Underthrown Pitches And The Pitchers Who Underthrow Them: Vol. 2 Cutters and Curves
Two weeks ago, I went searching for some of the league’s underthrown pitches. Which offerings by virtue of their paucity, despite excelling at inducing whiffs and weak contact, should be thrown more often? We’ve seen it so many times in the past, when a pitcher of whom we think a known quantity, suddenly leans on one pitch just a little more heavily and reinvents himself. Last week, we looked at the league’s underthrown four-seam fastballs and sinkers. This week, we turn to cutters and curves.
First, a quick refresher on the methodology. For any secondary pitch type thrown by a starter at least 50 times this season, I calculated a pitch score based on Z-scores of 1) whiffs per swing and 2) ground balls-plus-pop-ups per ball-in-play. I then divided that Pitch Score by the frequency the pitch is thrown to arrive at an Underthrown Index (UI). Sort descendingly and serve.
Cutters
Player | Num | Cutter% | zWhf/Sw | z(GB+PU)/BIP% | Pitch Score | UI |
---|---|---|---|---|---|---|
Marcus Stroman | 89 | 7.15% | 1.69 | 0.62 | 2.30 | 32.244 |
Hyun-jin Ryu | 126 | 14.88% | -0.07 | 2.47 | 2.40 | 16.145 |
Corey Kluber | 148 | 19.95% | 1.95 | 0.62 | 2.57 | 12.872 |
Ian Kennedy | 116 | 11.67% | 0.11 | 1.36 | 1.46 | 12.547 |
Drew Pomeranz | 58 | 5.23% | 2.24 | -1.61 | 0.63 | 12.081 |
Mat Latos | 62 | 28.18% | 1.93 | 0.89 | 2.82 | 10.007 |
Matt Boyd | 81 | 8.46% | 0.10 | 0.71 | 0.81 | 9.533 |
David Price | 71 | 24.74% | 1.02 | 1.17 | 2.19 | 8.862 |
Michael Wacha | 151 | 15.73% | -0.53 | 1.73 | 1.20 | 7.617 |
Nick Martinez | 164 | 23.16% | -0.11 | 1.64 | 1.52 | 6.567 |
Last season, Marcus Stroman threw his cutter once every five pitches. This year, it’s making an appearance just once every fourteen. That’s a dramatic year-over-year decline and frankly one that’s a bit perplexing considering that by Pitch Score, it was the 7th best cutter in baseball last year (min. 200 thrown). It ranked in the 61st percentile in whiffs per swing and 89th percentile in ground balls per ball-in-play. It was also the 7th hardest cutter thrown and hitters found it nearly impossible to do anything with; they mustered just a .085 isolated slugging and .214 True Average against it. Each showing ranked 5th among cutters.
This year? It’s even better (in some respects). By pitch score, it ranks 4th amongst its peers. But whereas it excelled last year in generating grounders, this year it’s elite at inducing whiffs. It ranks 7th among cutters in whiffs per swing while still generating one grounder for every ball hit in the air.
That being said, the results have yet to match the improvement. Hitters are lighting the pitch up, posting a .350 isolated slugging against. Lefties, in particular, are enjoying themselves.
ISO vs RHH | ISO vs LHH | ISO | |
---|---|---|---|
2016 | 0.154 | 0.059 | 0.085 |
2017 | 0.231 | 0.444 | 0.35 |
So, what’s going on? Despite the decline in usage, Stroman still throws the pitch nearly twice as often to left-handed hitters. It appears to be a simple matter of location. While he forced the pitch in-on-the hands last season, generating a ton of ground balls in the process, he’s much more out over the plate in 2017.
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That’s Stroman’s cutter location to lefties in 2016 on the left and this year on the right.
He’s also added a ton of horizontal movement but sacrificed some “rise” in the process. It may be that we’re looking at a very different pitch, though it’d seem that a cutter with more run and sinking action would lead to a higher ground ball rate with fewer swinging strikes. Then again, he’s only thrown 89 so it may just be noise. Still, given how great the pitch was just one season ago and that it seems to be inducing far more whiffs this time around, I’d like to see him go to the well just like he did late last year.
