Sparta Data Predicts ACL and Lower Extremity Injuries: ACSM Abstract – Prediction of Lower Extremity Injuries from Vertical Jump Kinetic Data in Collegiate Athletes

An abstract from University of Pennsylvania Medicine researchers was accepted by the American College of Sports Medicine to be presented at ACSM 2019: Prediction of Lower Extremity Injuries from Vertical Jump Kinetic Data in Collegiate Athletes, Authors Marisa Pontillo, PT, PhD, DPT, SCS; Shawn Hines, BS; Ryan Krochak, MD; Brian Sennett, MD. 

Study summary: Vertical jump testing using a force plate with dedicated software (Sparta Science AI system and database) was performed by all healthy varsity collegiate athletes at several intervals throughout the athletic year over 3 academic years. 

The testing procedure consisted of each subject performing a series of 6 consecutive vertical jumps (Sparta Jump Scan). Injuries were documented by the team athletic trainers and verified with the health care organization’s electronic medical documentation system.

Injuries were defined as occurring no more than 60 days after a jump and defined as lower extremity by OSICS 10 code. 234 lower extremity injuries were identified. Subjects were matched by age, sex and sport. 

Vertical jump variables used were Load, Explode and Drive, operationally defined as the average eccentric rate of force development, average concentric force, and concentric impulse, respectively. Logistic regression was used to determine if the battery of variables could predict whether or not an athlete would sustain a lower extremity injury. Additionally, athletes who sustained an ACL injury were identified, matched, and analyzed correspondingly.

Conclusion: Force data collected from vertical jumps predicted that athletes would sustain a lower extremity injury, including ACL injuries specifically.

Key takeaway: Clinicians, athletic training and coaching personnel can rely on the Sparta AI Force System and injury database for predictive analytics for lower extremity injuries, including ACL injuries, using the Jump Scan assessment. The Jump Scan takes less than 60 seconds to perform and produces an instant and actionable ‘injury risk report’ for the practitioner with prescriptive plans for exercises to help the athlete proactively minimize their risk of injury.