aceMachine learning applications in sport: a scoping review
Machine learning (ML) applications continue to grow in popularity across the sport industry, offering new opportunities for performance enhancement, injury prevention, and decision-making. The present scoping review examined the landscape of ML applications in sport by analyzing 270 peer-reviewed studies published between 2002 and 2024. ML was applied across 12 broad subject areas, with computer science, biomechanics, and sport psychology emerging as the most common domains of application. Key applications inclu…
Machine learning models demonstrated promising accuracy for sport applications including action recognition, injury prediction and prevention, and athlete selection, offering opportunities for performance enhancement and decision-making.
Practical utility of machine learning in sport was often limited by issues of data quality, interpretability, and accessibility for end users such as athletes and coaches.
Practical utility was often limited by data quality, interpretability, and accessibility for end users, constraining translation from accuracy to real-world use.
Evidence
- Peer-reviewedScientific Reports2025-11-17
- Peer-reviewedSensors2026-07-10
- Peer-reviewedApplied Sciences2023-12-04
- Peer-reviewedScience Advances2025-10-01
- Peer-reviewedFrontiers in Psychology2026-05-25
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Truvace Impact Record TRV-2026-0186, v5: “Machine learning applications in sport: a scoping review.” Truvace, 2026-10-10. /record/TRV-2026-0186 (accessed at citation time). sha256 d7f7908735594536…
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