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.

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.

A typical NBA game can yield approximately 2,800 statistical events in thirty-two different categories. In Numbers Don’t Lie Yago Colás started with a simple question: How did basketball analytics get from counting one stat, the final score, to counting thousands? He discovered that what we call “basketball”—rules, equipment, fundamental skills, techniques, tactics, strategies—has changed dramatically since its invention and today encompasses many different forms of play, from backyards and rec leagues to the NBA Finals. Numbers Don’t Lie explores the power of data to tell stories about ourselves and the world around us. As advanced statistical methods and big-data technologies transform sports, we now have the power to count more things in greater detail than ever before. These numbers tell us about the past, present, and future that shape how basketball is played on the floor, decisions are made in front offices, and the sport is marketed and consumed. But what is the relationship between counting and what counts, between quantification and value? In Numbers Don’t Lie Colás offers a three-part history of counting in basketball. First, he recounts how big-data basketball emerged in the past twenty years, examines its current practices, and analyzes how it presents itself to the public. Colás then situates big data within the deeper social, cultural, and conceptual history of counting in basketball and beyond and proposes alternative frameworks of value with which we may take fuller stock of the impact of statistics on the sport. Ultimately, Colás challenges the putative objectivity of both quantification and academic writing by interweaving through this history a series of personal vignettes of life at the intersection of basketball, counting, and what counts.

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.

Benjamin C. Alamar founded the first journal dedicated to sports statistics, the Journal of Quantitative Analysis in Sports. He developed and teaches a class on sports analytics for managers at the University of San Francisco and has published numerous cutting-edge studies on strategy and player evaluation. Today, he cochairs the sports statistics section of the International Statistics Institute and consults with several professional teams and businesses in sports analytics. There isn't a better representative of this emerging field to show diverse organizations how to implement analytics into their decision-making strategies, especially as analytic tools grow increasingly complex. Alamar provides a clear, easily digestible survey of the practice and a detailed understanding of analytics' vast possibilities. He explains how to evaluate different programs and put them to use. Using concrete examples from professional sports teams and case studies demonstrating the use and value of analytics in the field, Alamar designs a roadmap for managers, general managers, and other professionals as they build their own programs and teach their approach to others.

From one of basketball's foremost experts in the field of analytics, a fascinating new perspective on how to watch and think about the game. At its core, the goal of any basketball team is relatively simple: take and make good shots while preventing the opponent from doing the same. But what is a "good" shot? Are all good shots created equally? And how might one identify players who are more or less likely to make and prevent those shots in the first place? The concept of basketball "analytics," for lack of a better term, has been lauded, derided, and misunderstood. The incorporation of more data into NBA decision-making has been credited—or blamed—for everything from the death of the traditional center to the proliferation of three-point shooting to the alleged abandonment of the area of the court known as the midrange. What is beyond doubt is that understanding its methods has never been more important to watching and appreciating the NBA. In The Midrange Theory, Seth Partnow, NBA analyst for The Athletic and former Director of Basketball Research for the Milwaukee Bucks, explains how numbers have affected the modern NBA game, and how those numbers seek not to "solve" the game of basketball but instead urge us toward thinking about it in new ways. The relative value of Russell Westbrook's triple-doubles Why some players succeed in the playoffs while others don't How NBA teams think about constructing their rosters through the draft and free agency The difficulty in measuring defensive achievement The fallacy of the "quick two" From shot selection to evaluating prospects to considering aesthetics and ethics while analyzing the box scores, Partnow deftly explores where the NBA is now, how it got here, and where it might be going next.