Command PostNovember 02, 2007
Pitching to the Hitter
By Joe P. Sheehan

In my previous article, I looked at the decisions pitchers make about what pitches to throw. One thing I didn't look at, and was reminded of by a comment from MGL, was how this pertained to hitters. Do certain types of hitters see more fastballs than other types? I had some slight difficulties trying to determine if pitchers deviated from their normal pitching patterns in certain situations because I didn't have the ability to know what their "true" pitching patterns in different situations were. Since hitting is the reaction to the action of pitching, looking at hitters is much easier. I can look at how pitchers pitched in a given situation against certain hitters and then compare that to how the exact same pitchers pitched in the exact same situations, but against different hitters.

Including the post-season, I have 189 pitches in my database when David Ortiz was in a hitter's count. Those 189 pitches represent 17% of all the pitches Ortiz faced, which ranks him in the upper echelon of hitters as far as getting himself into a good count to hit in, but what happens once Ortiz is in a hitter's count? I've shown that certain pitchers exhibit an overreliance on their fastball in hitter's counts or pitcher's counts, but I haven't looked at how this impacts specific hitters.

When Ortiz is in a hitter's count, pitchers throw him 66% fastballs, which puts him right at the league average of 67% fastballs seen in those situations. However, Ortiz is far from a league average batter in terms of his power potential. How do pitchers approach other elite sluggers when they find themselves behind in the count? My definition of an elite slugger might be a little loose, but I took everyone with 300 ABs and a slugging average of .550 or higher this year and looked at how pitchers approached them in hitter's counts. Not surprisingly, pitchers gave these hitters fewer fastballs as a group in these situations. Instead of seeing 67% fastballs, elite sluggers only see 61% fastballs when in a hitter's count. Ortiz sees more fastballs than the other hitters in this group, but within a reasonable amount. Teammates Curtis Granderson and Magglio Ordonez are a different story. Granderson (73% fastballs) and Ordonez (72% fastballs) see the most fastballs out of the group. Perhaps pitchers didn't believe that Granderson was as good as he hit this season and kept challenging him with fastballs, even in hitter's counts. Using a hitter's career slugging average might fix that problem, but still wouldn't explain why Magglio saw so many fastballs. Maybe there is something with Comerica Park that is causing my labeling process screw up there and is impacting Granderson too.

At the other end of the spectrum lie Adam Dunn (50% fastballs) and Ryan Howard (45% fastballs). These two are very similar types of players according to their output and are both approached very cautiously by pitchers. Dunn and Howard see fewer fastballs than most of the group which is probably a result of their propensity to whiff and their power when they do connect. The chart below has all my top sluggers, the number of fastballs they saw in hitter's counts, the total number of pitches they saw in those situations, their overall slugging average and FB% in hitter's counts. There's a definite shift from the population mean to the group mean here that you can see from the table.

Name	           FBseen   TotPit.   SLG       FB%
Curtis Granderson   101      139       0.552     0.73*
Magglio Ordonez     78       109       0.595     0.72
Alfonso Soriano     38        54       0.560     0.70
Ryan Braun          73       108       0.634     0.68
Hanley Ramirez      31        46       0.562     0.67
David Ortiz         124      189       0.621     0.66
Prince Fielder      71       113       0.618     0.63
Alex Rodriguez      52        83       0.645     0.63
Carlos Pena         57        91       0.627     0.63
Chipper Jones       85       141       0.604     0.60
Albert Pujols       84       142       0.568     0.59^
Matt Holliday       62       105       0.607     0.59
Jim Thome           101      176       0.563     0.57^
Chase Utley         38        67       0.566     0.57
Barry Bonds         70       124       0.565     0.56^
Miguel Cabrera      29        54       0.565     0.54^
Adam Dunn           53       107       0.554     0.50^
Ryan Howard         53       118       0.584     0.45*^
*-significantly different from group mean (.61) at alpha=.01
^-significantly different from population mean (.68) at alpha=.05

Keep in mind, the FB% listed in the table are only for hitter's counts and while the chart isn't too revealing, I just think it's interesting to see the different ways each hitter was approached. I was surprised to see Soriano see so many fastballs, as he's a hacker, but maybe there's a good reason for it. Braun got a lot of fastballs, presumably even after started dominating offensively, so maybe there wasn't a good scouting report on him yet, although I'm not sure why there wouldn't be.

Getting back to how pitchers approached different types of hitters, I split up every batter (with a minimum of 300 ABs) based on their slugging average, and then found the FB% for that class of batters in hitter's counts. The table below shows the number of hitters in each group, the number of fastballs seen and total number of pitches seen in hitter's counts, the average slugging average for the group, and the percentage of fastballs the group saw.

