A study of the effect of fatigue state on soccer players’ shooting movements based on Mediapipe
Abstract
Soccer is recognized as one of the most widely played and commercially significant sports globally. An athlete’s performance is typically impaired during states of fatigue. Investigating the body mechanics of soccer players under states of fatigue can provide insights for coaches regarding the physical capabilities and movement deficiencies of their athletes. This understanding can facilitate the adjustment of game strategies and the development of tailored training regimens following competitive matches. Advancements in artificial intelligence have led to the maturation of image recognition technologies, which are increasingly applied across various industries, including promising applications within the realm of soccer. Consequently, this study analyzed a cohort of 5 amateur soccer players (mean age 19.8 years; mean height 1.82 m; mean weight 73.6 kg). The study involved participants who completed 10 shootings on goal as a control group before the implementation of a fatigue protocol, followed by an additional 10 shootings on goal as an experimental group after the completion of the fatigue protocol. Mediapipe image recognition tools and high-speed cameras were utilized to capture data on the various skeletal nodes of the athletes’ bodies and the velocity of the shooting ball, which were subsequently analyzed. The results of the study revealed that when in a state of fatigue, there were significant alterations in the angular displacement of the hip and knee joints in comparison to the ankle joint during shooting by soccer players. The decreased angular displacement of the hip and knee joints resulted in inferior contact between the foot and the ball, as well as a reduction in the speed applied to the ball, leading to a decline in shooting accuracy and ball speed. The findings substantiate the impact of fatigue on the shooting movements of athletes.
References
1. Rein, R., Memmert, D. Big data and tactical analysis in elite soccer: future challenges and opportunities for sports science. SpringerPlus 5, 1410 (2016). https://doi.org/10.1186/s40064-016-3108-2
2. Lees A, Asai T, Andersen TB, et al. The biomechanics of kicking in soccer: A review. Journal of sports sciences. 2010; 28(8): 805–817.
3. Liu H, Gómez MA, Gonçalves B, Sampaio J. Technical performance and match-to-match variation in elite football teams. Journal of sports sciences. 2016; 34(6): 509–518.
4. Mohr M, Thomassen M, Girard O, et al. Muscle variables of importance for physiological performance in competitive football. European journal of applied physiology. 2016; 116(2): 251–262.
5. Apriantono T, Nunome H, Ikegami Y, Sano S. The effect of muscle fatigue on instep kicking kinetics and kinematics in association football. Journal of sports sciences. 2006; 24(9): 951–960.
6. Mohr M, Krustrup P, Bangsbo J. Seasonal changes in physiological parameters of elite soccer players. Med Sci Sports Exerc, 2002, 36(5): 24.
7. Kellis E, Katis A, Vrabas IS. Effects of an intermittent exercise fatigue protocol on biomechanics of soccer kick performance. Scandinavian Journal of Medicine and Science in Sports. 2006; 16(5): 334–344. doi: 10.1111/j.1600-0838.2005.00496.x
8. Larson DJ. Exploring the relationship between dynamic stability and coordination variability of the lumbar spine using neuromuscular fatigue and movement training [PhD thesis]. University of Guelph; 2022.
9. Lin CC, Lee WC, Chen JC, et al. The influence of kinesio tape and an ankle brace on the lower extremity joint motion in fatigued, unstable ankles during a lateral drop landing. International journal of environmental research and public health. 2021; 18(11): 6081.
10. Tian C, Wang Y, Zhang D. Comprehensive assessment of lower limb alignment and forces during dance landings under fatigue. Molecular & Cellular Biomechanics. 2024; 21(4).
11. Lee H. The Effects of Fatigue on Biomechanics of Soccer Shooting [Master’s thesis]. Bridgewater State University; 2018.
12. Clarkson P M, Newham D J. Associations between muscle soreness, damage, and fatigue. Fatigue: neural and muscular mechanisms, 1995: 457-469.
13. Ekstrand J, Hägglund M, Waldén M. Epidemiology of muscle injuries in professional football (soccer). The American journal of sports medicine. 2011; 39(6): 1226–1232.
14. De Ste Croix MBA, Hughes JD, Lloyd RS, et al. Leg stiffness in female soccer players: Intersession reliability and the fatiguing effects of soccer-specific exercise. The Journal of Strength & Conditioning Research. 2017; 31(11): 3052–3058.
15. Ferraz R, Van Den Tillaar R, Marques MC. The effect of fatigue on kicking velocity in soccer players. Journal of human kinetics. 2012; 35: 97–107.
16. Pretorius A, Parry DA. Human decision making and artificial intelligence: A comparison in the domain of sports prediction. In: Proceedings of the Annual Conference of the South African Institute of Computer Scientists and Information Technologists; 26–28 September 2016; Johannesburg, South Africa. pp. 1–10.
17. Li Y. Research and application of deep learning in image recognition. In: Proceedings of the 2022 IEEE 2nd international conference on power, electronics and computer applications (ICPECA). 21–23 January 2022; Shenyang, China. pp. 994–999.
18. Mosele J. Artificial intelligence in the sport industry [Master’s thesis]. Politecnico Di Milano; 2017.
19. Liu J. Convolutional neural network-based human movement recognition algorithm in sports analysis. Frontiers in psychology. 2021; 12: 663359.
20. Akan S, Varlı S. Use of deep learning in soccer videos analysis: Survey. Multimedia Systems. 2023; 29(3): 897–915.
21. Choppin S, Wheat J. The potential of the Microsoft Kinect in sports analysis and biomechanics. Sports Technology. 2013; 6(2): 78–85.
22. Fang L, Sun M. Motion recognition technology of badminton players in sports video images. Future Generation Computer Systems. 2021; 124: 381–389.
23. Rong J, Dong H, Wang L, Sun H. Sports training posture recognition method based on Kinect body sensor and internet of things technology. Molecular & Cellular Biomechanics. 2024; 21(4): 747.
24. Wittels SH, Renaghan E, Wishon MJ, et al. Recovery of the autonomic nervous system following football training among division I collegiate football athletes: The influence of intensity and time. Heliyon. 2023; 9(7).
25. Alghannam AF. Metabolic limitations of performance and fatigue in football. Asian journal of sports medicine. 2012; 3(2): 65–73.
Copyright (c) 2025 Haidong Wang
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright on all articles published in this journal is retained by the author(s), while the author(s) grant the publisher as the original publisher to publish the article.
Articles published in this journal are licensed under a Creative Commons Attribution 4.0 International, which means they can be shared, adapted and distributed provided that the original published version is cited.
Submit a Paper
