Those who know me personally can attest to the fact that I am a big sports fan. More importantly, I am a sports fan who pays close attention to statistics and what those statistics mean — especially in baseball. One of my biggest pet peeves as a sports fan is when an announcer refers to a player as “clutch”. This bothers me because it is usually after pointing out that a particular batter is 6 for 7 with the bases loaded (or runners in scoring position or . . . ) thereby ignoring the relevance of sample size. It is with great pleasure that I discovered J.C. Bradbury’s recent post on clutch hitting. Here is an overview:
I used probit models to estimate the likelihood that a player would get a hit (1 = hit; 0 = otherwise), or get on base (1= hit, walk, or hbp; 0 = otherwise) controlling for the player’s seasonal performance in that area (AVG or OBP), RISP 1989–91 performance in that area, whether the the platoon advantage was in effect (1 = platton; 0 = otherwise), and the pitcher’s ability in that area. To test hitting power, I used the count regression negative binomial method to estimate the expected number of total bases during the plate appearance and used his RSIP SLG 1989–1991 as a proxy for clutch skill in this area.
In samples of this size, statistical significance isn’t difficult to achieve; therefore, it isn’t surprising that in all but two instances the variables are significant. The two that are insignificant are the past RISP performance in batting average and slugging average. Thus, clutch ability doesn’t appear to be strong here.
However, the estimate of a clutch effect is statistically significant for getting on base. Is this evidence for clutch ability? Well, let’s interpret the coefficient. Every one-unit increase in RISP OBP is associated with a 0.00018 increase in the likelihood of getting on base; thus, a player increasing his RISP OBP by 0.010 (10 OBP points) increases his on-base probability by 0.0000018. For practical purposes, there is no effect.
There is no such thing as “clutch”.