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The Changeup and BABIP: does throwing changeups help you lower your BABIP?

While a large part of our readers here on Bluebird Banter believes that pitchers have no influence over BABIP at all, there are a few pitchers who do their best to make us believe otherwise. Take former Jays pitcher Ted Lilly: he's got a .271 BABIP in 1904 career innings. That's not a small sample size by any means, and the BABIP is significantly lower than league average (.290-.300 range). He has managed to keep his career ERA at 4.17 even though his career FIP sits at 4.42. Another former Jay: Shaun Marcum. Career BABIP: .269. Career FIP: 4.28, but career ERA: 3.77. That's over 792 2/3 innings, so the sample isn't as large. Matt Cain (1317 1/3 IP) has a career .265 BABIP, a career 3.69 FIP and a career ERA of 3.35. So, obviously these guys are doing something right, right? While looking for explanations (the use of the cutter, quality of the fastball, horizontal movement on pitches) I believe to have found a relatively strong link between the use of the changeup and the ability to defy the league average BABIP.

What I'll do here is list the starting pitchers with over 700 innings pitched since 2006 who have a career BABIP of .287 or lower. (I wanted to include John Lannan who has 4.62 FIP but a 4.01 ERA over that period, and it seemed like a good cutoff point)

What you'll see in the table below is a pitcher's career BABIP, his most valuable pitches in order of value (Fangraphs' pitch values), his career changeup% (of pitches thrown), and the whiff% for the changeup since 2009 (league average for changeups is around 12%).

Name BABIP BestPitches CH%
Whiff%
Ted Lilly .271 FB/SL 16.2 12.6
Shaun Marcum .269 CH/CT 22.6 23.2
Matt Cain .265 FB/CH 11.3 14.3
Jeremy Guthrie .273 FB/SL 10.8 8.9
Johan Santana .275 CH/FB 24.8 16.5
Tim Wakefield .274 FB/CB/KN 0 -
Jered Weaver .276 CH/FB 14.9 17.4
Carlos Zambrano .276 FB/SL/CH/CT 10.8* 12.1
Barry Zito .268 CH/CB/SL/FB 16.8 10.2
Jarrod Washburn .273 SL/FB 12.8 4.0
Clayton Kershaw .279 FB/SL 3.6 10.8
Tim Hudson .279 FB/SL/CH 15.2* 12.2
Bronson Arroyo .282 SL/CB 14.3 7.4
Cole Hamels .280 CH/FB 28.5 27.5
Jair Jurrjens .280 FB/SL/CH 23.6 11.0
Randy Wolf .284 FB 11.3 5.5
Jamie Moyer .282 CH 28.1 15.2
Justin Verlander
.285
FB/CH/CB 15.3 19
Ubaldo Jimenez .286 FB/CH/SL 13.0* 16.3
Brandon Webb .286 FB/CH 11.9 25.4
John Lannan .286 CH 13.6 11.6
Chris Young** .248 FB 7.7 12.4

*=splitter, **=did not qualify, a "bonus" if you will

(analysis after the jump)

Star-divide

Chris Young is an interesting case, worthy of an article of his own, because he throws mostly a unique rising fastball that gets him a lot of popups and (probably) a lot of weak flyball outs. It is unfortunate that he has been injured so much the past couple of years, which is why he didn't get to the innings cutoff. Others who didn't make it to the cutoff but have limited BABIP are John Maine (FB/SL), Armando Galarraga (SL), Roger Clemens (FB/CH*), Ian Kennedy (FB/CH), Trevor Cahill (FB/CH), David Price (FB/CH), Colby Lewis (SL), Rich Harden (CH*/FB), Mat Latos (FB/SL), J.A. Happ (FB), Tommy Hanson (SL/FB/CB), Bruce Chen (SL/CB) and Jeff Niemann (FB). Of these, Niemann, Hanson, Latos, Lewis, Price and Galarraga throw their changeups less than 10% of the time, a percentage that is remarkably higher than the group where the sample size is bigger. Niemann (cutting action) and Price (running action) have pretty unique fastballs in terms of horizontal movement, and in Price's case, velocity. Hanson's fastball is a "rising" one. Latos's fastball is, like Niemann's more of a cutter in terms of movement, but it's thrown harder than most cutters. Lewis' fastball both cuts a bit and "rises" a bit. Galarraga is more of a mystery, his slider has a lot less cutting and a lot less downward movement than those of the other slider specialists, and he doesn't throw a four-seamer at all, just a "sinker". Perhaps he limited his BABIP because he gave up so many homers?

