Big data baseball: math, miracles, and the end of a 20-year losing streak
(Book)

Book Cover
Average Rating
Published:
New York : Flatiron Books, 2015.
Format:
Book
Edition:
First edition
Physical Desc:
242 pages ; 24 cm
Status:
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. 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. Hurdle and Huntington got to work trying to convince the entire Pirates organization and disgruntled fans to embrace these unconventional, yet groundbreaking methods. All this led to the end to the longest consecutive run of losing seasons in North American pro sports history.The Pirates' 2013 season is the perfect lens for examining baseball's burgeoning big-data movement. Using flawless reporting, award-winning journalist Travis Sawchik takes you behind-the-scenes to reveal a game-changing book of miracles and math"--

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Status
Guilford Adult Non-Fiction
796.357 SAWCHIK
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Meriden Adult Non-Fiction
796.357 SA
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More Details
Language:
English
ISBN:
9781250063502

Notes

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. 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. Hurdle and Huntington got to work trying to convince the entire Pirates organization and disgruntled fans to embrace these unconventional, yet groundbreaking methods. All this led to the end to the longest consecutive run of losing seasons in North American pro sports history.The Pirates' 2013 season is the perfect lens for examining baseball's burgeoning big-data movement. Using flawless reporting, award-winning journalist Travis Sawchik takes you behind-the-scenes to reveal a game-changing book of miracles and math"--,Provided by publisher.
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Citations
APA Citation (style guide)

Sawchik, T. (2015). Big data baseball: math, miracles, and the end of a 20-year losing streak. First edition New York, Flatiron Books.

Chicago / Turabian - Author Date Citation (style guide)

Sawchik, Travis. 2015. Big Data Baseball: Math, Miracles, and the End of a 20-year Losing Streak. New York, Flatiron Books.

Chicago / Turabian - Humanities Citation (style guide)

Sawchik, Travis, Big Data Baseball: Math, Miracles, and the End of a 20-year Losing Streak. New York, Flatiron Books, 2015.

MLA Citation (style guide)

Sawchik, Travis. Big Data Baseball: Math, Miracles, and the End of a 20-year Losing Streak. First edition New York, Flatiron Books, 2015.

Note! Citation formats are based on standards as of July 2022. Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy.
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Grouped Work ID:
1d0fee3c-6f8b-b488-5755-52a03c13780e
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Record Information

Last Sierra Extract TimeMar 18, 2024 08:02:23 PM
Last File Modification TimeMar 18, 2024 08:03:08 PM
Last Grouped Work Modification TimeMar 18, 2024 08:02:29 PM

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