So, Yu Darvish is off to a pretty good start to 2013. Through eight starts this season, the Ranger’s right-hander currently sports the following statistics:
Darvish currently ranks first (or tied for first) among qualified starters in K% and SwgStr%, and he has posted the 6th best adjusted FIP in the league (56 FIP-). After a blazing start, his ERA- has dropped to 20th and his HR/FB now ranks 84th, but overall it’s clear Darvish has been a beast in 2013.
After watching this wonderful footage from Darvish’s dismantling of the Angels last night I was struck by how slow is curveball actually is.
Our own Carson Cistulli isolated his four slow curves from that night — check out the final bender to Mike Trout, resulting in a strikeout in the 6th inning. And, yes, that was 61 mph.
I wondered whether the differential between Darvish’s fastball and curveball was the largest in the league. And, so, to the data I went.
I pulled the average velocity by pitch type from our PITCHf/x leaderboards and calculated the difference between each pitcher’s hardest thrown pitch and their slowest. I eliminated any pitches coded as an eephus pitch to get a more realistic read.
Through May 13, Darvish in fact has the greatest differential between his fastest and slowest thrown pitches at 26.1 mph. That’s 5 mph greater than the next starter, Chad Billingsley (21.1 mph) (note: Max and Min refer to the average velocities for a pitchers fastest and slowest pitches):
|2013||Jorge de la Rosa||Rockies||45.1||69||92||15.50%||91.4||73.4||18.0|
|2013||Jon Lester||Red Sox||52.2||64||78||21.50%||92.2||75.1||17.1|
Taking a look at the past four years, Darvish’s differential in 2013 ranks first among all starters since 2010. Darvish’s 2012 ranks 5th on the list:
|2012||Randy Wolf||– – –||157.2||142||121||14.90%||88.6||68.3||20.3|
|2012||Nathan Eovaldi||– – –||119.1||111||108||14.80%||94.3||74.5||19.8|
|2010||Roy Oswalt||– – –||211.2||69||83||23.10%||92.6||73.2||19.4|
Just eye-balling these lists it would appear that larger differentials in velocity are associated with better performance (i.e. ERA-, FIP-, K%). In fact, a pitchers velocity differential is significantly correlated with their K% (.167), HR/FB (.167), ERA- (.158), FIP- (.144), and IFFB% (.131). If we break starters up into various percentiles — based on the differential between their fastest and slowest pitches — we can better see the difference in their performance (weighted by innings pitched):
|Metric||90th P-tile||75th P-tile||25th P-tile|
On average, starters with differentials at or above the 75th percentile (15.3 mph) produce adjusted ERAs and FIPs about 7-8 points lower than those at or below the 25th percentile (10.7). Greater differential pitchers also strike out about two percent more of the batters they face (19.5% vs. 17.7 K%).
Between the correlations and the percentile comparisons it’s clear that, while making a difference, overall change of pace isn’t a huge differentiator for pitchers. However, it does have some impact and right now no one is doing it better than Yu Darvish.
Bill leads Predictive Modeling and Data Science consulting at Gallup. In his free time, he writes for The Hardball Times, speaks about baseball research and analytics, has consulted for a Major League Baseball team, and has appeared on MLB Network's Clubhouse Confidential as well as several MLB-produced documentaries. He is also the creator of the baseballr package for the R programming language. Along with Jeff Zimmerman, he won the 2013 SABR Analytics Research Award for Contemporary Analysis. Follow him on Twitter @BillPetti.