Review of Machine Learning in Baseball Analytics for Performance Improvement and Future Directions

The application of machine learning (ML) in baseball analytics has revolutionized the way teams and players approach performance improvement. This literature review explores the intersection of ML and baseball analytics, focusing on key areas such as player evaluation, injury prevention, game strategy, and skill development. Highlighting advancements in data collection, algorithmic approaches, and real-world applications, this review synthesizes findings from existing research to identify trends, challenges, and opportunities for future innovation.