Friday, April 18, 2008
Sequencing Pitches
Jnai at SOSH looks at how Beckett is sequencing his pitches:
The most striking pitch sequence information is in the Curveball. Check out the Curve - during the first half of the game, he never backs up a curveball with a second curveball, always going to either a Fourseamer or Cutter. In the second half of the game, it’s totally different: 50% of the time he throws a curve, it’s immediately followed by another curve.
One game only of course. Maybe he felt good about his curve. And, you also need to know the count, and to a smaller extent the batter and the game situation. Nonetheless, on the right track.


I have not read this piece yet, but this is one of the things I have been looking for a while now from the pitch f/x guys. Unfortunately, many of them (with all due respect, as I love their work) are spending WAY too much time worrying about classifying pitches (which matters none).
Of course, one game is worthless. One of the most important things a pitcher can do is to properly randomize his pitches, given the batter, count, game (score, inning, base/out state) situation, and perhaps most importantly, the quality of his own pitches.
My guess is that some pitchers (and catchers) are a little better than others at doing this, and that makes them, overall, considerably better pitchers. And of course the beauty of that, from a team, or teaching perspective, is that you can teach a pitcher (and catcher) to “sequence” his pitchers better. Every team should be analyzing their pitchers to see who could benefit from a “class” in game theory, randomizing pitches, and sequencing of pitches, depending on count, game situation, the batter, etc. In fact, I will volunteer, at no charge, to teach that class!
Of course, we need to start with a baseline of league average. And it is probably best to start with count. So, for example, we look at all 0-0 counts, and see how often each pitch is thrown by all pitchers combined. Then you probably break that up according to base/out state. On and on (certain batters, etc.).
It is absolutely critical for a pitcher to randomize his pitches in every count/game situation, so the batter has the least chance of knowing what is coming. Now, what those percentages are, given the count and situation, entirely depends on how good each pitch is for that particular pitcher, and how well he can command each one of those. For example, if a pitcher had a 105 mph fastball which was virtually impossible to hit, there would be little reason to throw anything else, even if the batter knew that. As far as commanding each type of pitch, for example, in a 3-1 count, the only reason that pitchers throw mostly fastballs, even if they don’t have a great fastball, is that they can’t get another pitcher over the plate often enough for it to be worth throwing that pitch, even if the batter is fooled.
A great clue that a pitcher is not good, for example, would be if his fastball were not that great in the first place, but that he threw 90% fastballs in fastball counts (meaning that he either is throwing them too often in those counts, or he can’t get his offspeed over enough or his offspeed pitches are so bad that it wouldn’t make enough of a difference if the batter were fooled by them).
In looking at pitch sequencing, we also have to be careful about testing for randomness. A pitcher could, say, throw 50% fastballs at a 2-1 count, but that does NOT mean that he is randomly throwing 50% fastballs at that count. It might be that he throws 70% fastballs to some batters and 20% to other batters, which may or may not be correct. Or, more likely (if he was not randomizing properly), it might be that he was throwing 30% fastballs after the last pitch was a fastball or a curveball, or whatever. A pitcher does not want to fall into the trap of following one pitcher with another, predictable one, like in Little League, where the pitcher tries to throw a curve, and bounces it 10 feet in front of the plate, and then never throws a curve on the next pitch no matter what the count.
Something similar to that would be the “setup” pitch in MLB. How many times have you heard the announcer, after a high tight fastball on a 0-2 or 1-2 pitch, say that it was a setup pitch, and the next pitch was going to be an off-speed away?
Well, that is ridiculous, of course, from the pitcher’s perspective. If the next pitch is going to be an off-speed, away, 85 or 90% of the time, then the batter simply knows what’s coming. It is not like a major league hitter is going to bail out on the next pitch just because the last pitch was high and tight. The idea of a “set-up” pitch followed by a predictable one 90% of the time, is ridiculous. Yes, after a high and tight pitch, you might be able to throw off-speed away a small percentage of the time more than you would normally, but not to the extent that anyone should “know” what is coming on the next pitch.
So is (ridiculous) the idea that a “smart” pitcher like Maddux can predict almost every pitch that the opponent pitcher throws, which you occasionally hear. (And of course, if he could, he would imply relay that info to his batters.) No person should EVER be able to predict what a pitcher throws to any degree of accuracy, other than, “There is a 70% chance he throws this, 20% that, and 10% that,” or whatever.
Anyway, pitch sequencing and game theory is a critical part of pitch f/x analysis. So far, the pitch f/x guys have been spending WAY too much time on esoteric (and some near worthless) things, like pitch classification, release points, spin rates, movement, etc., and not enough time on analyzing the things that make pitchers good or bad, so that we can evaluate pitchers in a much more reliable and granular level than their performance (in regular component stats).