Some Research on BABIP Using PITCHf/x Data
The advent of PITCHf/x has created a contingent of DIPS apostates. Dave Allen has done a substantial amount of research on how to evaluate the quality of a pitch in terms of run value, and I'd like to use similar methods while focusing solely on BABIP.
First, heat maps for plate location, a topic which Dave has already researched. You can click on the image to enlarge it, but the gist is that pitchers who can jam batters or force them to put low-and-outside pitches in play will achieve low BABIPs, while pitches extending from down-and-in to up-and-away yield high BABIPs.
However, few pitchers actually have significant control over both the location of the pitch and whether or not the batter puts it in play. It turns out that the range of expected BABIP for pitchers based on the location of pitches put in play is 25 points, except for one outlier. The average BABIP in RHB vs. LHP matchups is around .310, and the maximum expected BABIP for such situations was .325. The second-lowest was Scott Feldman at .300, whose actual BABIP against lefties these last couple of years was .265. I think Feldman's cutter has successfully jammed lefties, and if you look at the RHB vs. LHP heat map, you can see a thick blue area up at the hands where lefties manage a BABIP of about .100.
Mariano Rivera's expected BABIP against LHBs based on pitch location came out to .270 compared to an actual BABIP of .225. No other pitcher had an expected BABIP below .290. Dave has written extensively about Rivera's ability to control his BABIP by commanding his pitches. I think Mo is unique in this regard. Maybe Greg Maddux in his prime was controlling BABIP by locating his pitches, but I think any pitcher who can consistently force batters to put well-located pitches into play is an exception.
Next, release points. You can see that those pitches thrown at extreme release points result in different BABIPs than pitches at traditional release points. Some of this is the nature of local regression not regressing, or "smoothing," enough for outliers, but nevertheless, I think sidearmers can legitimately control BABIP. The range in expected BABIP for pitchers when based on release points is three times as large as it is when based on pitch location.
Darren O'Day, Peter Moylan, Joe Smith, Justin Masterson, J.P. Howell, Brian Shouse, and Trever Miller all throw at low arm angles and I think that is why they have been able to control BABIP against same-handed batters. Hideki Okajima and Trevor Hoffman, while not sidearm, also have unusual release points against same-handed batters that I think have contributed to deflated BABIPs.
Sidebar: Dave jinxed Brett Anderson with his fantastic post on FanGraphs about Anderson's release points varying by batter handedness. Even though Anderson has switched to a uniform release point regardless of the batter, he still has had one of the ten most extreme differences in horizontal release points depending on batter handedness. Alberto Castillo shifts 2.5 feet on the rubber, while Ben Sheets, Hoffman, Fu-Te Ni, and Francisco Liriano are the only other pitchers who move approximately a foot in the direction of the batter. At the other end, Jose Contreras, Darren O'Day, Felipe Paulino, and Manny Corpas shift about a foot the other way. Turns out there's no evident relationship between how much pitchers move on the rubber and their platoon splits. I suppose if there was a correlation, you'd see more guys doing it.
The effect of release points on BABIP might actually be the effect of pitch movement. I've yet to break BABIP down by pitch movement, but I did find the average BABIPs on pitch types.
Part of the reason sinker/slider guys have large platoon splits is because those two pitches exhibit the largest BABIP platoon splits. Changeups and splitters show reverse platoon splits with regards to BABIP. The first group of pitchers found with the ability to maintain a sub-.300 BABIP was knuckleballers, and knuckleballs do indeed have the lowest BABIP of any pitch type.