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Batter_v_Pitcher
Wednesday, May 09, 2012
I love hearing pitchers talk about how they approach each confrontation.
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Aside from that, my inclination (back when I was young) is to figure out who Blevins is talking about here. I mean, how many 7-pitch innings with that left-right configuration could we possibly have in such a short career? And then since he gave us the sequence of counts, and that it was near the bottom of the lineup… So, you guys with your RetroDB just sitting there doing nothing, now’s your chance to flex your SQL muscles.
Monday, April 30, 2012
Willie Bloomquist, and Emil Brown and Vernon Wells. And that’s why we can say we don’t care about batter-pitcher matchups if you only have 40 or 50 PA.
Bill James has a good article about the reason that strikeout rates are what they are.
Strikeouts, over time, always increase, for this reason. Strikeout pitchers are more effective than pitchers who don’t get strikeouts, therefore teams are always looking for pitchers who can get more strikeouts, and also looking to deploy those pitchers they have in such a way that they will get the most strikeouts. This effect would be offset by the tendency of teams to look for hitters who don’t strike out, if hitters who did not strike out were also better hitters. However, hitters who strike out are generally not less effective than hitters who do not strike out; hitters who strike out are generally just as effective as or more effective than hitters who don’t strike out. Thus, there is no pressure to find hitters who don’t strike out. This asymmetry pushes strikeout totals higher over time.
His basic point is that in eras when high-K pitchers are so much better than low-K pitchers, there’s an underlying pressure to find more high-K pitchers. And in eras when neither high-K nor low-K pitchers dominate, then there’s no reason that more high-K or low-K pitchers will enter the league disproportionately.
Similarly, in eras when high-K hitters are much better than low-K hitters, then there’s a pressure to look for great hitters and not worry about their K rates. And in eras when low-K hitters are better than high-K hitters, then the league will try to avoid high-K hitters in the future.
And then he goes ahead and does his Bill James thing, and looks at this historically. It’s great stuff, and you should give it a read. He concludes:
High-strikeout pitchers in today’s game are dramatically more effective than low-strikeout pitchers, while high-strikeout batters are also somewhat more effective than low-strikeout batters. We are where we have always been, only worse. Strikeouts, in my opinion, will continue to go up.
Bill didn’t talk about it, but I wouldn’t be surprised if the shift toward shorter relief outings (and more relief innings) also contributes toward the high-K phenomena of the last few years. In my day, it was a huge deal when a pitcher threw 95mph, and it would earn Clemens a name like Rocket (though never having it usurped from Maurice Richard, and thankfully we didn’t have to deal with Rocket Ismael for too long). But now? How many dozens of relievers are there out there that average touching at least one 95mph pitch per outing? And how many more in the minors?
Pitchers are bigger today than in years past. Pitchers are stronger today than in years past. Pitchers today train more today than in years past. The end result? They’re going to pitch faster than in years past. (Don’t worry you golden agers… pitchers of yesteryear are still better because they locate better, have more movement, and sequence better. I have no idea if that’s true, but I don’t want to spoil your beliefs.)
So, how do we stop this train wreck? What’s the ideal rate of contacted balls per pitches thrown? For every 300 pitches thrown each game, how many of those do you want the batter to connect on (either as a BIP or as a foul ball)? 10%? 15%? 20%?
Here’s some crazy ideas… go down to three balls and three strikes? K rates would drop 20%… but walk rates will go up 78%! So, that’s not going to work. Any other ball-count combination will lead to ever fewer contacted balls.
What if a foul-pitch is a “let"… at any count (not just 2-strike counts)? Hitters may be more aggressive, knowing that he doesn’t get a strike if he can at least nick the ball.
I’d like to hear more crazy ideas from you guys. And, consider your position that “everything is fine, nothing to change here” already being duly noted. Thank you for that inertial comment.
Friday, April 27, 2012
Great job by Max in capturing most of the important ones. I’d also include the base-out situation. And nice to see that he confirms my earlier point about offense peaking at somewhere around 5-6pm, so great job on Max in doing that work!