Hyun-Jin Ryu rolled out a cutter this season and so far, despite merely average swing-and-miss rates, it’s been one of the best in the game. Inducing grounders on nearly three quarters of the balls put in play, Ryu’s cutter is helping him maintain his highest ground ball rate since his rookie season. Encouragingly, his strikeout rate is back above 20% and his walk rate below 7%; there’s no doubt that his cutter, with its 61.5% zone-percentage and 7th best called strike-to-ball ratio, is in large part contributing to that resurgence.
Obviously, the overall results have disappointed thus far, in large part due to a 22.6% HR/FB rate which should regress. But playing around with this new toy a bit more, with its ground ball and strike-stealing proclivities, would certainly help his cause.
Mat Latos: this is the type of result that really makes you question your methods. Like Stroman’s cutter, Latos occupies some lofty leaderboard air, ranking 4th in whiffs per swing and 7th in ground ball rate. Also, like Stroman’s cutter, hitters are crushing it. Yes, it’s weird that Latos is on here. No, it’s not 2013 so he shouldn’t be on your team.
Curveballs
Player | Num | Curve% | zWhf/Sw | z(GB+PU)/BIP% | Pitch Score | UI |
---|---|---|---|---|---|---|
Tim Adleman | 86 | 10.11% | 1.87 | 0.82 | 2.69 | 26.599 |
Matt Harvey | 98 | 8.51% | -0.03 | 2.00 | 1.97 | 23.185 |
Mike Pelfrey | 107 | 12.31% | 3.03 | -0.30 | 2.73 | 22.184 |
Daniel Norris | 116 | 9.50% | 1.16 | 0.75 | 1.91 | 20.118 |
Carlos Carrasco | 134 | 13.11% | 1.42 | 1.08 | 2.50 | 19.059 |
Jesse Chavez | 67 | 5.74% | 1.32 | -0.30 | 1.02 | 17.799 |
Blake Snell | 80 | 10.19% | -0.32 | 1.87 | 1.55 | 15.205 |
Wade Miley | 105 | 8.61% | -0.47 | 1.61 | 1.14 | 13.251 |
Tyler Chatwood | 140 | 11.08% | -0.10 | 1.48 | 1.37 | 12.392 |
Jacob deGrom | 119 | 8.95% | 0.60 | 0.49 | 1.09 | 12.226 |
Over 13 starts last season, Tim Adleman threw his yacker 18% of the time. This season he’s showing it just around once every ten pitches, frequently enough to consider it a real pitch but given its insane swing-and-miss attributes, infrequently enough to consider it underthrown. His curve ranks 5th in whiffs per swing. It’s also been above average at inducing grounders and pop-ups making it a difficult pitch to do anything with. As one might suspect given a .000 isolated slugging and .133 batting average against, hitters have fared poorly when Adleman unleashes Uncle Charlie.
Considering his full arsenal, Adleman already boasts an above average swinging strike rate but unfortunately doesn’t generate nearly enough ground balls. That’s led to one of the worst HR/9 ratios in the league despite a league average homer-to-fly ball rate. Throwing his curve more often would certainly induce more ground balls and whiffs though possibly elevate his walks; Adleman’s curve ranks 111th out of 129th in called strike-to-ball ratio so despite its unremarkable depth, he appears to have a tough time locating it.
Matt Harvey also appeared on last edition’s list for his underthrown sinker. Perhaps he should be throwing his curve more as well. Like the sinker, his curve is not particularly effective at generating swings-and-misses but it is elite at inducing meek contact, specifically pop-ups. When hitters put bat-to-ball, it ends up a weakly hit pop-up 25% of the time, 2nd highest frequency in the league. It also induces a ground ball on 60% of balls-in-play.
The results, .045 isolated slugging against, match the peripherals so perhaps it’s only a matter of time before he starts bringing Uncle Charlie to dinner more often. Sure enough, Harvey’s last two starts represent season-highs for curveball usage.
Harvey’s teammate, Jacob deGrom, also made an appearance last time for his infrequent four-seam usage. Perhaps he should also mix in his curve a bit more; its 57% ground ball per ball-in-play percentage might help with his burgeoning homer problem.
It’s worth mentioning Carlos Carrasco because by Pitch Score, he’s in possession of the league’s 5th best curveball this season. He must know it too because he’s throwing it more often than he ever has before. But considering that high watermark as well as the quality of the rest of his arsenal, I doubt he’ll throw his curve much more than he already is. Still, if he does it could produce resurgent ground ball and strikeout rates.
