Baseball’s Most Extreme Pitches from Starters, So Far
Introduction
After reading Jeff Sullivan’s piece entitled “Identifying Baseball’s Most Unhittable Pitches, So Far” on August 21, I found his methodology to be quite interesting. It was suggested in the comments rather than looking at whiff rate we should consider who has allowed the weakest contact. Now, there are a couple of different ways to look at weakest contact. First, you could look at batted ball velocity. You could also look at batted ball distance as well. Both of these techniques would provide some measure of the severity of contact allowed by a pitcher. At the end of the day though, a warning track fly ball is still as effective for a pitcher as a pop up. I thought it would be better to look at who got hurt the least with their pitches.
In saying that, I mean to look at what pitchers are theoretically giving up nothing but singles on a pitch versus what pitchers are theoretically giving up nothing but home runs. A quick calculation to quantify this value is total bases per hit allowed (TB/H). This is the same as the ratio between slugging percentage and batting average (SLG/AVG). Values have to be between one and four. A value of 1.00 corresponds to only singles. A value of 4.00 corresponds to only home runs. Any value in between could represent a combination of all hit types.
Baseball Prospectus provides PitchF/X leaderboards for eight different pitch types: four-seam fastball, sinker, cutter, splitter, changeup, curveball, slider, and knuckleball. I chose to look at only starting pitchers in this study. Also, to be considered, a pitcher had to have thrown at least 200 of the pitch of interest. The league leaders in games started are just above 25. If we are conservative and estimate 80 pitches per start, that allows for 2000 pitches thrown, so 200 would represent roughly 10% of the pitcher’s arsenal. With that background information now covered, let’s look at the best and worst pitchers in each pitch type. All data is accurate through August 22.
Data
Four-Seam Fastball
Pitcher |
Team |
TB/H |
Pitcher |
Team |
TB/H |
Jarrod Cosart |
HOU |
1.20 |
Lucas Harrell |
HOU |
2.33 |
Tyler Chatwood |
COL |
1.20 |
Todd Redmond |
TOR |
2.20 |
Stephen Fife |
LAD |
1.22 |
Allen Webster |
BOS |
2.20 |
Bartolo Colon |
OAK |
1.26 |
Tyler Skaggs |
ARI |
2.15 |
Joe Kelly |
STL |
1.26 |
Erik Bedard |
HOU |
2.10 |
Sinker
Pitcher |
Team |
TB/H |
Pitcher |
Team |
TB/H |
Brandon Cumpton |
PIT |
1.10 |
Yu Darvish |
TEX |
2.27 |
Taylor Jordan |
WSH |
1.10 |
Bud Norris |
BAL |
2.12 |
John Lackey |
BOS |
1.21 |
Aaron Harang |
SEA |
1.96 |
Gerrit Cole |
PIT |
1.22 |
Scott Kazmir |
CLE |
1.93 |
Jonathan Pettibone |
PHI |
1.22 |
Jon Lester |
BOS |
1.92 |
Wade Davis |
KCR |
1.22 |
Cutter
Pitcher |
Team |
TB/H |
Pitcher |
Team |
TB/H |
Clay Buchholz |
BOS |
1.11 |
Jeff Samardzija |
CHC |
2.00 |
Jenrry Mejia |
NYM |
1.17 |
Jerome Williams |
LAA |
1.95 |
Lucas Harrell |
HOU |
1.20 |
Cole Hamels |
PHI |
1.90 |
Jonathon Niese |
NYM |
1.21 |
A.J. Griffin |
OAK |
1.86 |
Mike Pelfrey |
MIN |
1.31 |
Yu Darvish |
TEX |
1.85 |
Splitter
Pitcher |
Team |
TB/H |
Pitcher |
Team |
TB/H |
Hiroki Kuroda |
NYY |
1.22 |
Ubaldo Jimenez |
CLE |
1.72 |
Jake Westbrook |
STL |
1.31 |
Tim Hudson |
ATL |
1.70 |
Jorge de la Rosa |
COL |
1.32 |
Dan Haren |
WSH |
1.69 |
Doug Fister |
DET |
1.33 |
Tim Lincecum |
SFG |
1.61 |
Hisashi Iwamuka |
SEA |
1.33 |
Jason Marquis |
SDP |
1.58 |
Changeup
Pitcher |
Team |
TB/H |
Pitcher |
Team |
TB/H |
Stephen Strasburg |
WSH |
1.00 |
John Danks |
CHW |
2.21 |
Matt Harvey |
NYM |
1.06 |
Jeremy Hefner |
NYM |
