Big Data Baseball

Author: Travis Sawchik
Publisher: Flatiron Books
ISBN: 9781250094254
Category : Sports & Recreation
Languages : en
Pages : 0

Book Description
Big Data Baseball provides a behind-the-scenes look at how the Pittsburgh Pirates used big data strategies to end the longest losing streak in North American pro sports history. New York Times Bestseller After twenty consecutive losing seasons for the Pittsburgh Pirates, team morale was low, the club’s payroll ranked near the bottom of the sport, game attendance was down, and the city was becoming increasingly disenchanted with its team. Big Data Baseball is the story of how the 2013 Pirates, mired in the longest losing streak in North American pro sports history, adopted drastic big-data strategies to end the drought, make the playoffs, and turn around the franchise’s fortunes. Big Data Baseball is Moneyball for a new generation. Award-winning journalist Travis Sawchik takes you behind the scenes to expertly weave together the stories of the key figures who changed the way the Pirates played the game, revealing how a culture of collaboration and creativity flourished as whiz-kid analysts worked alongside graybeard coaches to revolutionize the sport and uncover groundbreaking insights for how to win more games without spending a dime. From pitch framing to on-field shifts, this entertaining and enlightening underdog story closely examines baseball’s burgeoning big data movement and demonstrates how the millions of data points which aren’t immediately visible to players and spectators, are the bit of magic that led the Pirates to finish the 2013 season in second place and brought an end to a twenty-year losing streak.

Big Data Baseball

Author: Travis Sawchik
Publisher: Macmillan + ORM
ISBN: 1250063515
Category : Sports & Recreation
Languages : en
Pages : 235

Big Data Baseball

Author: Travis Sawchik
Publisher: Macmillan
ISBN: 1250063507
Category : Sports & Recreation
Languages : en
Pages : 255

Book Description
"Pittsburgh Pirates manager Clint Hurdle was old school and stubborn. But after twenty straight losing seasons and his job on the line, he was ready to try anything. So when he met with GM Neal Huntington in October 2012, they decided to discard everything they knew about the game and instead take on drastic 'big data' strategies. Going well beyond the number-crunching of Moneyball, which used statistics found on the back of baseball cards to identify market inefficiencies, the data the Pirates employed was not easily observable. They collected millions of data points on pitches and balls in play, creating a tome of reports that revealed key insights for how to win more games without spending a dime"--

The MVP Machine

Author: Ben Lindbergh
Publisher: Basic Books
ISBN: 1541698959
Category : Sports & Recreation
Languages : en
Pages : 428

Book Description
Move over, Moneyball -- this New York Times bestseller examines major league baseball's next cutting-edge revolution: the high-tech quest to build better players. As bestselling authors Ben Lindbergh and Travis Sawchik reveal in The MVP Machine, the Moneyball era is over. Fifteen years after Michael Lewis brought the Oakland Athletics' groundbreaking team-building strategies to light, every front office takes a data-driven approach to evaluating players, and the league's smarter teams no longer have a huge advantage in valuing past performance. Lindbergh and Sawchik's behind-the-scenes reporting reveals: How undersized afterthoughts José Altuve and Mookie Betts became big sluggers and MVPs How polarizing pitcher Trevor Bauer made himself a Cy Young contender How new analytical tools have overturned traditional pitching and hitting techniques How a wave of young talent is making MLB both better than ever and arguably worse to watch Instead of out-drafting, out-signing, and out-trading their rivals, baseball's best minds have turned to out-developing opponents, gaining greater edges than ever by perfecting prospects and eking extra runs out of older athletes who were once written off. Lindbergh and Sawchik take us inside the transformation of former fringe hitters into home-run kings, show how washed-up pitchers have emerged as aces, and document how coaching and scouting are being turned upside down. The MVP Machine charts the future of a sport and offers a lesson that goes beyond baseball: Success stems not from focusing on finished products, but from making the most of untapped potential.

