A Few Thoughts on BABIP

Last week, I wrote about how the dramatic turnaround Josh Beckett has experienced this year has been mostly driven by a huge change in his BABIP, and in doing so, noted that this year’s version of Beckett doesn’t seem to be that different from last year’s version. The always insightful David Pinto responded, using Pitch F/x data and heat maps to show that Beckett’s pitches are showing a real difference this year. His conclusion:

To sum up, Beckett exhibited less control of a straighter fastball in 2010. Batters hit that pitch harder. Beckett’s bad luck seemed more due to an injury hurting his mechanics than balls finding holes on good pitches.

DIPS is often right, as it was on Dan Haren. In the case of Beckett, however, there is reason to believe that his improvement is more than just regression to and past the mean. Sometimes pitchers make their own luck.

In reality, I don’t think David and I actually disagree here — he just corrected some sloppy writing on my part, and that got me thinking that I probably needed to talk more about BABIP and regression, because too often, we just sum up variation as luck but don’t explain what we really mean by that. So, here’s a general take on what I see as the main causes of variations in BABIP.

Good or Bad Defense

I’m not overly surprised that the Brewers have the fourth-highest BABIP allowed in the Majors this year, as we all knew going into the season that they were gambling that they could win with a lousy defensive roster. Between Yuniesky Betancourt, Ryan Braun, and Prince Fielder, they have three guys who are among the worst defenders at their position in all of baseball – Carlos Gomez and Nyjer Morgan can only cover so many of their teammates’ sins.

This isn’t luck — this is just non-pitching skill that affects the results of a ball in play. This area has been extensively covered the last few years, and is generally accepted as a variable that needs to be accounted for, so we won’t spend too much time here.

Good or Bad Luck

Last week, Ervin Santana was trying to hold on to a 1-0 lead in Seattle. With two outs and the bases loaded, he got Carlos Peguero to hit a weak ground ball up the middle. Erick Aybar was in perfect position to pick up the ball and throw Peguero out to end the inning, but on it’s way to his glove, the ball hit the base and bounced into left field.

There’s no other way to describe that play than luck (good or bad, depending on your perspective). The pitcher got weak contact hit directly at a fielder, but because the ball bounced just so and deflected off an object embedded in the ground, it ended up as a two-run single. Not all lucky plays are this obvious, but there is no denying that outcomes like this happen, and they affect a pitcher’s results. Balls hit down the line are often fair or foul by a manner of inches, and the results are drastically different based on minuscule variations in when the batter started his swing. Balls are hit on a line but right at a defender. A wind gust knocks down a fly ball to the alley, or two defenders forget to communicate and a ball falls between them. This stuff happens, and the results obviously don’t reflect on the quality of pitch thrown.

These are the kinds of plays that most people think of when we describe a pitcher as being lucky or unlucky. And, given their frequency, it’s easy to understand their skepticism when someone states that a pitcher has been having a lot of luck (either good or bad), because these don’t happen so often that it’s easily memorable in most cases. These plays do have an impact on a pitcher’s BABIP, but most of the time, they’re not the driver of huge swings one way or another for any one pitcher.

Good or Bad Pitching

This is what David Pinto is talking about in his post about Josh Beckett, and it’s something I should have been more clear about. As many Boston fans noted, the Beckett they saw last year wasn’t just a victim of bad defense (though that may have been part of it) or bad luck (possible, but we don’t know for sure), but was giving up a ton of hits because he was throwing pitches that were just getting whacked. And this is the area where most fans have a hard time accepting DIPS theory.

When they see a guy throw a belt-high fastball and it gets ripped into the gap for a double, it sure doesn’t seem like bad luck; it seems like the guy threw a terrible pitch and got punished for it. And, if he repeatedly throws pitches that are getting hit hard all over the field, it’s tough to reconcile what just happened with a theory that says it won’t keep happening because the pitcher just got “unlucky.”

As David shows with his heat maps, and as most fans understand from just watching the sport for a while, not every pitch is equally hittable. It is certainly possible that Beckett just threw more hittable pitches last year than he is this year, and I should have been clearer about that in my post last week.

However, there is a commonality between all three of these areas that helps stats that just treat all BABIP variation as luck actually work pretty well — whether it’s defense, luck, or quality of pitches, all of them are mostly unsustainable in the long run for most pitchers.