Back to the pitchers who did make the cutoff. Not counting Wakefield (who is obviously a very different kind of pitcher), only Kershaw threw the changeup less than 10% of time. At just 3.6%, one can presume the hitters won't be sitting changeup against Kershaw. Of the 20 non-knuckleballers, 7 had the changeup as their best pitch, 12 the fastball and just one (Arroyo) the slider. None were curveball specialists. Only 4 got less than 10% whiffs on their changeup. For Wolf, Arroyo and Washburn, it seems quite strange to throw the changeup so often, though perhaps it made their other offerings that much better? Zambrano, Marcum and Hamels throw cutters, while Weaver throws a fastball that moves like a (rising) cutter. The only groundballers of the bunch are Webb and Hudson, and both have pretty extreme sinkers.

I think it's time to take a look at 20 guys who underperformed the league average BABIP the most, using the same criteria as for the other group (>700 innings since 2006):

Name BABIP BestPitches CH% Whiff%
Zach Duke .323 CH 15.5 12.2
Andy Pettitte .309 CT (SL) 8.1 8.2
Kevin Millwood .297 FB/SL 3.4 6.7
Ian Snell .315 SL 8.8 7.7
Doug Davis .307 CT/CB 11.4 8.4
Paul Maholm .310 SL/CB 13.3 7.8
Livan Hernandez .306 CB 8.0 8.4
Edwin Jackson .311 SL 8.0 12.9
Aaron Harang .308 FB/SL 6.5 8.3
Zack Greinke .308 SL 9.4 10.7
Ricky Nolasco .309 SL 8.5* 15.2
Joe Blanton .299 CH/SL 15.1 15.9
Brad Penny .301 FB 11.8 8.5
Joel Pineiro .298 CH/CB/SL 10.9 6.5
John Lackey .309 CB/SL 5.3 8.1
Jeff Suppan .297 CB/SL 14.3 10.0
Nick Blackburn .308 - (FB?) 11.1 8.8
Mike Pelfrey .306 FB 10.1 9.3
Jake Westbrook .300 FB/CB 13.2 15.6
Scott Baker .302 FB/SL 7.8 9.3

*=splitter

First thing to note here is that it's harder to find pitchers who have worse than league average BABIP than it is to find those who have lower BABIPs. This isn't too strange, as you'd expect most pitchers with bad BABIPs to not last long in the major leagues as a starting pitcher. Pitchers like Kevin Millwood, Joe Blanton, Joel Pineiro, Jeff Suppan and Jake Westbrook have had inflated BABIPs since 2006, but not too much over their careers. Most of them have seen their fastball effectiveness sharply decline.

Now another thing you will have noted is the large number of breaking ball specialists on this list. 7 pitchers are slider specialists, as Doug Davis and Andy Pettitte throw a "slutter" which is seen as cutter by PitchFX, but is, in my opinion, too different from the regular fastballs used by these gentlemen to be called a cutter. Whether you count 7 or 5 slider specialists, the group is a lot bigger than the lone slider specialist (Arroyo) in the group that limited hits on balls in play. In addition, there are 3 curveball specialists, which means it's 10 (BABIP underperformers) to 1 (BABIP overperformers) in breaking ball junkies. Only one (Duke) is a changeup specialist, compared to 7 in the other group. Six or seven (depending on if you count Blackburn) fastball specialists compared to 12 in the group of low BABIPers. Compared to just one in the other group, half of those who have suffered from bad BABIPs threw less than 10% changeups. Thirteen got less than 10% whiffs with their changeups, compared to four in the other group.

Two interesting cases here are Zach Duke and Edwin Jackson. Zach Duke has a bad fastball, and I mean very bad. Epically bad.  He has a -101.2 run value on the fastball over his career, which is quite an achievement, really. Edwin Jackson is no slouch either, he has -75.6 run value on the fastball over his career, and (despite the whiffs) -10.4 on the changeup. Throwing in the mid-90s isn't everything, huh, Edwin?

