F/X VisualizationsJuly 17, 2009
Can Pitchers Control Their BABIP by Controlling Pitch Location?
By Dave Allen

At the PITCHf/x summit I gave a presentation about making the type of contour and heat maps that I often show here. In the presenatation I listed some of the things one could do with such maps and I said 'for example you can see how BABIP varies by pitch location.' A questioner at the end of the talk asked if I had done so. He thought if BABIP did in fact vary by pitch location, and pitchers can control the locatoin of their pitches then pitchers could control their BABIP. I, at that point, had to fess up that it was just an example and I had not in fact looked at it. Unfortunately I don't know the name of the person who asked the question, but here it is.

There is a long history of examination of how much control a pitcher has of his BABIP (batting average of balls in play). The first major work was by Voros McCracken who, in 2001, suggested that pitchers do not have the ability to prevent hits on balls in play. In 2003, Tom Tippett found that some pitchers, in particular knuckleballers, had the ability to suppress hits on balls in play throughout their career. In addition, the BABIP of a ground ball is higher than that of a fly ball and we know pitchers do control their ground ball rate. So, we should expect BABIP differences between ground ball and fly ball pitchers. The general understanding, at this point, is that pitcher's have some, but probably a very small, amount of contrl over their BABIP beyond their control over batted ball type.

Obviously pitcher's control the location of their pitches, so if BABIP varies by pitch location could this be how some pitcher's have the ability to depress their BABIP? Let's see how BABIP varies by location. Here I am just looking at RHB.


There is some trend for pitches down in the zone to have a higher BABIP. I am sure this is driven by the fact that high-BABIP ground balls are more likely on hits low in the zone while low-BABIP fly balls are more likely up in the zone.

EDIT: In my initial post I had the outside/inside orientation flipped in my interpretation. Below I have corrected that. I would like to thank Mike Fast for bringing this to my attention and apologize for any confusion this might have caused. As always the images are from the catcher's perspective.

Along the horizontal axis pitches in the middle of the plate have the highest BABIP, which is not surprising. Beyond that, though, on pitches low in the zone those inside have a higher BABIP than those away, and pitches up in the zone those away have a higher BABIP than those inside. For those down in the zone, which will most likely be ground balls, those inside pitches will be pulled and pulled ground balls to the left side of the infield are more likely to be hits. On pitches up and in are most likely to be home runs, which are not counted as balls in play. This might be partially responsible for the drop in BABIP up there. Also maybe these pitches 'tie up' the hitter causing popups which have a near zero BABIP.

I wanted to examine the horizontal gradient further, so I took a one-foot-high band of pitches centered at y = 2.5. My hope is to see how much the BABIP changes by horizontal location to see if it is reasonable for a pitcher to depress his BABIP based on the location of his pitches. Again this is just for RHB.


So there is definitely a trend. The farther inside a pitch is hit the lower the BABIP. But look at the error bars the BABIP is effectively unchanged from x = 2 to x = -0.5. A pitch really has to be on the inside fourth of the plate before there is a significant drop in BABIP. From there to outside the zone away there is a big drop in BABIP.

It looks to me for a pitcher to seriously decrease his BABIP based on the horizontal loation of his pitches he either needs to induce swings (and contact) inside of the zone or be able to locate on the inner fourth of the plate.

If a pitcher could regularity locate pitches in the string zone, but just on the inner edge he could drastically lower his BABIP. I am not sure there are a lot of pitches with the control to pitch with the speed and movement required to get out major league hitters AND locate the ball that finely. If they miss too much to one side it is a ball, too much to the other it hits the heart of the plate. The one pitcher, off the top of my head, who I think might be able to do this is Mariano Rivera. Check out the location of his cutters to RHBs.


While most of the pitches are on the outer half, he locates a good number on the inner quarter. Exactly the type of pitches that are in the zone AND can depress BABIP.


This is great, Dave! Could you give us a list of expected BABIPs for various pitchers based on these numbers? Does that number correlate from year-to-year? I would expect it to be more consistent than BABIP.

Dave, I love the article, but I'm a bit confused on the horizontal axes for these graphs. The graph of Rivera's cutters looks correctly oriented to me, but either the x-axis labels on the second graph (the y=2.5 plot) are reversed or your descriptions of inside/outside pitches are backwards for the first two graphs.

David, that is a great idea, which I hadn't even thought about. I will look into getting together that list and post it here or in a full article next week.

Rivera's career BaBIP is .277.