Exceptionally bad defenses don’t stay together for too long. Pretty soon, the Brewers will realize that Yuniesky Betancourt is horrible, and he will be replaced. Even for a pitcher on a team with great defensive teammates, injuries, trades, or free agency can rip that apart pretty quickly. Obviously, a pitcher who has been getting lucky with things like sun balls or line drives right at fielders will see that come to an end just due to random variation.

But there’s also an unsustainable effect in play when it comes to throwing pitches that are easy or hard to hit. If a pitcher throws a bunch of hanging curve balls that are getting smacked all over the field, the catcher will eventually stop calling for them. Or, he might learn that he can’t throw that pitch in that location, and make an adjustment. Hitters make adjustments, too — they’ll watch video, realize that a pitcher likes to spot a certain pitch in a particular location, and once they expect it, the results will change.

Let’s use Charlie Morton as an example. In his first three starts of the year, he posted a .164 BABIP by throwing 90% sinkers to one particular spot, a massive change from the approach he had used last year. Hitters were hitting weak ground balls right at defenders, and to anyone who watched him pitch, it certainly didn’t look like good luck or good defense. But, it was unsustainable all the same — hitters began to adjust, the scouting report got out around the league, and now Morton has a .322 BABIP after getting lit up again last night.

A stat like FIP doesn’t distinguish between whether variations in BABIP are due to defense, luck, or the quality of pitches thrown, and this is where we need to do a better job in specifying which factors we think are actually causing the variation. In the case of Beckett, I shouldn’t have just lumped everything under luck — he probably was throwing pitches that were just easier to whack last year.

It doesn’t necessarily change the conclusion in most cases — with the exception of in-season defense for a player that isn’t changing teams — because whether luck or not, most BABIP variations are not something that predict future BABIP all that well, and for most of our purposes, that’s what we’re really trying to do. However, David is right to point out that pitchers can create their own luck, and I should have done a better job of clarifying what the cause of Beckett’s change in BABIP actually was.

It doesn’t mean I think he can keep posting a .220 mark this year, but it’s probably not accurate to say that it’s a result of balls finding gloves with regularity or other things that would generally be considered luck. Beckett probably has thrown a lot of good pitches this year, generated weak contact, and looked like a tremendous pitcher in the process. History suggests that this won’t last, but that’s different than saying it hasn’t happened already.



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Dave is the Managing Editor of FanGraphs.


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A guy from PA
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A guy from PA
5 years 3 months ago

The strange thing about your example is, Morton hasn’t gotten lit up in the traditional expectation in his last few games, but his BABIP seemed to go up based on factors 1 and 2 much more than 3. Tons of bloop singles and seeing eye grounders combined with a not great Pirates infield defense lately.

JRoth
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JRoth
5 years 3 months ago

And of course Morton was also a great example last year of a guy who earned an extremely high BABIP by being a lousy pitcher – flat, belt-high FBs. He spent some time in the minors and ended up pitching OK in September, but his .403 BABIP in April was deserved.

What’s funny about that is that, the last time Dave talked about Morton, he blithely assumed that his 2010 results were nothing but “luck”, when they actually reflected performance.

Telo
Guest
Telo
5 years 3 months ago

Short version:

Beckett’s true talent BABIP last year was probably .315
This year it’s probably: .280

There is real improvement, and also lot’s of other crap.

Telo
Guest
Telo
5 years 3 months ago

Also, take a look at this:

http://www.fangraphs.com/pitchfxg.aspx?playerid=510&position=P&season=2011&date=0&dh=0

http://www.fangraphs.com/pitchfxg.aspx?playerid=510&position=P&season=2010&date=0&dh=0

http://www.fangraphs.com/pitchfxg.aspx?playerid=510&position=P&season=2008&date=0&dh=0

Go back and forth between all of those pages.

What you see is that Beckett has had more movement on his Curve and two seamer than ever, and he has mixed in a nasty cutter. For the first time ever he has 4 plus pitches. And as Pinto shows, he is locating them.

Beckett has legitimately made impressive improvements. It’s staggering.

Telo
Guest
Telo
5 years 3 months ago

Oops. I meant FIVE pitches. Dirty.

