Machine Learning and Data Mining for Sports Analytics

This book features selected papers from the 7th International Workshop on Machine Learning and Data Mining for Sports Analytics, showcasing innovative research in the field.

The book Machine Learning and Data Mining for Sports Analytics presents the refereed post-conference proceedings from the 7th International Workshop on Machine Learning and Data Mining for Sports Analytics, held in September 2020 in Ghent, Belgium. Due to the COVID-19 pandemic, the conference transitioned to an online format, allowing participants from around the world to engage with the latest research in this dynamic field. The workshop focused on the intersection of machine learning, data mining, and sports analytics, showcasing innovative approaches to understanding and enhancing athletic performance.

In total, 11 papers were selected for publication from a competitive pool of 22 submissions, reflecting a diverse range of topics within sports analytics. The contributions cover various aspects such as tactical analysis, outcome predictions, data acquisition, performance optimization, and player evaluation. Each paper underwent a rigorous review process to ensure high-quality research was presented, making Machine Learning and Data Mining for Sports Analytics a valuable resource for academics and practitioners alike.

This compilation not only highlights the advancements in analytical techniques but also emphasizes the importance of data-driven decision-making in sports. By integrating machine learning and data mining methodologies, the insights gained can significantly impact training strategies, game tactics, and overall player performance. The findings and discussions in this book are essential for anyone interested in the future of sports analytics.