Conclusion

I do not want to make the conclusion that a good changeup will make a pitcher have lower than usual BABIP. Zach Duke is plenty of proof, and Edwin Jackson and James Shields are, too, that a bad fastball can mean a normal or even bad BABIP despite a good changeup. Along with a good, often used changeup, throwing a good four-seamer or cutter might also work towards a low BABIP. Sinkerballers and breaking ball pitchers who lack a good changeup might find themselves struggling to keep their BABIPs low.

What does this mean for Jays' pitchers? Ricky Romero now has a .285 career BABIP, which he might even improve upon, given his strong changeup/fastball (sometimes with some cutting action) combination. But I wouldn't expect him to put up anywhere near a .242 mark again, so I'd expect him to be a 3.40-3.70 ERA pitcher. Brett Cecil is also a changeup guy, but his fastball is a liability, I don't expect him to last long if he doesn't improve on his fastball. For Brandon Morrow, his BABIP hasn't been that problematic this year at .300, although last year it was .342, it's mostly the LOB% that needs to come down. As a pitcher who relies heavily on the slider, BABIP could still be a problem if his new cutter doesn't work out. Henderson Alvarez is probably safe from BABIP troubles, and time will tell if he's got the ability to pitch to a low BABIP with that power sinker of his, in the footsteps of Webb and Hudson, but although he throws harder, the pitch does not have as much sink. McGowan actually has a very good changeup, but he could use it more, and of course, he needs to command it. The command issue is of course also the worry with Drabek's change, which he has thrown for swings and misses but rarely for strikes (like his other pitches).

Comment 26 comments  |  6 recs  | 

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Woodman, that is a fantastic article

That would make the guys at Fangraphs proud. I wonder what that means for the quartet of pitchers at AA? Using this data, which of McGuire, Molina, Hutchison and Jenkins are most likely to succeed?

Hic sunt fortuna dracones

by JaysfanDL on Sep 29, 2011 9:55 AM EDT reply actions  

Thank you

I should not that the ability to reduce BABIP, while meaningful, doesn’t determine a pitcher’s success as much as the abilities to induce groundballs, get strikeouts and reduce walks do.

I would say Molina should be fine, if his best pitch is indeed the splitter (which functions as a changeup). But does he have enough fastball?

McGuire and Hutchison are said to have multiple above-average pitches, so I hope that includes a good change.

Chad Jenkins should be in the bullpen imo, and if he does start his sinker/slider combo might well lead to inflated BABIPs.

by Woodman663 on Sep 29, 2011 10:18 AM EDT up reply actions  

I'd agree with those assessments

Molina throws low 90s but if the splitter acts like a change and with his command, he may be ok.

Hutch’s best pitch when he was drafted was said to be his changeup and his fastball velocity has increased since being drafted, so he has a good shot. I think McGuire has a changeup but I have no idea where it ranks among his offspeed pitches.

Jenkins is the one to worry about the most. You’re probably right his sinker/slider combo works best in the pen. I’ve heard the Jays are working on his changeup though, so if he can refine that, he may have some potential but he has a lot of guys to beat out.

Hic sunt fortuna dracones

by JaysfanDL on Sep 29, 2011 10:36 AM EDT up reply actions  

great article

I’d like to see BABIP looked at in the context of pitch movement, because it seems intuitive that pitches that move a lot would lead to poor contact.

The changeup is generally the pitch that induces the most swinging strikes (along with the slider) though fewer called strikes than any other pitch, so it’s interesting to see how that correlates with BABIP

I thought Marcum might also be helped by his excellent defense on the mound. I’m not saying it explains everything, but it’d be another variable that could have an impact.

"Let us go forth awhile, and get better air in our lungs. Let us leave our closed rooms... The game of ball is glorious." - Walt Whitman

by hugo on Sep 29, 2011 10:45 AM EDT reply actions  

Another thing to look at

Is that if hitters fear the changeup, they might well be late more often on the fastball. I believe that is something that could cause weak flyouts off the fastball.

