The evolution of AI in sports performance: Current practice and future potential

Thanks to advancements in artificial intelligence (AI), sports are undergoing an unprecedented period of digital transformation. These technologies have the potential to revolutionize the analysis of sports performance, streamline data gathering, develop immersive training environments, and improve decision-making procedures. Sports performance analysis has traditionally depended on manual data gathering, subjective assessments, and conventional statistical models. Even though these techniques worked well, they were vulnerable to subjectivity and time constraints. But a new era of objective, real-time performance measurement has begun with recent technological advancements. Thanks to AI's ability to interpret large datasets, automate information synthesis, and streamline data collecting, sports analysis has undergone a revolution. In order to provide coaches and players with useful tools, we investigate in this study how these new technologies can revolutionize sports performance analysis. Our goals are to improve the performance of athletes, make informed decisions, and optimize training regimens. We also point out problems and offer fixes for incorporating these technologies into the way sports analysis is done now. This narrative review highlights the benefits and drawbacks of existing methodologies while offering a thorough examination of the historical background and development of performance analysis in sports science. It explores the revolutionary possibilities of AI and provides information on how these instruments might be incorporated into a theoretical framework.