Drew Pomeranz and Beating BABIP
Drew Pomeranz is in the midst of a breakout season. He’s already surpassed his season high for innings and his ERA is a very low 2.47, while his FIP is a low — if not quite as low — 3.15. Those very good numbers netted the San Diego Padres a very good pitching prospect recently in the form of Anderson Espinoza.
Much of Pomeranz’s newfound success has been attributed to the addition of a cutter to his repertoire, which Jeff Sullivan detailed just before the trade last week. One notes, however, that the success is aided by a .240 BABIP and 80.8% left-on-base rate. Even if those numbers aren’t sustainable, the 3.15 FIP indicates Pomeranz’s success is real. But there’s reason to believe that Pomeranz isn’t as susceptible to regression as the average pitcher. Or there’s reason, at least, to believe that the Red Sox believe he isn’t.
Speaking with WEEI’s John Tomase, former major-league pitcher and current Red Sox assistant pitching coach Brian Bannister has indicated that Pomeranz’s cutter makes it more likely that he’ll sustain some of his batted-ball suppression in Boston.
[Bannister] explained that like knuckleballers, whose BABIP numbers tend to skew low, pitchers who feature cutters tend to outperform league average on balls in play. He knows this because he did it over his first two years in the big leagues, posting BABIPs between .239 and .249.
“I was an example of it,” Bannister said. “[Cutters] generate a different batted-ball profile. There’s just different weak contact in there. Some guys it’s popups. Sometimes you get gyro-spin and it’s almost like a knuckleball. I mean, knuckleballers beat BABIP. It’s not always a given that a full regression is going to occur. When I look at a guy, if there’s a cutter involved or a knuckleball involved, you just can’t say for sure. I know a lot of people look at those two numbers — left on base percentage and the BABIP — and say, ‘Oh, he’s going to get worse in the second half.’ It’s not always a given.”
While we know pitchers tend to gravitate towards league average when it comes to BABIP, some pitchers are better than others at limiting hits on balls in play. Pop ups, like Bannister mentioned, can be a good way to induce easy outs. Fly balls and ground balls have different expected batting averages. Given a large enough sample size, we might be able to deduce which pitchers have these type of skills. With a smaller sample, perhaps looking at pitch types would help us determine which pitchers are likely to produce low BABIPs and thus more likely to outperfrom their fielding-independent numbers.
Regardless of whether Pomeranz’s cutter is a BABIP-beater, it’s a good pitch for the lefty. He generates whiffs on the pitch 16% of the time per Brooks Baseball. One quarter of the at bats ending on a cutter against Pomeranz have been strikeouts. The pitch likely helps his fastball and curve by providing an intermediary option of which hitters must remain aware. As far as the pop ups go, seven of the 35 balls in play against Pomeranz’s cutter this season have ended as pop ups. The pitch works for Pomeranz, but does it suppress BABIP?
Looking into 2016’s Statcast data at Baseball Savant, we can seek a preliminary answer. The simple chart below shows BABIP, batting average, and ISO on the cutter compared to the overall numbers this season:
| BABIP | BA | ISO | |
| Overall | .303 | .256 | .162 |
| Cutter | .296 | .254 | .144 |
In a sample of more than 5,000 cutters this season, there appears to be a seven-point difference between cutter BABIP and league BABIP. Batting average is going to include strikeouts and home runs, but the numbers are closer there while the ISO is much lower on the cutter. While a seven-point difference might not seem like a lot, it does lend some credence to the cutter’s possibility of reducing BABIP.
However, when we include other pitch types, we see we must go further to get better information. The chart below shows other pitches with more than 5,000 at-bats this season and their respective averages.
| BABIP | BA | ISO | |
| 4-seam | .314 | .275 | .189 |
| 2-seam | .314 | .291 | .160 |
| Overall | .303 | .256 | .162 |
| Cutter | .296 | .254 | .144 |
| Curve | .289 | .208 | .135 |
| Slider | .287 | .214 | .141 |
| Change | .282 | .242 | .161 |
So while the cutter has a lower BABIP than average, so do the curve, slider, and change. While the cutter does seem to suppress BABIP a bit overall on its own, there doesn’t seem to be anything inherently special about the pitch at this point. That said, returning to Bannister’s point, he never suggests that the pitch itself is responsible for suppressing BABIP. After all, Pomeranz has thrown the pitch only around 12% of the time this season and around 20% of the time since he used it heavily. That isn’t going to be enough to have a dramatic effect on BABIP. Bannister’s argument seems to be that pitcher’s featuring the cutter tend to produce lower BABIPs.
To test Bannister’s theory, first I looked at qualified pitchers from last season, and I separated them into two groups. First, I took the qualified starting pitchers who threw the cutter at least 10% of the time, and separated them from the rest of the pitchers. Here is how the two groups performed last season.
| K/9 | BB/9 | HR/9 | BABIP | LOB% | GB% | HR/FB | ERA | FIP | |
| Cutter Group (19) | 7.5 | 2.5 | 1.00 | .282 | 74.2% | 43.7% | 10.8% | 3.61 | 3.85 |
| Non-Cutter Group (58) | 8.0 | 2.6 | 0.93 | .296 | 74.0% | 46.8% | 11.0% | 3.67 | 3.67 |
Look at that. The group featuring the cutters had a much lower BABIP. The LOB% was the same, but the lower BABIP was enough to help them beat their FIP by 0.24 while the other group posted an average BABIP and had an ERA matching the FIP. Now let’s try 2014:
| K/9 | BB/9 | HR/9 | BABIP | LOB% | GB% | HR/FB | ERA | FIP | |
| Cutter Group (24) | 7.3 | 2.3 | 0.87 | .295 | 73.5% | 44.7% | 9.6% | 3.58 | 3.65 |
| Non-Cutter Group (63) | 7.5 | 2.6 | 0.85 | .289 | 74.1% | 45.2% | 9.4% | 3.51 | 3.66 |
What was true for 2015 wasn’t necessarily true for 2014: the cutter group here actually allowed a higher BABIP. Nothing conclusive here in either direction.
