AI-SPOT: a Novel Artificial Intelligence enabled Sport Optimisation Tracker to Enhance Performance and Prevent Injury in Elite Footballers

Abstract

This study introduces AI-SPOT, a novel artificial intelligence tool for optimizing performance and preventing injuries in elite footballers. Data were collected from four Singapore Premiere League clubs and the National Team, encompassing 68 male footballers over two seasons (2021–2022). The comprehensive dataset included diverse metrics, injury records, and automated live match data from established databases. AI-SPOT employs Python's scikit-learn for predictive analytics, using techniques like logistic regression and XGBoost, and was further developed with TensorFlow. Its effectiveness in injury prediction and performance assessment was validated with extensive local and international data sources. The system's potential for broader sports applications was underscored by user experience assessments, indicating a significant shift towards AI-driven strategies in sports management. Despite its reliance on high-quality, sport-specific data, AI-SPOT's adaptability highlights its role as a transformative tool in sports analytics, paving the way for advanced, data-driven approaches in sports management and strategy formulation.