Artificial intelligence (AI) and machine learning (ML) revolutionize sports by transforming how teams, coaches, and analysts understand and optimize performance. These technologies enable the collection, processing, and interpretation of data, ranging from player biometrics and in-game statistics to video footage and fan engagement metrics. By uncovering patterns and insights that are difficult to detect manually, AI and ML improve game strategies, prevent injuries, scout talent, and enhance the overall spectator experience. As the sports industry embraces data-driven decision-making, the role of AI and ML in sports analytics continues to grow. AI and Machine Learning Applications in Sports Analytics explores the possibilities offered by AI and ML within the realm of sports analytics. It examines various applications of these technologies, including player performance analysis, game strategy optimization, injury prediction, talent scouting, and fan engagement. This book covers topics such as sports science, neural networks, and data analytics, and is a useful resource for sports professionals, medical and healthcare workers, coaches, engineers, academicians, researchers, and data scientists.
