kiwi fruits are a good source of serotonin and contain several minerals, dietary fiber, and phytochemicals that also may aid in sleep (18, 55).

This section of the lesson also includes other nutritional considerations for quality sleep. For example, some foods that contain caffeine, can make it difficult to fall asleep and the recommendation is to reduce or eliminate its intake closer to bedtime (33). This lesson concludes with tips on how to establish an effective sleep routine such as minimizing screen time before it (33).

Lesson F: Gastrointestinal Issues and Sport

This lesson addresses common GI issues encountered in sport and concludes with practical applications for maintaining gut health.

Nausea and Vomiting: Nausea and vomiting are frequent complaints among athletes across various disciplines (77). These symptoms may result from elevated levels of norepinephrine reducing splanchnic blood flow to the gut, delayed gastric emptying, or increased production of gastric bile acids (77). This lesson outlines several risk factors that may contribute to these symptoms along with simple strategies to help prevent them.

Diarrhea: Diarrhea is a common condition experienced by athletes, particularly among endurance athletes (77). Proposed mechanisms include the secretion of vasoactive intestinal peptide which relaxes smooth muscle in the digestive system (35), and changes in gut motility (77). Many of the risk factors associated with diarrhea overlap with those linked to nausea and vomiting. This section concludes with evidence-informed approaches for minimizing the risk of diarrhea during training and competition.

Heartburn: Heartburn is another GI issue sometimes encountered by athletes during exercise and sport and can be caused by increased abdominal pressure, changes in posture, and changes in exercise intensity (74). Additionally, consuming large meals prior to exercise, not being properly hydrated, and having high levels of stress or anxiety can also trigger heartburn. Chronic heartburn could be caused by gastroesophageal reflux disease or GERD (74). This section provides strategies to prevent heartburn during practice or a game, with an emphasis on taking note of such foods that sometimes cause heartburn in an individual.

This lesson concludes by discussing several strategies to maintain gut health and gut microbiota which may impact immunological function and thus injury risk and recovery from them (75). Rationale for its inclusion within this lesson is from the US Olympic & Paralympic Committee sports nutrition handout on nutrients for GI injury (71). Consuming foods high in probiotics may maintain digestion and absorption while also preventing several GI issues described in this lesson (71). Prebiotic fibers are a type of fermentable fiber that stimulates intestinal bacteria growth and activity (64). In addition, prebiotic fiber consumption is associated with several other benefits including increasing the absorption of calcium, improving cognitive health, and reducing risk of some diseases (14). Therefore, it is important to incorporate prebiotic fibers into one’s diet.

CONCLUSIONS

Nutrition is a cornerstone of health and performance for adolescent athletes not only supporting their growth and development but also their ability to train, compete, and recover effectively (15). Integrating sound nutrition practices into youth athlete development programs is essential for promoting lifelong well-being and optimal athletic potential (16). In addition to enhancing performance, proper nutrition can play a key role in preventing injuries and accelerating recovery when injuries occur (3). To emphasize these critical areas, several new lesson have been added as targeted addendums to the PHP curriculum (25). When combined with the original PHP content, these additions aim to strengthen both general and sport-specific nutrition behaviors, equipping young athletes with the knowledge and habits needed to thrive on and off the field.

Following an injury, it is important to consume adequate kcals from protein, carbohydrates, and unsaturated fatty acids, along with being properly hydrated to facilitate recovery (3). Emphasizing certain micronutrients from food may also improve recovery from injury (3). Additionally, nutritional support is needed for athletes recovering from an mTBI (65). LEA is a common problem in youth sports and understanding its consequences and how to prevent it are important for reducing injury risk (9). Getting adequate sleep is important not only for athletic performance, but also injury prevention and healing from an injury (19, 49). Although not a direct injury caused by sport, GI issues can occur during it, and can be prevented using evidence-based nutritional strategies (77). Next steps are to examine adolescent knowledge of nutritional best practices for recovering from sports-induced injuries.

APPLICATIONS IN SPORT
These supplemental lessons are to serve as adjunct lessons to the PHP curriculum and to provide youth athletes with knowledge on injury management and other sports nutrition topics not otherwise discussed in athletic circles. Additionally, the hope is to encourage further research in this understudied area and add to the growing body of literature examining nutrition practices for injury management in youth athletes.

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Troy Palmer2025-09-25T16:05:07-05:00February 18th, 2026|Research, Sport Education, Sport Training, Sports Medicine, Sports Nutrition|Comments Off

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).

Center Backs (CB) (n = 4)
Outside Backs (OB) (n = 5)
Midfielders (MID) (n=6)
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 (HSR_REL) and Sprint Distance (SD_REL). 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 played	5,855.8 ±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 Defender	106.8 ± 14.4 Significantly greater than Center Back Defender	106.8 ±12.6 Significantly greater than Center Back Defender	93.8 ± 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 Defender	12.96 ±4.01 Significantly greater than Center Back Defender	13.18 ± 4.21 Significantly greater than Center Back Defender	7.53 ± 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 hour	3.45 ± 1.98	6.06 ± 2.64 Significantly greater than Center Back Defender Significantly different than Midfielders	5.53 ± 1.85 Significantly greater than Center Back Defender Significantly different than Midfielders	3.05 ± 1.92	4.72 ± 2.53

Relative Total Distance (TDREL)

A one-way ANOVA revealed a significant difference in positions for TD_REL, 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 HSR_REL, 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 SD_REL, 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 TD_REL (105 ± 14.5 m/min), HSR_REL (11.3 ± 4.2 m/min) and SD_REL (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 HSR_REL, with FWDs covering higher distances than MIDs and CBs. Whereas OBs covered more HSR_REL 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 SD_REL 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 (TD_REL), relative high-speed running distance (HSR_REL), and relative sprint distance (SD_REL), 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

