ROLE OF AI IN TALENT IDENTIFICATION AND PERFORMANCE PREDICTION IN TRACK AND FIELD - M. Raveena; Rathod, Lb Laxmikanth (ShodhKosh: Journal of Visual and Performing Arts, 2024)
The integration of Artificial Intelligence (AI) in sports has revolutionized talent identification and performance prediction, particularly in track and field events. AI-powered techniques leverage machine learning, deep learning, and data analytics to evaluate athletes’ physical attributes, biomechanics, and physiological responses, leading to data-driven decision-making. This study explores the role of AI in identifying promising talents, predicting athletic performance, and optimizing training methodologies. By analyzing vast datasets, AI can uncover hidden patterns, assess injury risks, and provide personalized training regimens. This paper presents a comprehensive review of AI applications in track and field, detailing various AI models and their effectiveness in talent scouting and performance forecasting. The study further highlights ethical concerns, challenges, and future research opportunities in AI-driven sports analytics. Findings suggest that AI-driven insights enhance coaches’ ability to refine training techniques and develop high-potential athletes, making AI a crucial tool for sports science and athlete development.