In today's baseball world, there is much more than simply runs, home run, wins and losses. The sabermetrics study has developed this into an actual course, as it is even being taught in universities around the country.
Even a statistic that seems straight forward, such as batting average, is not so simple in the sabermetrics world. A player's Equivalent Avereage, or EqA, is intended to express the production of a hitter in a context independent of park and league effects.
This statistic is also used to evaluate minor league players, and in fact has been shown to be a good determinant of how well they will perform in the major leagues. The PECOTA, or the Player Empirical Comparison and Optimization Test Algorithm, is the study that sabermetitians undergo every year for players. This PECOTA business is actually pretty interesting, as I will explain later.
Information such as EqA can be very valuable for a general manager. Perhaps a player played in a hitter friendly ballpark, or faced and above average number of terrible pitchers. These sorts of things can falsely improve the batter's statistics, yet he might not be as good as he seems. This EqA helps to eliminate this factor.
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