Alexander, R. (2014). Physical and Technical Demands of Women’s Collegiate Soccer. Electronic Theses and Dissertations, 2421. https://dc.etsu.edu/etd/2421
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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
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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
Hopkins, W. G. (2002). A scale of magnitude for effect statistics. http://www.sportsci.org/resource/stats/effectmag.html.
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
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Troy Palmer2025-09-25T15:33:55-05:00February 4th, 2026|Research, Sport Education, Sport Training, Sports Coaching, Sports Health & Fitness, Women and Sports|Comments Off

Understanding the Decline of Lacrosse Officials in the Midwest: A Study on Retention Challenges and Stakeholder Influence

Authors: Nicholas Zoroya¹, Joshua Greer², Carla Blakey³

Corresponding Author:

Nicholas Zoroya

20932 Hasenclever Dr., South Lyon, MI 48178

(248)420-9200, [email protected]

¹ Madonna University

² Cumberland University

³ University of Alabama

ABSTRACT

Purpose:

This study examines the ongoing decline of lacrosse officials in the Midwest by exploring how stakeholder behavior, organizational support, and personal motivations affect officials’ decisions to continue or leave the profession. The goal is to identify key factors contributing to attrition and provide practical recommendations for improving retention.

Methods:

A mixed-methods survey design was used to collect data from 55 lacrosse officials who had officiated in the Midwest within the past five years. Participants responded to a series of closed-ended questions assessing demographics, officiating experience, and interactions with coaches, fans, and players. Open-ended responses were also collected to contextualize and support quantitative results. Data were analyzed using descriptive statistics, and illustrative quotes were used to reinforce common trends.

Results:

Most participants were White males over the age of 40, with more than a decade of officiating experience. While abuse from players was reported less frequently, officials indicated that verbal abuse from coaches and fans occurred often and significantly impacted their officiating experience. Additionally, officials expressed mixed feelings about the support they receive from associations and assignors. Despite these challenges, most participants reported a strong personal connection to the game and cited their passion for lacrosse and desire to give back as primary reasons for continuing. A subset of respondents, however, acknowledged that negative experiences have made them consider leaving the profession.

Conclusions:

Findings highlight the important role personal passion plays in keeping officials engaged despite a lack of institutional support and ongoing negative stakeholder interactions. Without meaningful changes to reduce abuse and increase organizational support, the officiating pipeline will remain vulnerable. The study also raises concerns about the lack of demographic diversity in lacrosse officiating, warranting further exploration.

Applications in Sport:

The results have practical implications for lacrosse governing bodies, assignors, and administrators. Improving sideline behavior, increasing compensation, offering mentorship, and expanding recruitment efforts to underrepresented groups could significantly improve retention and build a more sustainable and inclusive officiating workforce.

Key Words: officiating, lacrosse, referee retention, stakeholder behavior, sport management

INTRODUCTION

The shortage of sports officials, particularly in youth and high school sports, is a pressing issue that threatens organized athletics’ operational integrity and sustainability. The National Federation of High School Associations (NFHS) found that around 50,000 individuals have stopped serving as high school officials since the onset of the pandemic in 2020 (Niehoff, 2022). This decline can be attributed to several interrelated factors, including occupational stress, abuse from spectators, insufficient support systems, and inadequate training opportunities for officials.

Literature Review

The shortage of sports officials is increasingly attributed to the rising incidence of verbal and physical abuse directed at referees by players and spectators. Research indicates that abusive behavior, particularly at the grassroots level, significantly contributes to high turnover rates, with negative experiences reducing officials’ willingness to continue in the profession (Dawson et al., 2021; Rayner et al., 2016). Dawson et al. (2021) highlight the alarming decline in the number of qualified officials, stressing that this culture of abuse not only affects officials but also threatens the integrity of competitive sports. Additionally, issues such as harassment and discrimination, especially against female officials, further intensify attrition, creating a hostile environment that undermines the overall health of sports communities (Marshall et al., 2022; Webb et al., 2020).

In addition, the lack of adequate support, resources, and effective training opportunities exacerbates attrition, as many organizations fail to provide the necessary infrastructure to sustain officials’ careers (Webb et al., 2020; Tingle et al., 2014). Insufficient professional development and an aging workforce further compound the issue, necessitating innovative strategies to attract and retain younger officials (Ryan et al., 2014; Barnhill et al., 2018; Pierce et al., 2021). This literature emphasizes the multifaceted challenges in officiating and highlights the critical need for systemic changes to address the issues of abuse, support, and recruitment.

The Decline of Lacrosse Officials

The decline of lacrosse officials in the Midwest has raised concerns regarding the sustainability of officiating in growing sports leagues. In recent years, the shortage of qualified officials has emerged as a critical issue. Lacrosse, a sport that has enjoyed significant regional growth in the Midwest, now faces challenges similar to those observed in other sports arenas (Ridinger et al., 2017). The decline in the number of lacrosse officials not only impedes game integrity but also affects the overall development of the sport. Existing literature has shown that multifaceted factors, including motivational changes, psychosocial stressors, and insufficient support structures, play essential roles in the retention and attrition of referees (Livingston & Forbes, 2016; Ridinger, 2015).

Negative Stakeholder Behavior

The decline in the number of lacrosse officials in the Midwest can be tied to negative stakeholder behavior, particularly from parents, coaches, and fans. This trend is troubling, as officials play a critical role in maintaining the integrity and safety of the game. The psychological impact of abuse from various stakeholders on referees cannot be overstated. Studies indicate that officials often experience significant stress and mental health challenges due to verbal abuse and aggression directed at them during games, which can lead to a decline in their overall job satisfaction and motivation (Breslin et al., 2022; Giel & Breuer, 2021).

It is important to note that the abuse received by officials, from players, coaches, and spectators, is frequently normalized within many sports environments. Research in sports such as rugby and football demonstrates that officials often report feeling overwhelmed by hostility from these groups (Webb et al., 2019; Webb et al., 2018). This hostility not only affects the officiating experience but can also deter potential new referees from entering the field. Furthermore, the retention rates of officials are directly influenced by the social interactions they have with these stakeholder groups, and the lack of positive reinforcement or sportsmanship has been shown to exacerbate dropout intentions (Giel & Breuer, 2021).

