The increasing availability of data has transformed the way sports are played, promoted and managed. This is the first textbook to explain how the big data revolution is having a profound influence across the sport industry, demonstrating how sport managers and business professionals can use analytical techniques to improve their professional practice. While other sports analytics books have focused on player performance data, this book shows how analytics can be applied to every functional area of sport business, from marketing and event management to finance and legal services. Drawing on research that spans the entire sport industry, it explains how data is influencing the most important decisions, from ticket sales and human resources to risk management and facility operations. Each chapter contains real world examples, industry profiles and extended case studies which are complimented by a companion website full of useful learning resources. Sport Analytics: A data-driven approach to sport business and management is an essential text for all sport management students and an invaluable reference for any sport management professional involved in operational research.

This book is the first to combine principles from analytics, complex systems theory, multi-disciplinary diagnostics and sport performance analysis. It considers athletes, teams, and sport organizations in individual and team games as complex systems, and demonstrates how complexity studies can enrich analytics and give us a more sophisticated understanding of the causalities of winning and losing in sports. Part I introduces the basic categories of analytics and their uses in elite sport. Part II presents an original conception of sport analytics both as a complex of different kinds of processes and as a complexity-adapted view of human systems acting in sport performance and management. Part III considers the main principles of complex sport analytics, expanding the prism of complexity to include all levels of a sport organization from athletes, coaches and trainers to top decision makers, and suggests practical applications and simulations for cases of both individual and team sports. This is illuminating reading for any advanced student, researcher or practitioner working in sport analytics, performance analysis, coaching science or sport management.

As the analysis of big datasets in sports performance becomes a more entrenched part of the sporting landscape, so the value of sport scientists and analysts with formal training in data analytics grows. Sports Analytics: Analysis, Visualisation and Decision Making in Sports Performance provides the most authoritative and comprehensive guide to the use of analytics in sport and its application in sports performance, coaching, talent identification and sports medicine available. Employing an approach-based structure and integrating problem-based learning throughout the text, the book clearly defines the difference between analytics and analysis and goes on to explain and illustrate methods including: Interactive visualisation Simulation and modelling Geospatial data analysis Spatiotemporal analysis Machine learning Genomic data analysis Social network analysis Offering a mixed-methods case study chapter, no other book offers the same level of scientific grounding or practical application in sports data analytics. Sports Analytics is essential reading for all students of sports analytics, and useful supplementary reading for students and professionals in talent identification and development, sports performance analysis, sports medicine and applied computer science.

Applied Sport Business Analytics With HKPropel Access provides a practical explanation of the use of data analytic metrics in sport, exploring selected techniques and tools as well as addressing fundamental applications of analytics within modern sports organizations. Current and aspiring sport managers will develop their understanding of how analytics can be used strategically to make data-informed decisions by selecting and translating data into evidence and meaningful metrics. The text begins with an introduction to the world of analytics, exploring the social, economic, and business foundations that form the history of data analytics. Different strategies used to make data-driven decisions are discussed to demonstrate the importance of analytics in a modern sport context. The text explains terms and methods that are typical in sport analytics, bridging the gap between sport managers and sport analysts to help them understand the perceptions and needs of one another. The text’s focus on quantitative statistical analysis—with its exploration of modeling, predictive analytics, and forecasting—helps students learn how to analyze data and make use of it. Students will then learn to turn data into visual representations such as cluster diagrams to reveal clear results. With practical exercises that utilize five included datasets and are heavily support by related video tutorials delivered through HKPropel, even those without programming experience will learn how to program and transform complex statistical data into easy-to-understand visuals. Case studies exploring real-world scenarios—including player position analysis in women's professional basketball, esport player popularity and market analysis, and prospective player evaluation for the NFL draft—examine managerial implications to help develop understanding of what questions to ask, how to interpret data, and how to use data to make informed decisions. Finally, an in-depth look at how cutting-edge analytics mechanisms were used to analyze over one million tweets associated with the NBA over an entire season will illustrate how to successfully work with large amounts of data to achieve results. Concepts throughout the book are made easy to understand through exercises, datasets, and video lectures on key topics, all accessible through HKPropel. These tools combine to provide valuable experience and practical understanding. Interview With a Professional sidebars offer additional real-world glimpses into the use of analytics by practitioners in sport business. Applied Sport Business Analytics will provide a broader and deeper knowledge of the use of sport analytics for aspiring sport managers, data analysts, and practitioners alike. It will prepare them to translate metrics in a useful way that allows them to make data-informed and data-driven decisions to achieve desired outcomes in their organization. Note: A code for accessing HKPropel is not included with this ebook but may be purchased separately.

The increasing availability of data has transformed the way sports are played, promoted and managed. This is the first textbook to explain how the big data revolution is having a profound influence across the sport industry, demonstrating how sport managers and business professionals can use analytical techniques to improve their professional practice. While other sports analytics books have focused on player performance data, this book shows how analytics can be applied to every functional area of sport business, from marketing and event management to finance and legal services. Drawing on research that spans the entire sport industry, it explains how data is influencing the most important decisions, from ticket sales and human resources to risk management and facility operations. Each chapter contains real world examples, industry profiles and extended case studies which are complimented by a companion website full of useful learning resources. Sport Analytics: A data-driven approach to sport business and management is an essential text for all sport management students and an invaluable reference for any sport management professional involved in operational research.

Data and analytics have the potential to provide sports organizations with a competitive advantage both on and off the field. Yet even as the use of analytics in sports has become commonplace, teams regularly find themselves making big investments without significant payoff. This book is a practical, nontechnical guide to incorporating sports data into decision making, giving leaders the knowledge they need to maximize their organization’s investment in analytics. Benjamin C. Alamar—a leading expert who has built high-performing analytics groups—surveys the current state of the use of data in sports, including both specifics around the tools and how to deploy them most effectively. Sports Analytics offers a clear, easily digestible overview of data management, statistical models, and information systems and a detailed understanding of their vast possibilities. It walks readers through the essentials of understanding the value of different types of data and strategies for building and managing an analytics team. Throughout, Alamar illustrates the value of analytics with real-world examples and case studies from both the sports and business sides. Sports Analytics has guided a range of sports professionals to success since its original publication in 2013. This second edition adds examples and strategies that focus on using data on the business side of a sports organization, provides concrete strategies for incorporating different types of data into decision making, and updates all discussions for the rapid technological developments of the last decade.

Sports Analytics in Practice with R A practical guide for those looking to employ the latest and leading analytical software in sport In the last twenty years, sports organizations have become a data-driven business. Before this, most decisions in sports were qualitatively driven by subject-matter experts. In the years since numerous teams found success with “Money Ball” analytical perspectives, the industry has sought to advance its analytical acumen to improve on- and off-field outcomes. The increasing demand for data to inform decisions for coaches, scouts, and players before and during sporting events has led to intriguing efforts to build upon this quantitative approach. As this methodology for assessing performance has matured and grown in importance, so too has the open-source R software emerged as one of the leading analytical software packages. In fact, R is a top 10 programming language that is useful in academia and industry for statistics, machine learning, and rapid prototyping. Sports Analytics in Practice with R neatly marries these two advances to teach basic analytics for sports-related use—from cricket to baseball, from basketball to tennis, from soccer to sports gambling, and more. Sports Analytics in Practice with R readers will also find: A broad perspective of sports, focusing on a wide range of sports rather than just one The first book of its kind that features coding examples Case study approach throughout the book Companion website including data sets to work through alongside the explanations Sports Analytics in Practice with R is a helpful tool for students and professionals in the sports management field, but also for sports enthusiasts who have a coding background.