Artificial Intelligence in Sports Science: A Global Perspective
Main Article Content
Abstract
Artificial Intelligence (AI) has emerged as a transformative technology in the modern era, playing a vital role in advancing sports science on a global scale. This academic article aims to 1) synthesize knowledge regarding AI technologies and innovations related to the sports industry, 2) analyze the roles of AI in enhancing athletic performance, sports management, and rehabilitation within the context of sports science, and 3) assess the global impacts of AI on the sports sector across economic, social, cultural, and ethical dimensions. The study reveals that AI has been extensively developed in both hardware and software and has been applied in sports science through systems for tracking physical fitness and performance, real-time data analysis, decision-making tools with high precision, and integrated health information management. AI contributes significantly to optimizing athletic performance, reducing injury risks, and designing more accurate and personalized rehabilitation processes. Moreover, the macro-level analysis indicates that the advancement of AI technologies supports the growth of the sports technology industry, transforms patterns of play and sports spectatorship, and raises emerging ethical concerns regarding fairness in competition and data privacy. Finally, this article proposes policy-oriented approaches that emphasize equitable access to technology, the reduction of systemic disparities, and the development of appropriate regulatory frameworks to ensure the sustainable evolution of global sports science.
Article Details
References
Atasoy, B., Efe, M., & Tutal, V. (2021). Towards the artificial intelligence management in sports. International Journal of Sport Exercise and Training Sciences-IJSETS, 7(3), 100-113. https://doi.org/10.18826/useeabd.845994
Beal, R., Norman, T. J., & Ramchurn, S. D. (2019). Artificial intelligence for team sports: a survey. The Knowledge Engineering Review, 34, e28.
Chen, Z., & Dai, X. (2024). Utilizing AI and IoT Technologies for Identifying Risk Factors in Sports. Heliyon, 10(11), e32477. https://doi.org/10.1016/j.heliyon.2024.e32477
Chidambaram, S., Maheswaran, Y., Patel, K., Sounderajah, V., Hashimoto, D.A., Seastedt, K.P., McGregor, A.H., Markar, S.R., & Darzi, A. (2022). Using artificial intelligence-enhanced sensing and wearable technology in sports medicine and performance optimisation. Sensors, 22(18), 6920. https://doi.org/10.3390/s22186920
Dahmen, J., Kayaalp, M. E., Ollivier, M., Pareek, A., Hirschmann, M. T., Karlsson, J., & Winkler, P. W. (2023). Artificial intelligence bot ChatGPT in medical research: the potential game changer as a double-edged sword. Knee Surgery, Sports Traumatology, Arthroscopy, 31(4), 1187-1189. https://doi.org/10.1007/s00167-023-07355-6
Dinca-Panaitescu, T., & Dinca-Panaitescu, S. (2023). Artificial intelligence in the sports industry. In C.E. Morr (Eds), AI and Society Tensions and Opportunities. (pp. 113-125). CRC Press. https://doi.org/10.1201/9781003261247-9
Dindorf, C., Bartaguiz, E., Gassmann, F., & Fröhlich, M. (2022). Conceptual structure and current trends in artificial intelligence, machine learning, and deep learning research in sports: a bibliometric review. International Journal of Environmental Research and Public Health, 20(1), 173. https://doi.org/10.3390/ijerph20010173
Dindorf, C., Bartaguiz, E., Gassmann, F., & Fröhlich, M. (2024). Artificial Intelligence in Sports, Movement, and Health. Springer. https://doi.org/10.1007/978-3-031-67256-9
Duan, S., Zhang, H., Liu, L., Lin, Y., Zhao, F., Chen, P., Cao, S., Zhou, K., Gao, C., Liu, Z., Shi, Q., Lee, C., & Wu, J. (2024). A comprehensive review on triboelectric sensors and AI-integrated systems. Materials Today, 80(11), 450-480. https://doi.org/10.1016/j.mattod.2024.08.013
Dwyer, D. B., Kempe, M., & Knobbe, A. (2022). Using Artificial Intelligence to Enhance Sport Performance. Frontiers in sports and active living, 4, 886730. https://doi.org/10.3389/fspor.2022.886730