The influence of these stressors is particularly notable in the context of youth sports, where the pressure from parents and coaches can create a toxic atmosphere for officials trying to enforce rules and manage games. Coaches, in their roles, often have a substantial impact on how players perceive referees, which in turn affects the emotional atmosphere during matches (Webb, 2020). If coaches model negative behaviors, such as disrespect towards referees, it can lead to a cycle of abuse where players mimic these actions, further isolating officials and intensifying their negative experiences (Webb et al., 2018).

Interventions aimed at increasing awareness and promoting mental health support among referees are essential in addressing this decline. Recommendations have been made for mental health training for stakeholders to improve the overall environment surrounding officiating and reduce instances of abuse (Breslin et al., 2022). Additionally, stakeholder education on the consequences of negative behaviors towards officials can help reshape perspectives and foster a more respectful sporting culture. Such measures would not only help in maintaining a robust pool of lacrosse officials but also promote a healthier, more inclusive environment for all participants in the sport.

Abuse
Abuse, both verbal and physical, is a significant contributor to officiating attrition, with numerous studies highlighting its impact on officials’ mental health and intentions to quit. Brick et al. (2022) found that nearly all Gaelic Games officials surveyed (94.29%) had encountered verbal abuse, and almost one in four (23.06%) had experienced physical abuse during their careers. Verbal abuse was shown to be frequent and directly linked to mental health issues and quitting intentions, with distress acting as a mediating factor. Similarly, Webb et al. (2018) documented the prevalence of both verbal and physical abuse in rugby league, finding that emotional abuse (i.e., intimidation, swearing, and threats) and physical aggression (i.e., pushing and hitting) significantly reduced job satisfaction. These hostile environments, particularly when abuse is persistent and unaddressed, contribute to officials leaving their roles.

The impact of abuse on officiating extends across various sports and levels. For instance, Ridinger et al. (2017) revealed that 42% of 2,485 high school referees identified abuse as the most significant challenge in their roles, and 10% cited abuse as a factor in their intention to quit. This aligns with findings from Kavanagh et al. (2021), who reported that abuse in youth soccer led to emotional exhaustion and burnout among officials. Tingle et al. (2014) also noted that the normalization of verbal abuse within sports culture exacerbates the negative effects on officials, especially for newcomers lacking support systems. Collectively, these studies underscore the need for sports organizations to implement proactive abuse prevention measures and institutional support to mitigate attrition and improve the officiating experience.

Unsupportive Interactions
Unsupportive social dynamics play a critical role in officials’ decisions to leave their positions. Warner et al. (2013) examined the effects of problematic peer interactions and inadequate mentoring in sports such as lacrosse, revealing how these relational shortcomings contribute to officiating attrition. When officials lack meaningful support from mentors or peers and feel disconnected from a broader officiating community, their engagement and satisfaction decline. The Referee Retention Scale (Ridinger et al., 2017) identifies several social factors that contribute to retention, including several factors that address a sense of community and mentoring support. These elements reflect the importance of fostering interpersonal relationships that reinforce a positive officiating experience (Table 1).

Table 1
Key Factors Contributing to Referee Retention

Factor Name	Description
Administrator Consideration	Level of perceived fairness and consideration from assigners and administrators
Mentoring	Support and encouragement from a mentor or a friend to become involved with officiating
Sense of Community	Perceived sense of belonging to a supportive community of officials
Lack of Stress	Infrequent encounters with stressful situations related to officiating

Note. Adapted from Ridinger, L. L., Kim, K. R., Warner, S., & Tingle, J. K. (2017). Development of the Referee Retention Scale. Journal of Sport Management, 31(5), 514–527.

In addition to interpersonal issues, organizational shortcomings also undermine retention efforts. Warner et al. (2013) highlighted how insufficient policy frameworks and administrative neglect exacerbate attrition, particularly when officiating structures fail to proactively address the evolving needs of officials. The Referee Retention Scale provides a methodological foundation for identifying these structural deficiencies. Notably, factors such as “Administrator Consideration” and “Lack of Stress” underscore the role of fair management practices and manageable work environments in referee satisfaction. Furthermore, Livingston and Forbes (2016) and Ridinger (2015) emphasize the necessity of aligning recruitment and retention strategies with officials’ motivations and expectations. Collectively, these findings stress that without intentional and sustained institutional support, officiating organizations risk ongoing loss of personnel due to preventable burnout and disengagement.

Referee Retention

Research on referee retention has provided useful insights into the systemic and individual challenges impacting officiating roles. Ridinger et al. (2017) developed the Referee Retention Scale to assess factors such as job satisfaction, perceived organizational support, and the prevalence of abuse, all of which are directly linked to declining retention rates. Their work underscores that referee attrition is often precipitated by issues that extend beyond the administrative domain and delve into psychosocial and environmental stressors. Similarly, Livingston and Forbes (2016) investigated the evolving motivations of amateur sport officials and confirmed that changes in personal goals and external support diminish retention levels over time. Their study, although centered on Canadian officials, provides a framework that is applicable to the Midwest context, where similar socio-organizational dynamics are at play.

Ridinger (2015) compared the experiences of baseball umpires and lacrosse officials, revealing common constraints such as economic shortages and inadequate mentorship. This comparative analysis highlights that lacrosse officials, in particular, face challenges that are exacerbated by limited training opportunities and the absence of community-based support systems. In other research pertinent to community sports, Baxter et al. (2021) examined the experiences of female volunteer officials, outlining barriers and motivators that resonate with broader issues affecting retention. Although focused on gender-related dimensions of officiating, their findings reinforce the notion that organizational policies and social support are crucial to sustaining a committed officiating workforce.