Telo
Guest
Telo
5 years 3 months ago

Not to keep responding to myself….

But if anyone reads hockey stuff, you may have come across a guy named Hawerchuk. He loves to bet on people regressing to their career levels after short term success, showing people the power of recency bias.

I am willing to take an OPPO Hawerchuk bet here. See, he would say, I’ll take the over on a .291 BABIP for Beckett (or something around there) to prove he will regress back to his norm.

To me, I am looking at real true talent improvement. I would take the under at .280 maybe even as low as .275 ROS on Beckett right now.

Telo
Guest
Telo
5 years 3 months ago

I’ll be happy to take your bet first!

Did you see how much more action he has on all of his pitches in those links above? It’s real, and it’s pretty staggering, considering his success before he showed those improvements. Plus he refined his cutter, which have been seen over the last few years to have the lowest BABIP of any non-knuckleball pitch. His control, movement, and full arsenal of 5 pitches would give me confidence in a true talent level of .280.

Telo
Guest
Telo
5 years 3 months ago

I think Mike Fast showed somewhere that cutters had a .275 BABIP or something. Can’t remember where I saw it.

KyleL
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KyleL
5 years 3 months ago

Great article Dave, this makes a TON of sense, and should be hard for anyone to find fault with. This coming from a Red Sox fan, and long time Beckett Apologist.

Matt
Guest
Matt
5 years 3 months ago

This is getting really strained. Of course players make adjustments. But if they can just adjust their way into better results and throw less hittable pitches, it puts the lie to the entire concept of BABIP as largely out of the pitcher’s control. This has always been my problem with DIPS — yes, pitchers have highly volatile BABIP from start to start, month to month, year to year, but why is that evidence of goood or bad luck? Can’t it just be evidence of pitching well or poorly, and throwing more or fewer hittable pitches? You can say it is hard to control throwing hittable vs. non-hittable pitches, but that is a far different thing from saying the pitcher can’t control BABIP. It just means it’s hard to do.

Anon21
Member
Anon21
5 years 3 months ago

Volatility is one piece, but a complete inability to distinguish good pitchers from bad pitchers is probably a bigger deal. By BABIP, Roy Halladay is more or less a league-average pitcher. In reality, he’s probably the best pitcher in baseball. Is it just that the best pitcher in baseball happens to get by without what you posit is a controllable and important skill, or is it more likely that it just isn’t a skill?

Meddler
Guest
Meddler
5 years 3 months ago

I think this is kind of what Dave is saying, but also clarifying that often types we use the term “luck” as a catch-all for “trait that is not demonstrably sustainable”. The evidence is that there are very few pitchers who can sustain BABIP’s even a bit better than the mean–that’s not to say there are none, but that empirical evidence of past accounts have shown that its exponentially rarer than pre-DIPS baseball common sense suggests. Accounting for the reasons is a different question entirely, but insofar as empiricism functions, we can make a very strong assumption that a pitcher with a .220 BABIP over 15 starts is not all that much more likely to go his next 15 starts with a .220 BABIP than one who is coming off 15 starts with a BABIP of simply “X,” with the only given assumption that the latter pitcher is a pitcher who reasonably should be starting major league games (i.e. not someone whose talent level is within the range of major league caliber). This is not deductive modal logic, it is a strong induction, just as any non-tautological prediction is an induction. It is strong because the quantity of data is large and because it is a closed system with discrete rules and a finite set of identifiable outcomes. But it still has all the hallmark epistemic flaws of induction.

To empirically determine if there is some elusive trait a pitcher functionally controls that can supress BABIP, which based on cursory research and common sense it seems there should be, a different type of investigation is necessary. I have not seen a specific argument that is sufficiently convincing. That doesn’t mean I don’t generally believe one is possible, but from a scientific perspective its very difficult to assume any kind of significant validity until something specific and cogent is presented. Its like the Higgs-boson, we can sort of loosely discuss it in theoretical terms because BABIP control justifies some advanced notions that are soundly agreed upon after the fact, but until BABIP control is identified its at best a disputable theory or functional hypothesis. Not something we can make practical application out of. Its possible that the act of pitching is simply too entropic for any such trait to be practically sustained, even if it can be so theoretically. Attrition might, at least at this time, be as much at the heart of the BABIP issue as it is so many other elements of pitching.