1.96 |
Gio Gonzalez |
WSH |
1.10 |
Dan Straily |
OAK |
1.91 |
Francisco Liriano |
PIT |
1.14 |
Randall Delgado |
ARI |
1.89 |
Bud Norris |
BAL |
1.22 |
Edinson Volquez |
SDP |
1.87 |
Curveball
Pitcher |
Team |
TB/H |
Pitcher |
Team |
TB/H |
Clayton Kershaw |
LAD |
1.00 |
Homer Bailey |
CIN |
2.33 |
Jason Hammel |
BAL |
1.00 |
Zack Greinke |
LAD |
2.09 |
C.J. Wilson |
LAA |
1.07 |
Wandy Rodriguez |
PIT |
2.00 |
Dillon Gee |
NYM |
1.14 |
Tim Hudson |
ATL |
2.00 |
Max Scherzer |
DET |
1.17 |
John Lackey |
BOS |
2.00 |
Slider
Pitcher |
Team |
TB/H |
Pitcher |
Team |
TB/H |
Tyson Ross |
SDP |
1.00 |
Jordan Zimmermann |
WSH |
2.24 |
Jorge de la Rosa |
COL |
1.17 |
Wade Miley |
ARI |
2.07 |
Bartolo Colon |
OAK |
1.18 |
Dallas Keuchel |
HOU |
2.06 |
Jeremy Hefner |
NYM |
1.24 |
Carlos Villanueva |
CHC |
2.06 |
C.J. Wilson |
LAA |
1.24 |
Hisashi Iwamuka |
SEA |
1.96 |
And for completeness,
Knuckleball
Pitcher |
Team |
TB/H |
R.A. Dickey |
TOR |
1.68 |
Combining all that data together, we get the following five pitches as the best in baseball so far.
Pitcher |
Team |
Pitch |
TB/H |
Stephen Strasburg |
WSH |
Changeup |
1.00 |
Clayton Kershaw |
LAD |
Curveball |
1.00 |
Jason Hammel |
BAL |
Curveball |
1.00 |
Tyson Ross |
SDP |
Slider |
1.00 |
Matt Harvey |
NYM |
Changeup |
1.06 |
Also, to complete the picture, here are the worst five pitches in baseball so far.
Pitcher |
Team |
Pitch |
TB/H |
Lucas Harrell |
HOU |
Four-Seam |
2.33 |
Homer Bailey |
CIN |
Curveball |
2.33 |
Yu Darvish |
TEX |
Sinker |
2.27 |
Jordan Zimmermann |
WSH |
Slider |
2.24 |
John Danks |
CHW |
Changeup |
2.21 |
Analysis
As you can see, there are a lot of “good” pitchers that throw “lousy” pitches. This metric is far from perfect. For example, Yu Darvish appears in the bottom five in two different categories. Does that mean Darvish should stop throwing his sinker and cutter? No, it most certainly does not. It just shows that when Darvish makes a (albeit rare) mistake with either pitch hitters are mashing it. I found this a fun exercise that yielded results that may not be the most meaningful but that are interesting for discussion nonetheless.
Stats All Folks is a frustrated former Little League pitcher that knows if he could have only been taller, stronger, more athletic with more velocity on his fastball, better offspeed stuff, and improved control, he could have been the first overall pick in the MLB First-Year Player Draft. Alas, it was not in the cards for him.
Interesting approach. I wonder, though — using TB per H removes the whiff rate from the equation entirely. Wouldn’t it be better to use something like wFB/C to show the pitch’s effectiveness on a per-pitch scale, not it’s effectiveness on a per-times-put-in-play scale? Thanks for the read.
Yes, it would be much more accurate to do as you suggested. This was just a quick, sort of back of the envelope calculation that I found interesting. I do plan to look at this more closely and make changes similar to what you’ve suggested. I already am working on this. I just haven’t completely finished compiling the data. I plan to post another article when I’m finish. Thanks for you comments.
I like where this is going, but wouldn’t it be a good idea to use something like TB/BIP? If a player gives up 5 HR, 95 outs in 100 fastballs,that’s a score of 4. But 80 singles and 20 outs is a score of 1.
That’s a good step, but sing BIP as the denominator removes swinging strikes, which is a major part of a pitch’s dominance. Only including the balls that get swung at and hit removes the balls that get swung at and missed, which is probably more impressive.