This article is part of our The Z Files series.
Whether it's a team's penchant for making the routine play, the outstanding play or simply better positioning, the best measure for our purposes is BABIP (batting average on balls in play). This is especially apropos for those generating pitching projections using component metrics. Each hurler's BABIP is usually regressed towards league mean for that type of pitcher (groundball, fly ball). Tempering towards team defense seems like a worthwhile endeavor.
Unfortunately, there's one catch. For BABIP to be reliable, it needs to be predictable. Today, team BABIP from the past five seasons will be investigated to gauge just how predictable, hence useful, it is in projecting pitcher performance.
The method will look at the correlation between projected team BABIP and actual, both in total and broken into components. The statistics will be kept relatively simple, gauging the linear relationship between projected and actual using the Pearson Coefficient (r). By means of explanation, r=1 means there is a direct relationship, actual is perfectly predicted by the past data. If r=0, the variables are completely random. When r=-1, there's a perfect inverse relationship. In this case, it would entail the worst BABIP becoming the best BABIP and vice versa.
To get things started, here's a table with each team's overall BABIP for the last five seasons: