This study investigates biomechanical risk factors contributing to non-contact anterior cruciate ligament (ACL) injuries among athletes in jumping and landing sports. ACL injuries are among the most common and costly sports-related injuries, often occurring without direct contact during dynamic movements such as jumping, landing, cutting, and sudden stops. With over 70% of ACL injuries being non-contact in nature, early identification of at-risk individuals through accurate screening is critical for effective prevention and reduction of long-term treatment costs.

Previous studies have largely focused on isolated variables during single motor tasks; however, these traditional methods have shown limited predictive power in real-world sports settings. In contrast, the present study introduces the concept of a “movement signature” — a stable, individual-specific biomechanical pattern that persists across various tasks — as a more reliable indicator of injury risk.

Participants will include male and female athletes aged 18 to 35 who regularly engage in high-intensity dynamic sports. Movement assessments will be conducted in a biomechanics laboratory, using tasks such as bilateral and single-leg vertical drop jumps and unanticipated cutting maneuvers. The study aims to determine whether consistent individual movement patterns can be identified and used to improve multi-task screening models.

The findings may lead to the development of more personalized, task-independent, and effective screening and intervention strategies to prevent ACL injuries in athletic populations, ultimately enhancing sports performance and long-term joint health.