From the front office to the family room, sabermetrics has dramatically changed the way baseball players are assessed and valued by fans and managers alike. Rocketed to popularity by the 2003 bestseller Moneyball and the film of the same name, the use of sabermetrics to analyze player performance has appeared to be a David to the Goliath of systemically advantaged richer teams that could be toppled only by creative statistical analysis. The story has been so compelling that, over the past decade, team after team has integrated statistical analysis into its front office. But how accurately can crunching numbers quantify a player's ability? Do sabermetrics truly level the playing field for financially disadvantaged teams? How much of the baseball analytic trend is fad and how much fact? The Sabermetric Revolution sets the record straight on the role of analytics in baseball. Former Mets sabermetrician Benjamin Baumer and leading sports economist Andrew Zimbalist correct common misinterpretations and develop new methods to assess the effectiveness of sabermetrics on team performance. Tracing the growth of front office dependence on sabermetrics and the breadth of its use today, they explore how Major League Baseball and the field of sports analytics have changed since the 2002 season. Their conclusion is optimistic, but the authors also caution that sabermetric insights will be more difficult to come by in the future. The Sabermetric Revolution offers more than a fascinating case study of the use of statistics by general managers and front office executives: for fans and fantasy leagues, this book will provide an accessible primer on the real math behind moneyball as well as new insight into the changing business of baseball.
Born in the 1970s as a radical challenge to traditional baseball statistics, sabermetrics has developed into a new way of understanding many aspects of the game. Its practitioners have created new statistical tools and revised our old ways of thinking about established measures such as the batting average, tactics such as the sacrifice bunt, and even who among the greats was truly great. This introduction to the basics of sabermetric analysis explains concepts including normalization, peak versus career performance, linear weights and runs created, as well as popular calculations like OPS (On-Base plus Slugging), WHIP (Walks and Hits per Inning Pitched), PF (Park Factor) and others increasingly used by baseball fans. Instructors considering this book for use in a course may request an examination copy here.
The past 30 years have seen an explosion in the number and variety of baseball books and articles. Following the lead of pioneers Bill James, John Thorn, and Pete Palmer, researchers have steadily challenged the ways we think about player and team performance—and along the way revised what we thought we knew of baseball history. This book by the authors of Understanding Sabermetrics (2008) goes beyond the explanation of new statistics to demonstrate their use in solving some of the more familiar problems of baseball research, such as how to compare players across generations; how to account for the effects of ballparks and rules changes; and how to measure the effectiveness of the sacrifice bunt or the range of the Gold Glove–winning shortstop. Instructors considering this book for use in a course may request an examination copy here.
"This delightfully written, lesson-laden book deserves a place of its own in the Baseball Hall of Fame." —Forbes Moneyball is a quest for the secret of success in baseball. In a narrative full of fabulous characters and brilliant excursions into the unexpected, Michael Lewis follows the low-budget Oakland A's, visionary general manager Billy Beane, and the strange brotherhood of amateur baseball theorists. They are all in search of new baseball knowledge—insights that will give the little guy who is willing to discard old wisdom the edge over big money.
Sabermetrics, the specialized analysis of baseball through empirical evidence, provides an impartial perspective from which to explore the game. In this work, the third in a series, three mathematicians employ statistical science in an attempt to answer some of baseball's toughest questions. For instance, how good were the 1961 New York Yankees? How bad were the 1962 Mets? Which team was the best of the Deadball Era? They also strive to determine baseball's greatest player at various positions. Throughout, the objective evidence allows for debate devoid of emotion and personal biases, providing a fresh, balanced evaluation of these and many other challenging questions. Instructors considering this book for use in a course may request an examination copy here.
