The Predictive Power of AFL Batting Stats: A Partial Study
Despite the fact that they are generally cited as probably providing little in the way of predictive power, the batting lines of prospects in the Arizona Fall League are also frequently cited by baseball writers in discussions of those same prospects. Nor is this entirely surprising: one wants to make some sort of comment about Kris Bryant, for example, who’s just finished his own AFL season with six home runs and a .727 slugging percentage. Even after noting that he recorded those figures in just 92 plate appearances, one is compelled to suggest that Bryant’s performance was impressive. And it was, certainly, within the context of the 2013 season of the Arizona Fall League.
The present author, attempting to behave somewhat responsibly, has produced statistical reports for the AFL this fall which utilize an offensive metric (called SCOUT+) that combines regressed home-run, walk, and strikeout rates in a FIP-like equation to produce a result not unlike wRC+. By isolating and regressing those metrics (i.e. not BABIP) which become reliable in smaller samples, one reasons, it’s possible to reduce the noise otherwise present in slash lines — and perhaps to better identify how performances from the AFL might inform future major-league production.
“How successful is this (theoretically) more responsible and (definitely) more nerdy attempt to measure AFL production, to the extent that it might hold within it some manner of predictive power?” one might, perhaps already has, wondered. “Not very,” appears to be the answer.