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

The Most Underthrown 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
SOURCE: PITCHf/x

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.

Stroman’s Cutter Year-Over-Year
ISO vs RHH ISO vs LHH ISO
2016 0.154 0.059 0.085
2017 0.231 0.444 0.35
SOURCE: Brooks Baseball

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.

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

Yack It Up
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
SOURCE: PITCHf/x

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.

Underthrown Cutters: The Complete List
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
SOURCE: PITCHf/x

 

Underthrown Curveballs: The Complete List
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
SOURCE: PITCHf/x





Rylan writes for Fangraphs and The Hardball Times. Look for his weekly Deep League Waiver Wire and The Chacon Zone columns this season.

7 Comments
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Moranall
6 years ago

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.

Moranall
6 years ago
Reply to  Rylan Edwards

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.

Moranall
6 years ago
Reply to  Rylan Edwards

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?