An Introduction to Applied Sport Analytics offers a step-by-step path for applying data-driven methods in sports. The book begins with the evolution of sport analytics and foundational concepts like the Pythagorean theorem, correlation, and regression, then moves into hands-on instruction with industry tools such as Excel, SQL, R, Python, and Power BI. Readers learn how to explore data, evaluate performance, and make informed decisions across team operations, player valuation, and sport business strategy. The book features real-world examples, chapter exercises, and review questions and a dedicated section on data visualization walks readers through designing reports and dashboards using Power BI and Tableau.

The book also introduces the growing role of artificial intelligence in sport, showing how tools like machine learning and coding assistants can enhance analysis. A robust ancillary program also provides support to students with additional practice opportunities. With its practical focus and clear structure, this book is ideal for undergraduate and graduate courses in sport management, analytics, and business, as well as for professionals seeking to build essential skills in a data-driven sport industry.

• Provides a clear and didactic understanding of essential concepts in sports analytics, including correlation and linear regression
• Includes numerous illustrations, examples, and case studies, which provide clear explanations and additional context
• Aligns with commonly offered upper-level courses in sports analytics, sports management, and related fields
• Serves as a valuable resource for students and as a solid foundational material for early-stage researchers
• Offers online support, including additional datasets, quizzes and solutions, and supplemental video content