Relationships between Sprint, Acceleration, and Deceleration Metrics with Training Load in Division I Collegiate Women’s Soccer Players
 
More details
Hide details
1
Center for Sport Performance, Department of Kinesiology, California State University, Fullerton, Fullerton, CA, USA
 
 
Publication date: 2023-02-16
 
 
Journal of Human Kinetics 2022;85:53-62
 
KEYWORDS
ABSTRACT
Player load is a variable derived from GPS technology that quantifies external load demands. Sprints and change-of-direction movements are high-intensity activities that place stress on the body. Research is needed to determine which sprint metrics may relate to and predict player load during practice sessions in collegiate women’s soccer players, as coaches could manipulate the most impactful variables. This study analyzed which sprint metrics related to GPS player load in women’s soccer players from one Division I team. Data from 19 practice sessions for 18 field players were analyzed. Players wore GPS sensors during all training sessions, and the variables assessed were player load, sprint count, sprint volume, sprint distance, average top speed, maximum top speed, and the number of accelerations and decelerations in different speed zones (±1, ±2, ±3, ±4, ±5 m/s2 ). Pearson’s correlations (p < 0.05) analyzed relationships between the sprint variables and player load. Stepwise regression analyses (p < 0.05) determined if any metrics predicted player load. The results indicated significant relationships between player load and sprint count, maximum top speed, sprint distance, sprint volume, number of decelerations at –1, –2, and –3 m/s 2 , and accelerations at 1, 2, and 5 m/s 2 (r = 0.512–0.861, p ≤ 0.025). Sprint distance and decelerations at 1 m/s2 predicted player load (p = 0.001, r2= 0.867). Maximal sprinting and decelerations and accelerations at different speeds were significant contributors to player load in collegiate women’s soccer players. Sprint distance, decelerations, and accelerations could be targeted in training drills via dimension and movement manipulation to adjust training intensity for collegiate women’s soccer players.
 
REFERENCES (31)
1.
Bangsbo, J., Mohr, M., Krustrup, P. (2006). Physical and metabolic demands of training and match-play in the elite football player. Journal of Sports Sciences, 24(7), 665–674.
 
2.
Bloomfield, J., Polman, R., O'Donoghue, P. (2007). Physical demands of different positions in FA Premier League soccer. Journal of Sports Science and Medicine, 6(1), 63–70.
 
3.
Cardinale, M., Varley, M. C. (2017). Wearable training-monitoring technology: Applications, challenges, and opportunities. International Journal of Sports Physiology and Performance, 12(S2), 55–62.
 
4.
Čoh, M., Hébert-Losier, K., Štuhec, S., Babić, V., Supej, M. (2018). Kinematics of Usain Bolt’s maximal sprint velocity. Kinesiology, 50(2), 172–180.
 
5.
Coutts, A. J., Duffield, R. (2010). Validity and reliability of GPS devices for measuring movement demands of team sports. Journal of Science and Medicine in Sport, 13(1), 133–135.
 
6.
Datson, N., Hulton, A., Andersson, H., Lewis, T., Weston, M., Drust, B., Gregson, W. (2014). Applied physiology of female soccer: An update. Sports Medicine, 44(9), 1225–1240.
 
7.
Douchet, T., Humbertclaude, A., Cometti, C., Paizis, C., Babault, N. (2021). Quantifying accelerations and decelerations in elite women soccer players during regular in-season training as an index of training load. Sports, 9(8), 109.
 
8.
Duffield, R., Reid, M., Baker, J., Spratford, W. (2010). Accuracy and reliability of GPS devices for measurement of movement patterns in confined spaces for court-based sports. Journal of Science and Medicine in Sport, 13(5), 523–525.
 
9.
Gaudino, P., Iaia, F., Alberti, G., Strudwick, A. J., Atkinson, G., Gregson, W. (2013). Monitoring training in elite soccer players: Systematic bias between running speed and metabolic power data. International Journal of Sports Medicine, 34(11), 963–968.
 
10.
Gentles, J. A., Coniglio, C. L., Besemer, M. M., Morgan, J. M., Mahnken, M. T. (2018). The demands of a women’s college soccer season. Sports, 6(1) 16.
 
11.
Girard, O., Mendez-Villanueva, A., Bishop, D. (2011). Repeated-sprint ability – Part I. Sports Medicine, 41(8), 673–694.
 
