<p style="margin:0px">This is a complete, practical guide to sports data science and modeling, with 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.</p><p style="margin:0px"></p><p style="margin:0px">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 Python and R.</p><p style="margin:0px"></p><b><i><p style="margin:0px">Sports Analytics and Data Science</b> </i>will be an invaluable resource for everyone who wants to seriously investigate and more accurately predict athletic performance, including students, teachers, sports analysts, sports fans, physiologists, coaches, and managers of sports teams. It will also be valuable to all students of analytics who want to build their skills through familiar and accessible sports applications.</p>