Rays first baseman Carlos Peña simply shakes his head when he thinks about some of the nasty changeups he sees these days: “The changeup really is the equalizer. You don’t want to be late on the high speed and you don’t want to look bad on the changeup. Look at that split-minded focus. … What a pitch. It’s really a weapon.”

From this article.

by Woodman663 on Sep 29, 2011 10:55 AM EDT up reply actions  

The key to good pitching is disrupting a hitter's timing

The changeup probably does that better than any one pitch since a good one looks like a fastball coming in but isn’t as hard. Other breaking pitches are probably easier to recognize due to different arm motions, spin, how the ball looks in the pitcher’s hand, etc. With a changeup/fastball combo, If the hitter guesses wrong on the speed, that leads to either a strikeout or weak contact.

I remember reading an interview with Greg Maddux years ago where he said the pitcher has all the advantages because hitting is hard. He said that if you keep changing speeds and hitting different sides of the plate, the hitter stands no chance because he can’t look for everything at the same time. Of course, easy for a control artist like Maddux to say, but the principle is sound. IIRC, he had a fantastic changeup too.

Hic sunt fortuna dracones

by JaysfanDL on Sep 29, 2011 11:34 AM EDT up reply actions  

Proof that BBB doesn't hibernate. Great job

A day that will live in infamy: August 4th, 2011
7 pissed off members of the Aaron Hill fanclub

by jays182 on Sep 29, 2011 11:14 AM EDT reply actions  

nice work, woodman!

Though I do wonder if the hit-suppressing effect of changeups that we’re seeing here isn’t an artifact of those pitchers have having higher flyball-rates. Many of the pitchers described here are extreme flyballers. Because flyball% is related to BABIP, before you can tell that there is a relationship between changeup% (for example) and BABIP, you’d need to disentangle the relationship between changeup% and FB%.

As jono suggested in an earlier thread, a multiple regression model with both factors (and their interaction) should work for this. If you don’t have statistics software, R is available for free (though it can be a bit of a bear to get started using it!).

If you’d prefer, when I get a minute, I can run the analyses for you

"Look at me! I'm Tomokazu Ohka of the Montreal Expos!"

by jessef on Sep 29, 2011 12:48 PM EDT reply actions  

I know little to nothing

about the processes you described. If you could run the analyses, that would be great!

The thing with changeup% is that it doesn’t factor in the quality of the changeup. Although I think the frequency is probably more closely correlated to lower BABIPs than the quality.

But, as we saw with Jackson and Duke, the quality of the fastball might be essential for BABIP, too.

by Woodman663 on Sep 29, 2011 2:27 PM EDT up reply actions  

Woodman and Jessef, if you two are on to something, don't post it to a public forum

Just send your findings to:

The Toronto Blue Jays Baseball Club
c/o Alex Anthopoulos
1 Blue Jays Way
Toronto, ON
M5V 1J3

Hic sunt fortuna dracones

by JaysfanDL on Sep 29, 2011 2:47 PM EDT up reply actions  

hahahahahaha

I’m pretty sure they’re way ahead of us

"Look at me! I'm Tomokazu Ohka of the Montreal Expos!"

by jessef on Sep 29, 2011 3:59 PM EDT up reply actions  

Sure thing

We can make the model as complicated (or as simple) as we want. You’re right that changeup-frequency isn’t perfect. We can also look at relative value per changeup and total value for all changeups.

Basically, whatever factors you want to include into the model. I’d think that Matt Swartz and the folks who favour SIERA would want to include strikeout-rate, too.

Thanks to fangraphs making all these data available for quick download into spreadsheets, I can a bunch of different models and I can post the output here or email it to you directly, whichever you prefer. The neat thing about doing it this way is that it should tell us not only which factors have effects, but also the relative importance of those effects.

"Look at me! I'm Tomokazu Ohka of the Montreal Expos!"

by jessef on Sep 29, 2011 4:05 PM EDT up reply actions  

actually,

it’s probably better for me to e-mail it to you rather than post it here straight off mostly because we can’t use tables here which would make understanding the output extremely difficult. There’s also a fair bit of interpretation that needs to be done and that would likely read better in the body of the post, rather than in the comments.

This is a quick and dirty summary, woodman, if you drop me an e-mail, I’ll draft a full-on explanation of the methods, results, and conclusions. I think we’re looking at something pretty interesting here, so you should be really proud!

