2020 Minor League Baseball Analyst

2020 Minor League Baseball Analyst

The first book of its kind to fully integrate sabermetrics and scouting, the 2020 Minor League Baseball Analyst provides a distinctive brand of analysis for more than 1,000 minor league baseball players. Features include scouting reports for all players, batter skills ratings, pitch repertoires, performance trends, major league equivalents, and expected major league debuts. A complete sabermetric glossary is also included. This one-of-a-kind reference is ideally suited for baseball analysts and those who play in fantasy leagues with farm systems.

2016 Minor League Baseball Analyst

2016 Minor League Baseball Analyst

Essential information for fantasy league baseball players and the best resource available to project future performance of minor leaguers The first book of its kind to fully integrate sabermetrics and scouting, the 2016 Minor League Baseball Analyst provides a distinctive brand of analysis for more than 1,000 minor league baseball players. Features include scouting reports for all players, batter skills ratings, pitch repertoires, performance trends, major league equivalents, and expected major league debuts. A complete sabermetric glossary is also included. This one-of-a-kind reference is ideally suited for baseball analysts and those who play in fantasy leagues with farm systems.

2015 Minor League Baseball Analyst

2015 Minor League Baseball Analyst

The first book of its kind to fully integrate sabermetrics and scouting, the 2015 Minor League Baseball Analyst provides a distinctive brand of analysis for more than 1,000 minor league baseball players. Features include scouting reports for all players, batter skills ratings, pitch repertoires, performance trends, major league equivalents, and expected major league debuts. A complete sabermetric glossary is also included. This one-of-a-kind reference is ideally suited for baseball analysts and those who play in fantasy leagues with farm systems.

Baseball Prospectus 2016

Baseball Prospectus 2016

The 2016 edition of the "New York Times" Bestselling Guide Welcome to The Show! After 20 All-Star seasons, the creators of this, the 21st edition of the industry-leading Baseball Prospectus annual, could have been content to rest on their laurels. Instead, "Baseball Prospectus 2016" contains significant improvements along with the usual key stat categories, player predictions and insider-level commentary that readers expect from Baseball Prospectus annual guide. "Baseball Prospectus 2016" once again provides fantasy players and insiders alike with prescient PECOTA projections, which "Sports Illustrated" has called perhaps the game s most accurate projection model. Still, stats are just numbers if you don t see the larger context, and Baseball Prospectus brings together an elite team of analysts to provide the definitive look at all thirty teams their players, their prospects and their managers to explain away flukes, hot streaks, injury-tainted numbers and park effects. Nearly every major-league team has sought the advice of current or former Prospectus analysts, and readers of "Baseball Prospectus" 2016 will understand what all those insiders have been raving about. In a book that sports personality Ken Tremendous calls The tip of the nerd spear, the team at Baseball Prospectus is proud to bring the following improvements to the 2016 Annual: Two full years of projections PECOTA lines for 2016 and 2017 Historical Peak MPH added for major-league pitchers Deserved Run Average (DRA) added for major-league pitchers cFIP added for major-league and minor-league pitchers Pitcher WARP redesigned, utilizing DRA and cFIP for all pitchers Revised cFIP-driven PECOTA pitching projections Catcher-specific defensive stats for all catchers Double-A and above Outfield assists and catcher defense integrated in FRAA and WARP Ballpark schematic and wall height study for every stadium Hit List, finance, and farm system ranking graphs for each team Every organization s key front office personnel and Baseball Prospectus alumni identified"

Game 7, 1986

Failure and Triumph in the Biggest Game of My Life

Game 7, 1986

New York Times Bestseller Every little kid who's ever taken the mound in Little League dreams of someday getting the ball for Game Seven of the World Series. Ron Darling got to live that dream - only it didn't go exactly as planned. In New York Times bestselling Game 7, 1986, the award-winning baseball analyst looks back at what might have been a signature moment in his career, and reflects on the ways professional athletes must sometimes shoulder a personal disappointment as his team finds a way to win. Published to coincide with the 30th anniversary of the 1986 New York Mets championship season, Darling's book will break down one of baseball's great "forgotten" games - a game that stands as a thrilling, telling and tantalizing exclamation point to one of the best-remember seasons in Major League Baseball history. Working once again with New York Times best-selling collaborator Daniel Paisner, who teamed with the former All-Star pitcher on his acclaimed 2009 memoir Game 7, 1986, Darling offers a book for the thinking baseball fan, a chance to reflect on what it means to compete at the game's highest level, with everything on the line.