Pat
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Pat
5 years 3 months ago

Great article, one of the best I’ve read on here in a while. Nice to see you look at BABIP from a different perspective, because I’ve said many times that anyone can do simple analysis by looking at a guys BABIP numbers and saying they will get better or regress with no reasons other than luck, and we go to this site to see more than that.

Pitchers are bound to have a few games where they can’t command their pitches as well, and Beckett probably had a lot of them last year since he was battling injuries and getting hit hard. This year, it’s safe to say he’s putting his pitches in the right spots and hasn’t had any games where he’s been way off. Same can be said about James Shields, he’s minimizing his mistakes and his delivery looks much different to me, and he is getting some better luck but that’s not the main reason why he’s pitching great.

Snarky Fangraphs Commenter
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Snarky Fangraphs Commenter
5 years 3 months ago

Actually, the score was tied. The Angels had not yet scored at that juncture in the game.

Dan in Philly
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Dan in Philly
5 years 3 months ago

To my way of thinking, the term “luck” is the problem here. It’s not really accurate to what’s driving BABIP to normalize (among other things). Rather, the fact seems to be that baseball is a perfectly effecient market, where every player has almost instant knowledge of what every other player is doing and why and what to do about it. When a pitcher changes his approach, it works for a while or it doesn’t, causing his periphs to improve or decline. If he improves, hitters very quickly catch on and adjust to his approach, causing his line to come back down to normal. If he declines, he adjusts again, and so on.

For the most part, this is immeasurable, since we as outsiders have no real idea what the pitcher is trying to do, and what the hitters are trying to do, and whether they consider the results successful or not. We only have the results, and lacking the “game theory” aspect of it we can only judge the emperical results and attribute what we don’t know about as “luck.” Maybe a better term would be “Things which we cannot accurately measure or predict.”

On the other hand, there really are things which are luck, such as bad bounces, bad wood on a bat, a vaiable strike zone, and so on. If we had perfect knowledge of the hitters, pitchers, and managers minds during every single play, we would be better able to measure success and failure and better able to predict future events, and better able to say what truly is luck and what truly is the players reacting to each other’s ever changing approaches. I certainly hope that day never comes :)

Person
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Person
5 years 3 months ago

I tried and failed to get this started on the last article, but does all this mean anything for FanGraphs whipping boy John Lannan, who is doing his thing again? If his FIP- is still 25 points higher than his ERA- at the end of the year, what would we make of that?

WinsBelowReplacement
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WinsBelowReplacement
5 years 3 months ago

As for DIPS, specifically FIP, I’ve wondered why something like LD% isn’t part of the equation. For example, we can make the generalization that pitchers that give up significantly more line drives tend to be making worse pitches, and I’m wondering why that isn’t really reflected in FIP. Whether the LD% is reflected in BABIP is one thing, but a ridiculous LD% just seems like a sign of hittability, and I feel like that should be reflected in DIPS.

Or maybe I’m just frustrated that I own Brandon Morrow in a league that counts ERA.

CheeseWhiz
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CheeseWhiz
5 years 3 months ago

I think the primary reason for not using LD% (although it is used in tRA) is inconsistency in scoring. If we could use HitFx to standardize hit classification that would probably make that information a lot more useful.

tenags
Member
tenags
5 years 3 months ago

I don’t know if its readily available anywhere, but instead of using a flat BABIP, I would prefer to see BABIP split by Batted Ball (FB / LD / GB). The common thought is that a Fly Ball should get caught, a Line Drive should be a hit, and a Ground Ball is 50-50.

So if you see a high BABIP on Fly Balls, you can make a general assumption of luck, a high BABIP on Ground Balls would imply poor defense, and a high BABIP on Line Drives should imply poor pitching.

I realize that these are overly simplified, but it helps to give better insight into the three variables that would affect BABIP.

Dave
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Dave
5 years 3 months ago

Great piece. You’ve defined your terms and clarified misconceptions enormously.

Big Oil
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Big Oil
5 years 3 months ago

The data and stuff is great. The analysis would be even better to hear from someone like Granderson, or another divisional opponent who exhibits a similar level of preparation (likely all of them) and have them comment on the differences they observe from start to start and year to year.