Saturday, April 07, 2012
By , 09:04 PM
You’ve all heard that refrain from commentators (and sometimes players and managers) lots of times. And most of you know that it is a nonsensical statement, because it doesn’t really mean anything. It is usually just “post-hoc” whining after a pitcher throws a pitch and the batter gets a somewhat crucial or at least a run scoring hit. Often the pitcher misses his location on the pitch, so it “looks” like a “bad” pitch, or maybe the batter happened to be looking for that pitch or it appeared as if he did.
Today in the 4th or 5th inning of the Yankee, Tampa game, the Rays were leading 4-0with 2 outs, a runner on second, and David Price pitching. He threw a 3-2 change up (I didn’t see where the pitch was), the batter got a hit and the runner scored to make the score 4-1.
The radio commentators went on and on about how, “With a runner in scoring position and 2 outs, you have to throw your best pitch,” presumably his 96 mph fastball.
There are so many things wrong with that statement, besides the fact, that again, it is meaningless. I’ll touch on a few of them.
First of all, there is no one pitch in almost any situation that is the “correct” pitch to throw, as most of you know. Pitching involves game theory, or making the batter guess, as much as possible what pitch is coming. Rarely is it correct to throw a certain pitch (and location) 100% or 95% of the time. If it is, then the batter (presumably) knows that that pitch is coming, in which case it is probably not going to be that effective (it is no longer a pitcher’s “best pitch"). There are exceptions, like 3-0 counts to pitchers and weak hitters in certain situations, or a pitcher that primarily throws one pitch, like a Rivera (his cutter is extremely effective even though the batter knows it is coming). But, by and large, most pitchers, including Price, must throw all or some of their pitches a certain percentage of time, randomly, in almost all situations whether the count is 0-2 or 3-2. Obviously at 0-2 most pitchers are more likely to throw an off-speed pitch and at 3-2, they are more likely to throw the fastball, depending on the score, inning, outs, and the batter.
In this particular case, or with a runner in scoring position, a base open, and 2 outs in general, the announcers had their “logic” (whatever logic there is in their statement) exactly wrong. If you are mostly a fastball pitcher, while it is likely to be correct to throw the fastball with a 3-2 count, it is LESS likely that you would and should throw the fastball in that exact situation, 2 outs, a runner in scoring position, and a base open. The reason should be obvious to anyone who played baseball or watches baseball and has half a brain (and these guys do this for a living). The ONLY reason you are more likely to throw a fastball with a 3-2 count (or 3-0, 3-1, and 2-0), in general (again, it depends on the batter and the pitcher’s repertoire, among other things), is because the off-speed pitch is more likely to result in a ball and thus a walk. However, in that situation, the gap between the walk and the hit is large, such that the fastball is least likely than at other times with a 3-2 count.
So, their logic and statement of, “With 2 outs and a runner in scoring position (and a base open, which they did not mention),” is completely wrong and completely backwards.
Finally, there really is no such thing as a pitcher’s “best pitch,” at least in context. In any given situation, game theory tells us that all of a pitcher’s pitches must have the same win value. We have discussed this before and many of you have probably read about this before. In case you are not familiar with this concept, I’ll give you a brief primer/illustration.
Let’s say that you are a fastball/slider pitcher only. And let’s say that in a vacuum (no game context), your fastball is much better than your slider. There are many pitchers like this. What this means is that if there were an equal chance of the batter getting either pitch or you told the batter what pitch you were throwing and the situation was neutral (the win value of all offensive events were league average), the fastball would yield a better run value (for the pitcher) than the slider. So, you could say that the fastball was this pitcher’s “best” pitch.
So why not throw it all the time? For three principle reasons: One, in certain situations where the value of the offensive events were not league average, the win values of the two pitches would not be the same. For example, in the situation above the win value of the walk goes down and the win value of a hit goes up. Those values actually change all the time, with the score, count, inning, runners, etc.
