Basketball Analytics

Basketball Analytics is a must-read for any sports analytics enthusiast or student of the game of basketball. Authors Stephen Shea, Ph.D. (Professor of Mathematics) and Christopher Baker (Software Engineer) utilize their unique skill-set to introduce original metrics for analyzing player performance, team style and team construction in the NBA. While demonstrating an awareness of the industry's best ideas, the authors present original, objective and efficient strategies for understanding how teams win. New player performance statistics include Offensive Efficiency (OE), Efficient Offensive Production (EOP), Defensive Stops Gained (DSG), and Approximate Value (AV). OE reflects a player's ability to make the most fundamental offensive decisions. EOP adjusts a player's points and assists based on his efficiency. DSG gives a complete measure of a player's defensive contributions, without relying on individual player statistics like blocks and steals. AV is a measure of total player performance that rivals any publicly available statistic. Basketball Analytics introduces groundbreaking metrics on player involvement in the offense. Point, Rebound and Assist Balance aggregate player usage in these critical statistics. New studies on the NBA show whether teams should strive for balance or unbalance. An NBA draft pick value study determines the average value of each pick and the likelihood of landing a star or role player with each draft position. The results of this study are used to discuss topics including the biggest draft blunders and steals, the draft success of each NBA team, and the quality of each draft class dating back to 1977. This valuable understanding of the NBA Draft creates a foundation for discussing various approaches to team development and construction. Additionally, the authors discuss redefining the positions on the court, unpredictability in the game, data visualization, and applications of spatial tracking technology. There are many intensely debated questions surrounding the NBA today. Who are the most valuable players, and how do they compare to past greats? Which players have the greatest impact on their team's defense? Should Kobe Bryant be concerned with getting his teammates involved in the offense? How do offenses differ in the clutch, and which players thrive in these situations? How difficult is it for a team to rebuild through the draft? Basketball Analytics introduces new statistics and new concepts to explore these questions and more.

Journey "inside the numbers" for an exceptional set of statistical tools and rules that can help explain the winning, or losing, ways of a basketball team. Basketball on Paper doesn't diagram plays or explain how players get in shape, but instead demonstrates how to interpret player and team performance. Dean Oliver highlights general strategies for teams when they're winning or losing and what aspects should be the focus in either situation. He describes and quantifies the jobs of team leaders and role players, then discusses the interactions between players and how to achieve the best fit. Oliver conceptualizes the meaning of teamwork and how to quantify the value of different types of players working together. He examines historically successful NBA teams and identifies what made them so successful: individual talent, a system of putting players together, or good coaching. Oliver then uses these statistical tools and case studies to evaluate the best players in history, such as Magic Johnson, Wilt Chamberlain, Bill Russell, and Charles Barkley and how they contributed to their teams' success. He does the same for some of the NBA's "oddball" players-Manute Bol, Muggsy Bogues, and Dennis Rodman and for the WNBA's top players. Basketball on Paper is unique in its incorporation of business and analytical concepts within the context of basketball to measure the value of players in a cooperative setting. Whether you're looking for strategies or new ideas to throw out while watching the ballgame at a sports bar, Dean Oliver'sBasketball on Paper will give you amazing new insights into teamwork, coaching, and success.

Equipped with new spatial tracking data collected by SportVU and others, Basketball Analytics investigates game strategy, player evaluation, player types, and prospect potential. Author Stephen Shea, Ph.D. introduces new measures of a player's scoring and playmaking efficiency, quantifies the spacing in an offense and the stretch of a defense, and demonstrates several ways in which the NBA game has changed over the years. He also reveals the full methodology behind popular topics from the blog, BasketballAnalyticsBook.com, such as the College Prospect Rating System and the periodic tables of NBA elements. The author presents a modern viewpoint on basketball analytics' most fundamental principles and demonstrates the power of the industry's latest statistical breakthroughs. Basketball Analytics is a must-read for any sports analytics enthusiast.

Are top scorers really the most valuable players? Are games decided in the final few minutes? Does the team with the best player usually win?Thinking Basketball challenges a number of common beliefs about the game by taking a deep dive into the patterns and history of the NBA. Explore how certain myths arose while using our own cognition as a window into the game's popular narratives. New basketball concepts are introduced, such as power plays, portability and why the best player shouldn't always shoot. Discover how the box score can be misleading, why "closers" are overrated and how the outcome of a game fundamentally alters our memory. Behavioral economics, traffic paradoxes and other metaphors highlight this thought-provoking insight into the NBA and our own thinking. A must-read for any basketball fan -- you'll never view the sport, and maybe the world, the same again.

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.

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.