Below you’ll find the full list of underthrown cutters and curves. I was hoping to get to sliders but that’ll have to wait until next week when we cover changeups as well.
Player | Num | Cutter% | zWhf/Sw | z(GB+PU)/BIP% | Pitch Score | UI |
---|---|---|---|---|---|---|
Marcus Stroman | 89 | 7.15% | 1.69 | 0.62 | 2.30 | 32.244 |
Hyun-jin Ryu | 126 | 14.88% | -0.07 | 2.47 | 2.40 | 16.145 |
Corey Kluber | 148 | 19.95% | 1.95 | 0.62 | 2.57 | 12.872 |
Ian Kennedy | 116 | 11.67% | 0.11 | 1.36 | 1.46 | 12.547 |
Drew Pomeranz | 58 | 5.23% | 2.24 | -1.61 | 0.63 | 12.081 |
Mat Latos | 62 | 28.18% | 1.93 | 0.89 | 2.82 | 10.007 |
Matt Boyd | 81 | 8.46% | 0.10 | 0.71 | 0.81 | 9.533 |
David Price | 71 | 24.74% | 1.02 | 1.17 | 2.19 | 8.862 |
Michael Wacha | 151 | 15.73% | -0.53 | 1.73 | 1.20 | 7.617 |
Nick Martinez | 164 | 23.16% | -0.11 | 1.64 | 1.52 | 6.567 |
Charlie Morton | 92 | 10.23% | 0.68 | -0.03 | 0.65 | 6.366 |
Jharel Cotton | 246 | 26.09% | 1.25 | 0.34 | 1.59 | 6.102 |
Rick Porcello | 148 | 10.08% | 1.00 | -0.40 | 0.60 | 5.944 |
Kendall Graveman | 104 | 14.15% | -0.20 | 0.99 | 0.78 | 5.527 |
James Paxton | 100 | 11.81% | 2.43 | -1.79 | 0.64 | 5.446 |
Johnny Cueto | 319 | 23.97% | 0.07 | 1.17 | 1.24 | 5.181 |
Jon Lester | 354 | 27.61% | 0.02 | 1.17 | 1.20 | 4.331 |
Andrew Cashner | 188 | 18.43% | -0.58 | 1.36 | 0.78 | 4.217 |
Madison Bumgarner | 112 | 27.93% | -0.37 | 1.54 | 1.18 | 4.210 |
Shelby Miller | 96 | 25.00% | 1.72 | -0.87 | 0.86 | 3.432 |
Dallas Keuchel | 113 | 10.96% | -0.62 | 0.89 | 0.28 | 2.537 |
Trevor Bauer | 145 | 12.35% | 1.73 | -1.42 | 0.31 | 2.475 |
Kyle Freeland | 264 | 22.68% | 0.28 | 0.25 | 0.53 | 2.337 |
Adam Wainwright | 268 | 23.06% | -0.19 | 0.71 | 0.52 | 2.271 |
Jesse Chavez | 202 | 17.31% | 0.05 | 0.25 | 0.29 | 1.703 |
Chris Tillman | 155 | 25.83% | 0.45 | -0.03 | 0.42 | 1.620 |
Chase Anderson | 159 | 12.80% | -0.09 | 0.25 | 0.16 | 1.235 |
Yu Darvish | 228 | 15.80% | 0.99 | -0.96 | 0.03 | 0.193 |
Tyler Anderson | 194 | 21.00% | 1.63 | -1.61 | 0.02 | 0.115 |
Player | Num | Curve% | zWhf/Sw | z(GB+PU)/BIP% | Pitch Score | UI |
---|---|---|---|---|---|---|
Tim Adleman | 86 | 10.11% | 1.87 | 0.82 | 2.69 | 26.599 |
Matt Harvey | 98 | 8.51% | -0.03 | 2.00 | 1.97 | 23.185 |
Mike Pelfrey | 107 | 12.31% | 3.03 | -0.30 | 2.73 | 22.184 |
Daniel Norris | 116 | 9.50% | 1.16 | 0.75 | 1.91 | 20.118 |
Carlos Carrasco | 134 | 13.11% | 1.42 | 1.08 | 2.50 | 19.059 |
Jesse Chavez | 67 | 5.74% | 1.32 | -0.30 | 1.02 | 17.799 |
Blake Snell | 80 | 10.19% | -0.32 | 1.87 | 1.55 | 15.205 |
Wade Miley | 105 | 8.61% | -0.47 | 1.61 | 1.14 | 13.251 |
Tyler Chatwood | 140 | 11.08% | -0.10 | 1.48 | 1.37 | 12.392 |
Jacob deGrom | 119 | 8.95% | 0.60 | 0.49 | 1.09 | 12.226 |