Two, obviously the strengths and weaknesses of the batter will change the value of those pitches too.
But, let’s say that in a certain situation, the fastball is still the “best pitch.” Again, why not throw it all the time in that situation? Remember I said that it is rare that any one pitch is correct 100% of the time. Why is that? That does not seem to make sense. That is because if it were correct to throw a certain pitch all the time in any given situation, the batter would know that. So, the value of that pitch would include the fact that the batter knows it is coming. We all know that there are very few pitchers who can throw a certain pitch effectively when the batter knows it is coming.
So what happens in this confrontation? Well, when the pitcher throws his “second” or “third best” pitch, it becomes a surprise. So, even though in a vacuum, it is not a great pitch, it is going to have a nice win value to the pitcher if the batter is sure that he is getting something else. Typically, if a batter thought that he was getting a fastball at a 3-2 count, and he gets an off-speed pitch in or near the zone, he is not going to be very successful, and thus the value to that pitch is going to be great, perhaps more than the value of the fastball, since the batter knows that the fastball is coming (if indeed the fastball still has greater value when the batter knows it is coming and will be completely surprised at an off-speed, then the pitcher becomes a one-pitch pitcher, in which case this analysis is moot).
So now, if the surprise off-speed is a “better” pitch than the “known” fastball, the pitcher should throw the off-speed more. What would happen if he did? The batter is now less surprised by the off-speed but more surprised by the fastball. So the value of the off-speed goes down and the value of the fastball goes up. As you can probably guess, what happens is that the pitcher throws more and more off-speed until the value of both pitches is exactly equal! That is called the Nash equilibrium and that is why there is no such thing as a pitcher’s “best pitch” in any given situation once context and the percentage of time each pitch is thrown is taken into consideration.
I suppose you can call the pitch that is thrown with the most frequency the “best” pitch, but you MUST keep in mind that all pitches in that situation will yield exactly the same win value (unless the pitcher is making a mistake in utilizing the precepts of game theory, which is entirely possible).
Keep in mind that if you were to check whether pitchers are indeed mixing up their pitches optimally such that the win values of all pitches are equal in a certain situation, you must bucket the pitches into situations and then check the win values of each pitch in each bucket/situation, and see if they are equal. The “situation” should include the identity of the batter, or at least similar characteristics for the batter.
Overall the win values of all of a pitcher’s pitchers will NOT be equal. A simple example will explain why. Let’s say that a pitcher’s off-speed pitch is his dominant pitch. He is not that accurate with it but it is so good that when it is in or near the zone, the batter almost never gets a hit.
And let’s say that a very weak pitcher is at the plate and the count is 3-0. Let’s say that this is the ONLY time that the pitcher should throw the fastball and increase his chances of throwing a strike. The assumption is that no matter what pitch is thrown, if it is in or near the zone, the batter/pitcher is likely to make an out when he swings or it is likely to be a called strike (the batter/pitcher will obviously be taking anyway) . You can see how the otherwise bad fastball might be the correct pitch a high proportion of the time (maybe even 100%, but we will assume less than that).
Now, if we look at this pitcher’s pitches for the year, we will see 99% off-speed and 1% fastballs (only on 3-0 counts versus weak hitting pitchers). Will the value of all the fastballs and off-speed pitches be the same? Not necessarily and probably not. But, the value of the off-speed and fastballs in this exact situation, a weak-hitting pitcher and a 3-0 count, should definitely be the same.
Monday, April 02, 2012
By , 05:32 AM
Last night, Jimenez threw at Tulo and hit him in the elbow. Here is the video and the story:
http://espn.go.com/mlb/spring2012/story/_/id/7762625/ubaldo-jimenez-cleveland-indians-drills-troy-tulowitzki-colorado-rockies
Jim Tracy, the Rockies’ manager and Jimenez’ former manager said this:
...the most gutless act I’ve seen in 35 years in the game, that’s what I saw.”
