Does Fastball Velocity Influence a Pitcher’s HR/FB Ratio?
On Thursday, I posted an update on three American League rookie pitchers, including Seattle phenom Michael Pineda. One of my criticisms of Pineda was his 56% fly ball rate at the time, which should lead to lots of home runs, despite the fact that he had yet to give up even one long ball. One of the commenters noted Pineda’s fantastic average fastball velocity, currently sitting at 96.1 MPH, and opined that it will be more difficult for hitters to homer off of him, leading to a sustainable depressed HR/FB ratio compared to the league average. Not satisfied with just taking his word for it, I decided to test this hypothesis.
Using what limited knowledge I still retain from my college statistics class, I calculated the correlation between a pitcher’s fastball velocity and his HR/FB ratio. My sample size totaled 226 pitchers from 2001-2010 with a minimum of 500 innings pitched, and included both starters and relievers. Park adjustments or any other such fixes to make the study more accurate were not made. The correlation between the two variables was -.29. Below is a scatter plot of the data with the trendline.
There is a clear positive relationship between higher fastball velocity and a lower HR/FB ratio. This makes intuitive sense, so that is always a good sign. It appears that the commenter may be on to something that may help explain at least some of the differential between an outliers’ HR/FB ratio and the league average.
Over the years, there have been many formulas devised to estimate a pitcher’s ERA based on true talent, defense independence or only factors that are supposedly within the pitcher’s control. However, none of these ERA estimators include anything relating to pitch velocity or pitch type. This data is easily accessible and it does not seem like it would be too difficult to include it in future iterations of these formulas.
Mike Podhorzer is the 2015 Fantasy Sports Writers Association Baseball Writer of the Year and three-time Tout Wars champion. He is the author of the eBook Projecting X 2.0: How to Forecast Baseball Player Performance, which teaches you how to project players yourself. Follow Mike on X@MikePodhorzer and contact him via email.
interesting…but the big flaw i see is that you lumped relievers and starters together. relievers seem to have the ability to sustain slightly lower hr/fb rates than starters. i would think that they also tend to throw harder (at least this is true of the same pitcher pitching in relief vs. starting, and i would assume that it is true for the general population of relievers vs. starters). what happens if you redo it with only starters? i bet the correlation decreases significantly.
I wonder if it’s only relievers with exceptionally high velocity who can sustain low HR/FB…
Yes, it would have been better to have only included starters. Completely forgot FG has a “Starters” and “Relievers” tab to easily filter only starters. With only starters from 2001-2010, minimum 500 innings pitched and a total of 182 pitchers in the sample, correlation drops to -0.21. A decline as expected, but still appears to have some significance.
ok…and what’s the p-value? because the -0.21 might be significant…or it might not be