Predicting Biomechanical Risk Factors for Division - I Women’s Basketball Athletes

Collegiate basketball is characterized by high-impact movements such as jump landings, making athletes more susceptible to injuries. Critical biomechanical factors like knee flexion, lateral trunk flexion, and foot landing asymmetry are strongly associated with injury risk. This study aims to predict six biomechanical risk factors in the landing error scoring system (LESS). The dataset comprises 8600 video frames of counter-movement jumps (CMJs) from 17 NCAA Division I female basketball athletes, recorded from frontal and lateral perspectives and annotated using a customized error annotation algorithm. The study uses the You Only Look Once (YOLOv5nu) model to analyze the basketball athletes’ CMJ videos. It demonstrates high reliability in predicting risk factors with an average Box Precision (Box P) of 0.800, recall (R) of 0.877, and mean Average Precision at IoU threshold 0.5 ([email protected]) of 0.879.

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Publication Details

Published
2025-03-12
DOI
https://doi.org/10.1109/icassp49660.2025.10887636
Primary Topic
Sports injuries and prevention
Type
article
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article

Predicting Biomechanical Risk Factors for Division - I Women’s Basketball Athletes

Christopher B. Taber, Vikas Agarwal, Aayushi Shah, Dhairya Shah et al.
Sports injuries and prevention
article

Predicting Biomechanical Risk Factors for Division - I Women’s Basketball Athletes

Christopher B. Taber, Vikas Agarwal, Aayushi Shah, Dhairya Shah, Srishti Sharma, Mehul S. Raval, Tolga Kaya, H Jani
article en

Abstract

Collegiate basketball is characterized by high-impact movements such as jump landings, making athletes more susceptible to injuries. Critical biomechanical factors like knee flexion, lateral trunk flexion, and foot landing asymmetry are strongly associated with injury risk. This study aims to predict six biomechanical risk factors in the landing error scoring system (LESS). The dataset comprises 8600 video frames of counter-movement jumps (CMJs) from 17 NCAA Division I female basketball athletes, recorded from frontal and lateral perspectives and annotated using a customized error annotation algorithm. The study uses the You Only Look Once (YOLOv5nu) model to analyze the basketball athletes’ CMJ videos. It demonstrates high reliability in predicting risk factors with an average Box Precision (Box P) of 0.800, recall (R) of 0.877, and mean Average Precision at IoU threshold 0.5 ([email protected]) of 0.879.

Sacred Heart University (US), Ahmedabad University (IN)
Gender equality
Openalex Percentile: Top 94%
Sports injuries and prevention
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