12.
Hopkins, W. G. (2006). A Scale of Magnitudes for Effect Statistics. http://www.sportsci.org/resour....
 
13.
Johnston, R., Watsford, M., Pine, M., Spurrs, R., Murphy, A., Pruyn, E. (2012). The validity and reliability of 5-hz global positioning system units to measure team sport movement demands. Journal of Strength and Conditioning Research, 26(3), 758–765.
 
14.
Jones, P., Bampouras, T., Marrin, K. (2008). An investigation into the physical determinants of change of direction speed. Journal of Sports Medicine and Physical Fitness, 49(1), 97–104.
 
15.
McFadden, B., Walker, A., Bozzini, B., Sanders, D., Arent, S. (2020). Comparison of internal and external training loads in male and female collegiate soccer players during practices vs. games. Journal of Strength and Conditioning Research, 34(4), 969–974.
 
16.
McLean, B., Petrucelli, C., Coyle, E. (2012). Maximal power output and perceptual fatigue responses during a Division I female collegiate soccer match. Journal of Strength and Conditioning Research, 26(12), 3189– 3196.
 
17.
Mohr, M., Krustrup, P., Andersson, H., Kirkendal, D., Bangsbo, J. (2008). Match activities of elite women soccer players at different performance levels. Journal of Strength and Conditioning Research, 22(2), 341–349.
 
18.
NCAA. (2020). 2020-2021 NCAA Division I Manual. http://www.ncaapublications.co....
 
19.
Papla, M., Krzysztofik, M., Wojdala, G., Roczniok, R., Oslizlo, M., Golas, A. (2020). Relationships between linear sprint, lower-body power output and change of direction performance in elite soccer players. International Journal of Environmental Research and Public Health, 17(17), 6119.
 
20.
Radzimiński, Ł., & Jastrzębski, Z. (2021). Evolution of physical performance in professional soccer across four consecutive seasons. Balt J Health Phys Activ, 13(3), 79-85. https://doi.org/10.29359/BJHPA....
 
21.
Rampinini, E., Alberti, G., Fiorenza, M., Riggio, M., Sassi, R., Borges, T. O., Coutts, A. J. (2015). Accuracy of GPS devices for measuring high-intensity running in field-based team sports. International Journal of Sports Medicine, 36(1), 49–53.
 
22.
Ravé, G., Granacher, U., Boullosa, D., Hackney, A. C., Zouhal, H. (2020). How to use global positioning systems (GPS) data to monitor training load in the "real world" of elite soccer. Frontiers in Physiology,11, 944.
 
23.
Scott, M., Scott, T., Kelly, V. (2016). The validity and reliability of global positioning systems in team sport: Abrief review. Journal of Strength and Conditioning Research, 30(5), 1470–1490.
 
24.
Spiteri, T., Newton, R., Binetti, M., Hart, N., Sheppard, J., Nimphius, S. (2015). Mechanical determinants of faster change of direction and agility performance in female basketball athletes. Journal of Strength and Conditioning Research, 29(8), 2205–2214.
 
25.
Stølen, T., Chamari, K., Castagna, C., Wisløff, U. (2005). Physiology of soccer. Sports Medicine, 35(6), 501–536.
 
26.
Thorpe, R. T., Atkinson, G., Drust, B., Gregson, W. (2017). Monitoring fatigue status in elite team-sport athletes: Implications for practice. International Journal of Sports Physiology and Performance, 12(Suppl 2), S227–S234.
 
27.
Vanrenterghem, J., Nedergaard, N. J., Robinson, M. A., Drust, B. (2017). Training load monitoring in team sports: A novel framework separating physiological and biomechanical load-adaptation pathways. Sports Medicine, 47(11), 2135–2142.
 
28.
Vescovi, J. D. (2012). Sprint speed characteristics of high-level American female soccer players: Female athletes in motion (FAiM) study. Journal of Science and Medicine in Sport, 15(5), 474–478.
 
29.
Wallace, L. K., Slattery, K. M., Coutts, A. J. (2013). A comparison of methods for quantifying training load: Relationships between modelled and actual training responses. European Journal of Applied Physiology, 114(1), 11–20.
 
30.
Windt, J., MacDonald, K., Taylor, D., Zumbo, B. D., Sporer, B. C., Martin, D. T. (2020). “To tech or not to tech?” A critical decision-making framework for implementing technology in sport. Journal of Athletic Training, 55(9), 902–910.
 
31.
World Medical Association. (1997). World Medical Association Declaration of Helsinki. Recommendations guiding physicians in biomedical research involving human subjects. Journal of the American Medical Association, 277(11), 925–926.
 
eISSN:1899-7562
ISSN:1640-5544
Journals System - logo
Scroll to top