When Big Data Was Small

Author: Richard D. Cramer
Publisher: U of Nebraska Press
ISBN: 1496215761
Category : Sports & Recreation
Languages : en
Pages : 317

Book Description
Richard D. Cramer has been doing baseball analytics for just about as long as anyone alive, even before the term "sabermetrics" existed. He started analyzing baseball statistics as a hobby in the mid-1960s, not long after graduating from Harvard and MIT. He was a research scientist for SmithKline and in his spare time used his work computer to test his theories about baseball statistics. One of his earliest discoveries was that clutch hitting--then one of the most sacred pieces of received wisdom in the game--didn't really exist. In When Big Data Was Small Cramer recounts his life and remarkable contributions to baseball knowledge. In 1971 Cramer learned about the Society for American Baseball Research (SABR) and began working with Pete Palmer, whose statistical work is credited with providing the foundation on which SABR is built. Cramer cofounded STATS Inc. and began working with the Houston Astros, Oakland A's, Yankees, and White Sox, with the help of his new Apple II computer. Yet for Cramer baseball was always a side interest, even if a very intense one for most of the last forty years. His main occupation, which involved other "big data" activities, was that of a chemist who pioneered the use of specialized analytics, often known as computer-aided drug discovery, to help guide the development of pharmaceutical drugs. After a decade-long hiatus, Cramer returned to baseball analytics in 2004 and has done important work with Retrosheet since then. When Big Data Was Small is the story of the earliest days of baseball analytics and computer-aided drug discovery.

Analyzing Baseball Data with R, Second Edition

Author: Max Marchi
Publisher: CRC Press
ISBN: 1351107070
Category : Mathematics
Languages : en
Pages : 302

Book Description
Analyzing Baseball Data with R Second Edition introduces R to sabermetricians, baseball enthusiasts, and students interested in exploring the richness of baseball data. It equips you with the necessary skills and software tools to perform all the analysis steps, from importing the data to transforming them into an appropriate format to visualizing the data via graphs to performing a statistical analysis. The authors first present an overview of publicly available baseball datasets and a gentle introduction to the type of data structures and exploratory and data management capabilities of R. They also cover the ggplot2 graphics functions and employ a tidyverse-friendly workflow throughout. Much of the book illustrates the use of R through popular sabermetrics topics, including the Pythagorean formula, runs expectancy, catcher framing, career trajectories, simulation of games and seasons, patterns of streaky behavior of players, and launch angles and exit velocities. All the datasets and R code used in the text are available online. New to the second edition are a systematic adoption of the tidyverse and incorporation of Statcast player tracking data (made available by Baseball Savant). All code from the first edition has been revised according to the principles of the tidyverse. Tidyverse packages, including dplyr, ggplot2, tidyr, purrr, and broom are emphasized throughout the book. Two entirely new chapters are made possible by the availability of Statcast data: one explores the notion of catcher framing ability, and the other uses launch angle and exit velocity to estimate the probability of a home run. Through the book’s various examples, you will learn about modern sabermetrics and how to conduct your own baseball analyses. Max Marchi is a Baseball Analytics Analyst for the Cleveland Indians. He was a regular contributor to The Hardball Times and Baseball Prospectus websites and previously consulted for other MLB clubs. Jim Albert is a Distinguished University Professor of statistics at Bowling Green State University. He has authored or coauthored several books including Curve Ball and Visualizing Baseball and was the editor of the Journal of Quantitative Analysis of Sports. Ben Baumer is an assistant professor of statistical & data sciences at Smith College. Previously a statistical analyst for the New York Mets, he is a co-author of The Sabermetric Revolution and Modern Data Science with R.

