Predicting injury risk in NCAA Division I athletes using biomechanical and body composition screening data - Strogalev, N.; Bernhardt, V.; Oldham, M. D.; Kramarenko, V.; Jones, B.; Banks, B.; Sabo, D. T.; Alonso, D.; Nate, J.; Pegueros, K.; Bakcha, O.; Ochoa, S. T. (International Journal of Exercise Science Conference Proceedings, 2026)
INTRODUCTION: Injuries are a significant concern in athletic populations, limiting performance, shortening careers, and negative impact on health. There is growing evidence that intrinsic factors such as body composition and biomechanical characteristics are associated with injury risk, with metrics like fat and muscle distribution linked to injury likelihood across multiple sports. Moreover, recent research has demonstrated that predictive models incorporating physiological and biomechanical variables can effectively estimate injury risk, supporting the feasibility of data-driven injury risk prediction in sport science.