Amazing that in 35 years of baseball, he’s never seen a pitcher throw at a batter. Just amazing. Unless there was something particularly “gutless” about the beaning. It looked like your run of the mill beaning to me. Maybe he meant that Ubaldo didn’t throw at his head. That would have been “gutsy” I guess. Throwing at someone’s midsection is for pussies.
That’s exactly what I witnessed,” Tracy said. “He intentionally threw at him, he should be suspended. I’ll be very disappointed if he doesn’t get suspended because he deserves to be suspended.”
I know it’s hard to believe, but he saw it with his own eyes. He actually intentionally threw at him. Can you imagine the nerve? He might have hurt him. Not only should he be suspended, but he should be banned from the game! Oh, the inhumanity!
Disclaimer: I do NOT advocate intentionally throwing at batters, although I don’t think it is that big of a deal. It is just that don’t the managers often order this? TLR used to, didn’t he? And if you DON’T throw at a batter and your teammates think he deserves it (by maybe running around the bases slowly or flipping your bat after a HR), isn’t THAT considered gutless? (I am not suggesting that Tulo did something to deserve it, although Ubaldo must have thought so.)
Saturday, February 04, 2012
By , 06:48 PM
I downloaded Bill James Baseball IQ onto my iphone (I don’t think it is available on droid phones, but I’m not sure). Here is the web site for the app on Acta Sports:
http://www.actasports.com/titles/bill_james_baseball_iq_app/
It is pretty cool. You can read a description and see some screen captures on the above site, but basically it allows you to see heat maps and color maps of batters and pitchers (in all combinations, counts, situations, etc.) for K zone, batted balls, pitch type, etc.
Best of all, the app is free! Seems to me that they could have charged for this one, but I know nothing about the best way to make money from apps. It also seems like they could use these graphics more often on TV broadcasts.
Anyway, give it a try and see what you think…
Thursday, January 26, 2012
By , 04:36 AM
It is generally accepted in the sabermetric community that the AL is a better league than the NL, at least for the last several years. This is evidenced by the fact that the AL has a large advantage in IL games, although at least some of that edge could be something other than overall “talent”, although this is not likely and several people, including myself, have found little or no inherent advantage to the AL in IL games (e.g., the NL teams do not have any DH’s, so they have to juggle their lineup in AL parks, on the other hand, in NL parks, AL teams have to sit their DH’s or juggle their lineup, perhaps putting a bad defender - their DH - in the field, the AL pitchers typically are poorer hitters than the NL pitchers, etc.).
Read More
Thursday, October 27, 2011
Colin says:
Once we have that expected value, we can also look at the TAv from that batter-pitcher matchup from all previous seasons. We can run this data from 1951 through 2011, giving us sixty years of data and over 16,000 data points to look at.
Using a technique known as ordinary least squares regression, we can see how well our expected TAv and our prior batter-pitcher matchup TAv predict future batter-pitcher matchup TAv. After controlling for whether the batter has the platoon advantage, what we find is that our log5 estimate of the outcome of a batter-pitcher matchup is 67 times more predictive than the batter’s past performance against that pitcher. Now, that’s slightly better for the batter-pitcher matchup data than we might have expected; there were on average 78 times as many PA for the log5 expectation as there were for the batter-pitcher matchup. (Since there are both batter PA and pitcher PA against used to generate the log5 expectation, I used what’s known as a harmonic mean to come up with the PA totals for the log5 expectation.)
We can conclude that one plate appearance against a specific pitcher is slightly more predictive than a plate appearance against any pitcher at all. But that effect is dwarfed by the number of plate appearances a batter makes against all pitchers
...
But what about cases where a batter has really owned a pitcher in the past—just utterly demolished him? Let’s restrict ourselves to cases with a prior TAv of .520 against a pitcher, or twice the average TAv. (By happy coincidence, that’s just about two standard deviations above the average, for those of you who care about such things.)