Future Value

Author: Eric Longenhagen
Publisher: Triumph Books
ISBN: 1641253975
Category : Sports & Recreation
Languages : en
Pages : 256

Book Description
An unprecedented look inside the world of baseball scouting and evaluation from two of the industry's top prospect analysts For the modern Major League team, player evaluation is a complex, multi-pronged, high-tech pursuit. But far from becoming obsolete in this environment—as Michael Lewis' Moneyball once forecast—the role of the scout in today's game has evolved and even expanded. Rather than being the antithesis of a data-driven approach, scouting now represents an essential analytical component in a team's arsenal. Future Value is a thorough dive into baseball's changing world of talent acquisition and development, a world with its own language, methods, metrics, and madness. From rural high schools to elite amateur showcases, from the back fields of spring training to major league draft rooms, Eric Longenhagen and Kiley McDaniel break down the key systems and techniques used to assess talent. It's a process that has moved beyond the quintessential stopwatches and radar guns to include statistical models, countless measurable indicators, and a broader international reach. ?Practical and probing, discussing wide-ranging topics from tool grades to front office politics, this is an illuminating exploration of how to watch baseball and see the future.

The Church of Baseball

Author: Ron Shelton
Publisher: Vintage
ISBN: 0593313968
Category : Biography & Autobiography
Languages : en
Pages : 257

Book Description
LA TIMES BESTSELLER • From the award-winning screenwriter and director of cult classic Bull Durham, the extremely entertaining behind-the-scenes story of the making of the film, and an insightful primer on the art and business of moviemaking. "This book tells you how to make a movie—the whole nine innings of it—out of nothing but sheer will.” —Tony Gilroy, writer/director of Michael Clayton and The Bourne Legacy "The only church that truly feeds the soul, day in, day out, is the church of baseball."—Annie in Bull Durham Bull Durham, the breakthrough 1988 film about a minor league baseball team, is widely revered as the best sports movie of all time. But back in 1987, Ron Shelton was a first-time director and no one was willing to finance a movie about baseball—especially a story set in the minors. The jury was still out on Kevin Costner’s leading-man potential, while Susan Sarandon was already a has-been. There were doubts. But something miraculous happened, and The Church of Baseball attempts to capture why. From organizing a baseball camp for the actors and rewriting key scenes while on set, to dealing with a short production schedule and overcoming the challenge of filming the sport, Shelton brings to life the making of this beloved American movie. Shelton explains the rarely revealed ins and outs of moviemaking, from a film’s inception and financing, screenwriting, casting, the nuts and bolts of directing, the postproduction process, and even through its release. But this is also a book about baseball and its singular romance in the world of sports. Shelton spent six years in the minor leagues before making this film, and his experiences resonate throughout this book. Full of wry humor and insight, The Church of Baseball tells the remarkable story behind an iconic film.

Analyzing Baseball Data with R

Author: Max Marchi
Publisher: CRC Press
ISBN: 1466570237
Category : Mathematics
Languages : en
Pages : 349

Book Description
With its flexible capabilities and open-source platform, R has become a major tool for analyzing detailed, high-quality baseball data. Analyzing Baseball Data with R provides an introduction to R for sabermetricians, baseball enthusiasts, and students interested in exploring the rich sources of baseball data. It equips readers with the necessary skills and software tools to perform all of the analysis steps, from gathering the datasets and entering them in a convenient format to visualizing the data via graphs to performing a statistical analysis. The authors first present an overview of publicly available baseball datasets and a gentle introduction to the type of data structures and exploratory and data management capabilities of R. They also cover the traditional graphics functions in the base package and introduce more sophisticated graphical displays available through the lattice and ggplot2 packages. Much of the book illustrates the use of R through popular sabermetrics topics, including the Pythagorean formula, runs expectancy, career trajectories, simulation of games and seasons, patterns of streaky behavior of players, and fielding measures. Each chapter contains exercises that encourage readers to perform their own analyses using R. All of the datasets and R code used in the text are available online. This book helps readers answer questions about baseball teams, players, and strategy using large, publically available datasets. It offers detailed instructions on downloading the datasets and putting them into formats that simplify data exploration and analysis. Through the book’s various examples, readers will learn about modern sabermetrics and be able to conduct their own baseball analyses.

Moneyball: The Art of Winning an Unfair Game

Author: Michael Lewis
Publisher: W. W. Norton & Company
ISBN: 0393066231
Category : Sports & Recreation
Languages : en
Pages : 337

Book Description
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?