Robbie Ray | 293 | 21.91% | 1.40 | 1.15 | 2.54 | 11.604 |
Trevor Cahill | 166 | 24.48% | 1.78 | 0.95 | 2.73 | 11.159 |
Jeff Hoffman | 66 | 17.93% | 0.26 | 1.67 | 1.93 | 10.788 |
Zack Greinke | 121 | 9.32% | 0.85 | 0.16 | 1.01 | 10.787 |
Jordan Montgomery | 217 | 21.34% | 0.92 | 1.21 | 2.14 | 10.017 |
Lisalverto Bonilla | 73 | 20.98% | -0.05 | 2.13 | 2.08 | 9.917 |
Alex Wood | 185 | 24.15% | 0.98 | 1.28 | 2.25 | 9.332 |
Andrew Cashner | 60 | 5.88% | -1.13 | 1.67 | 0.54 | 9.193 |
Chase Anderson | 206 | 16.59% | 0.50 | 1.02 | 1.51 | 9.108 |
Alec Asher | 76 | 17.16% | 0.73 | 0.82 | 1.55 | 9.037 |
Joe Musgrove | 100 | 10.29% | 1.21 | -0.30 | 0.91 | 8.861 |
Stephen Strasburg | 282 | 22.01% | 1.01 | 0.88 | 1.89 | 8.593 |
James Paxton | 170 | 20.07% | 0.56 | 1.15 | 1.71 | 8.513 |
Jake Arrieta | 182 | 16.64% | 1.23 | 0.09 | 1.33 | 7.983 |
Zack Godley | 190 | 31.56% | 1.42 | 1.02 | 2.43 | 7.704 |
Joe Biagini | 131 | 23.52% | 0.59 | 1.21 | 1.80 | 7.649 |
Christian Bergman | 61 | 11.23% | 0.45 | 0.36 | 0.81 | 7.189 |
Jarred Cosart | 54 | 11.76% | -0.75 | 1.54 | 0.79 | 6.712 |
Gio Gonzalez | 291 | 21.41% | 0.85 | 0.55 | 1.40 | 6.539 |
Madison Bumgarner | 68 | 16.96% | 1.06 | 0.03 | 1.09 | 6.444 |
Marcus Stroman | 81 | 6.51% | -0.67 | 1.08 | 0.42 | 6.393 |
Luis Perdomo | 324 | 33.44% | 1.56 | 0.36 | 1.92 | 5.742 |
Matt Garza | 62 | 9.08% | -1.49 | 2.00 | 0.51 | 5.668 |
Jhoulys Chacin | 112 | 10.88% | 0.05 | 0.55 | 0.61 | 5.592 |
Charlie Morton | 244 | 27.14% | 1.94 | -0.43 | 1.51 | 5.546 |
Ian Kennedy | 136 | 13.68% | 0.19 | 0.55 | 0.75 | 5.478 |
Alex Meyer | 252 | 35.74% | 1.18 | 0.75 | 1.94 | 5.418 |
Ivan Nova | 229 | 19.84% | 0.97 | 0.09 | 1.06 | 5.344 |
Nate Karns | 264 | 37.18% | 1.51 | 0.42 | 1.93 | 5.197 |
Jesse Hahn | 149 | 16.63% | 0.43 | 0.42 | 0.86 | 5.152 |
Mike Fiers | 208 | 19.10% | 0.30 | 0.62 | 0.92 | 4.795 |
Kyle Gibson | 125 | 15.63% | 0.85 | -0.10 | 0.74 | 4.752 |
Jameson Taillon | 154 | 24.44% | -0.04 | 0.95 | 0.90 | 3.700 |
Tyler Glasnow | 233 | 22.51% | 0.29 | 0.49 | 0.78 | 3.468 |
Jose Quintana | 360 | 30.90% | 0.64 | 0.42 | 1.07 | 3.452 |
Jeff Samardzija | 171 | 12.80% | 0.05 | 0.36 | 0.41 | 3.187 |
Trevor Bauer | 298 | 25.38% | 0.16 | 0.62 | 0.78 | 3.067 |
Hyun-jin Ryu | 130 | 15.35% | 1.21 | -0.76 | 0.45 | 2.901 |
J.C. Ramirez | 170 | 17.51% | -0.05 | 0.55 | 0.51 | 2.897 |
Lance McCullers | 538 | 44.98% | 0.67 | 0.55 | 1.22 | 2.712 |
Tyler Skaggs | 147 | 32.89% | -0.02 | 0.88 | 0.87 | 2.635 |
A.J. Griffin | 175 | 26.88% | 0.22 | 0.42 | 0.65 | 2.403 |
German Marquez | 194 | 23.49% | 0.94 | -0.43 | 0.51 | 2.175 |
Jon Lester | 154 | 12.01% | 2.19 | -1.94 | 0.24 | 2.036 |
Aaron Nola | 218 | 30.19% | 0.17 | 0.36 | 0.53 | 1.759 |
