More Testing of the Verducci Effect
After doing my analysis of the Verducci Effect yesterday, I became aware of Jeremy Greenhouse’s analysis on the subject. He uses a different method, but also finds little support for the Verducci Effect. His analysis pointed me to Josh Hermsmeyer’s Free Player Injury Database, which is valuable new resource. The database contains injury information dating back to the 2002 season. Because the Verducci Effect is largely about predicting injuries I wanted to see how player workloads predicted time on the Disabled List (DL). If significantly increasing pitcher workloads raises the incidence of future injuries, then pitchers who meet Verducci’s criteria should be more likely to get injured.
The table below lists the estimates for the impact of the Verducci Effect on DL stints. I estimated several models (including continuous estimates of pitcher workload), but I report only four specifications below because the results are consistent with the unreported estimates. I looked at the number of days on the DL (continuous) and whether or not a player ended up on the DL (discrete) using random-effects estimation models, least-squares for the former and logit for the latter. I also included the number of days on the DL in the preceding seasons in two specifications to control for the natural injury propensity of players.
DL Days DL Days On DL On DL Verducci 4.27 -1.89 0.28 0.06 [0.76] [0.59] [0.66] [0.12] Mean IP -0.19 -0.16 -0.006 -0.003 [9.33]** [12.75]** [4.69]** [2.01]* DL Days (t-1) 0.64 0.10 [54.16]** [14.06]** Constant 37.67 29.48 -0.50 -1.68 [14.77]** [18.60]** [3.23]** [8.69]** Observations 1428 1428 1428 1428 Overall R2 0.04 0.63 -- -- Absolute value of z statistics in brackets * significant at 5%; ** significant at 1%
Again, the results do not support the existence of the Verducci Effect. The estimates are small and not statistically significant. A change in workload by more than 30 innings for pitchers under 26 is not associated with more days on or trips to the DL. I would like to reiterate that there needs to be further testing of Verducci Effect, but so far there doesn’t appear to be much empirical support for the hypothesis.
At first, I was thinking the Verducci Effect had some pretty solid merit to it, but the statistics Verducci used to support his claim (during the MLB Channel interview) really made me suspicious. I agree that the idea necessitates more research, but it really seems to be more of a testament of MLB injury volatility rather than young workload hazards.