Ender wrote:Pitchers and hitters both control their own BABIP in different ways. They just tend to regress towards their own statistical mean over time.
Ground Balls tend to have a higher BABIP, thus a GB pitcher will have a higher BABIP. Fly balls have a lower BABIP, thus flyball pitchers have a lower BABIP. Line Drives tend to have the highest BABIP. BABIP is also strongly affected by doubles. Speed players also tend to have higher BABIP. Finally BABIP is influenced quite a bit by defense.
There are certain levels that BABIP tend to fall into, if someone has lower than a .250 BABIP or higher than a .350 BABIP whether they are a pitcher or a hitter the safe money is on their stats being a fluke. If you have 3+ years of data on a player you should assume that their BABIP will regress towards their career rate.
I was going to make a post in this thread tonight, but Ender covered it. I'd also add that currently unpublished - but apparently reputable - studies reinforce the notion that pitchers actually have a degree of control over BAPIP - much more than what the McCracken study implied. Again, it's still a great stat to look at, but you shouldn't assume pitchers will always head toward .290 as I had assumed a couple of years ago.
Here's an article that I posted here from HBT that discusses this:http://www.hardballtimes.com/main/artic ... -at-babip/
Here's the conclusion from that article if you don't feel like reading the whole thing:
The game of baseball is saturated with luck—round ball, round bat. Uncertain outcomes are part of the game’s appeal. The BABIP phenomenon appears random at a large scale because we typically observe it in a way that is random when part of the information is hidden from the observer. In this article I’ve exposed some of the hidden information about the performances of two pitchers whose BABIP seems especially random. Although luck was certainly a factor, a large portion of each pitcher’s BABIP variance can be explained by non-spurious baseball regularities.
Chalking up BABIP as merely the result of chance outcomes does disservice to pitchers’ skill at preventing solid contact, which is the essence of pitching. Tossing a coin is chance, not skill, because you can’t control the result by how you flip the coin. Pitchers demonstrate skill in their control over the hardness of hitter contact, which indirectly but positively affects outcomes on in-park batted balls.
BABIP inevitably includes a random element because of the many unpredictable external events involved in a putout. After a recent loss to the Giants, Tom Glavine complained that “When their guys are hitting ground balls, I’m doing my job. I’m just not getting the results. There’s nothing I can say to make people understand when you go out there, do what you want to do, make the pitches and you don’t get the results.” That’s BABIP luck, the disconnect between pitching skill and batted ball outcome.
But some of the randomness in BABIP, as shown in the Zito and Greinke examples, amounts to a missing data problem. Ordinary baseball records omit pitch and batted ball attribute values, limiting our understanding of pitcher contributions to BABIP.