The literature clearly indicates that the decline of lacrosse officials in the Midwest is a complex phenomenon influenced by issues of retention, support deficiency, and exposure to abuse. By synthesizing insights from multiple studies, this review stresses the importance of a comprehensive strategy that includes recruitment, retention, and preventive measures to improve the working environment for lacrosse officials. Future research and policy changes informed by these findings will be crucial in reversing the downward trend and ensuring the long-term sustainability of lacrosse officiating.

Conclusion

Despite a growing body of literature on officiating attrition, few studies have examined the distinct cultural and geographic dynamics affecting lacrosse officials in emerging regions like the Midwest. The reviewed research highlights a multifaceted crisis, with lacrosse serving as a representative case of the broader challenges afflicting youth and high school sports. Across regional and national contexts, verbal abuse and safety concerns have emerged as key contributors to attrition. In the Midwest, the shortage of lacrosse officials is impeding sport development and compromising game quality.

National survey findings from NASO and NFHS reinforce the severity of the crisis, revealing that a majority of new officials depart within three years due to burnout, safety concerns, and undervaluation. While recent initiatives, such as the NFHS National Officials Consortium Summit and the #BecomeAnOfficial campaign, represent positive steps forward, the literature suggests that these efforts must be part of a broader, coordinated strategy. Interventions focused on stakeholder education, mental health support, structured mentorship, and the public acknowledgment of officials’ contributions are necessary to reverse current trends. Sustaining officiating in lacrosse will require systemic change, cultural realignment, and a renewed commitment to valuing those who enforce the rules and protect the integrity of the game.

METHODS

Purpose

The purpose of this study is to examine the underlying causes of the declining number of lacrosse officials in the Midwest. Specifically, it seeks to determine how stakeholder interactions, support structures, and personal motivations influence officials’ decisions to remain active in the field. The study is designed to inform retention strategies and stakeholder education efforts.

Methodology

Participants

Participants in this study were 55 lacrosse officials who officiated games across the Midwest region of the United States. Eligibility criteria required participants to have officiated lacrosse at any level (youth, high school, college, or club) within the past five years in a Midwest state. Participants were predominantly male and white, and ranged in age from 25 to 72 years old, with officiating experience spanning from less than 1 year to over 30 years. Participation was voluntary, and no compensation was provided.

Procedures

Data was collected via an anonymous online survey distributed through Qualtrics. Recruitment was conducted through email invitations sent to lacrosse officiating associations, assignors, and personal networks within the officiating community, as well as through social media posts targeting officials in the Midwest. The survey remained open for three weeks, with one reminder sent midway through the collection period. Prior to data collection, the study received Institutional Review Board (IRB) approval from Madonna University. Participants provided informed consent at the beginning of the survey.

The survey consisted of both closed and open-ended questions. Closed-ended items collected demographic information (age, gender, race/ethnicity, years of officiating experience) and information on perceived challenges in officiating (e.g., pay, scheduling, respect from stakeholders). Open-ended questions invited participants to elaborate on their experiences, including reasons for continuing or discontinuing officiating and suggestions for improving the officiating experience.

Data Analysis

Quantitative data were analyzed using descriptive statistics (frequencies, percentages, means) to summarize participant demographics and the prevalence of key issues identified by officials. Open-ended responses were reviewed to identify illustrative quotes that reinforced or provided examples of the quantitative findings. Qualitative responses were not formally coded or thematically analyzed but were used to add narrative context to the statistical results.

RESULTS

A total of 55 lacrosse officials from the Midwest region completed the survey. Participants ranged in age from 23 to 67 years (M = 45.8, SD = 11.2), with the majority identifying as male (85%) and White/Caucasian (94%). Officials reported working across multiple states, most commonly Indiana, Illinois, Michigan, Ohio, and Wisconsin. On average, participants had 14.3 years of officiating experience, with nearly all officiating at the youth and high school levels (92%). Additionally, 64% reported officiating collegiate lacrosse, and 9% officiated at the professional level.

Officials were asked about their experiences with negative interactions from various stakeholders. Verbal abuse from coaches was reported as occurring “sometimes” by 58% of respondents and “often” by 16%. Similar patterns emerged regarding fans and parents, with 49% reporting “sometimes” and 22% reporting “often” experiencing verbal abuse. Abuse from players was less frequent, with 51% of officials reporting “rarely” and 38% reporting “sometimes.” Despite these negative interactions, officials rarely reported fearing for their personal safety, with 74% indicating “never” and 18% “rarely” feeling unsafe while officiating.

Perceptions of support from officiating associations were mixed. While 42% of respondents felt “often” supported by their associations, 33% reported “sometimes” feeling supported, and 25% “rarely.” When asked how often they considered quitting due to negative experiences, 56% reported “never” considering leaving officiating, 24% “rarely,” 11% “sometimes,” and 9% “often.”

Qualitative responses provided further insight into officials’ motivations and concerns. Officials frequently cited a love for the game, a desire to give back to the sport, camaraderie with fellow officials, and ensuring opportunities for young athletes as primary reasons for continuing to officiate. One participant explained, “I won’t stop until my body no longer allows me to officiate,” while another noted, “If associations or assignors supported officials more, I’d feel better about continuing.” Conversely, low pay, spectator abuse, insufficient support from associations, and the physical demands of officiating as they age were commonly cited factors contributing to potential attrition.

Discussion

The findings of this study provide a nuanced look into the factors influencing lacrosse officials’ retention in the Midwest. Despite frequent reports of verbal abuse from coaches, players, and fans, many respondents reported continuing to officiate due to intrinsic motivations such as a love of the sport and a desire to give back. This aligns with prior research emphasizing passion and sport commitment as key drivers of officiating persistence. Finding joy in officiating can lead to better psychological outcomes, fostering an environment where officials are more likely to continue their engagement with the sport (Carson et al., 2020).

