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Last week I posted some numbers on how the addition of Matt Holliday had impacted the way pitchers approach Albert Pujols, and the conclusion was not at all.  I also wanted to take a look at how Albert looming in the on deck circle impacts those hitting in front of him.  For this particular case study I looked at Colby Rasmus since he has a good amount of at-bats both before and after Pujols.  The next few tables summarize the findings, first the pitch distribution

Pitch Before Pujols Other
FB 53.2% 50.0%
CU/SL 28.7% 34.5%
CH 18.0% 15.4%

While Colby sees a few more fastballs hitting before Pujols, it’s not as big of a difference as the main stream media would have us believe. However, does he get more first pitch fastballs or fastball when the pitcher is behind in the count?

Before Pujols Other
0-0 57.4% 54.9%
1-0 52.5% 47.6%
2-0 44.0% 43.7%

So it appears the pitchers are a little more hesitant to fall too far behind in the count, but nothing too drastic. And finally are the pitches themselves “better”, meaning more strikes/fatter pitches

Before Pujols Other
In Zone 56.6% 54.1%
“Fat” 37.4% 34.2%
FB in zone 59.6% 61.9%

Overall he sees more strikes and more pitches in the fat part of the zone, but sees less fastballs for strikes when hitting in front of Albert. While there are advantages to hitting in front of Albert (usually on the order of 2-3% to the “good” side of the comparisons) those advantages appear to be minimal.

Steve Sommer

Simulation analyst by day, father and baseball nerd by night

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5 Responses to “Lineup Protection Part 2”

  1. what’s the # of pitches we’re talking about?

    • It’s ~670 before and ~450 other.

      • Just looking at Fangraphs, I’m about 400 pitches short in my data… Has to do with a non updated database, plus I think I missed some early season games somehow.

      • We’re still left with some significant variables — does the #2 slot normally see more fastballs than other spots? Does this effect (even if small) hold true for other hitters in front of AP?

        There’s always a contention (though it’s basically unfalsifiable) that Albert is a true outlier and he really does offer protection. But like I said, you’d need a pretty significant sample size to prove that and even then I’d have doubts.

  2. AZ,

    All clearly valid points. I’d tend to agree that we still have a small sample size, and there could be other muddying factors at work. That being said, I may investigate the second question some more after I get some more data (to include 2008). I may also compare the same metrics for some other noteworthy hitters. We’ll see if I find some time or not.

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