I don’t think it is far fetched to assume that the observations of those playing the game can help make more likely a valid explanation for any specific player X, while the aggregate data serves a great base for macro projections. Whether FG has this sort of access or not, I don’t know.

David Laurila to the courtesy phone.

Big Oil
Guest
Big Oil
5 years 3 months ago

Didn’t mean to get lazy with the “stuff” comment – the breakdown of the subparts of BABIP was very helpful. Player opinion serves to supplement subpoint #3 — good or bad pitching — but, due to reasons identified in the article (one side adjusting to another), players may find it undesireable to speak on what makes their opponents effective.

everdiso
Member
everdiso
5 years 3 months ago

I find it hard to believe that Beckett can apparently have such superior pitch quality and control this year than he did last year, with it having no positive effect on his K and BB ratios.

channelclemente
Guest
5 years 3 months ago

Rather than ‘luck’, maybe the word, chance, makes more sense. What is your guess on the noise in BABIP, that is to say, the background chance likely to be there no matter what. I looked earlier this year and Ogando had a BABIP of 0.119 or there abouts. That seems close to me. The regression model should yield that, shouldn’t it, if you investigate the confidence limits?

supgreg
Member
supgreg
5 years 3 months ago

Good article. It’s long overdue for a lot of fantasy experts to move away from the term “luck” as it relates to BABIP.

Rick
Guest
Rick
5 years 3 months ago

I think we sometime forget to realize that skill itself can vary over short stretches of time. Variance doesn’t have to be a function of luck. It’s just players will regress back to some average leverage of skill. A better example might be free throw shooting. A 70% shooter can go 10 for 10 or 42 for 50 and it’s not because of “luck” per se. There was no gust of wind or lucky bounces. He just managed to properly execute that shot more effectively in that sample.

Who knows why that happened. Maybe he had a great night of sleep; maybe he was trying harder. But it wasn’t luck in the form of random external influence. This is what people mean when they talk about “hot” or “cold”. Now we know that those streaks are not necessarily predictive of future performance, but that doesn’t mean that the change in performance was not reflective of a temporary change in skill.

Chris
Guest
Chris
5 years 3 months ago

I don’t doubt at all that something as simple as “pitching better” can account for a drop in BABIP, but as a previous poster pointed out, this has all happened while his k and bb rates stayed pretty level… he’s also stranding 84% of baserunners which is way higher than he’s ever done ( as well as being above league average)

In short, I think Beckett’s success may be due to just throwing better pitches, but it seems to me there has been some good fortune in there as well.

Chris
Guest
Chris
5 years 3 months ago

Also, while it is true that batters simply aren’t hitting the ball as hard against him this year (16% LD rate) I just can’t see how that HR/FB rate (3.9) Can possibly be sustainable….

evenbilljameshatesu
Guest
5 years 3 months ago

This post contradicts the definition of BABIP that is posted at urbandictionary.

AJS
Guest
AJS
5 years 3 months ago

Yes, the definition you wrote.

odditie
Member
odditie
5 years 3 months ago

I view this as the same as what was happening in April with Alex Gordon (or any hitter who is driving the ball for a lot of XBH with a great BABIP), there is an element of luck driving their overall numbers, but ultimately they are seeing the ball well, timing their swing well and getting hittable pitches along with an additional element of luck.

All of these things are pulling/pushing each at bat in every game. The amount of noise is much greater than we would like to believe when we do statistical analysis on a players performance.

Tittymac
Guest
Tittymac
5 years 3 months ago

Dave, this is an excellent article. I’ve subscribed to DIPS theory, but I always still held the view that it wasn’t just simply luck and it would frustrate me to see people simply sum up a performance as bad luck and end the discussion there. This article sums up precisely what I would have tried to explain if I had writing talent.

Barkey Walker
Guest
Barkey Walker
5 years 3 months ago

Dave, here is one for you. Tonight Bumgarner got a -3.04 FIP, (1 K in 0.1 IP, 0 HR, 8 ER, 1.00 BABIP). Was that just luck, should he have gotten about a -3.04 ERA pitching that way instead of the ERA- of 5,646?

