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Bill James, who coined the term "sabermetrics". Sabermetrics (originally SABRmetrics) is the original or blanket term for sports analytics in the US, the empirical analysis of baseball, especially the development of advanced metrics based on baseball statistics that measure in-game activity.
In baseball, isolated power or ISO is a sabermetric computation used to measure a batter's raw power. One formula is slugging percentage minus batting average.
NERD was originally created by Carson Cistulli [1] and is part of his project of exploring the "art" of sabermetric research. [2] The original NERD formula only took into account the pitcher's expected performance [1] while a later model factors in the entire team's performance. [3] [4]
The formula is (ISO is isolated power): = + + = + + Power/Speed Number . A statistic that attempts to consolidate the various "clubs" of players with impressive numbers of both home runs and stolen bases (e.g., the 30–30 club ( Bobby Bonds was well known for being a member), the 40–40 club ( Jose Canseco was the first to perform this feat ...
Batting Park Factor, also simply called Park Factor or BPF, is a baseball statistic that indicates the difference between runs scored in a team's home and road games. Most commonly used as a metric in the sabermetric community, it has found more general usage in recent years.
PECOTA, an acronym for Player Empirical Comparison and Optimization Test Algorithm, [1] is a sabermetric system for forecasting Major League Baseball player performance. The word is a backronym based on the name of journeyman major league player Bill Pecota, who, with a lifetime batting average of .249, is perhaps representative of the typical PECOTA entry.
Win Shares is a 2002 book about baseball written by Bill James and Jim Henzler. The book explains how to apply the concept of sabermetrics to assess the impact of player performance in a combination of several areas, including offensive, defensive, and pitching on their team's overall performance.
Initially the correlation between the formula and actual winning percentage was simply an experimental observation. In 2003, Hein Hundal provided an inexact derivation of the formula and showed that the Pythagorean exponent was approximately 2/(σ √ π) where σ was the standard deviation of runs scored by all teams divided by the average number of runs scored. [8]