However, respondents also highlighted significant deterrents to retention, including low compensation, lack of recognition, poor treatment from stakeholders, and limited support from assigning organizations. These challenges are consistent with broader officiating literature identifying unsupportive environments and abuse as predictors of attrition. Research supports the notion that the challenges of managing player dynamics and external pressures, such as crowd noise, significantly impact officials’ performance and mental states (Carter et al., 2024). Therefore, the emotional and psychological investment in sport, empowered by both passion and commitment, is essential in nurturing a sustained career in officiating.

Interestingly, while many officials expressed dissatisfaction with aspects of the officiating experience, few indicated plans to immediately stop officiating, suggesting a complex interplay between commitment, tolerance for negative experiences, and practical constraints.

The demographic homogeneity of the sample raises additional concerns. The overwhelming representation of older White men suggests potential gaps in recruitment or retention efforts targeting women and racial minorities. Given lacrosse’s growing popularity and emphasis on inclusion, this lack of diversity warrants further investigation and intervention.

Collectively, these findings reinforce the need for officiating associations and lacrosse governing bodies to implement more robust training, mentorship, and support systems. Addressing verbal abuse, improving communication, and recognizing officials’ contributions may improve retention. Ultimately, sustaining a high-quality officiating workforce requires addressing both systemic challenges and individual experiences.

Future Research

While this study offers valuable insight into the experiences of lacrosse officials in the Midwest, it also highlights several opportunities for future research. First, the demographic composition of respondents (predominantly White, male, and middle-aged or older) suggests a need to explore barriers to entry and advancement for underrepresented groups in officiating. Investigating the experiences of women, racial minorities, and younger officials could help identify structural or cultural factors limiting diversity in the officiating pipeline.

Additionally, future research could expand beyond the Midwest to assess whether similar trends exist nationally or vary by region. Comparative studies across different competitive levels (youth, high school, collegiate, professional) may also reveal distinct challenges and support mechanisms. Finally, longitudinal research could track officials over time to better understand career trajectories, burnout risk, and retention strategies. Together, these avenues of inquiry can build a more comprehensive understanding of officiating challenges and inform evidence-based recruitment and retention initiatives.

CONCLUSIONS

This study sheds light on the complex realities facing lacrosse officials across the Midwest, revealing a profession challenged by inadequate pay, lack of respect from key stakeholders, inconsistent scheduling practices, and minimal institutional support. Despite these hurdles, officials overwhelmingly cited their love of the game, passion for supporting athletes, and commitment to the sport as primary motivators for continuing their work. This finding underscores a critical dynamic: lacrosse officiating, particularly in under-resourced regions, is being sustained largely by the intrinsic dedication and personal investment of its officials rather than by systemic support or professional incentives.

Without this fierce passion for the sport, it is likely that attrition would be even higher. Many participants described tolerating negative treatment, logistical difficulties, and low compensation solely because of their deep-rooted connection to lacrosse. While this dedication is admirable, it raises serious concerns about sustainability and burnout. The profession cannot rely indefinitely on goodwill and personal sacrifice without addressing the structural and cultural issues contributing to official dissatisfaction and turnover.

These findings highlight the urgent need for action to support and retain lacrosse officials and ensure the sport’s long-term sustainability. Ultimately, this study emphasizes that lacrosse officiating in the Midwest stands at a crossroads.

APPLICATION IN SPORT

The findings of this study have clear implications for lacrosse governing bodies, officiating associations, assignors, coaches, and athletic administrators seeking to address the shortage of officials. First, targeted efforts to reduce verbal abuse and improve sideline behavior are critical for creating a more supportive environment that encourages retention. Educational workshops for coaches, parents, and athletes focused on respecting officials may help shift cultural norms and reduce negative interactions.

Second, the study highlights the need for stronger mentoring and peer support systems within officiating communities. Developing formal mentorship programs that connect new officials with experienced referees could foster a greater sense of belonging and resilience, improving retention among newer and younger officials. Assigning bodies should prioritize community-building activities, recognition initiatives, and accessible professional development opportunities to sustain engagement.

Additionally, improving compensation and scheduling practices may directly influence retention by addressing key logistical frustrations reported by officials. Providing consistent game assignments, clear communication, and timely pay can increase satisfaction and encourage officials to remain active longer.

Finally, the demographic homogeneity observed in this study signals an urgent need to broaden recruitment efforts to underrepresented groups, including women and racial minorities. Intentional outreach, training scholarships, and inclusive recruitment messaging may help diversify the officiating pipeline and ensure the sport’s continued growth. Implementing these strategies can help sport leaders, administrators, and policy makers foster a more sustainable, inclusive, and supportive officiating environment in lacrosse and beyond.

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Troy Palmer2025-07-21T14:29:22-05:00December 9th, 2025|Contemporary Sports Issues, General, Research, Sport Training, Sports Coaching, Sports Studies|Comments Off

The Evolving Role of Technology and Analytics in Coaching: Transforming Practices and Enhancing the Impact on the Profession

Authors: Lawrence W. Judge¹,Matt Moore²

¹College of Health, Ball State University

² College of Social Work, University of Kentucky

Corresponding Author:

Dr. Matt Moore

Associate Dean of Academic and Student Affairs

College of Social Work

University of Kentucky

601 Patterson Office Tower

Lexington, KY 40506

[email protected]

ABSTRACT

This commentary examines the evolving landscape of coaching, focusing on the transformative integration of artificial intelligence, advanced analytics, and real-time performance tracking. These technologies enhance athlete monitoring, optimize decision-making, and redefine coaching pedagogy. However, the rapid adoption of data-driven methodologies presents challenges, including resistance among experienced coaches and ethical considerations regarding athlete privacy. This commentary explores strategies for effectively integrating coaching tools into coaching while preserving the critical human elements of mentorship and decision-making. As the digital age reshapes sports, embracing innovative technologies is essential for meeting athletes’ complex, evolving needs and achieving performance goals. This integration ensures a balance between innovation and the enduring human elements of coaching, elevating the profession to unprecedented levels of effectiveness and impact.