Historically, these have been more predictive of batter success than ordinary batter-pitcher matchups. But they are still dwarfed by the predictive power of our log5 expectation, by a factor of about 24 times. A manager is likely doing himself a favor if he puts a guy with that kind of extreme success in the lineup in place of a batter who’s otherwise reasonably close in ability. However, such cases are extremely rare, and even in these extreme cases, the whole of a batter’s historic performance (combined with knowledge of the platoon advantage) is still a much better gauge of how a batter will perform against a pitcher going forward.
...
The data isn’t telling us that batters can’t pick up certain cues about a pitcher, or that a pitcher’s repertoire is equally suited to all batters. However, 10, 50, or even 100 plate appearances aren’t enough to tell us whether what we’re seeing is one player with a special edge against another, or simply a small-sample-size fluke, and there’s too much at stake for La Russa and Washington to let themselves be overly swayed by such statistics to the detriment of their teams.
Thank you Colin for doing the work!
Moral of the story: take your noses out of your spreadsheets and index cards, and watch the baseball game instead.
Colin: I’d like to know the regression equation, of how much to weight the batter-pitcher matchup and how much to weight the log5 expectation.
Monday, October 24, 2011
Someone asked me about small sample size. I answered as follows:
==========================
It’s a fair question to ask. Basically, the choice is presented as follows:
1. Octavio Dotel has faced Ian Kinsler 8 times in his career (and got him out 100% of the time).
2. Octavio Dotel has faced 3800 MLB batters in his career (and got them out 70% of the time).
Therefore, how much weight do we place on the 8 Kinsler PA, compared to the 3800 non-Kinsler PA? Ian Kinsler does have something in common with everyone else: he’s a MLB player. That is a huge commonality we have. In that group of players are guys who are better hitters than Kinsler, but also quite worse than Kinsler.
So, we can limit the 3800 batters if you want down to the say 1000 batters faced that are about as good as Kinsler.
Now our choices become:
1. 8 PA against Kinsler
2. 1000 PA against guys as good as Kinsler is a hitter
The choice however is not either/or. You can overweight the Dotel-Kinsler matchups, and I have NO PROBLEM with doing that. How much do we want to overweight that? Two times? Five times? Ten times? Give me a number.
So, let’s say that Dotel-Kinsler tells us 10 times as much as Dotel-GoodHitter does in terms of giving us an estimate. The 8 actual PA becomes 80 weighted PA. You still have 80 weighted PA to add to the 1000 other PA in the pool. That 8 actual PA is still only 7% of the conversation when weighted 10 times.
Not to mention the reality is that if you study it, as we have in The Book, the matchups are simply not predictive. This is not a matter of opinion. It’s a matter of fact.
If someone ignores fact because they believe in their gut they are right, Colbert coined the word “truthiness” for that. I have no argument against truthiness. By definition, those who argue based on truthiness can never be wrong.
Tom
Friday, October 21, 2011
Note: You may feel you are walking in the middle of a conversation. You can take a step back and go here.
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Ok, given that we accept that there are pecularities with the 9th inning, bottom half, tied game scenario (unintentional-intentional walks; fielders de-aligned from norm to either defend against the bunt, to guard the line, or to play the OF shallow), I’m now going to focus only on the tied-game scenarios for all innings.
So, here’s the A_empty group (as a reminder, all bases empty situations, regardless of outs), for tied games, broken down by inning (1st, 2nd thru 8th, 9th, extra innings):
topBot inn obp babip wBABIP diff
0 1 0.333 0.297 0.297 0.000
0 2.8 0.325 0.289 0.289 0.000
0 9 0.326 0.295 0.289 0.006
0 10 0.336 0.302 0.298 0.004
1 1 0.360 0.310 0.309 0.001
1 2.8 0.337 0.298 0.298 (0.001)
1 9 0.349 0.313 0.307 0.006
1 10 0.361 0.315 0.310 0.005
First 4 lines is top of inning, and next 4 is bottom.
