Is Brian Bannister on to something?

by archivedposts on January 31, 2008

In a recent interview with MLB Trade Rumors, Kansas City

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{ 7 comments… read them below or add one }

Ren January 31, 2008 at 12:44 am

Jacob: I feel the same. It’s not quite “who can throw a breaking ball for a strike”, but who feels confident enough in his breaking ball (not quite the same, because some don’t trust their pitch even though it’s good).
I think Bannister is missing out on cause and effect. Why does the count affect BABIP? I don’t think that it’s because the hitter needs to swing, as much as I think that it’s because pitchers vary their selections. In hitters’ counts they will throw more fastballs/sinkers (which produce worse BABIP) while in pitchers’ counts they will go to their secondary stuff.
The only thing is that I think it has more to do with what they feel they need to do rather than with what they are able to do. Not all pitchers throw their fastball for strikes that much more than their breaking balls, but most will automatically go to their fastballs when they need a strike. This will help hitters generate a higher BABIP. But then take a look at pitchers like Glavine, Litsch, Rogers and Timlin who beat average BABIP easily last season: they all throw their secondary pitches often, much more often than average, despite walking their share (and therefore falling into hitters’ counts relatively often).

Ren January 31, 2008 at 12:44 am

Jacob: I feel the same. It’s not quite “who can throw a breaking ball for a strike”, but who feels confident enough in his breaking ball (not quite the same, because some don’t trust their pitch even though it’s good).
I think Bannister is missing out on cause and effect. Why does the count affect BABIP? I don’t think that it’s because the hitter needs to swing, as much as I think that it’s because pitchers vary their selections. In hitters’ counts they will throw more fastballs/sinkers (which produce worse BABIP) while in pitchers’ counts they will go to their secondary stuff.
The only thing is that I think it has more to do with what they feel they need to do rather than with what they are able to do. Not all pitchers throw their fastball for strikes that much more than their breaking balls, but most will automatically go to their fastballs when they need a strike. This will help hitters generate a higher BABIP. But then take a look at pitchers like Glavine, Litsch, Rogers and Timlin who beat average BABIP easily last season: they all throw their secondary pitches often, much more often than average, despite walking their share (and therefore falling into hitters’ counts relatively often).

tangotiger January 31, 2008 at 9:57 am

Granted all that, what happens if you take the MLB BABIP at each count, and apply that to each pitcher’s frequency at those counts?
That is, let’s say that Curt Schilling is the greatest pitcher in terms of getting into a pitcher’s count. His frequency distribution at the 0-2 count might be say 10% if the MLB level is 5% (all numbers for illustration only). Let’s say then that you apply the MLB BABIP level to his 0-2 count frequency.
Do this for all pitchers at all counts. What’s the resulting BABIP for all the pitchers? That is, how much does one side of the equation (controlling the frequency of counts) affect the overall BABIP. I will guess that 1 SD will be less than .005 points.

Ken Arneson January 31, 2008 at 11:21 am

This is the kind of stuff I’ve been waiting for sabermetrics to get to. Up until now, so much of sabermetrics has been about learning how things work from the GM’s point of view. I’m far more interested in how things work from the player’s point of view.
I heard Rick Peterson say recently that batting average (not sure if he meant BA or BABIP) is much lower down in the zone than up. So you could add pitch location as another dimension to this analysis. Peterson’s point was that you try to get ahead in the count with low pitches, because if the batter does put the ball in play, the average is lower. Then once you’re ahead, you have an extra advantage because of the count, and you can move the ball around elsewhere in the zone.

Jacob January 31, 2008 at 11:22 am

Cool stuff Pizza Cutter,
I wonder about this part though:
It

Pizza Cutter January 31, 2008 at 11:55 am

Tom, I just ran the analysis you suggest. (2003-2006, min 200 BIP) All expected BABIP’s were between a range of .295 and .300. Standard deviation (N = 929) was .00068.
Further I ran a correlation between actual BABIP and projected BABIP, done in this manner. The result was a measly r = .065.
The effect size is probably pretty small, but it’s there.

RollingWave January 31, 2008 at 10:05 pm

Brian Bannister is now suddenly the most popular ” not exactly the most awsome pitcher ever” pitcher on the net :P

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