Trotter76
Guest
Trotter76
5 years 3 months ago

Oof-da! MLB Network was able to show the final pitch of every AB for Bumgarner (thanks to him facing only 9 batters) and let me tell you, he fell into category 3: Bad Pitching. His ball was flat and consistently out over the fat part of the plate. Now, chance (I do like that better than “luck” — thanks ChannelClemente) factors in here too, as we’ve all seen fat pitches get hit right at a defender, and tonight that didn’t happen for Bumgarner. But he flat out pitched poorly and got lit up for it.

Sylvan
Guest
Sylvan
5 years 3 months ago

Every pitcher, no matter how good, has variation in how good a feel they have for their pitches on any given day. You have no idea when you get up in the morning whether your fastball is going to have great movement that day. It’s performance but it’s luck, too.

Rufio Magillicutty
Guest
Rufio Magillicutty
5 years 3 months ago

A lot of the variance between FIP and a pitcher’s BABIP can be resolved by adjusting BABIP to league averages while maintaining the hit-type ratios, then applying linear weights, thus calculating runs allowed. An alternative would be adjusting a pitcher’s BABIP and how it relates to runs to other pitchers of a similar skill set.

Magic Man
Guest
Magic Man
5 years 3 months ago

Maybe BABIP should be evaluated in combination with a pitcher’s well-hit average against. If high BABIP and low well-hit, then BABIP regression is likely and vice versa.

JJK
Member
JJK
5 years 3 months ago

I’m confused

#1 and #2 are truly out of the control of pitchers, so not differentiation there

#3 really comes down to what you’re calling “hittability”. I’ll give you that hittability can change for a pitcher from game to game based on “stuff”, and that over the long run that will normalize for an individual pitcher. However, wouldn’t that precisely mean pitchers have control over their babip, based on how hittable they are relative to other pitchers?

As an example, Roy Halladay’s hittability changes game to game. Jarrod Washburn’s hittability changes game to game. But Washburn has a career babip 20 points lower than Roy. Are his pitches, on average, less hittable?

Buzzy
Guest
Buzzy
5 years 3 months ago

Verlander’s BABIP is even lower than Beckett’s…

Buzzy
Guest
Buzzy
5 years 3 months ago

and Beckett has a lower LD%, higher IFFB% and far lower HR/FB%. Not all of these things are completely skill-and the last one cannot be manitained at levels close to where it is now- but they do suggest some level of skill correlated with bad contact.

Drew
Guest
Drew
5 years 3 months ago

Seems to me there definitely is a disagreement between your original post and what Pinto rightly pointed out. In fact, the notion that pitchers can control the types of contact and, in turn, control the number of hits allowed — that contradicts the very idea of BABIP that Fangraphs is married to.

Pinto is correct of course. And just like Cole Hamels two years ago, Beckett struggled last year not just because of bad luck but bad pitching–giving up solid contact where previously (and subsequently) he didn’t. He won’t stay at .220 all season because he won’t keep pitching this well. But it ain’t luck brother.

Matthew Cornwell
Guest
Matthew Cornwell
5 years 2 months ago

The problem with assuming batting average on batted ball types is that huge assumptions are made. Batted ball type BABIP assumes that groundball pitchers have a higher BABIP on BIP than flyball pitchers. Unfortunately, there are a whole lot of extreme GBers that this is not true for. So you get something like PZR saying that Greg Maddux “should have been” about 100 runs alolwed worse than what he was. Extreme flyballers also tend to have worse BABIP on LD too. Almost too many exceptions to take it seriously.

Given a large enough sample size, I would always prefer to look at the pitcher’s BABIP vs. his mates BABIP to see true BABIP skill. The key is sample size of course; it takes about 7-8 seasons to reach the r=.5 mark for BABIP.

Finally, if we want to make a prediction on Beckett’s true BABIP…I would put good money on it being whatever his career rates are. If he really has found new ways to throw stuff well that he never has before, then I will adjust down. But I’d like to see another year of this new fangled pitching mastery before I would predict a true talent level much better than his career BABIP.

Dale
Guest
5 years 2 months ago

How much of the Brewers high BABIP is due to all the funky shifts that Ron Roenicke puts out? I wonder if it helps or hurts. Any way to find out?

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