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.
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.
"This book addresses the fundamental use of analytical metrics to inform sport managers, framing sport analytics for practical use within organizations. The book is organized to present the background of sport analytics, why it is useful, selected techniques and tools employed, and its applications in sport organizations. The text guides the reader in selecting and communicating information in a useable format, and the translation of metrics in informing managers, guiding decisions, and maximizing efficiency in achieving desired outcomes"--
This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. This up-to-the-minute reference will help you master all three facets of sports analytics — and use it to win! Sports Analytics and Data Science is the most accessible and practical guide to sports analytics for everyone who cares about winning and everyone who is interested in data science. You’ll discover how successful sports analytics blends business and sports savvy, modern information technology, and sophisticated modeling techniques. You’ll master the discipline through realistic sports vignettes and intuitive data visualizations–not complex math. Every chapter focuses on one key sports analytics application. Miller guides you through assessing players and teams, predicting scores and making game-day decisions, crafting brands and marketing messages, increasing revenue and profitability, and much more. Step by step, you’ll learn how analysts transform raw data and analytical models into wins: both on the field and in any sports business.
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.
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.
In today’s sports world, decision makers, coaches, trainers, and athletes readily embrace sport performance analytics (SPA) and expect decisions to be based on such analyses. Organizations adept at collecting data, analyzing data, and applying findings enjoy a competitive advantage on the field—and a positive impact on the bottom line. For sport management students with a passion for sports and an aptitude for analytics, SPA presents an enticing career choice—one in high demand. Sport Performance Analytic Methods With HKPropel Access not only introduces students to the field of sport performance analytics but also walks them through the entire SPA process. This unparalleled approach equips students to employ SPA tools and techniques to make informed decisions affecting organization performance and success. The content of the book is driven by the SPA model, a seven-step process providing a guided pathway for conducting SPA analyses: Establish what you want to know Define the data you will collect Determine the data collection process and collect data Analyze the data Interpret the results Present the results Make data-based decisions The opening chapter emphasizes the importance of establishing the SPA objectives. The focus then shifts to understanding foundational data concepts, with discussions on quantitative and qualitative data, types and scale of variables, temporal aspects of data, process and product data, and validity and reliability of data. Methods and tools for collecting data are explored next, including technology-assisted data acquisition tools such as wearable devices and biometric sensing devices. Students will then examine quantitative statistical concepts that can be used to analyze data and even help make predictions about future player or team performance. Key concepts include descriptive statistics, data sets, inferential statistics, group comparisons, and linear regressions. The text also addresses techniques for collecting and analyzing qualitative data—including observation, content, narrative, discourse, thematic, and grounded theory analyses—ensuring that all forms of data are considered to produce successful outcomes. Finally, the text demonstrates how to present SPA data in a format useful to apply in decision making. Students learn how coaches and performance data analysts use data to inform pre- and postcompetition strategic and tactical plans, make in-game decisions, evaluate team and individual performance, and make decisions for teams, players, and organizations. Related online resources, delivered via HKPropel, provide students with hands-on learning tools. In addition to descriptions of the primary SPA software packages, included are nine learning modules that allow students to go through various statistical procedures step by step, checking results, and improving performance. With Sport Performance Analytic Methods, students will gain a solid understanding of the principles made famous by Moneyball, and they will learn to use sport analytics to improve sport performance outcomes. Note: A code for accessing HKPropel is not included with this ebook but may be purchased separately.