Fayed, A. M., Mansur, N. S. B., de Carvalho, K. A., Behrens, A., D’Hooghe, P., & de Cesar Netto, C. (2023). Artificial intelligence and ChatGPT in Orthopaedics and sports medicine. Journal of Experimental Orthopaedics, 10(1), 74. https://doi.org/10.1186/s40634-023-00642-8
Forinsights Consultancy. (2024). Artificial intelligence in sports market – Global forecast to 2030. https://www.forinsightsconsultancy.com/reports/artificial-intelligence-in-sports-market/
Glebova, E., Madsen, D. Ø., Mihaľová, P., Géczi, G., Mittelman, A., & Jorgič, B. (2024). Artificial intelligence development and dissemination impact on the sports industry labor market. Frontiers in Sports and Active Living, 6, 1363892. https://doi.org/10.3389/fspor.2024.1363892
Haase, J. (2025). Augmenting Coaching with GenAI: Insights into Use, Effectiveness, and Future Potential. arXiv preprint arXiv:2502.14632. https://arxiv.org/pdf/2502.14632
Herold, E., Singh, A., Feodoroff, B., & Breuer, C. (2024). Data-driven message optimization in dynamic sports media: an artificial intelligence approach to predict consumer response. Sport Management Review, 27(5), 793-816. https://doi.org/10.1080/14413523.2024.2372122
Liu, J., Wang, L., & Zhou, H. (2021). The application of human–computer interaction technology fused with artificial intelligence in sports moving target detection education for college athlete. Frontiers in Psychology, 12, 677590. https://doi.org/10.3389/fpsyg.2021.677590
Mateus, N., Abade, E., Coutinho, D., Gómez, M. Á., Peñas, C. L., & Sampaio, J. (2024). Empowering the Sports Scientist with Artificial Intelligence in Training, Performance, and Health Management. Sensors, 25(1), 139. https://doi.org/10.3390/s25010139
Molavian, R., Fatahi, A., Abbasi, H., & Khezri, D. (2023). Artificial intelligence approach in biomechanics of gait and sport: a systematic literature review. Journal of Biomedical Physics & Engineering, 13(5), 383. https://doi.org/10.31661/jbpe.v0i0.2305-1621
Munoz-Macho, A. A., Domínguez-Morales, M. J., & Sevillano-Ramos, J. L. (2024). Performance and healthcare analysis in elite sports teams using artificial intelligence: a scoping review. Frontiers in Sports and Active Living, 6, 1383723. https://doi.org/10.3389/fspor.2024.1383723
Nagovitsyn, R. S., Valeeva, R. A., & Latypova, L. A. (2023). Artificial Intelligence Program for Predicting Wrestlers’ Sports Performances. Sports, 11(10), 196. https://doi.org/10.3390/sports11100196
Naughton, M., Salmon, P. M., Compton, H. R., & McLean, S. (2024). Challenges and opportunities of artificial intelligence implementation within sports science and sports medicine teams. Frontiers in Sports and Active Living, 6, 1332427. https://doi.org/10.3389/fspor.2024.1332427
Novatchkov, H., & Baca, A. (2013). Artificial intelligence in sports on the example of weight training. Journal of sports science & medicine, 12(1), 27.
O’Brien, K. A., & O’Keeffe, M. (2022). Reimagining the role of technology in sport officiating: How artificial intelligence (AI) supports the design and delivery of ecologically dynamic development processes. Managing Sport and Leisure, 1-13. https://doi.org/10.1080/23750472.2022.2126996
Palermi, S., Vecchiato, M., Saglietto, A., Niederseer, D., Oxborough, D., Ortega-Martorell, S., Olier, I., Castelletti, S., Baggish, A., Maffessanti, F., Biffi, A., D’Andrea, A., Zorzi, A., Cavarretta, E., & D’Ascenzi, F. (2024). Unlocking the potential of artificial intelligence in sports cardiology: does it have a role in evaluating athlete’s heart? European Journal of Preventive Cardiology, 31(4), 470-482. https://doi.org/10.1093/eurjpc/zwae008
Pavitt, J., Braines, D., & Tomsett, R. (2021). Cognitive analysis in sports: Supporting match analysis and scouting through artificial intelligence. Applied AI letters, 2(1), e21. https://doi.org/10.1002/ail2.21
Phatak, A. A., Wieland, F. G., Vempala, K., Volkmar, F., & Memmert, D. (2021). Artificial intelligence based body sensor network framework—narrative review: proposing an end-to-end framework using wearable sensors, real-time location systems and artificial intelligence/machine learning algorithms for data collection, data mining and knowledge discovery in sports and healthcare. Sports Medicine-Open, 7(1), 79. https://doi.org/10.1186/s40798-021-00372-0
