A Quantitative Approach to Studying Release Point Consistency
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. And, thanks to MLB.tv and MS Paint, we're getting there.
Take this low-quality screengrab of Felix Hernandez, immediately prior to release:
The ball is a little fuzzy, but it's definitely there about to leave his hand. Just moments from now, it's going to fly past some unfortunate hitter's bat at 95 miles per hour, since all Felix ever does is dominate. But anyway, here's the really cool part: copy and paste that picture into MS Paint. Now move your cursor to the center of the ball. In the lower right corner of the window, there should be a set of coordinates - for me, it reads 124,37. Think of this like a set of coordinates on any generic x,y plot. The center of the ball is 124 units (pixels) from the left of the window, and 37 from the top.
I didn't know quite what to make of this the first time I noticed it, but after a little brainstorming, I realized that this could be an effective way to quantify both release point location and, with a large enough sample, consistency (it's the second one that I actually care about). So I devised a plan: collect a group of images of a pitcher much like the one of Felix above, enter the x,y location of the ball into a spreadsheet, and calculate 95% confidence intervals at the end to get an idea of his release point consistency.
For the purposes of this article, I decided to compare Mark Prior to Kerry Wood, since one is considered to have picture-perfect mechanics while the other...not so much. As far as further methodology is concerned, note that:
1) For each pitcher, I looked at 40 pitches - 20 from the windup, and 20 from the stretch. These are kept separate, in case either pitcher happens to change his delivery with runners on.
2) I only used images from one game so that I didn't have to account for differences in center field camera angle. Incidentally, both Wood and Prior's games took place on the same day - April 13th, a doubleheader vs. San Diego.
3) All pitches were chosen randomly.
4) To account for any differences in scale between images (since the camera has a tendency to zoom in and out), I chose reference points at opposite corners of the batter's box and adjusted accordingly.
5) Once I had 95% confidence intervals in pixels, I converted to inches by using the fact that a baseball is about three inches in diameter, and showed up as eight pixels wide on screen.
So, onto the results of this study:
Kerry Wood, Windup
The little red box represents the 95% confidence interval - based on the collected data, Wood would be expected to release 95% of his pitches from the windup within a box measuring 1.6 by 3.1 inches. The area of this box is 4.84 square inches.
Kerry Wood, Stretch
Same deal - based on the data, Wood should throw 95% of his pitches from the stretch within a box whose dimensions are 2.5 by 2.8. The area of this box is 6.95 square inches.
Although we obviously don't have a baseline for how much variation you'll see in a standard pitcher's release point, since this is a fledgling analysis, Wood's results compare favorably to Felix's, at least as far as pitching from the windup is concerned.
Mark Prior, Windup
Dimensions of the box: 3.4 by 5.0. Area: 17.0 square inches. That's more than three times the variability that we saw in Kerry Wood's release point, which I wasn't expecting. That's a huge difference.
Mark Prior, Stretch
That's more like it. Dimensions of the box: 1.6 by 2.3. Area: 3.52 square inches. Better than Wood, and better than Felix.
As far as Prior is concerned, something that may have influenced his final numbers is the fact that the game I looked at was his season debut, six days after throwing 87 pitches in a minor league rehab start. Looking at the spreadsheet, Prior's release point was getting lower as the game wore on, the gradual dropping of his arm being a possible sign of fatigue with his arm strength not yet at 100%. It is worth noting, though, that his considerable improvement with men on base in the April 13th game wasn't a fluke - opponents put up a .766 OPS against him with the bases empty last season, striking out in 23.1% of their plate appearances, but with men on their OPS dropped to .578 while their strikeout rate jumped to 32.8%. In 2005, Mark Prior was a much better pitcher with men on base, and based on the results of this preliminary study, it may have been because he was way more consistent with his release.
A study like this is going to have both its strengths and limitations. On the downside, it's a very tedious process, as you're going to lose the better part of an entire day if you're looking to gather any sort of meaningful results. It's also strictly two-dimensional, as it doesn't give a real good idea of how far forward the ball is being released. Short-arming the ball a foot in front of your throwing shoulder is going to make it do one thing, while a full-extension release will make it do quite another. The system could be improved by having a side-view camera providing z-axis location information, but until then we'll have to maximize the resources at hand. Additionally, it should be noted that this kind of investigation would be difficult to perform on someone who deliberately mixes up his arm angles, a la Jamie Moyer.
All that said, the biggest issue is how to properly interpret the data once you have it. Release point consistency is nice and all, but a consistently good release point and a consistently bad release point are two very different things that cause very different things to happen. Looking at the numbers, we can see that Kerry Wood's release point was more consistent with nobody on than Prior's, but Wood got slapped around while Prior was terrific. Why? Was Wood releasing the ball in a bad place all game long? I'm guessing that better pitchers will generally have more consistent release points, and that these kinds of apparent exceptions are considerably outnumbered by their opposites, but I can't say that with any degree of certainty.
Accepting that any new kind of study is going to have its kinks to smooth out, I think the potential upside here makes it worth pursuing further. Although it's possible to perform manually, one could conceivably automate the whole process, turning what used to be three hours of work into three minutes of watching a machine do everything for you. With the data that would provide, you could look at anything - release point consistency against right- and left-handed batters, correlations with things like walks and strikeouts...pretty much everything you can do with the stats we already have. Comparing a guy's consistency when throwing different pitches (fastballs, curveballs, changeups, etc.) could prove to be a pretty telling indicator of what he needs to work on in the bullpen. And those are just a few examples. Like with any metric, you could use this one in any number of ways.
Still, the most important thing here is: it's something. It's putting a number to what used to be educated guesswork. And as far as I'm concerned, doing that is always worth the effort.
Jeff Sullivan is the creator and primary author of the Lookout Landing Seattle Mariners blog. He's also a student at Trinity College, although nobody's sure where he finds the time. He can be reached by email at email@example.com.