F/X VisualizationsMarch 17, 2009
Home Run Rate by Pitch Location
By Dave Allen

So far I have looked at the run value of a pitch based on its location as it passes the batter's plane. Today I am going to take a slightly prosaic break from that and look at everyone's favorite contributor to run value: the home run. Below are maps of HR rate per pitch by pitch location. Again I average over pitch type, count and speed, so there are some obvious limitations to the analysis. The number presented at the top of each figure is the average HR rate per pitch.

These figures confirm a number of assumptions:

  • The highest home run rate is slightly in from the center of the strike zone.
  • The extreme inside of the strike zone has a higher home run rate than the extreme outside.
  • The home run rate is higher above the strike zone than it is below.
  • The home run rate location is determined by the handedness of the batter and not the pitcher (the images are more similar going across a row than they are going down a column).
There are a couple of things that I found surprising.
  • There is a considerable area down-and-away within the strike zone that has a near-zero home run rate.
  • There is a relatively large region in which the HR rate per pitch is over 2.5%, which seems high to me. For pitchers, this reinforces the importance of being able to locate a pitch in a corner of the zone.
As stated above this analysis is limited by the fact that it averages over all pitch types. It would be interesting to see, for example, how the home run rate map differed for fast balls and curve balls. I hope to address this in a future post. Until then the current analysis allows for comparison between a individual hitter's home run map and the composite map.

Since the batter's handedness is more important than the pitcher's I averaged across the rows above to create just two maps, one for RHBs and one for LHBs. Over the composite map I plotted all the home runs for an individual hitter to see how he compares to his peers. Here are the HRs of everyone's favorite HR hitter, Jack Cust, plotted over the composite LHB map. Cust's home runs are, for the most part, where you expect for a left-handed batter: the highest density slightly in from the center of the zone, none in the down and away corner of the zone and more above the zone than below.

I made such images for a number of last year's top HR hitters and most resemble Cust's with the given player's HRs largely mapping to the regions of high home run rate in the composite map. But a handful of batters had quite different maps. Carlos Quentin's HRs are overwhelmingly away and down in the zone, and a large portion of the inside of the strike zone, where the average right handed batter has a high HR rate, is completely devoid of HRs. Since this is aggregated for all pitch types our insight is limited here. It will be interesting to see if players with HR maps very different from the composite map tend to also have a skewed distribution of which pitch types their HRs come from compared to average.

Here are two other batters I thought were particularly interesting. Alfonso Soriano is almost a caricature of a right-handed batter with his highest HR rate region even more down and in than expected. Carlos Pena, on the other hand, mashes outside pitching and the inside half of the zone has surprisingly few HRs. A possible explanation for this pattern could be that Pena just gets very few inside pitches because pitchers know he is a dangerous HR hitter. This shows one problem with my analysis. I am comparing the composite HR rate to a player's raw HRs not adjusted for the number of pitches a player sees in that region. I should be comparing that player's HR rate to the composite rate. For two reasons I did not do this: (1) I am having a hard time creating rate maps for individual players based on so few HRs and (2) even if I had such a map I cannot think of an effective way to overlay the two rate maps (individual player and composite) as nicely as I can overlay the actual HRs on the composite rate map. But it is something I am going to think about and work on in the future.

Oh and I have to assume the home run in Pena's map around (2,4.5) is a mistake.


You know who's not surprised about the near-zero hr rate down-and-away?

Leo Mazzone.

These articles are great, Dave! I look forward to seeing more of your work.


Great work here. I have a couple questions about massaging the data to create a continuous matrix for R's contour plotting function. Do you have an email address posted where I can contact you?


Thanks Mike,

I am glad that you enjoyed them.

Really cool, although I expected color.

One idea I never followed thru on is first identify hr% by location (and pitch type and count), as you have done here, then for each hitter (his favorite zones and pitches to go deep) then finally see how well each player recognizes the mashable pitches - what are the swing% for batters when they see a pitch in the best hitting zone? My opinion is that Barry Bonds and Brian Giles hit a high pct of homers because of superior pitch recognition, and putting the bat on the ball when they swung, not because of hitting the ball an extra-ordinary distance.


Yeah, Rich, suggested I do color too. For some reason I liked the gray-scale. There is a link at the bottom of this comment to an example of what they look like in color, I think all the red was off putting to me.

That is a really interesting idea, looking at how a batter's swing percentage by location correlates with his HR rate location. My next post will look at something similar, comparing swing percentage by location and run-value of hit pitches by location. But it will average over all hitters.


Interesting plotting, but be wary. As in the Pena reference, in making inferrences because his plotting doesn't fit the "norm." There are some hitters who simply hit different zones better then others, and can "work" that location out of a pitcher by a variety of box methods, such as box depth and proximity to plate, varied further by degree of closed to open stance.

I see you quickly surmise that charting pitch type as a variable would make for an interesting study. Of course, the variables never end, as even amongst LHP and RHP there are every degree of arm slots. But lots of fun, for sure. Cool stuff.