Hitter Groups   #     FBseen   Totseen  SLG     FB%     PFB%
>=.550          18    1200     1966     0.591   0.61*   0.68
.549-.500       27    1761     2760     0.520   0.64*   0.67
.499-.450       68    4020     6142     0.471   0.65*   0.67
.449-.400       71    3871     5660     0.425   0.68    0.67
.399-.350       52    2626     3623     0.376   0.72*   0.67
<.350           20    975      1309     0.332   0.74*   0.67
*-significant difference from PFB% at alpha=.05

This table has a lot of things going on, but the most obvious one is that in hitter's counts, as the caliber of a batter increases (slugging goes up), FB% goes down. This isn't true for every batter individually, but the overall trend is really clear. I don't know exactly why pitchers are behaving this way, (maybe bad hitters as a group can't hit fastballs very well and there is less of a cost to the pitcher's stamina for throwing a fastball), but they do throw fewer fastballs to each progressive range of hitters. It makes sense that pitchers would avoid throwing fastballs to better hitters and try to fool them with junk, while getting after the weak hitters and not worrying about home runs and doubles. Even though all these batters are in hitter's counts, some got many more fastballs than others. Not every hitter's count is created equal.

The last column in the table, PFB%, is the other big thing to see. For every hitter, I found the different pitchers they faced in hitter's counts, and then found out what those pitchers had thrown in all other hitter's counts they were in during the season, regardless of hitter quality.
When any pitcher who faced one of my top hitters was facing any other batter, he threw 68% fastballs. These values are slightly more interesting on the individual hitter level (Willie Bloomquist saw 100% fastballs in hitter's counts, while those same pitchers threw 75% fastballs whenever the faced someone other than Bloomquist), but this value is my best guess about what these exact pitchers should throw in a hitter's count to a random batter. By comparing what they actually threw to that value, you find that the differences are not due to randomness but rather a decision on the part of the pitcher.

The next table uses the same hitter groupings, but looks at the pitches they saw in pitcher's counts. This chart tells a much different story than the first one. In hitter's counts, pitchers seem to be aware of the type of hitter at the plate and pitch accordingly. Ortiz gets fewer fastballs than Nick Punto. However, if both those types of hitters were in a pitcher's count, they could expect to see a virtually identical amount of fastballs. A pitcher doesn't seem to know or care who is at-bat when the count is in the pitcher's favor. Both good and bad hitters should expect close to the same proportion of fastballs in these counts.

Hitter Groups   #     FBseen   Totseen  SLG     FB%     PFB%
>=.550          18    2131     4522     0.591   0.47    0.47
.549-.500       27    3158     6559     0.520   0.48    0.48
.499-.450       68    7766     16210    0.471   0.48    0.48
.449-.400       71    7212     15606    0.425   0.46    0.46
.399-.350       52    4629     9856     0.376   0.47    0.47
<.350           20    1650     3414     0.332   0.48    0.48
*-significant at alpha=.05

MGL's comment that prompted this article, about whether Sabathia and Carmona throwing more fastballs to good hitters was a double mistake, proved to be spot on. Intuitively his premise made sense because good hitters usually see fewer fastballs than bad hitters in these cases and are able to hit the fastballs they do see, so it’s nice to see that the data back it up.

When looking at the relationship between slugging average and FB% for hitters, I thought about trying to predict the FB% of a pitcher, given any situation. For a pitcher with a given set of pitches, you could possibly figure out how often he should throw his fastball in a situation and then compare how often he actually threw it. I’m not sure exactly what factors I would use to predict this, but I think the quantity of pitches a pitcher throws, the nastiness of those pitches, the batter, and some measure of the pitcher’s control would play a big role. For a batter, I think the FB% that he should see would be primarily impacted by his quality as a hitter, in terms of batting eye, ability to make contact and ability to hit the ball hard, as well as any holes in his swing.


Very cool article, Joe. Could you clarify exactly what you consider hitter's counts and pitcher's counts? I'm guessing hitter's counts are 1-0, 2-0, 3-0, 2-1, 3-1, while pitcher's counts would be 0-1, 0-2, 1-2, 2-2. The other two counts, 0-0 and 3-2, would be washes.

Sorry about that, I had mentioned how I broke up the counts in the last article but forgot to do so here. I used 3-0, 3-1, 2-0 and 2-1 as hitter's counts, 0-2, 1-2, 2-2, and 0-1 as pitcher's counts, and anything else as a neutral count. gives some batting stats by each count. I didn't follow exactly what Tango found but it's close.

Not to hijack this site, but there will probably be a nice discussion of this article here:

The other factor in throwing the FB is to avoid throwing a ball. If I am a catcher and Granderson is at the plate I might be thinking that if we walk him he might steal second. I am not thinking that with Ryan Howard. Now David Ortiz is up there despite his lack of speed, maybe there is more often a runner at 1st that I don't want to move into scoring position.