Zach Eflin | 79 | 10.55% | -0.25 | 0.42 | 0.18 | 1.664 |
Jimmy Nelson | 151 | 13.71% | 0.53 | -0.30 | 0.23 | 1.655 |
Zach Davies | 169 | 15.23% | 0.07 | 0.16 | 0.23 | 1.533 |
Clayton Kershaw | 201 | 16.02% | 0.30 | -0.10 | 0.19 | 1.207 |
Adam Wainwright | 299 | 25.73% | 0.17 | 0.09 | 0.26 | 1.012 |
Tanner Roark | 170 | 12.71% | 0.10 | 0.03 | 0.12 | 0.981 |
Alex Cobb | 444 | 34.55% | 0.02 | 0.29 | 0.31 | 0.909 |
Jose Berrios | 180 | 29.70% | -0.15 | 0.36 | 0.20 | 0.684 |
Chris Tillman | 64 | 10.67% | -0.03 | 0.09 | 0.07 | 0.612 |
Michael Wacha | 103 | 10.73% | -0.24 | 0.29 | 0.05 | 0.483 |
Drew Pomeranz | 454 | 40.90% | -0.42 | 0.55 | 0.13 | 0.327 |
Felix Hernandez | 70 | 23.49% | 0.36 | -0.30 | 0.06 | 0.266 |
Mike Clevinger | 69 | 12.55% | 1.98 | -1.94 | 0.03 | 0.262 |
Jerad Eickhoff | 362 | 31.21% | 0.08 | -0.04 | 0.04 | 0.127 |
Rylan writes for Fangraphs and The Hardball Times. Look for his weekly Deep League Waiver Wire and The Chacon Zone columns this season.
Rylen, I write for a community fansite that covers a specific team. Would you be opposed if I used your “pitch score” metric to value my team’s pitches? I’d link back to your original post, of course.
Of course, feel free. Thanks for reading and glad you found it useful.
I like it. I’ve been using the PitchF/X database on Baseball Prospectus more and more.
Have you looked into anything regarding called strike rates? I think that’s an underrated skill.
So I really like called strike-to-ball ratio ever since I wrote up Rich Hill in the off-season. BP features it on their PitchF/X leaderboards. It’s not great for out pitches though; I’m thinking of a spiked curve or splitter for example. After next week’s article I think I’m going to put it all together and grade overall pitch mix instead of individual offerings; I’ll try to incorporate some element of command like called K:BB or called strike%.
I’m just now diving into called strike-to-ball ratio but I found it useful. I used to help explain how Robbie Ray had walk issues when he was fastball/slider (slider has second-worst ratio in the game) but now that he’s incorporating his curveball a lot, his walks have dropped (it has the 5th-best ratio).
Regarding called strikes, from a value perspective, a called strike should be equivalent to a swinging strike. I know whiff% is a better skill, but I think called strikes are completely overlooked. Do you think adding a z-score for called-strikes to your pitch score metric (in addition to zWhf/Sw and z(GB+PU/BIP%)) would be useful?
Yeah I think it could. I’d probably want to aggregate pitch scores into an overall arsenal score and then regress against something like FIP or ERA to see which is more useful/predictive.