Our “control” group is basically innings 2 thru 8. As we can see, at home, you get a 12 point advantage in OBP, 10 point advantage in BABIP, and since wBABIP=BABIP that means the rate of extra base hits per in-play hit remains constant (i.e., excludes HR).
wBABIP is BABIP but with extra weight placed on extra base hits and less weight placed on singles.
As we saw in the other thread, the massive difference in OBP in the 9th inning is explained by the walk rate and singles rate. The extra innings carries this issue as well. So, any analysis of tied games in the 9th inning has to be able to handle these parameters, otherwise you are going to introduce a bias.
The interesting one though is the 1st inning. We ALSO see a massive gap in the 1st inning, with a 27 OBP point gap at home than on the road. As we said, 12 points of that is the home field advantage. The K and BB rates are simply hugely different, as it plummets to 14.5% K rate in the bottom half (compared to 17.3% in the top half) and jumps to 10.0% in BB+HB rate in the bottom (compared to 8.7% in the top). It might be clearer to see it as a K to BB+HB ratio: 2.00 in the top half and only 1.45 in the bottom half.
My original speculation was that the road pitcher, being the second pitcher to take the mound, simply hasn’t found his mound groove. I wish I would have included one other parameter in my dataset (which I can do on the weekend): handedness of pitcher. If both pitchers are right-handed, they may “compete” for the mound groove. If they were opposite-handed, then it might make it easier for each to take their own side. Just a thought, one that I will also leave with the PITCHf/x-ers. Anyway, someone asked about day/night splits maybe. So, let’s see.
Here are the splits by day:
topBot inn obp babip wBABIP diff
0 1 0.327 0.292 0.292 0.000
0 2.8 0.321 0.286 0.286 (0.000)
0 9 0.325 0.300 0.294 0.006
0 10 0.338 0.306 0.302 0.004
1 1 0.356 0.308 0.307 0.001
1 2.8 0.335 0.294 0.295 (0.001)
1 9 0.349 0.309 0.302 0.007
1 10 0.362 0.315 0.311 0.003
The control group (innings 2 thru 8) shows a 14 point home advantage for OBP and a 8 point advantage in BABIP. There’s no extra base hit advantage.
Innings 9 and extra innings shows the same massive gap, as explained earlier.
Inning 1 shows a 29 point OBP advantage at home, and 16 point advantage on BABIP, numbers that are a bit bigger than overall.
Here it is at night:
topBot inn obp babip wBABIP diff
0 1 0.335 0.299 0.299 0.000
0 2.8 0.327 0.291 0.291 0.000
0 9 0.326 0.292 0.287 0.005
0 10 0.335 0.299 0.296 0.004
1 1 0.361 0.312 0.310 0.001
1 2.8 0.338 0.299 0.300 (0.000)
1 9 0.349 0.314 0.309 0.005
1 10 0.360 0.315 0.309 0.005
The gap is somewhat smaller at night in terms of home advantage. The control group shows a 11 point OBP advantage and 8 point BABIP advantage. The first inning shows a 26 point OBP advantage and 13 point BABIP advantage.
Across the board, the day time advantage is an extra 3 points in OBP. I would not be surprised that if you look at historical home/away splits, that the day splits show a slightly higher home advantage.
Anyway, let me now focus on the B_2out grouping (all PA with runners on base and 2 outs). Maybe by this point, the mound familiarity starts to come into focus (and maybe not using the windup helps too in combating the mound effect).
topBot inn obp babip wBABIP diff
0 1 0.354 0.292 0.294 (0.002)
0 2.8 0.336 0.290 0.290 (0.000)
0 9 0.327 0.281 0.277 0.004
0 10 0.333 0.294 0.290 0.003
1 1 0.372 0.305 0.307 (0.002)
1 2.8 0.350 0.293 0.293 (0.000)
1 9 0.337 0.289 0.269 0.019
1 10 0.361 0.307 0.286 0.020
Control group shows a 14 point OBP advantage and 3 point BABIP advantage at home. The first inning effect shows only an 18 point OBP advantage at home, but 13 point BABIP advantage. The OBP gap between 1st inning and control group is no longer very wide.
