Advanced Artificial Intelligence in Sports Science presents a comprehensive, application-oriented guide to artificial intelligence in sports science, integrating machine learning, Bayesian methods, and neural networks with real-world performance data to support evidence-based decision-making in sport.

Readers will gain practical and methodological expertise in applying AI models to sports data, including regression, neural networks, and time series approaches. The book combines theoretical foundations with reproducible case studies, LLM-assisted workflows, and transparent analytical pipelines. It emphasizes interpretability, uncertainty quantification, and ethical considerations, enabling readers to design, implement, and critically evaluate AI-driven solutions in sport. By bridging statistical reasoning, domain expertise, and modern AI techniques, the book provides a structured framework for both research and applied practice.

This book is intended for researchers, graduate students, and professionals in sports science, data analysis, and artificial intelligence, as well as practitioners such as coaches, analysts, and sport managers seeking to apply advanced data-driven methods in performance analysis and decision-making.

Michal Bozděch is an Assistant Professor at the Faculty of Sports Studies, Masaryk University (Czech Republic), specializing in artificial intelligence, data analysis, and research methodology in sports science. His research focuses on the application of machine learning, Bayesian approaches, and neural networks to performance analysis, talent identification, and athlete development, with a particular emphasis on the junior-to-senior transition in sport.

He is the author of more than 40 scientific publications and has published in leading journals. He serves as a principal investigator and collaborator on multiple research projects and is actively involved in international academic cooperation.

In addition to his research, he teaches courses in methodology, data analysis, and artificial intelligence, and contributes to the development of innovative educational approaches integrating AI into higher education. His work bridges statistical reasoning, domain expertise, and applied artificial intelligence in sports science