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Is Your Favorite Ballplayer Hitting When It Matters, or Just Padding His Stats?


Carlos Beltran, recently traded by the New York Yankees to the Houston Astros.

A team of computer scientists at Johns Hopkins University is adding to the ocean of baseball statistics with what appears to be the first analysis of hitters performance when their team is either just about guaranteed to win, or hopelessly behind.

Credit: Tom Szczerbowski/Getty Images

Johns Hopkins University researchers have added to the field of baseball statistics with the first analysis of hitters' performance when their team is either almost guaranteed to win, or is so far behind the game is out of reach, known as the Meaningless Game Situation (MGS).

The researchers found some players can significantly improve their overall season statistics by maximizing their performance in those situations.

The team views their data as a new kind of "split," similar to comparing players' performance in day games versus night games, or home games versus road games.

The analysis is based on statistics from four Major League seasons representing a sample of more than 9,600 games. The MGS standard applies to progressively smaller leads as the game unfolds. For example, it is considered if one team has a seven-run lead in the first inning, a six-run lead in the second through seventh innings, a five-run lead in the eighth inning, or a four-run lead in the ninth inning or later. Using that scale, the researchers determined for all 30 Major League teams during the 2016 regular season there were 21,089 plate appearances by 781 hitters categorized as MGS.

From Johns Hopkins University
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Abstracts Copyright © 2016 Information Inc., Bethesda, Maryland, USA


 

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