Ever wonder whether Tiger Woods in his prime would have beaten Bobby Jones, Ben Hogan, or Jack Nicklaus in their primes? And could any of them have beaten Babe Zaharias? Obviously, if Bobby Jones were returned to life and health and then given his old hickory-shafted mashie, persimmon-headed driver, and rubber-core ball in a match against Jordan Spieth, the outcome would be foreordained. But what if the impact of the training, equipment, courses, and traveling conditions could be neutralized in order to create a measurement? Now for the first time, questions are answered about the relative abilities of the greatest players in the history of professional golf. In The Hole Truth Bill Felber provides a relativistic approach for evaluating and comparing the performance of golfers while acknowledging the game's changing nature. The Hole Truth analyzes the performances of players relative to their peers, creating an index of exceptionality that automatically factors the changing nature of the game through time. That index is based on the standard deviation of the performances of players in golf's recognized major championships dating back to 1860. More than two hundred players are rated in comparison with one another, more than sixty of them in detail with profiles providing context on their ranking. For the dedicated golf fan, The Hole Truth is an engaging way to see in the numbers where their favorite golfers rank across eras and where current players like Rory McIlroy and Inbee Park compare to the game's greats.
There isn't much spectacular about Satchel Delaney. His life revolves around baseball, fishing, scholarly pursuits, and carousing with his three best friends, Felix, Vincent, and Tae. However, in the summer before they enter college, Satchel and his companions find themselves amidst a preternatural transformation in their hometown. Rumor has it a mythical bird of prey is lurking somewhere in the woods, or is it only in the dark corners of the imaginations of the town elders?
Broken up into sections (pitching, fielding, hitting), this authoritative yet fun and easy guide will help readers young and old fully understand and comprehend the statistics that are the present and future of our national pastime. We all know what a .300 hitter looks like. The same with a 20-game winner. Those numbers are ingrained in our brains. But do they mean as much as we think? Do we feel the same way when we hear a batter has a .390 wOBA? How about a pitcher with a 1.2 WHIP? These statistics are the future of modern baseball, and no fan should be in the dark about how these metrics apply to the game. In the last twenty years, an avalanche of analytics has taken over the way the game is played, managed, and assessed, but the statistics that drive the sport (metrics like wRC+, FIP, and WAR, just to name a few) read like alphabet soup to a large number of fans who still think batting average, RBIs, and wins are the best barometers for baseball players. In A Fan’s Guide to Baseball Analytics, MLB.com reporter and columnist Anthony Castrovince has taken on the role as explainer to help such fans understand why the old stats don’t always add up. Readers will also learn where these modern stats came from, what they convey, and how to use them to evaluate players of the present, past, and future. For instance, what if we told you that when Joe DiMaggio had his famous 56-game hitting streak in 1941, helping him win the AL MVP, that there was, perhaps, someone more deserving? In fact, the great Ted Williams actually had a higher fWAR, bWAR, wRC+, OPS, OPS+, ISO, RC . . . well, you get the picture. So, streak or no streak, Williams should have been league MVP. An introductory course on sabermetrics, A Fan’s Guide to Baseball Analytics is an easily digestible resource that readers can keep turning back to when they see a modern metric referenced in today’s baseball coverage.
Matrix Methods: Applied Linear Algebra and Sabermetrics, Fourth Edition, provides a unique and comprehensive balance between the theory and computation of matrices. Rapid changes in technology have made this valuable overview on the application of matrices relevant not just to mathematicians, but to a broad range of other fields. Matrix methods, the essence of linear algebra, can be used to help physical scientists-- chemists, physicists, engineers, statisticians, and economists-- solve real world problems. Provides early coverage of applications like Markov chains, graph theory and Leontief Models Contains accessible content that requires only a firm understanding of algebra Includes dedicated chapters on Linear Programming and Markov Chains
When Bill James published his original Historical Baseball Abstract in 1985, he produced an immediate classic, hailed by the Chicago Tribune as the “holy book of baseball.” Now, baseball's beloved “Sultan of Stats” (The Boston Globe) is back with a fully revised and updated edition for the new millennium. Like the original, The New Bill James Historical Baseball Abstract is really several books in one. The Game provides a century's worth of American baseball history, told one decade at a time, with energetic facts and figures about How, Where, and by Whom the game was played. In The Players, you'll find listings of the top 100 players at each position in the major leagues, along with James's signature stats-based ratings method called “Win Shares,” a way of quantifying individual performance and calculating the offensive and defensive contributions of catchers, pitchers, infielders, and outfielders. And there's more: the Reference section covers Win Shares for each season and each player, and even offers a Win Share team comparison. A must-have for baseball fans and historians alike, The New Bill James Historical Baseball Abstract is as essential, entertaining, and enlightening as the sport itself.
Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. Pages: 43. Chapters: Baseball plays, Sabermetrics, Sacrifice fly, Squeeze play, Double play, Triple play, Closer, Fastball, Curveball, Unassisted triple play, Small ball, First-pitch strike, Batting order, Pickoff, Bunt, Left-handed specialist, Appeal play, Hidden ball trick, Double switch, Lefty-righty switch, Hit and run, Changeup, Sacrifice bunt, Wheel play, Catch, Infield shift, Force play, Cutter, Inside Baseball, Knuckle curve, Power pitcher, Manager, Long reliever, Setup pitcher, Tag out, Control pitcher, Slap bunt, Middle relief pitcher, Rundown, Baltimore chop, Whiteyball, Ace, Contact play, Groundball pitcher, Wall climb, Flyball pitcher, Shagging. Excerpt: In baseball, a double play (denoted on statistics sheets by DP) for a team or a fielder is the act of making two outs during the same continuous playing action. In baseball slang, making a double play is referred to as "turning two." Double plays are also known as "the pitcher's best friend" because they disrupt offense more than any other play, except for the rare triple play. Pitchers often select pitches that make a double play more likely (typically a pitch easily hit as a ground ball to a middle infielder) and teams on defense alter infield positions to make a ground ball more likely to be turned into a double play. Because a double play ends an inning in a one-out situation, it often makes the scoring of a run impossible in that inning. In a no-out situation with runners at first base and third base, the double play may be so desirable that the defensive team allows a runner to score from third base so that two outs are made and further scoring by the batting team is more difficult. Double plays initiated by a batter hitting a ground ball (but not a fly ball or line drive) are recorded in the official statistic GIDP (Grounded Into a Double Play), an indicator of one f...
Predictably Irrational meets Moneyball in ESPN veteran writer and statistical analyst Keith Law’s iconoclastic look at the numbers game of baseball, proving why some of the most trusted stats are surprisingly wrong, explaining what numbers actually work, and exploring what the rise of Big Data means for the future of the sport. For decades, statistics such as batting average, saves recorded, and pitching won-lost records have been used to measure individual players’ and teams’ potential and success. But in the past fifteen years, a revolutionary new standard of measurement—sabermetrics—has been embraced by front offices in Major League Baseball and among fantasy baseball enthusiasts. But while sabermetrics is recognized as being smarter and more accurate, traditionalists, including journalists, fans, and managers, stubbornly believe that the "old" way—a combination of outdated numbers and "gut" instinct—is still the best way. Baseball, they argue, should be run by people, not by numbers.? In this informative and provocative book, teh renowned ESPN analyst and senior baseball writer demolishes a century’s worth of accepted wisdom, making the definitive case against the long-established view. Armed with concrete examples from different eras of baseball history, logic, a little math, and lively commentary, he shows how the allegiance to these numbers—dating back to the beginning of the professional game—is firmly rooted not in accuracy or success, but in baseball’s irrational adherence to tradition. While Law gores sacred cows, from clutch performers to RBIs to the infamous save rule, he also demystifies sabermetrics, explaining what these "new" numbers really are and why they’re vital. He also considers the game’s future, examining how teams are using Data—from PhDs to sophisticated statistical databases—to build future rosters; changes that will transform baseball and all of professional sports.