Keywords: Leadership, Development, Strategy, Mentoring, Performance, Education

Introduction

In the evolution of coaching, technology has transitioned from rudimentary tools to sophisticated systems that have transformed the way athletes are trained and developed (Zhang et al., 2023). Early coaching methodologies heavily relied on basic instruments such as stopwatches, tape measures, and handwritten training logs to assess performance metrics and track progress (Sohail et al., 2022). These tools, while limited, served as the foundation for the integration of technology into coaching practices. Video analysis, introduced in its nascent stages, provided groundbreaking insights into athletes’ movements, enabling coaches to refine techniques with unprecedented precision (Cronin et al., 2019). Similarly, the advent of heart rate monitors and early biomechanical sensors marked the initial shift toward data-driven decision-making in athletic training (Goudsmit et al., 2022).

As technology evolved, so did its application in sports. The introduction of analytics into coaching practices in the 1970s marked a significant turning point (Passmore & Woodward, 2023). One notable example is the Oakland Athletics’ pioneering use of statistical analysis under General Manager Billy Beane, a methodology that revolutionized talent evaluation and team composition in professional baseball (Abisaid & Cassidy, 2017). Popularized as the “Moneyball” approach, this strategy demonstrated the potential of empirical data to transcend traditional methods and optimize performance, sparking a broader analytics revolution across various sports (Gin, 2018). Building on this foundation, modern coaching now incorporates advanced technologies such as wearable devices, artificial intelligence (AI), virtual and augmented reality, and machine learning algorithms to deliver real-time performance analytics, injury prevention insights, and skill acquisition strategies (Catapult, 2023; Müller et al., 2022; Wang et al., 2024).

Despite these advancements, the adoption of technology in coaching presents challenges, particularly among seasoned professionals accustomed to traditional practices (Judge et al., 2024). Resistance to change underscores the importance of balancing innovative tools with the human elements of coaching, including mentorship, trust, and the nuanced understanding of individual athletes’ needs (Passmore & Woodward, 2023). Effective integration of technology requires not only familiarity with innovative tools but also an appreciation of how these tools can complement established coaching principles, rather than supplant them. Additionally, data analytics plays a crucial role in helping athletes evaluate their performance by providing insights into key metrics, enabling personalized training strategies and enhancing decision-making to improve outcomes (Bennett & Szedlak, 2023).

This commentary explores the historical evolution, current applications, and future potential of technology in coaching, offering a comprehensive framework for understanding its transformative role in improving athlete performance and competitive outcomes. By examining how technology integrates with and enhances traditional coaching practices, the work aims to provide actionable insights for leveraging innovation while preserving the foundational principles that define the profession and the commitment to maximizing athlete potential. This dual focus ensures that coaches can navigate the rapidly advancing digital landscape without compromising the interpersonal connections essential to athlete development (Bishop et al., 2023).

Current Roles of Technology in Coaching

The integration of advanced technologies, particularly analytics and AI, has significantly transformed the landscape of sports coaching, enabling precise, evidence-based approaches to athlete development (Catapult, 2023; Zhang et al., 2023). These tools allow coaches to analyze extensive datasets, offering actionable insights for decision-making, personalized training design, and effective athlete monitoring (Baraniuk, 2015; Zhang et al., 2023). Historically, coaching was driven by intuition, anecdotal evidence, and experiential knowledge (Sohail et al., 2022). The advent of AI and advanced analytics has augmented these traditional methods, introducing unparalleled precision and efficiency into coaching practices (Judge et al., 2024). Furthermore, these advances in technology empower athletes to self-reflect on their performance by providing real-time, data-driven insights that foster deeper understanding and targeted improvements (Bennett & Szedlak, 2023).

Modern performance analytics tools provide granular assessments of key metrics, including speed, distance, exertion levels, and tactical patterns (Judge et al., 2021). These insights enable tailored interventions that optimize training regimens and improve competitive tactical strategies that engage coaches and athletes in a collaborative process (Talha & Sohail, 2023). Wearable technologies, such as GPS trackers and heart rate monitors, deliver real-time data on physiological responses and recovery profiles, enhancing injury prevention and facilitating optimal workload management (Catapult, 2023; Müller et al., 2022). Additionally, cloud-based platforms streamline communication between coaching teams and athletes by enabling seamless sharing of playbooks, video analyses, and tactical adjustments (Cronin et al., 2019).

Innovations in skill acquisition and cognitive training have further elevated coaching methodologies. Virtual reality (VR) and augmented reality (AR) create immersive simulations of competitive environments, fostering improved decision-making and technical precision under realistic conditions for both coaches and athletes (Müller et al., 2022). Technologies such as PlaySight© and TrackMan© provide sport-specific feedback on mechanics and strategy, offering coaches and athletes valuable data to refine performance (Bishop et al., 2023; Stanescu, 2018). Emerging innovations, including Catapult’s Vector S7/T7 wearable GPS-tracking systems, deliver detailed insights into athlete movement, speed, and workload, facilitating personalized training and injury prevention strategies (Catapult, 2023). Similarly, Omega’s AI-powered systems analyze historical and real-time performance data, generating comprehensive feedback to enhance race preparation with data related to split times, stride frequency, pacing, and race strategies (Wired, 2023).

These innovative technologies bridge the gap between practice and competition by enabling targeted skill development, data-driven decision-making, and tailored performance optimization (Catapult, 2023; Stanescu, 2018). Data metrics and AI in sport go beyond what a coach can see by providing in-depth, quantifiable insights into an athlete’s biomechanics, performance trends, and recovery patterns, enabling a more comprehensive understanding of strengths and areas for improvement that might otherwise be overlooked (Bishop et al., 2023).

