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Practicing Sabermetrics

Author: Gabriel B. Costa

Publisher: McFarland

Published: 2009-10-21

Total Pages: 241

ISBN-13: 0786454466

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.

Understanding Sabermetrics

Author: Gabriel B. Costa

Publisher: McFarland

Published: 2019-06-05

Total Pages: 221

ISBN-13: 1476667667

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Interest in Sabermetrics has increased dramatically in recent years as the need to better compare baseball players has intensified among managers, agents and fans, and even other players. The authors explain how traditional measures--such as Earned Run Average, Slugging Percentage, and Fielding Percentage--along with new statistics--Wins Above Average, Fielding Independent Pitching, Wins Above Replacement, the Equivalence Coefficient and others--define the value of players. Actual player statistics are used in developing models, while examples and exercises are provided in each chapter. This book serves as a guide for both beginners and those who wish to be successful in fantasy leagues.

Reasoning with Sabermetrics

Author: Gabriel B. Costa

Publisher: McFarland

Published: 2012-08-17

Total Pages: 217

ISBN-13: 0786492813

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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.

Sabermetrics

Author: Gabriel B. Costa

Publisher: Academic Press

Published: 2021-10-27

Total Pages: 219

ISBN-13: 0128223464

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Sabermetrics: Baseball, Steroids, and How the Game has Changed Over the Past Two Generations offers an introduction to this increasing area of interest to statisticians, students of the game, and many others. Pairing a primer on the applied math with an overview of the origin of the field and its context within baseball today, the work provides an engaging resource for students and interested readers. It includes coverage of relevant baseball history, Bill James and SABR, broken records and steroids. Drawing on the author’s experience teaching the subject at Seton Hall University since 1988, Sabermetrics also offers practice questions and solutions for class use. Provides an accessible, brief introduction to the practice of sabermetrics Approaches the topic in context with recent trends and issues in baseball Includes questions and solutions for math practice

Analyzing Baseball Data with R, Second Edition

Author: Max Marchi

Publisher: CRC Press

Published: 2018-11-19

Total Pages: 318

ISBN-13: 1351107070

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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.

Moneyball: The Art of Winning an Unfair Game

Author: Michael Lewis

Publisher: W. W. Norton & Company

Published: 2004-03-17

Total Pages: 336

ISBN-13: 0393066231

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"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.

Understanding Sabermetrics

Author: Gabriel B. Costa,

Publisher: McFarland

Published: 2019-06-07

Total Pages: 220

ISBN-13: 1476635021

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Interest in Sabermetrics has increased dramatically in recent years as the need to better compare baseball players has intensified among managers, agents and fans, and even other players. The authors explain how traditional measures—such as Earned Run Average, Slugging Percentage, and Fielding Percentage—along with new statistics—Wins Above Average, Fielding Independent Pitching, Wins Above Replacement, the Equivalence Coefficient and others—define the value of players. Actual player statistics are used in developing models, while examples and exercises are provided in each chapter. This book serves as a guide for both beginners and those who wish to be successful in fantasy leagues.

Baseball Hacks

Author: Joseph Adler

Publisher: "O'Reilly Media, Inc."

Published: 2006-01-31

Total Pages: 486

ISBN-13: 1491949422

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Baseball Hacks isn't your typical baseball book--it's a book about how to watch, research, and understand baseball. It's an instruction manual for the free baseball databases. It's a cookbook for baseball research. Every part of this book is designed to teach baseball fans how to do something. In short, it's a how-to book--one that will increase your enjoyment and knowledge of the game. So much of the way baseball is played today hinges upon interpreting statistical data. Players are acquired based on their performance in statistical categories that ownership deems most important. Managers make in-game decisions based not on instincts, but on probability - how a particular batter might fare against left-handedpitching, for instance. The goal of this unique book is to show fans all the baseball-related stuff that they can do for free (or close to free). Just as open source projects have made great software freely available, collaborative projects such as Retrosheet and Baseball DataBank have made great data freely available. You can use these data sources to research your favorite players, win your fantasy league, or appreciate the game of baseball even more than you do now. Baseball Hacks shows how easy it is to get data, process it, and use it to truly understand baseball. The book lists a number of sources for current and historical baseball data, and explains how to load it into a database for analysis. It then introduces several powerful statistical tools for understanding data and forecasting results. For the uninitiated baseball fan, author Joseph Adler walks readers through the core statistical categories for hitters (batting average, on-base percentage, etc.), pitchers (earned run average, strikeout-to-walk ratio, etc.), and fielders (putouts, errors, etc.). He then extrapolates upon these numbers to examine more advanced data groups like career averages, team stats, season-by-season comparisons, and more. Whether you're a mathematician, scientist, or season-ticket holder to your favorite team, Baseball Hacks is sure to have something for you. Advance praise for Baseball Hacks: "Baseball Hacks is the best book ever written for understanding and practicing baseball analytics. A must-read for baseball professionals and enthusiasts alike." -- Ari Kaplan, database consultant to the Montreal Expos, San Diego Padres, and Baltimore Orioles "The game was born in the 19th century, but the passion for its analysis continues to grow into the 21st. In Baseball Hacks, Joe Adler not only demonstrates thatthe latest data-mining technologies have useful application to the study of baseball statistics, he also teaches the reader how to do the analysis himself, arming the dedicated baseball fan with tools to take his understanding of the game to a higher level." -- Mark E. Johnson, Ph.D., Founder, SportMetrika, Inc. and Baseball Analyst for the 2004 St. Louis Cardinals

Benchmarking in Institutional Research

Author: Gary D. Levy

Publisher: John Wiley & Sons

Published: 2012-12-21

Total Pages: 105

ISBN-13: 1118641043

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While the term benchmarking is commonplace nowadays in institutional research and higher education, less common, is a solid understanding of what it really means and how it has been, and can be, used effectively. This volume begins by defining benchmarking as “a strategic and structured approach whereby an organization compares aspects of its processes and/or outcomes to those of another organization or set of organizations to identify opportunities for improvement.” Building on this definition, the chapters provide a brief history of the evolution and emergence of benchmarking in general and in higher education in particular. The authors apply benchmarking to: Enrollment management and student success Institutional effectiveness The potential economic impact of higher education institutions on their host communities. They look at the use of national external survey data in institutional benchmarking and selection of peer institutions, introduce multivariate statistical methodologies for guiding that selection, and consider a novel application of baseball sabermetric methods. The volume offers a solid starting point for those new to benchmarking in higher education and provides examples of current best practices and prospective new directions. This is the 156th volume of this Jossey-Bass series. Always timely and comprehensive, New Directions for Institutional Research provides planners and administrators in all types of academic institutions with guidelines in such areas as resource coordination, information analysis, program evaluation, and institutional management.

Big Data Baseball

Author: Travis Sawchik

Publisher: Macmillan + ORM

Published: 2015-05-19

Total Pages: 235

ISBN-13: 1250063515

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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.