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.
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.
Table of Contents
Section I. Laying the Groundwork1. The Evolution of Sport Analytics
2. The Pythagorean Theorem of Sports
Section II. Applying the Fundamentals
3. Applying the Pythagorean Theorem
4. Correlation
5. Simple Linear Regression
6. Multiple Linear Regression
7. Linear Weights and Probability
Section III. Visualizing the Game
8. Data Visualization
9. An Introduction to Microsoft Power BI
10. Power BI and Sport I
11. Power BI and Sport II
Section IV. Tools of the Trade
12. SQL
13. Python
14. R
15. Artificial Intelligence
Section V. Sharing Your Insights
16. Next Steps
Authors
Jon Nachtigal Assistant Professor, Florida Southern College, USA.Jon Nachtigal is an Assistant Professor at Florida Southern College. He holds a Ph.D. in Sport Administration with a specialization in Strategic Management and Policy. His work focuses on sport analytics, law, and marketing, and he has contributed to the development of widely used online courses in sport business. He has also worked as a technician for Major League Baseball, supporting innovations in game technology.
Daniel Krywaruczenko Assistant Professor, Centenary College of Louisiana, USA. Daniel Krywaruczenko is an Assistant Professor at Centenary College of Louisiana. He has a background spanning coaching, analytics, and operations, with experience at organizations such as InstantScouting, Pillar Sports Management, and Arizona Christian University. He holds a Ph.D. in Sport Administration and advanced degrees in Economics and Statistics. His academic research includes studies on reaction time and false start penalties in the NFL.