The Only Rule Is It Has to Work

Our Wild Experiment Building a New Kind of Baseball Team

The Only Rule Is It Has to Work

The New York Times bestseller about what would happen if two statistics-minded outsiders were allowed to run a professional baseball team It’s the ultimate in fantasy baseball: You get to pick the roster, set the lineup, and decide on strategies -- with real players, in a real ballpark, in a real playoff race. That’s what baseball analysts Ben Lindbergh and Sam Miller got to do when an independent minor-league team in California, the Sonoma Stompers, offered them the chance to run its baseball operations according to the most advanced statistics. Their story in The Only Rule is it Has to Work is unlike any other baseball tale you've ever read. We tag along as Lindbergh and Miller apply their number-crunching insights to all aspects of assembling and running a team, following one cardinal rule for judging each innovation they try: it has to work. We meet colorful figures like general manager Theo Fightmaster and boundary-breakers like the first openly gay player in professional baseball. Even José Canseco makes a cameo appearance. Will their knowledge of numbers help Lindbergh and Miller bring the Stompers a championship, or will they fall on their faces? Will the team have a competitive advantage or is the sport’s folk wisdom true after all? Will the players attract the attention of big-league scouts, or are they on a fast track to oblivion? It’s a wild ride, by turns provocative and absurd, as Lindbergh and Miller tell a story that will speak to numbers geeks and traditionalists alike. And they prove that you don’t need a bat or a glove to make a genuine contribution to the game.

Try Not to Suck

The Exceptional, Extraordinary Baseball Life of Joe Maddon

Try Not to Suck

With his irreverant personality, laid-back approach, and penchant for the unexpected, Joe Maddon is a singular presence among Major League Baseball managers. Whether he's bringing clowns and live bear cubs to spring training or leading the Chicago Cubs to their first World Series victory in 108 years, Maddon is always one to watch. In Try Not to Suck, ESPN's Jesse Rogers and MLB.com's Bill Chastain fully explore Maddon's life and career, delving behind the scenes and dissecting that mystique which makes Maddon so popular with players and analysts alike. Packed with insight, anecdotes, and little-known facts, this is the definitive account of the curse-breaker and trailblazer at the helm of the Cubs' new era.

Analyzing Baseball Data with R

Analyzing Baseball Data with R

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.

Big Data Baseball

Math, Miracles, and the End of a 20-Year Losing Streak

Big Data Baseball

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. Pittsburghers joked their town was the city of champions...and the Pirates. 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. 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 small-market Pirates played the game. For manager Clint Hurdle and the front office staff to save their jobs, they could not rely on a free agent spending spree, instead they had to improve the sum of their parts and find hidden value. They had to change. From Hurdle shedding his old-school ways to work closely with Neal Huntington, the forward-thinking data-driven GM and his team of talented analysts; to pitchers like A. J. Burnett and Gerrit Cole changing what and where they threw; to Russell Martin, the undervalued catcher whose expert use of the nearly-invisible skill of pitch framing helped the team's pitchers turn more balls into strikes; to Clint Barmes, a solid shortstop and one of the early adopters of the unconventional on-field shift which forced the entire infield to realign into positions they never stood in before. Under Hurdle's leadership, a culture of collaboration and creativity flourished as he successfully blended whiz kid analysts with graybeard coaches—a kind of symbiotic teamwork which was unique to the sport. Big Data Baseball is Moneyball on steroids. It is an entertaining and enlightening underdog story that uses the 2013 Pirates season as the perfect lens to examine the sport's burgeoning big-data movement. With the help of data-tracking systems like PitchF/X and TrackMan, the Pirates collected millions of data points on every pitch and ball in play to create a tome of color-coded reports that revealed groundbreaking insights for how to win more games without spending a dime. In the process, they discovered that most batters struggled to hit two-seam fastballs, that an aggressive defensive shift on the field could turn more batted balls into outs, and that a catcher's most valuable skill was hidden. All these data points which aren't immediately visible to players and spectators, are the bit of magic that led the Pirates to spin straw in to gold, finish the 2013 season in second place, end a twenty-year losing streak.