We know an awful lot about pitchers. We know how hard they throw, how many batters they strike out, what kinds of pitches they have, and whether their deliveries are fluid and easy or violent and rough. This is all objective and indisputable information that has a lot of value when it comes to projecting a pitcher's future health and success.
One thing we don't know much about, though, is the consistency of a pitcher's release point. The fact that we don't have a good way of measuring what's arguably the most important part of being a good pitcher is one of the more ironic twists of modern analysis. Sure, you can look at a bad curveball and say "he let go too early" or "he held on too long," but that's just one of a few thousand pitches that the guy's going to throw all year, so it doesn't tell you very much. What we need is a way to quantify the extent to which release points varies over a larger period of time for different pitchers.
I took a couple courses on digital signal processing in college. We worked mostly with audio, which only has one dimension, but many of the same techniques would likely work with two-dimensional images.
With the right person doing the programming, you could analyze each photo, normalize for zoom and pinpoint the location of the ball automatically. Not sure how you would normalize for differing CF camera angles from game to game, but it could probably be done.
Separately, I wonder how the study might be affected by the pitcher’s positioning on the rubber? Jeff, if you read this, did you notice whether the pitchers tended to start from the same spot on the mound over the course of a game?