Concept

Sabermetrics

Summary
In sports analytics, sabermetrics (originally SABRmetrics) is the empirical analysis of baseball, especially baseball statistics that measure in-game activity. Sabermetricians collect and summarize the relevant data from this in-game activity to answer specific questions. The term is derived from the acronym SABR, which stands for the Society for American Baseball Research, founded in 1971. The term "sabermetrics" was coined by Bill James, who is one of its pioneers and is often considered its most prominent advocate and public face. Henry Chadwick, a sportswriter in New York, developed the box score in 1858. This was the first way statisticians were able to describe the sport of baseball by numerically tracking various aspects of game play. The creation of the box score has given baseball statisticians a summary of the individual and team performances for a given game. Sabermetrics research began in the middle of the 20th century with the writings of Earnshaw Cook, one of the earliest sabermetricians. Cook's 1964 book Percentage Baseball was one of the first of its kind. At first, most organized baseball teams and professionals dismissed Cook's work as meaningless. The idea of a science of baseball statistics began to achieve legitimacy in 1977 when Bill James began releasing Baseball Abstracts, his annual compendium of baseball data. However, James's ideas were slow to find widespread acceptance. Bill James believed there was a widespread misunderstanding about how the game of baseball was played, claiming the sport was not defined by its rules but actually, as summarized by engineering professor Richard J. Puerzer, "defined by the conditions under which the game is played--specifically, the ballparks but also the players, the ethics, the strategies, the equipment, and the expectations of the public." Sabermetricians—sometimes considered baseball statisticians—began trying to replace the longtime favorite statistic known as the batting average. It has been claimed that team batting average provides a relatively poor fit for team runs scored.
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