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Spring Training: Still Useless For Predicting Stats March 12, 2015

A few days ago, I watched a Mets-Marlins spring training game that ended in a brutal 13-2 loss. It had all of the usual spring training fun – Zack Wheeler working too far inside and hitting two batters, Michael Cuddyer starting at first with Lucas Duda out, and Don Kelly’s hustle allowing him to draw a walk, steal a base, and score on a single, even while Cliff Floyd was snickering about how Jim Leyland kept him on the roster for no apparent reason in the playoffs.

(Yeah, I know, Kelly’s a Marlin. Shut up.)

During the game, I tweeted out a link to a file-drawer post from last year that indicated that there’s almost no correlation between spring performance and regular-season performance. I thought I’d run a quick update on that, so I dug up the Mets’ individual performance in spring training and analyze it compared to the regular season.

There were 15 Mets who had 30 plate appearances in Spring Training and 100 plate appearances in the regular season. That’s a really small sample, so accuracywise we’d better keep our fingers crossed, but it’s enough data to spitball a little.

I ran four correlations on this – spring and regular season batting average, OBP, SLG, and OPS – and then created an additional stat to measure whether hitters changed hitting style from spring to the regular season. This was a quick and dirty attempt to measure whether hitters favored OBP or SLG, so I took the ratio (SLG/OPS) and reasoned that a power hitter will have a larger ratio and a singles hitter will have a smaller. I measured this correlation, too, to determine if there were big changes.

The results are unsurprising – the correlations are really low. Batting average correlates at around .019, and SLG at .305. OBP actually had a negative correlation, indicating that a high spring OBP may be a bad sign for the regular season. This is probably sampling error, due to the tiny number of observations, due almost entirely to Anthony Recker’s magical .426 spring and average regular season. That was about a -.25 correlation, which explains why OPS has a -.05 (near-zero) correlation – that big flip in OBP is going to offset the OPS correlation, too.

The strongest correlation was style – at about .619, it’s a pretty good indicator that if a hitter’s SLG is how he scores, he’ll maintain that hitting style throughout the season.