Let’s try to use a larger sample. For the next set, I looked at the five-year period between 2011 and 2015 and looked at qualified starters who threw the pitch more than 10% of the time. I looked at 50 players who were throwing the cutter and 129 players who were not, and weighted the results by innings, as some players had as few as 300 innings while some had a bit more than 1,000 innings pitched. This is how the groups played out:
| K/9 | BB/9 | HR/9 | BABIP | LOB% | GB% | HR/FB | ERA | FIP | |
| Cutter Group | 7.3 | 2.5 | 0.97 | 0.293 | 72.8% | 45.0% | 10.6% | 3.81 | 3.81 |
| Non-Cutter Group | 7.4 | 2.8 | 0.96 | 0.293 | 73.1% | 45.1% | 10.5% | 3.85 | 3.85 |
It is possible a deeper dive or looking at more specific characteristics of players might yield different results, but based on the information above it doesn’t appear that pitchers emphasizing the cutter have any special ability to suppress BABIP compared to the rest of their pitching brethren. It is possible that Pomeranz has a skill set that can reduce BABIP, but it would appear too early to draw that conclusion based on the above information.
Craig Edwards can be found on twitter @craigjedwards.
Good stuff Craig. Could we also expect some BABIP regression due to park, league and division changes? Not to mention any possibility of fatigue.
I would suspect that some of the variance comes from pitchers who feature different cutter shapes. Some cutters drop (e.g. Arrieta), while others tail (e.g. Price). Without any evidence at all, I would suspect that the latter are better for strikeouts, while the former are better for ground balls and (probably) BABIP suppression. At least, that’s the way it goes for changeups.
The other thing to think about is the shape of the cutter relative to the shape of the other pitches. Having an array of pitches which look similar out of the hand but have strongly differentiated horizontal and/or vertical movement patterns is always a good thing for a pitcher, but when those differentiations are generally downward, you get a significant tendency toward weak ground balls. This is one of those things that’s pretty hard to search for.
I wonder if you could look at statistically pitchers who have cutters that that have increased/decreased their strike% of four-seamers on the inside corner for opposite-handed hitters.
I have noticed that pitchers who throw inside more for strikes will get more swings from batters, thereby adding a cutter movement to create bad contact on the inside part of the plate.
The command part is important, as both throwing inside (especially if your stuff isn’t great heat) with fastball can lead to hard-hit pulled contact for power, as well the same for a cutter that stays on the plate or moves too far off the plate to persuade swinging at it.
Jon Lester was two different pitchers when his inside fastball was commanded well. When it wasn’t, he gets shelled pretty easily. Maybe look at Pomeranz heat map to see if there is an increase of inside strikes with the four-seam by itself. That usually is a great weapon to vary a cutter and keep away from the barrel of the bat, or curve and keep hitters off-balance for outside protection.
He has had command issues, but even before the cutter has had successful runs when his command was on, so if it shows with inside-corner success with the fastball, you might see correlations with other pitchers doing the same. (or not, thereby demonstrating the lack of variance on cut-fastball use on its own).
Good thinking. Good work.
You should probably look at pitchers who never used the cutter to their performance after they added a cutter to their repertoire
Esteban Loaiza was one of the first I read about to be a veteran pitcher to add a cutter, and had said it lead to a revival of his career (when he had that crazy 20-win season with the White Sox).
But he never retained any similar performance afterwards, which can also be another case study FG had discussed before about if the cutters cause fastball velocity decreases, or general deterioration of performance. There are also two types of cutters pitchers throw; I remember Dan Duquette emphasizing one being more important to prevent arm injury over another, but drawing a blank on when he mentioned it.
Want to add that some cutters we might assume are “cutters” might not be based on how they are taught to pitchers. I remember the Duquette argument on how they don’t develop any pitchers to ever , EVER, throw a cutter, but as well had specified that Mariano Rivera’s cutter isn’t the cutter he has an issue with:
http://www.masnsports.com/steve-melewski/2012/08/dan-duquette-on-the-os-pitching-philosophy-we-dont-like-the-cutter.html
You should probably look at pitchers who never used the cutter to their performance after they added a cutter to their repertoire
You cursed it.
Seems similar to face-off wins in hockey. Stacked distribution around the mean, seemingly mean-reverting. However, it is always the guys among the league leaders in face-off winning percentage. The distribution would suggest it is just a coin flip but certain guys seem to have a special ability. There are a few consistently strong performers in BABIP with Estrada being off the charts and some other pitchers with a live ball up there as well. It could be execution and movement rather than pitch selection. You’d have to have a way to break it down within pitch group rather than between pitch groups to see that though.
I believe Bannister said elsewhere that there are certain spin number thresholds for this to hold true.