"Look at me! I'm Tomokazu Ohka of the Montreal Expos!"

by jessef on Sep 29, 2011 5:02 PM EDT up reply actions  

Okay . . .

Here’s a summary of the methods and analyses:

I included all starting pitchers with 300+ innings since 2009 and fit a linear model for babip to fixed effects of flyball-rate, strikeout-rate, changeup frequency, total value by linear weights of all changeups, and value by linear weights per changeup. The model accounted for about 25% of variance in babip. I had the model use the Lindeman, Merenda and Gold (lmg) method to determine the relative importances of contributions from each factor.

What we find is that the effects of flyball-rate are highly significant (p = 2 × 10**-16). The effects of value per changeup are moderately significant (p = 0.0568). None of the other effects (including K%!) were significant. A model including only those two factors fit the data just as well as the initial model, which also included k-rate, changeup frequency and total changeup value.

In terms of relative importance, flyball-rate was most important but the changeup inputs made important contributions to the model as well. K-rate made the least important contribution (just 2% relative importance).

On the overall, according to the method and model described above, fly-rate accounts for about 16% of pitcher babip variability. The total contributions per pitch changeup value, total changeup value, and changeup frequency account for about 7.5% of pitcher babip variability. K-rate accounts for only about 0.5% of pitcher babip variability.

"Look at me! I'm Tomokazu Ohka of the Montreal Expos!"

by jessef on Sep 29, 2011 5:50 PM EDT up reply actions  

Very interesting

But while using all pitchers with 300+ innings since 2009 increases the sample of pitchers, I do wonder if it’s not too low an amount of innings pitched. After all, pitchers might get away with a lower BABIP than normal if they’re new to the league and batters haven’t fully figured them out yet.

by Woodman663 on Sep 29, 2011 6:03 PM EDT up reply actions  

but they also might have a higher BABIP than normal

if they’re rookies and thus not as able to induce poor contact than veterans

by benk on Sep 29, 2011 6:11 PM EDT up reply actions  

notsureifsrs

does inducing poor contact increase with experience?

Sad, Drunk, And Poorly

My friends, love is better than anger. Hope is better than fear. Optimism is better than despair. So let us be loving, hopeful and optimistic. And we'll change the world. - JL

Twit Twat.

by Pikachu on Sep 29, 2011 6:37 PM EDT up reply actions  

meh

maybe, maybe not. I don’t think players with around 300 IP would be able to “get away” with anything though

by benk on Sep 29, 2011 6:41 PM EDT up reply actions  

right, there's no perfect number of innings

300 innings, though, is roughly a season and a half worth of data, which is better than using this year only.

"Look at me! I'm Tomokazu Ohka of the Montreal Expos!"

by jessef on Sep 29, 2011 6:36 PM EDT up reply actions  

You be okay using % rather than quality

since game theory would largely (humans rarely do it optimally, hence “would largely”) dictate that the % is a good proxy for the quality of a pitcher’s changeup. The only minor issue is that it would also be affected by the pitcher’s other pitches as well – the better his other pitches, the less he’d throw the changeup, regardless of its quality

Great post btw.
 ——-
I agree entirely with jessef. There’s a not-insignificant difference in expected BABIP between grounders (which go for hits more often, but, barring idiocy, never extra bases) and fly balls (which turn into outs more often, but also lead to more XBH), so you/jesse/the collective we need to account for what proportion of your results are due to fly ball tendencies (and then, if it’s significant, which it should be, find the correlation between change up rate/ability/whatever and fly ball rate.

I'm more than a little jealous of Grantland's ability to use footnotes rather than excessively long bracketed statements.

by Gerse on Sep 29, 2011 5:08 PM EDT up reply actions  

not really

it’s a good proxy for quality of a pitcher’s changeup relative to his other pitches as well as (probably less correlated) the quality of his fastball

by benk on Sep 29, 2011 5:16 PM EDT up reply actions  

...That was the second sentence of what I said

I'm more than a little jealous of Grantland's ability to use footnotes rather than excessively long bracketed statements.

by Gerse on Sep 29, 2011 5:53 PM EDT up reply actions  

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