I think the next thing to look at is simply by 1st, 2nd, 3rd batter in the game. I’d bet we’ll see a huge gap in OBP when comparing the 1st batter’s first plate appearance in games at home and on the road. And then a progressively smaller gap for the 2nd batter faced in the game, and 3rd batter. And that by some point, maybe the 2nd inning, the gap remains static.
If it’s not due to the mound, then perhaps this effect is that the road pitcher has to sit around waiting to pitch in the 1st inning. The home pitcher gets to pitch right away after his mound session. Maybe the solution is that the road pitcher should warm up during the top of the 1st inning even?
Wednesday, October 19, 2011
An interesting observation, that when the chips are down, the pitcher will go with what he’s good at:
DL: When you’re studying video, do you pay particular attention to how a pitcher attacks hitters who are similar to you?
KJ: Oh, yeah, although I look at all lefties. And I always check with guys in scoring position, because a lot of times that will tell you what a pitcher wants to throw, and what he feels comfortable throwing.
There are of course reasons that the pitcher will do that beyond that this is what he’s most comfortable with (runner on 3B, less than 2 outs, pitcher will pitch for a K, and batter will swing to avoid K). In any case, good idea to see a pitcher’s repertoire by the 24 base-out states.
Friday, September 09, 2011
This rarely happens, and when it does, no one swings at it:
Going back to 2009, PITCHfx has identified 83 first pitches as curveballs, or 0.6%. Of those 83 first-pitch curveballs, batters have swung at just three of them. Of those three swings, two have resulted in fouls, and one has resulted in a home run - Ichiro’s swing, last night.
...
That’s a first-pitch curveball, a little out of the zone. Not only did Ichiro swing at it - Ichiro made contact, and obliterated the pitch into the right field stands. Said Hochevar:
“The first-pitch curveball to Ichiro, I don’t even know what to say about that one,” Hochevar said. “The [first pitch] of the game—it was a good pitch and he hit it eight rows deep. I’ve never seen it, I’ve never had it happen. I normally don’t throw first-pitch curveballs in a game, but what do you do?”
Wednesday, September 07, 2011
Love the interview.
DL: Are you a believer in protection?
KS: Yes I am. Most definitely. I could sense what was happening as soon as they started batting Eddie behind me. He was younger and a little more aggressive than I was, and he was trying to make a name for himself. And he was doing so. He was in the process of building a Hall-of-Fame career. Pitchers had a choice. We were both switch hitters and they could either pitch around me and go after him, or they could try to get me and be careful with him. It was sort of a “pick your poison” sort of thing.
I believe him. And we’ve shown as much that protection exists. The question is if the change in pitching to a hitter because of protection makes the batter, OVERALL, more effective. There’s a shift. But, is that a shift that overall has an impact? And the current research says: no.
Tuesday, August 02, 2011
SABR presentation by Patrick Kilgo, Hillary Superak, Lisa Elon, Mark Katz, Paul Weiss, Jeff Switchenko, Brian Schmotzer and Lance Waller.
Here are their conclusions. I’ll post their file on my site tonight. You can also read from Phil.
Umpires absolutely favor veterans with respect to false strikes
Umpires most likely favor veteran pitchers with respect to false balls. No evidence of benefit to veteran hitters
“Good” pitchers see the most preferential benefit
No evidence of rookie hazing
SABR_Umpires_Talk.pdf (pdf)
Monday, July 11, 2011
Phil continues his look.
Conclusion: from 2000 to 2009, home teams were somewhat more likely to get a strike call in higher-leverage situations than in lower-leverage situations. This is significant only at approximately p=0.1.
Wednesday, June 22, 2011
Fantastic stuff. I’d quote the whole thing really. This part I particularly liked:
DL: Why did you have so much success against Bruce Sutter [8 for 20, 4 home runs]?