Pisaniello, A. (2024). The Game Changer: How Artificial Intelligence is Transforming Sports Performance and Strategy. Geopolitical, Social Security and Freedom Journal, 7(1), 75-84. https://doi.org/10.2478/gssfj-2024-0006
Raab, M., Schinke, R., & Maher, C. A. (2024). Technology meets sport psychology: How technology and artificial intelligence can shape the future of elite sport performance. Journal of Sport Psychology in Action, 15(2), 63-69. https://doi.org/10.1080/21520704.2023.2287324
Richter, C., O’Reilly, M., & Delahunt, E. (2024). Machine learning in sports science: challenges and opportunities. Sports Biomechanics, 23(8), 961-967. https://doi.org/10.1080/14763141.2021.1910334
Sampaio, T., Oliveira, J. P., Marinho, D. A., Neiva, H. P., & Morais, J. E. (2024). Transforming tennis with artificial intelligence: a bibliometric review. Frontiers in Sports and Active Living, 6, 1456998. https://doi.org/10.3389/fspor.2024.1456998
Sperlich, B., Düking, P., Leppich, R., & Holmberg, H. C. (2023). Strengths, weaknesses, opportunities, and threats associated with the application of artificial intelligence in connection with sport research, coaching, and optimization of athletic performance: a brief SWOT analysis. Frontiers in Sports and Active Living, 5, 1258562. https://doi.org/10.3389/fspor.2023.1258562
Suman, D. C. (2022). Artificial Intelligence in Sport: An Ethical Issue. Unity Journal, 3(1), 27-39. https://doi.org/10.3126/unityj.v3i01.43313
Suo, X., Tang, W., Mao, L., & Li, Z. (2024). Digital human and embodied intelligence for sports science: advancements, opportunities and prospects. The Visual Computer, 1-17. https://doi.org/10.1007/s00371-024-03547-4
Torgler, B. (2024). Big Data, Artificial Intelligence, and Quantum Computing in Sports. In S. L. Schmidt (Eds.), 21st Century Sports: How Technologies Will Change Sports in the Digital Age (pp. 169-189). Springer International Publishing. https://doi.org/10.1007/978-3-031-38981-8_10
Van Eetvelde, H., Mendonça, L. D., Ley, C., Seil, R., & Tischer, T. (2021). Machine learning methods in sport injury prediction and prevention: a systematic review. Journal of experimental orthopaedics, 8, 1-15. https://doi.org/10.1186/s40634-021-00346-x
Vec, V., Tomažič, S., Kos, A., & Umek, A. (2024). Trends in real-time artificial intelligence methods in sports: a systematic review. Journal of Big Data, 11(1), 148. https://doi.org/10.1186/s40537-024-01026-0
Venzke, J., Hohmann, R., Krombholz, A., Platen, P., & Reichert, M. (2024). Enhancing learning experiences in Sports Science through video and AI-generated feedback. In P. Salden, & J. Leschke (Eds.), Learning Analytics und Künstliche Intelligenz in Studium und Lehre: Erfahrungen und Schlussfolgerungen aus einer hochschulweiten Erprobung (pp. 79-95). Springer Fachmedien Wiesbaden. https://doi.org/10.1007/978-3-658-42993-5_5
Vila-Lopez, N., Kuster-Boluda, I., & Sarabia-Sanchez, F. J. (2023). Artificial intelligence in sports: Monitoring marathons in social media–The role of sports events in Territory Branding. In L. Moutinho, L. Cavique, & E. Bigne (Eds.), Philosophy of Artificial Intelligence and Its Place in Society. IGI Global. https://doi.org/10.4018/978-1-6684-9591-9.ch015
Wang, D., & Song, G. (2023). An exploratory study of artificial intelligence applications in sports medicine. Open Journal of Clinical & Medical Images, 3(2), 1147.
Zhang, H., & Zhu, J. (2022). Practicability of sports goods in the sports field based on artificial intelligencetechnology. Mobile Information Systems, 2022(1), 4964894. https://doi.org/10.1155/2022/4964894
Zhao, J., Yang, Y., Bo, L., Qi, J., & Zhu, Y. (2024). Research Progress on Applying Intelligent Sensors in Sports Science. Sensors, 24(22), 7338. https://doi.org/10.3390/s24227338
Zou, R. (2025). Exploring the Role of Artificial Intelligence in Sports Injury Prevention and Rehabilitation. Scalable Computing: Practice and Experience, 26(1), 316-325. https://doi.org/10.12694/scpe.v26i1.3544