Artificial Intelligence in Sports Analytics for Performance Enhancement and Injury Prevention

Authors

Mayank Panchal, Dr. Manish Singh

Abstract

The integration of Artificial Intelligence (AI) in sports analytics is transforming the way teams assess player performance and prevent injuries. Traditional methods of performance evaluation rely on statistical analysis and subjective assessments, whereas AI-driven models leverage machine learning algorithms to provide data-driven insights with greater accuracy and efficiency. This research explores the application of AI in sports analytics, particularly in enhancing player performance, optimizing workload management, and predicting injury risks. A Long Short-Term Memory (LSTM) network is implemented to develop a predictive model capable of forecasting player performance and injury risks based on historical match data. The results indicate that AI-based models achieve an 85-90% accuracy rate. Furthermore, AI-driven workload management strategies have shown a 20-30% reduction in overuse injuries, ensuring sustainable athlete performance.

Keywords

Artificial Intelligence, Sports Analytics, Machine Learning, Player Performance, Injury Prevention, Predictive Modeling, Workload Management

Artificial Intelligence in Sports Analytics for Performance Enhancement and Injury Prevention. Mayank Panchal, Dr. Manish Singh. 2025. IJIRCT, Volume 11, Issue 2. Pages 1-15. https://www.ijirct.org/viewPaper.php?paperId=2503052