RS: His split-finger fastball came into my hot spot. I was able to recognize that pitch, and also anticipate it, coming down and hard into me. With him, I would swing where the ball would end up, which is very unnatural. That’s what made him so tough; if you swung at the pitch where it was, by the time your bat head got there it was too late. The ball would have disappeared. I was able to anticipate where the pitch went, which was in my hot spot.
Mike Bossy would say something similar. While the goalie was angled to one side, Bossy was in the slot in front of the goalie. When he’d get the pass, and he’d have to one-time it, he would shoot the puck directly at the goalie, because he knew the goalie would have to move from his angle to face him straight on. So, he anticipated that the goalie would get into the right position (for everyone else except Bossy), and thereby leaving the position he was previously in.
So, this part also captured me:
RS: I faced them both a lot, and Darling mixed his pitches up. He was effective against an aggressive hitter, an aggressive fastball hitter, because he’d throw his split-finger fastball — a forkball is what he had — which to me appeared to be a fastball. I considered myself a fastball hitter, and when I was ahead in the count I was aggressive on the fastball. I tried to put those balls in play hard somewhere. He knew me as a hitter and would pitch me backwards a bit. He was a guy I had to battle, so I’d take a single up the middle if I could, or a single to right field.
That’s game theory right there. While Sandberg would get success with other pitchers by anticipating, Darling knew that’s what Sandberg would do, so he had to “pitch backwards” against him.
Cue the Youtube video of Princess Bride.
Friday, June 10, 2011
Every matchup has a specific and true mean. God herself would establish that specific and true mean at that specific point in time-space with zero level of uncertainty. Pujols at Busch on July 3, 2011 against Doc and God knows that he can’t handle an outside cutter well, and the next pitch is going to be telegraphed by Doc as an outside cutter? God says that Pujols will contact that pitch 23% of the time (if allowed to replay in that time-space an infinite number of times) with 0 level of uncertainty.
But what about humans? If Pujols v Doc has an expected contact rate of 70% any time Pujols swings (with a certain level of uncertainty, say 10%), then how much a better mean estimate can we get in more specific situations (we find more data about Pujols and or Doc and or Busch and or the weather), and how much more can we reduce the uncertainty level?
Friday, June 03, 2011
I appreciate that the authors of this paper were able to figure out that “at counts” are silly almost all the time (pdf). They realize that the performance “at counts” requires us to know that the plate appearance has ended. It seems an obvious concept if you think about it, but most people won’t think about it. So, they get lulled into thinking that “at counts” mean something that they really don’t. Plenty an analyst has fallen into this trap.
Now, the solution is to instead look at “through counts”, which means, given that you are at an 0-1 count, what happens by the time the plate appearance has ended? Virtually all the time you need to talk about counts, you want through-counts. The linear weights (or wOBA) by count is based on through-counts.
The authors of this paper however instead talk about “hits per strike” (and hits per contacted ball). These are partial views to the performance. Without talking about how often they take a called ball, the discussion will always be incomplete.
Therefore, whenever you see one of these papers or articles, and the central point is not about through-counts, then a large hole in the analysis will exist.
Glove-slap: Peter.
Friday, May 27, 2011
Fascinating stuff, from our favorite saber-interviewer:
DL: What do you see when the ball comes out of the pitcher’s hand?
AG: I see rotation. I can pick up on what the pitch is as soon as the pitcher lets go of it. Most of what you see is innate. If you ask some of the great hitters, they won’t all say the same thing. Some just see balls. Some guys see speed out of the hand. I can’t recognize speed, but I can recognize rotation. Some guys can recognize speed but not rotation and some guys just see a ball and swing. They just let their abilities take over and that’s not something you can teach.
If he can’t recognize speed, then does that mean that Gonzalez has a harder time against a fastball-changeup pitcher, as opposed to a fastball-curveball pitcher?
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