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This book offers a comprehensive guide for sports organizations to effectively manage and leverage data for optimal outcomes. It bridges theory and practice, providing frameworks for sports data strategy and analytics, and emphasizing data governance, quality, and security. Through case studies and examples, it demonstrates data-driven improvements in player recruitment, game strategy, fan engagement, and revenue generation. Exploring emerging trends like AI and machine learning, it empowers readers to make informed decisions and meet the growing demand for data-driven decision-making in sports. The book aims to unlock the potential of sports data for sustained success in the industry.
List of contents
Introduction.- Trends in Sports Management.- Data Challenges in Sports Organizations.- Sports Data Management Framework.- Best Practices in Sports Data Management.- Conclusion.- Index.- Reference.
About the author
Dr. oec. Dominik Schwizer, a lecturer in Sport Management at UAS Grisons and in Marketing at the University of St. Gallen (HSG), Switzerland, holds a Ph.D. in Business Administration from HSG. His work focuses on the intersection of business and sport, with emphasis on the economics of sport, data-driven management, and ethical questions in sport. As an observer, analyst, and translator between academia and practice, he reflects on, teaches, and writes about sport in close exchange with practitioners.
Dr. rer. nat. Michael Burch, a lecturer at UAS Grisons in Switzerland, holds a Ph.D. in Computer Science from the University of Trier, Germany. Specializing in Information Visualization, Visual Analytics, and Eye Tracking, he has made significant contributions to research at institutions like Technische Universiteit Eindhoven and VISUS in Stuttgart, Germany. With nearly 15 years of experience, Dr. Burch brings invaluable expertise to interdisciplinary projects.
Summary
This book offers a comprehensive guide for sports organizations to effectively manage and leverage data for optimal outcomes. It bridges theory and practice, providing frameworks for sports data strategy and analytics, and emphasizing data governance, quality, and security. Through case studies and examples, it demonstrates data-driven improvements in player recruitment, game strategy, fan engagement, and revenue generation. Exploring emerging trends like AI and machine learning, it empowers readers to make informed decisions and meet the growing demand for data-driven decision-making in sports. The book aims to unlock the potential of sports data for sustained success in the industry.
