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...given Fast's results over one season's worth of data - veyr suggestive they are indeed - we need to figure out if there are other reliable predictors of BABIP in the common statistics (we don't have his velo data to work with...and even if we did, it doesn't go back beyond 2008).
But this is actually a bit more complicated than it sounds, because the park can influence BABIP and HR/Fly without the speed of the ball off the bat being any different.
So the problem I have is that I can't park adjust for K, HR, BB, and BABIP because I can't assume that equal pitching was in each park in equal measure when it comes to controlling for those factors.  The standard ratio method of park factors is demonstrably a false approach, which is the entire reason I pursued a linear matrix solver approach to park factors, umpire factors, league scoring contexts and strength of schedule.  So I need some kind of multivariable linear solver for this problem too...I need Fiato/Souders matrix solutions for HR park factors, K park factors, BB park factors, and BABIP park factors that account for the variability in the pitchers and batters facing each park.
As I do not have time to do that...my best efforts will not be very conclusive, I fear...but what I CAN do is control for the park...or at least control for non-extreme parks in the +/- several points of park HR factor...under the assumption that HR, K, BB, and BABIP will not vary much in the "standard" parks and thus ignore park effects entirely for now.
This is what I'm going to have to attempt here while I have a few days off for Thanksgiving.