A perfect case for this would be Ryan Franklin for season. All the numbers, his K rate, batting average allowed, adjusted ERA, point towards Franklin being stunningly lucky this season.

Franklin has excellent control, so he is pitching to locations that minimizes damage or the likelihood of seeing the balls in play fall in safely?

My previous comment to this effect seems to have been blocked, but I think the horizontal scales of the first two graphs are opposite that of the third graph.

What about HRs? I assume they're not included in your calculation of BABIP. If so, I'd love to see the heat map for BACon (batting average on contact).

I have a brother who is the perfect example of this. He had the movement, location and finesse to reduce his BABIP.

Great stuff Dave. Would love to see how this interacts with pitch type, especially for the low pitches (maybe this would help explain why low-away has a higher babip than low-in).

Great work, as usual, but why are the numbers on the axis and legend so big in the first figure?


Is the confusion because it looks like Rivera throws lots of pitches to the area of high BABIP. That is my fault, on the Rivera plot I included his pitches to RHB and LHB, while graphs one and two are just for RHBs. I really should have just shown his pitches to RHBs. Still Rivera throws a ton of pitches to RHBs on that inside edge too, where you would expect high BABIP. I bet he gets a low BABIP on those inside pitches too. I hope that rambling cleared it up.


Franklin's K and BB rates look pretty good so I don't think it is all luck, but his BABIP of .207 does scream unsustainable. I don't think any pitcher can suppress it that much. Over his career his is .277, so he probably does have some BABIP-suppression skills.

Shawn, great idea maybe I will check that out.

Jimboslice, yeah that looks horrible. That was a mistake on my part. I have been trying to make my figures a little smaller than in my old posts. In this case I used some code from an old post to generate that figure. I changed the figure size but forgot to change to change the axis size parameter.

Actually, this concept has been around for a long while now, since Ted Williams wrote his "Science of Hitting" book. He had a strike zone diagram with basically a similar to your heat chart but with an old fashioned chart showing how batting average varies by pitches in the zone. Of course, his was all theory and empirical by his experience, and I don't recall if it matches your heat diagram, but thought it would be interesting to add to this discussion.

Here is a link to a picture of it: http://tewalkerjr.com/blog/wp-content/strike-zone.jpg

Oh, I probably should include this link for some explanation of the chart: http://tewalkerjr.com/blog/?p=921

Dave, what I mean is that I believe the coordinates on the x-axis for the Rivera graph are correct because the RHH usually stands at -2 or -3 feet, so the left side of that graph would be inside to a RHH and the right side of that graph would be inside to a LHH. The angle of both the inside and outside clusters of cutters lines up with that understanding based on the fact that Mariano is a RHP and his pitches would tend to land at an angle from high-inside sweeping down toward low-outside to a RHH.

But in the middle graph you call x=-2 as "outside" to a RHH. This seems backwards. The x=-2 point should be inside to a RHH, unless you have switched coordinate systems from the first two graphs to the last graph.

Oh yeah, Mike, I see the problem. Boy, I had that totally turned around in my head. Thanks for bringing this up. I will have to edit that soon.

Thanks again.

So all three charts are from the catchers view, correct Mike? Therefore, BABIP is lower on pitches inside to RHB, not outside?

Jay, yes this is correct. Sorry for the confusion. The text has now been corrected, thanks again to Mike for pointing out my mistake.

This is great stuff. Is it possible to do wOBA by location?

I would think that being in the zone above the inside boxes may lead to a higher SLG%, thus making pitching high less valuable than pitching low.


I made heat maps with the linear weights run value of a pitch by location, which is equivalently wOBA. Click my name for the link.

Thanks Dave. Great thought provoking article by the way. I agree on Franklin, his career BABIP scare the heck out of me, meaning that there's little chance he can continue at the rate he's going right now. Of course the laws of probability say the same thing.

When he does falter some, hopefully he can minimize the damage and continue to pile up saves for the Cards. Of course, with age and a new role, maybe he's also finally found the ideal situation to best suit his talents.


This catches me as the future of baseball analysis, going beyond how good a player IS and moving on to how to MAKE players good.

I feel like a full analysis/breakdown by pitch type, batter type (not just handedness but also the kind of batter, contact, power, etc), along with meshing the information with swing-and-miss results, could allow us to discover exactly what pitchers should be trying to do, and what coaches should be teaching.

Going even further, you could break this all down for individual batters, and heady pitchers could plan out exactly how to approach tough hitters before games. Amazing stuff, thanks for getting the ball rolling here!

Hey, ok, I get it, I guess - but does this really work?