Despite these advancements, it is critical to maintain a balance between technology and traditional coaching practices. Over-reliance on automated systems can undermine essential human elements such as emotional intelligence, trust, and mentorship, which are fundamental to effective coaching (Goudsmit et al., 2022). Coaches must critically assess and integrate tools that align with their methodologies and philosophies while preserving the interpersonal dynamics that underpin athlete development (Judge et al., 2024). By synthesizing advanced technologies with traditional coaching principles, practitioners can create comprehensive training environments that address the physical, cognitive, and emotional dimensions of athletic performance (Passmore & Woodward, 2023).

This section underscores the importance of blending coaching tools with evidence-based practices to maximize their impact while safeguarding the human-centric essence of coaching. Integrating wearable sensors, cognitive training platforms, and collaborative digital tools into coaching workflows ensures an integrated approach that meets the multifaceted demands of modern sports (Catapult, 2023). This integration is essential for meeting modern athletes’ expectations in highly competitive environments. Furthermore, the data-centric revolution is complemented by the potential for greater customization and enhanced feedback mechanisms, which together can pave the way for more effective coaching interventions and superior athletic performance (Zhang et al., 2023) (See Table 1).

Future Roles of Technology in Coaching

Advanced technologies form the backbone of evidence-based coaching strategies, facilitating a personalized approach tailored to each athlete’s physiological and psychological needs (Cronin et al., 2019; Rajasinghe et al., 2022). As such, the integration of experimental technologies not only enhances performance optimization but also reshapes the future role of the coach as a data-driven strategist and mentor. Athletes are also increasingly becoming consumers of data, using detailed performance metrics to engage in self-reflection, identify areas for improvement, and make informed decisions to enhance their training and competitive outcomes (Bishop et al., 2023). Among these innovations, technologies like TrackMan© stand out by offering real-time data on critical metrics, such as release angles, velocity, and distance in track and field events. Such precise measurements empower coaches to refine techniques with unprecedented accuracy (Judge et al., 2021). Similarly, in golf, TrackMan© enhances swing mechanics and ball trajectory analysis, enabling targeted adjustments that optimize performance outcomes (Bishop et al., 2023). Reflexion’s touchscreen lightboards and mixed reality headsets, enhance athletes’ focus, decision-making skills, and mental resilience by strengthening cognitive abilities critical for competitive performance (Reflexion, 2023). PlaySight© empowers tennis players and coaches by providing instant video feedback and detailed data points, such as stroke speed, ball placement, rally length, serve percentages, and location of unforced errors, allowing athletes to analyze their technique, adjust strategies, and track progress with precision (Stanescu, 2018). PlaySight and other advanced software systems save coaches and athletes valuable time by automating video analysis and providing instant feedback, allowing coaches and athletes to focus more on strategy and individualized development rather than manual data collection and review (Judge et al., 2021; Stanescu, 2018).

The National Basketball Association (NBA) initiated the Launchpad program, selecting companies to develop basketball technologies. For instance, SkillCorner utilizes computer vision and machine learning to generate player tracking data from existing video feeds, enabling detailed analysis of player movements and strategies. Similarly, Springbok Analytics employs AI-based technology to transform MRI data into 3D digital twins, quantifying an athlete’s musculature for precision health and performance optimization (NBA, 2023).

Moreover, the NBA has partnered with Sony’s Hawk-Eye Innovations to deploy 3D optical tracking technology, capturing real-time movements of players and the ball in three dimensions with sub-second latency. This system enhances officiating accuracy and provides detailed performance data (Hawk-Eye Innovations, 2023). These technological advancements serve as a bridge to previously elusive performance metrics, enabling granular analysis of biomechanical efficiency, tactical awareness, and psychosocial factors. Such insights not only inform but also revolutionize training regimens, allowing coaches to create hyper-personalized programs tailored to the physiological and psychological profiles of individual athletes (Catapult, 2023).

Beyond sport-specific tools, technology has made significant strides with AI in enhancing athletes’ mental performance. For example, AI-driven applications such asNeuroTrainer andMentalEdge provide personalized cognitive training programs to improve focus, decision-making, and mental resilience, while tracking vital internal metrics such as confidence and concentration (MentalEdge, 2023; NeuroTrainer, 2023). These platforms deliver tailored mental health and performance support, complementing physical preparation with robust psychological strategies (Talha & Sohail, 2023). Monitoring the physical and psychological attributes of athletes provides coaches with a holistic understanding of how best to prepare practice and training opportunities that simulate competitive settings (Passmore & Woodward, 2023).

Similarly, predictive modeling through AI enables coaches to anticipate performance trends and design hyper-personalized training regimens. Tools such as IBM Watson’s Sports Performance Analytics analyze vast datasets to identify patterns, forecast outcomes, and provide initiative-taking adjustments to maximize developmental trajectories (IBM, 2023). Platforms like Megalabs AI further demonstrate the potential of AI in sports training by using advanced algorithms to assess athlete performance and suggest data-driven interventions (Megalabs, 2023). By leveraging historical data and advanced algorithms to forecast future performance trends, injury risks, and game outcomes, coaches and athletes can strategically prepare for competition with greater precision and foresight (Megalabs, 2023).

Balancing Technology with Traditional Coaching Practices

As technology advances, maintaining a balance between its application and the humanistic core of effective coaching is paramount (Judge et al., 2024). While technological tools offer unprecedented data-driven insights into athlete performance, they remain insufficient substitutes for the interpersonal connections, mentorship, and empathy that underpin successful coaching relationships (Carson & Collins, 2016; Driska et al., 2017). These humanistic elements are indispensable in cultivating trust, resilience, and holistic growth in athletes, outcomes that technology alone cannot achieve. The integration of technology must enhance, not replace, the relational dynamics essential to coaching (Rajasinghe et al., 2022). Research underscores that the mentorship and emotional intelligence of coaches are critical in navigating the psychological and emotional challenges faced by athletes, fostering a foundation for long-term development and achievement (Carson & Collins, 2016). Thus, while technology can serve as a powerful adjunct in optimizing training and performance, it must be grounded in and guided by the human-centered principles of the coaching process (Driska et al., 2017). This balance not only ensures effective athlete development but also reinforces the irreplaceable role of coaches as mentors and leaders in the evolving landscape of sports.

