Qingrong TANG, Xiufang WEI, Bo TAN
Journal of Sports Science & Medicine - 2026;25(1):58-83
Talent identification (TID) in team sports is complex, influenced by biological, technical, psychological, and socio-cultural factors. Machine learning (ML) offers tools to integrate high-dimensional data, yet its applications in youth TID remain underexplored. Objectives: To systematically review ML approaches applied to youth talent identification in team sports, with emphasis on data domains, algorithms, validation strategies, and interpretability.
