Download Free Basketball Stats Vs Analytics Book in PDF and EPUB Free Download. You can read online Basketball Stats Vs Analytics and write the review.

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.
Using data from one season of NBA games, Basketball Data Science: With Applications in R is the perfect book for anyone interested in learning and applying data analytics in basketball. Whether assessing the spatial performance of an NBA player's shots or doing an analysis of the impact of high pressure game situations on the probability of scoring, this book discusses a variety of case studies and hands-on examples using a custom R package. The codes are supplied so readers can reproduce the analyses themselves or create their own. Assuming a basic statistical knowledge, Basketball Data Science with R is suitable for students, technicians, coaches, data analysts and applied researchers. Features: One of the first books to provide statistical and data mining methods for the growing field of analytics in basketball Presents tools for modelling graphs and figures to visualize the data Includes real world case studies and examples, such as estimations of scoring probability using the Golden State Warriors as a test case Provides the source code and data so readers can do their own analyses on NBA teams and players
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.
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.
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.
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.
"Beautifully illustrated and sharply written, SprawlBall is both a celebration and a critique of the 3-point shot. If you want to understand how the modern NBA came to be, you'll need to read this book." --Nate Silver, editor of fivethirtyeight.com From the leading expert in the exploding field of basketball analytics, a stunning infographic decoding of the modern NBA: who shoots where, and how. The field of basketball analytics has leaped to overdrive thanks to Kirk Goldsberry, whose visual maps of players, teams, and positions have helped teams understand who really is the most valuable player at any position. SprawlBall combines stunning visuals, in-depth analysis, fun, behind-the-scenes stories and gee-whiz facts to chart a modern revolution. From the introduction of the 3-point line to today, the game has changed drastically . . . Now, players like Steph Curry and Draymond Green are leading the charge. In chapters like "The Geography of the NBA," "The Interior Minister (Lebron James)," "The Evolution of Steph Curry," and "The Investor (James Harden)," Goldsberry explains why today's on-court product--with its emphasis on shooting, passing, and spacing--has never been prettier or more democratic. And it's never been more popular. For fans of Bill Simmons and FreeDarko, SprawlBall is a bold new vision of the game, presenting an innovative, cutting-edge look at the sport based on the latest research, as well as a visual and infographic feast for fans.
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.
Michael Lewis’s instant classic may be “the most influential book on sports ever written” (People), but “you need know absolutely nothing about baseball to appreciate the wit, snap, economy and incisiveness of [Lewis’s] thoughts about it” (Janet Maslin, New York Times). One of GQ's 50 Best Books of Literary Journalism of the 21st Century Just before the 2002 season opens, the Oakland Athletics must relinquish its three most prominent (and expensive) players and is written off by just about everyone—but then comes roaring back to challenge the American League record for consecutive wins. How did one of the poorest teams in baseball win so many games? In a quest to discover the answer, Michael Lewis delivers not only “the single most influential baseball book ever” (Rob Neyer, Slate) but also what “may be the best book ever written on business” (Weekly Standard). Lewis first looks to all the logical places—the front offices of major league teams, the coaches, the minds of brilliant players—but discovers the real jackpot is a cache of numbers?numbers!?collected over the years by a strange brotherhood of amateur baseball enthusiasts: software engineers, statisticians, Wall Street analysts, lawyers, and physics professors. What these numbers prove is that the traditional yardsticks of success for players and teams are fatally flawed. Even the box score misleads us by ignoring the crucial importance of the humble base-on-balls. This information had been around for years, and nobody inside Major League Baseball paid it any mind. And then came Billy Beane, general manager of the Oakland Athletics. He paid attention to those numbers?with the second-lowest payroll in baseball at his disposal he had to?to conduct an astonishing experiment in finding and fielding a team that nobody else wanted. In a narrative full of fabulous characters and brilliant excursions into the unexpected, Michael Lewis shows us how and why the new baseball knowledge works. He also sets up a sly and hilarious morality tale: Big Money, like Goliath, is always supposed to win . . . how can we not cheer for David?
One of the greatest changes in the sports world in the past 20 years has been the use of mathematical methods to analyze performances, recognize trends and patterns, and predict results. Analytic Methods in Sports: Using Mathematics and Statistics to Understand Data from Baseball, Football, Basketball, and Other Sports, Second Edition provides a concise yet thorough introduction to the analytic and statistical methods that are useful in studying sports. The book gives you all the tools necessary to answer key questions in sports analysis. It explains how to apply the methods to sports data and interpret the results, demonstrating that the analysis of sports data is often different from standard statistical analyses. The book integrates a large number of motivating sports examples throughout and offers guidance on computation and suggestions for further reading in each chapter. Features Covers numerous statistical procedures for analyzing data based on sports results Presents fundamental methods for describing and summarizing data Describes aspects of probability theory and basic statistical concepts that are necessary to understand and deal with the randomness inherent in sports data Explains the statistical reasoning underlying the methods Illustrates the methods using real data drawn from a wide variety of sports Offers many of the datasets on the author’s website, enabling you to replicate the analyses or conduct related analyses New to the Second Edition R code included for all calculations A new chapter discussing several more advanced methods, such as binary response models, random effects, multilevel models, spline methods, and principal components analysis, and more Exercises added to the end of each chapter, to enable use for courses and self-study