Coaches must adopt a strategic approach to technology, utilizing it to complement their expertise rather than overshadowing it. For instance, wearable devices provide critical performance metrics, but their true value lies in a coach’s ability to interpret these data points and translate them into actionable insights (Catapult, 2023; Goudsmit et al., 2022). This equilibrium ensures that the art of coaching, characterized by intuition, adaptability, and emotional intelligence, remains integral to athlete development. Over-reliance on technology risks diluting these people skills, potentially leading to standardized approaches that overlook individual athlete needs (Sperlich et al., 2023). Coaches must critically evaluate the relevance and utility of each technological tool to ensure it aligns with their objectives and enhances the natural flow of training sessions. Coaches must also help athletes make sense of the data in a way that supports their technical, tactical, mental, and physical growth (Judge et al., 2024).

Table 2 illustrates the critical balance between integrating new coaching technologies and preserving traditional practices, emphasizing the importance of maintaining personal connections, leveraging intuitive experience, and fostering holistic athlete development alongside the adoption of innovative tools.

The Role of Relationships in Coaching

At its core, coaching is built on trust, empathy, and mentorship. These human-centric attributes enable coaches to inspire athletes, navigate challenges, and provide a sense of purpose that transcends physical performance (Judge et al., 2024). Unlike technology, which focuses on quantifiable metrics, the human aspects of coaching address intrinsic motivation, emotional intelligence, and adaptive problem-solving (Rajasinghe et al., 2022). Studies have shown that a strong coach-athlete relationship significantly influences athlete satisfaction, engagement, and performance (Passmore & Woodward, 2023). Consequently, even as technology becomes increasingly integrated into coaching, preserving the integrity of these interpersonal dynamics is essential.

Integrating Human-Centered and Data-Driven Approaches

The most effective coaching strategies blend human intuition with technological precision. While data can provide valuable performance insights, its utility is contingent on the coach’s ability to interpret and apply it within the broader context of athlete development. For example, injury prevention algorithms may flag overreaching and or overtraining risks, but the coach’s awareness of an athlete’s mental state and external stressors can provide critical context for tailoring interventions (Goudsmit et al., 2022). By combining the quantitative power of technology with the qualitative insights derived from interpersonal relationships, coaches can address athletes’ holistic needs and support the growth and nurturing of the athlete-coach relationship (Passmore & Woodward, 2023).

Challenges in Balancing Innovation with Tradition and the Road Ahead

Despite its transformative potential, over-reliance on technology can undermine essential coaching principles. Automated systems and analytics platforms, while efficient, risk depersonalizing the coaching experience (Driska et al., 2017). Algorithms often lack the flexibility to accommodate the unique, context-dependent variables that human coaches intuitively recognize (Sperlich et al., 2023). Furthermore, the adoption of technology poses a learning curve for seasoned coaches accustomed to traditional methods, highlighting the need for ongoing education and training in technological applications (Passmore & Woodward, 2023). Addressing these challenges requires fostering a culture of collaboration between coaches, sports scientists, and data analysts, ensuring that technological integration enhances rather than detracts from the human aspects of coaching.

The future of coaching is set to be fundamentally transformed by advancements in technologies such as AI and advanced analytics, which offer unparalleled opportunities to revolutionize strategic planning, optimize athlete performance, and redefine the landscape of sports development. The successful integration of these tools requires maintaining the balance between leveraging technological innovation and preserving the coach’s pivotal role as a mentor, strategist, and leader. Coaches who master the art of blending traditional practices with support from innovative technology will not only thrive but also redefine the coaching profession by offering their athletes a multidimensional support system.

Concurrently, the sports industry is increasingly incorporating technology through the strategic employment of data scientists and analysts within collegiate and professional teams. Roles such as Performance Science Analysts and Data Scientists are becoming essential, as teams leverage these professionals to collect and analyze performance data. This analysis translates complex metrics into actionable insights, informing strategic decisions and personalized training interventions (Indeed, 2023).

The convergence of AI-driven cognitive training tools and the integration of data science technology into coaching methodologies signifies a change in thinking in the sports industry. By leveraging these advancements, coaches can cultivate athletes who are not only physically adept but also possess the cognitive agility required for high-level competition. This integrated approach to athlete development is redefining performance optimization in modern sports.

Applications in Sport

The integration of technology into coaching represents a transformative frontier, providing tools that enhance precision in performance analysis and training methodologies. Yet, the heart of coaching remains deeply rooted in its human elements—empathy, trust, adaptability, and connection. By combining technological advancements with time-honored practices, coaches can create a dynamic, holistic, and sustainable approach to athlete development. This balance not only elevates athletic performance but also ensures that coaching continues to be a profoundly human-centered profession.

The rise of the Sport Scientist as a key position within collegiate and professional teams exemplifies this evolution. Sport Scientists collect and analyze vast amounts of data, ranging from biomechanical efficiency to cognitive performance metrics, translating these insights into actionable strategies for coaches. Their role bridges the gap between data-driven innovation and the human-centric principles of coaching, creating a collaborative environment where technology enhances, rather than replaces, the core values of mentorship and personal connection.While advancements in technology offer unprecedented opportunities to optimize athlete performance, successful coaches understand that these tools are only as effective as the human insight guiding their use. The essence of coaching lies in forming meaningful relationships, delivering individualized motivational strategies, and fostering resilience, qualities that remain inherently human. By integrating traditional coaching expertise with advanced technological tools, coaches can unlock their athletes’ full potential, cultivating a harmonious environment where data and human-centered guidance coalesce to achieve excellence. The future of coaching lies in this symbiotic relationship, ensuring that innovation complements, rather than competes with, the enduring principles of mentorship and connection.

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Troy Palmer2025-06-09T14:04:33-05:00November 14th, 2025|Commentary, Research, Sport Education, Sport Training, Sports Coaching, Sports Studies|Comments Off