Machine Learning in Sports Talent Identification: A Systematic Review

Sports talent identification is drawing an increasing research interest from the academic community. The traditional approaches are being systematized into the scientific approaches. The scientific approaches project an analytical understanding of the Talent Identification and Development (TID) process. This paper reviews the work done in this field from 1996 – 2021. We have reviewed the articles in accordance with the PRISMA guidelines. We trace the computational procedures that have evolved with time, for the sports talent identification. The special focus has been given to the role of machine learning in Cricket Talent Identification. The review delivers and discusses some key findings.