BABIP? Again?

Just like HR/FB Rate, BABIP works for both hitters and pitchers and in this case, it is very similarly used. Remember BABIP from when we covered hitting stats stands for Batting Average on Balls In Play. Basically what it measures, for both hitters and pitchers, is the result of non home run balls put in play. But it goes deeper than that, so lets dig into it.

The Stat

When you see the BABIP number, it’s going to look similar to how batting average looks, no matter if you are looking at the BABIP for a hitter or a pitcher. And it looks that way because it measures something similar to batting average. Batting average is calculated by measuring how much a batter hits the ball – counting every thing from singles to home runs – divided by their at bats. And generally, you can say a .300 batting average is very good, and go from there. However, it doesn’t work that way for BABIP. BABIP instead, takes home runs out of the equation. BABIP is also reflective of the defense behind the pitcher. For example, a batter who hits the ball into an outfield gap against a poor defensive outfield may record a hit would improve his BABIP, but a better outfielder may reach the ball which would reduce his BABIP. So as we explored in one of the earlier posts, BABIP is often called the “luck” statistic because there are some elements of luck involved. And generally for a hitter, an extremely high BABIP means a batter is getting lucky and an extremely low BABIP means a batter is getting unlucky. But, this is the OPPOSITE for pitchers. So we have to look at how this works for pitchers, so I’ll use an example. If you missed the FIP or xFIP posts, you’ll want to go back and read them, because I’m going to be referencing those stats here.

Pitching BABIP is important to understand because pitchers have less control of their BABIPs. Once the bat hits the ball it is out of the pitcher’s control, so it is important to consider the defense behind the pitcher when evaluating pitchers based on BABIP. So if a pitcher has an astronomically high BABIP, there is a good chance it means he’s been getting unlucky – either because of bloop hits falling or because his defense has made some mistakes – and an astronomically low BABIP could be influenced by a defense doing extremely well or because the pitcher is inducing ground balls and double plays. Some quick examples are Justin Verlander, whose BABIP was .218 last year. Just like with hitting, we want to measure BABIP against his career BABIP, and not look at it in isolation. His career BABIP is .281, so we have to wonder if this was something that Verlander was actively doing to lower his BABIP, or was it more the result of luck or defense. His FIP and xFIP were higher than his ERA, meaning that his defense is better than the league average because it kept his ERA lower than it should have been with league average defense behind him. That’s my first hint that his low BABIP was because of defense. Verlander did induce a 35% ground ball rate (which is not high in relation to some other pitchers), but again, once the ball is in play, pitchers are reliant on their defenses to complete the play, which the Astros defense did do. There isn’t really anything in his peripheral stats to suggest he did anything special to limit his BABIP aside from limiting hits altogether, and so that tells me he was getting pretty lucky last year, and as we see some regression to the mean, I wouldn’t expect his ERA to stay as low as it was in 2019.

Why Is This Stat Important

This stat is important because you can use it to measure a pitcher’s talent in season and use it to make decisions on drop/adds, start/sits, and trades. As a reminder, do not just look at a pitcher’s BABIP in isolation. You should be measuring it against their career BABIP and look for anomalies there. If you see a BABIP that is much higher or lower than their career number, you have to assume that there is something affecting the stat, and then you have to figure out if it is something the pitcher is doing or if it is defense or luck related. Normally it takes probably half of the season to establish a solid reading on the BABIP for pitchers because you need a decent sample size to measure it and that creates a problem for this season. I still recommend using BABIP as a point of analysis for this season, though don’t make it your only one. And look at BABIP in conjunction with other stats too. Someone with a really high BABIP last season was Jon Lester. Last year his BABIP was .347 compared to a career .301 number. Remember, the higher the BABIP for a pitcher, generally the unluckier he’s getting. So lets see if we can figure out if he really was getting unlucky or if this was something he was doing to spike the number. He actually improved his strikeout, walk, and ground ball rate from the previous year, all of which should be good signs. One issue is that his hits, runs allowed, and earned run numbers all went up from the year before. So if you present me with those two data sets, what I see is a pitcher who is improving on things in his control, but not getting the results that should go along with it, and that tells me maybe the defense or some bad luck could be to blame. To go a step further, if you look at his FIP and xFIP, you’ll see that they are lower than his ERA. That’s a sign that if he had league average defense, his ERA could have been BETTER! That means his defense last year was below league average and likely turned potential good outcomes into bad results. He’s a guy who you can reasonably predict in a normal seasons to do better than he did in 2019, although I wouldn’t bet on him to have a top season this year.

How Do I Find This Stat

Go to Fangraphs of course! Once you’re there, go to leaders at the top right and select pitching leaders from last year.

Once you’re at the leaderboard, sort by ERA this time – and sort it so that it starts at the lower ERA. What I want to do with you is to find a pitcher with a low BABIP shows how good luck and defense influenced his season.

First, we’ll look at Jack Flaherty. His BABIP last season was .247, which was low even for pitchers with similarly low ERAs. Was this due to good luck, defense, or good pitching? My first inkling that his defense helped him a lot is that his FIP and xFIP are nearly a run higher than his ERA. That means a good defense behind him saved him nearly a run on average. If he had a league average defense behind him, he would have done worse, meaning his defense was above league average. He also had similar peripheral numbers across the board to the previous season where he had a 3.34 ERA, so that also makes me thing his defense helped him out.

To try to put a bow on pitching BABIP, here’s a way to think about it in easier terms with a couple of possible ERA/BABIP combos.

High ERA + High BABIP usually = a pitcher getting unlucky or bad defense.

High ERA + Low BABIP usually = the defense and luck are in the pitcher’s favor, and he is doing something poorly that is spiking his ERA.

Low ERA + Low BABIP usually = a pitcher may be getting lucky, but there is a good chance he is doing something well to limit hits and runs

Low ERA + High BABIP usually = a pitcher has a poor defense behind him and may be getting unlucky, but he is doing well at limiting runs and hits

Who Do I Target

What we want is a pitcher whose 2019 BABIP is in line with their career number, and whose BABIP reflects that they had control of their outcome. And hopefully we can use that to reasonably predict good things for this season.

One player that I like going into this season is Matthew Boyd from Detroit. He had a .307 BABIP last year, up from his .297 career number. But like Jon Lester, he improved in a lot of peripheral statistics from the previous year, some were significant improvements, all in only 15 more innings. So it’s not hard to figure out that a big uptick in hits, runs, and earned runs are not necessarily a result of the pitcher, but are more so likely a sign that his defense did not help him out very much, and that he got pretty unlucky. His FIP and xFIP being lower than his ERA also suggest he would have done better had his defense improved. That being said, Detroit did make some improvements this year adding CJ Cron, a deceptively good defensive first baseman, and Cameron Maybin , a defensive outfield upgrade. I don’t think Boyd will ever have the best ERA in baseball, but he is going to strike out a lot of batters, which is valuable, and some improvements to the defense could help his ERA dramatically. We already know with his BABIP that he is doing well with things that are in his control.

Well, that’s all for today, next week, we’ll go way off the beaten path and look at a sabermetric stat called SIERA. Thanks for reading.