Sports analytics and data science: Winning the game with methods and models - Miller, T. W. (Pearson Education, 2015)
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. Thomas W. Miller, leader of Northwestern University s pioneering program in predictive analytics, guides you through defining problems, identifying data, crafting and optimizing models, writing effective R and Python code, interpreting your results, and more. 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. Whether you re a team executive, coach, fan, fantasy player, or data scientist, this guide will be a powerful source of competitive advantage "in any sport, by any measure. " All data sets, extensive R and Python code, and additional examples available for download at http: //www.ftpress.com/miller/ This exceptionally complete and practical guide to sports data science and modeling teaches through realistic examples from sports industry economics, marketing, management, performance measurement, and competitive analysis. Thomas W. Miller, faculty director of Northwestern University s pioneering Predictive Analytics program, shows how to use advanced measures of individual and team performance to judge the competitive position of both individual athletes and teams, and to make more accurate predictions about their future performance. Miller s modeling techniques draw on methods from economics, accounting, finance, classical and Bayesian statistics, machine learning, simulation, and mathematical programming. Miller illustrates them through realistic case studies, with fully worked examples in both R and Python. "Sports Analytics and Data Science "will be an invaluable resource for everyone who wants to seriously investigate and more accurately predict player, team, and sports business performance, including students, teachers, sports analysts, sports fans, trainers, coaches, and team and sports business managers. This book is about building winning teams and successful sports businesses. Winning and success are more likely when decisions are guided by data and models. Sports analytics is a source of competitive advantage. This book provides an accessible guide to sports analytics. It is written for anyone who needs to know about sports analytics, including players, managers, owners, and fans. Itis also a resource for analysts, data scientists, and programmers. The book views sports analytics in the context of data science, a discipline that blends business savvy, information technology, and modeling techniques. To use analytics effectively in sports, we must first understand sportsthe industry, the business, and what happens on the fields and courts of play. We need to know how to work with data-identifying data sourees, gathering data, organizing and preparing them for analysis. We also need to know how to build models from data. Data do not speak for themselves. Useful predictions do not arise out of thin air. lt is The book shows how to learn from data and build models that work. It will also be valuable to all students of analytics and data science who want to build their skills through familiar and accessible sports applications Gain powerful, actionable insights for: