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Friday, December 23, 2011
This was from Tippett, and a followup.
In a blog entry the next day, we offered the opinion that this was a poor decision with the league leader in strikeouts on the mound. We didn’t get into the details then, but we will now.
In last year’s essay, we pointed out that 11.4% of all plate appearances in double-play situations result in a ground ball double play. Not all of these plate appearances see the batter put the ball in play, though, and when we subtract the walks, hit batsmen, and strikeouts, it turns out that 15.4% of balls in play produce GDPs.
If you DON’T send the runner on a 3-2 pitch, the chance of getting a ball in play that produces a GDP is a little over 5%. That’s because 15% of balls in play result in a GDP and batters put 3-2 pitches in play about a third of the time.
So what are the chances of a double play if you DO send the runner on a 3-2 pitch? Last year, we estimated that probability at about 5.5% based on the frequency of strikeouts, a typical caught stealing percentage, and the small chance that a ground ball up the middle will produce a GDP even with the runner going.
In other words, the overall averages showed a rough balance between sending and not sending the runner, leaving the decision to an evaluation of the skills of the specific players involved.
But that was for the case where the only runner was on first base. What about the first-and-second situation?
Wednesday, December 21, 2011
Mike does a great job at identifying situations that are disproportionately hit and run situations:
Finally, we arrive at the definition used for a hit-and-run situation in this study: (1) runner on first, bases not loaded, (2) none or one out, (3) a ball-strike count of 0-0, 1-0, 2-0, 1-1, or 2-1, and (4) the team leading or trailing by four runs or less. If the runner went on the pitch and the batter swung in such a situation, I will consider it a likely hit-and-run play.
And gives us these results, among many others:
Teams that attempted the hit-and-run play scored 0.11 runs on the play and 0.69 runs in the remainder of the inning on average, compared to 0.17 runs scored on the play and 0.70 runs in the remainder of the inning by teams that did not attempt the hit-and-run play in hit-and-run situations.
There are a few biases here that need to be controlled, before we can compare the .69 to the .70 (i.e., a wash). Later in the article, Mike does an excellent job of reviewing most of them, and adjusting for them. What he does there is exactly the kind of thing a saberist should be doing: identifying reasons for bias, and adjusting for it, as best you can.
He ends up with this huge finding:
Thus, the advantage for attempting a hit-and-run play during 2003-2011 appears to be about .061 runs on average.
That is a much larger number than I expected when I embarked on this research. I have attempted to remove as much of the selection bias as I could reasonably identify. It is possible that I have overlooked some bias or used a mistaken assumption, but every direction from which I came at the analysis pointed to the hit-and-run being a positive offensive play in most circumstances in which it was attempted.
I agree that that number seems simply too high. Adding .06 runs on one PA is the equivalent of one of the best hitters in baseball. Basically, it’s too big to be taken as the final number.
One bias that he noted early on, but that it doesn’t look like he adjusted for, is that a hit and run is in neutral or moderate hitter’s counts. So, we expect more runs on that basis. This will probably account for .03 or .04 runs of bias. But, Mike says:
The ball-strike count also plays a role. The more favorable the count is to the hitter, the less likely that the batter will be forced to swing at a pitch he does not like. On the other hand, the same is true if the batter is not protecting the runner, and in that case, he may be more selective and take more powerful swings.
But his chart ends up with actually a net benefit for the hit and run. Which is confusing me.
In any case, it’s a great piece of research, and hopefully will inspire more people to take up the cause. You really couldn’t ask for any more for an initial piece of work. It was a real pleasure to read.
Tuesday, December 20, 2011
If you are going to compare to a baseline, you CANNOT compare to zero. You have to compare to the actual hitter’s true talent level. It’s not the average hitter that bunts, but a below average hitter. So, we EXPECT to see a negative win value relative to the average hitter, not only on bunts, but on non-bunts too.
Glove-slap: Mike.
Friday, December 16, 2011
Dewan has some data for us.
Batting Average by Zone, 2011
Non-Sacrifice Situations
Zone 1 .246
Zone 2 .412
Zone 3 .164
Zone 4 .139
Zone 5 .520
Zone 6 .720
Overall .438
So, a .438 batting average if bunting for a hit, with no one on base, or runners on base and two outs. What’s the breakeven point?
Well, a single with no one on adds around +.25 runs, while an out costs .16 runs. That gives us a break-even point of .390. That is, if you bunt for a hit with no one on base, and you have a .390 batting average, you are a league-average hitter.
Players are bunting for a .438 average, which means they are picking their spots pretty well, bunting when they think they have a .375 to .500 batting average.
***
Note that with a runner on base and 2 outs, the batting average breakeven point shoots way up. Here are some numbers (all with 2 outs):
runner on 1B: .500
runner on 2B: .670
runner 1B/2B: .580
As you can see, only the absolute very best bunters should EVER bunt with runners on base and two outs. Either that, or the fielders have to be playing very deep.
So, I’d like to see those numbers, of bunt batting average with no runners on base, and with runners on base and 2 outs. We should see that .438 be pretty different, something like .420 with bases empty and at least .500 with runners on base.
Thursday, December 01, 2011
By , 11:55 PM
http://www.nesn.com/2011/12/bobby-valentine-plans-blending-sabermetrics-with-baseball-experience-to-make-decisions-with-red-sox.html
I could end up being wrong, but I have a feeling that Bobby V may be the first manager we will see that actually uses correct sabermetric principles. I think that the only reason Boston would hire such a controversial manager is for that reason - they finally found a manager who is astute and progressive enough not to think that he knows everything about baseball and is willing to throw away half of what he thinks he knows. I have a feeling that he is going to work very closely with James, Tippett, and the rest of the Sox’ sabermetric department, and that we will see (or not see) things that we have never seen on a baseball field, other than fake noses and glasses…
Friday, November 18, 2011
MGL’s terrific guest piece at BPro:
In any case, it is easy enough to see how these starters pitched after they were allowed to bat. Remember that, on average, the starter pitched another 1.42 innings after his stint at the plate. What was the average TAv against over these 1.42 innings, again, after removing all pitcher batting? Remember, these were .258 pitchers for the season who had pitched to the tune of .221 so far in the game. They were also facing the lineup for the third time on the average; if there was no carryover effect, we would actually expect them to have pitched worse than their normal .258, all other things— like the park, weather, and opposing batters—being equal.
So how did they pitch? (We’re going to exclude the ninth inning for the reasons stated above.) They pitched to the tune of a .251 TAv against (after adjusting for opponent batter pool)—better than we expected, but quite a bit worse than their .221 prior to being allowed to hit. Coincidentally, .251 is almost exactly the same as the average reliever, who is a .250 pitcher. So leaving your “hot” starter in the game yields no advantage over replacing him with an average reliever, unless he is a considerably above-average pitcher.
What about when the starter was taken out of the game for a pinch hitter? How did the relievers pitch in the very next inning? They allowed a TAv of .243, which is around what you would expect from a late-inning reliever.
So let’s recap the last few paragraphs. When a manager allows his starter, who is an overall .258 pitcher but has thus far pitched at a .221 level, to bat in a high-leverage situation (LI > 1.5) after he has pitched at least five full innings, he pitches at a .251 level (TAv) for the next 1.42 innings, on the average. When the starter is removed in the same situation, relievers pitch at a .243 clip for at least the next inning. Clearly, there are some starters who are good enough to post a sub-.243 TAv later in the game, but remember we are asking the question, “What if we were to remove all starters when they have completed at least five innings on the mound and they are due to bat in a situation where the LI is greater than 1.5?” Whatever our answer is, we can perhaps leverage that one-size-fits-all strategy by letting some pitchers (aces) bat for themselves and continue to pitch. Of course, you are still giving up the value of using a pinch hitter, which is almost the whole point of the strategy. In other words, a pitcher would have to pitch a heck of a lot better than .243 or .250 in order to justify allowing him to bat. This brings us to our next, vitally important question:
...
Also remember that each team averages around 28 of these decisions per season, and the starter ends up batting around 12 of the 28 times. Multiplying 12 times .032 wins yields a gain of .384 wins per season per team by virtue of this simple strategy.
If one were to argue that such a strategy might tax a bullpen or hurt the confidence or ego of a team’s starting pitchers, remember that the average subsequent IP whenever a starter is not removed for a pinch hitter is only 1.42. That means that we would be transferring a total of 12 * 1.42, or 17 IP, from the starters to the bullpen, an average of around three fewer innings per starter and perhaps one or two more innings per reliever. This hardly seems like a crisis.
A gain of 0.384 wins on 17 innings? That’s a gain of +.200 wins per 9 IP, which is like replacing an average pitcher with Roy Halladay.
Saturday, November 12, 2011
So speaks Bob McClure, with another HR from Laurilia:
Banny had a heck of a year [in 2007], but it got in his head that the way he was pitching wasn’t good enough. You’re talking about a guy who was third or fourth in Rookie of the Year voting and who won 12 games. He said, “I’m giving up too many fly balls.” I said, “Yeah, but they’re mis-hitting them, because you have deception and because of the way your pitches come in.”
He tried to get guys to do this and do that. He got into the rotation of the baseball. He got into where hitters hit their extra-base hits and what the best pitches are to throw to them. He started subscribing to all of that and getting into the terminology. I mean, he’s a very bright kid; he went to Stanford. He got into things like how the ball was turning, and to me, it’s not that complicated.
As a pitcher, what I’m trying to do is keep you off balance just enough, and locate my pitches. I’m trying to get ahead in the count, keep you off balance, and make pitches. That’s all I’m trying to do. I don’t think it’s any more complicated than that. The first three pitches are the most important ones you throw. If you can get to 1-2 on three quarters of the batters you face, you’re probably going to have a good game.
Banny got a little overboard and tried to do more than he was capable of doing. The next thing you know, his walks go up and his hits go up. He’s trying to sink the ball instead of what he was doing in the first place, which was commanding his fastball and his cutter. It kind of turned into a mess.
Banny was convicted in what he was doing and I don’t think anyone was going to change his mind. Now, that being said, I think that if he was 100-percent healthy… he had some very good points in wanting to sink the ball a little bit and get the ball on the ground a little more. He could maybe not take as many pitches to put a hitter away by getting them to hit it on the ground. He had some very good points, it’s just that we’re dealing with someone whose shoulder, here and there… as far as health, at times it was difficult to do enough work in order for him to get where he wanted to be.
Friday, October 28, 2011
Here’s the situation. It’s the bottom of the 10th, the defense is up by 2 runs, there’s runners on 2B, 3B, and there’s 1 out.
There’s a GB to third base, and a decent chance for a play at the plate, or a sure out to first base. What do you do?
You need to know the chance of winning in those situations. Let’s start off with the win probability before the ball is put in play (and average batters following, which is NOT the case anyway, with Pujols and Berkman due up): Markov says .301 chance for the home team. You don’t really need to know this, but it just sets it up for you.
You get the sure out, let the runner on third score, and now you have a runner on 3B, up by 1, and 2 outs. Home team has a .172 chance of winning.
If instead you go home, you have these two outcomes:
everyone is safe: up by 1, ONE out, runners on the corners, chance of home team winning is .478
runner out at the plate: up by 2, two outs, runners on the corners, home team is .107
So, that’s the choice facing Beltre: go for the sure out for a .172 chance of losing the game, against try for home, and get into either a .478 chance of losing if he doesn’t make the play (.306 change in win probability) or get into a .107 chance of losing if he does (.065 change in win probability).
The breakeven point is 82%. He has to make the out at home 82% of the time in order for that play to breakeven. If he thinks he can make that play 90% of the time (chance of losing for Rangers goes down to .144), then he should go home. If he thinks he can make that play 75% of the time (chance of losing goes up to .200), then he should get the sure out at first. If it’s somewhere in-between, then it’s pretty much a gray area.
Things get more complicated with Pujols on deck. Going for the sure out at 1B allows Pujols to be placed at first base. According to page 306 of The Book, with the defense up by 1 in the bottom of the last inning, and runner on 2B and 2 outs, the defense BENEFITS by walking the batter, if his true talent wOBA is 120% that of the guy on deck. In his last three years, Pujols has a .418 wOBA, while Berkman is at .380, or Pujols is 110% of the guy on deck. When you include the platoon disadvantage for Pujols, it becomes even more of a reason to not walk Pujols. But, let’s just say there’s enough uncertainty in our estimate of Pujols’ true talent and Berkman’s true talent in a Game 6 do-or-die situation that maybe Pujols was at least 120% the hitter that Berkman was, and so, it’s a net benefit to the defense for not wanting to face Pujols.
I’d love to hear Beltre’s (and Washington’s I suppose) reasoning in wanting to go to first on that play.
Probably a dozen plays at least to talk about. I’m going to bed, so I’d be interested to hear what you guys think.
Matt Holliday picked off third is what sticks in my mind.
Wednesday, October 26, 2011
By , 02:56 AM
The overwhelming consensus on BP, FG, this blog, and lots of other sites I have visited is, “No!” How did all these people come to that conclusion? Because it failed and it “cost” the Cardinals a good chance to tie or win the game. Does that make any sense? Of course not. Not in a rational sense. Can the outcome of a play that swings the percentages one way or the other maybe 1 or 2% inform us of the “correctness” of the play? Not in one single instance and not enough that a human being could possibly discern even after dozens or even hundreds of such plays. But people are irrational beings. When it comes to sports, they are out of their minds irrational.
So, can one determine whether running was correct in that instance without “running the numbers?” Not a chance. One can take a guess and be right 50% of the time, I guess. If you are a good sabermetrician, you might be able to do some quick mental calculations and maybe come up with the right answer with some degree of certainty, as long as the actual answer is not particularly close (i.e., the WE from each alternative is not a dead heat).
So what are all those people doing with their, “opinions?” I have no idea. To me, opinions should be reserved for ice cream flavors, what color car you like, and whom you would choose for your dream date. To me, there is no such thing as an “opinion” on which of two strategies yields the highest win expectancy. That is a matter of fact. That seems to be lost on 99.7% of the population.
So what is the right answer? I’m not going to tell you because I don’t know. I could know if I “ran the numbers” but I don’t want to deprive some aspiring sabermetrician of doing the work and making a name for himself.
OK, in all honesty, I can’t “know for sure” because I can only estimate the value of the requisite variables. Some more than others. But when the smoke clears, I could tell you one of three things with almost exactitude:
1) It is clearly a “run.”
2) It is clearly a “no run.”
3) It is close, depending on the exact values of all the variables, so we’ll just call it a draw.
Nowhere does my opinion matter…
Tuesday, October 25, 2011
There are different variations of the “double walk”. The first time I read it was from Bill James’ Baseball Abstract, but according to Peter Morris, it originated with a sportswriter in 1937. Anyway, one version is that a batter has the option to decline ANY walk, which resets the ball count, but maintains the strike count. A second walk moves the batter to second base: the double walk. (Any runners that have to be forced over are forced over.)
One version that we discussed a few years ago focused only on 4-0 walks walks.
The rule is simple: Any 4-0 walk, intentional or not, results in a two-base penalty. If you have a runner on 2B, the 4-0 walk gets you runners on 1B and 3B. If you have a runner on 3B, then it’s guys on 2B and 3B. And, with runners on 2B and 3B, the batter goes to 1B, the runner on 2B stays put, and the runner on 3B scores. Under this scenario, how often would a pitcher not give the batter at least one strike?
Of course, you’re going to have to tie this in with a change to hit batter, as you don’t want to avoid the 4-0 walk by plunking the batter. Therefore, a hit batter (or perhaps a no-strike hit batter) counts the same as a 4-0 walk.
The law of unintended consequence may creep in. Batters will look to get hit, the pitcher will groove too many in, etc.
The challenge is out. Give me your proposals, and please, don’t maintain the status quo, or knock down every thing you see. This is a brainstorming session. Be creative.
Monday, October 24, 2011
By , 08:10 PM
I’m pretty busy getting ready to head back west tomorrow, but I’ll probably watch the game and pop in here from time to time. Hopefully, you guys can keep a lively discussion going…
Sunday, October 23, 2011
By , 08:05 PM
Saturday, October 22, 2011
By , 06:44 PM
Here we go again, in Texas!
Thursday, October 20, 2011
I took all data from 1993-2010, focusing only when the score is tied, there are no outs, and there are no runners on base. (Not technically leadoff hitters of the inning, but, I don’t want to say “hitters batting with no outs and bases empty”.)
I then split it up by inning, and by home/away. Here are the results:
From innings 2 through 8, the home batters made outs at a rate of 98% of the away batters. In innings 1 and 9, it was 96%.
If I focus on the K rate, home batters K at 99% of the away batters in innings 2 through 8 (range of 92% to 104%), but in the 1st inning, home batters K only 80% of the rate of the away batters.
This pattern repeats itself with walks+hitbatters: innings 2-8, home batters have a rate of 104% of the away batters, but in inning 1, it’s 119%, and in inning 9, it’s 117%.
So, there’s a decided disadvantage to the away pitcher in the 1st inning, in terms of K and BB. Whereas the home pitcher has a K and BB+HB rate of 16.4% and 7.9% respectively, the away pitcher is at 13.2% and 9.4%.
For singles, doubles, triples, there’s a slight uptick in singles in the 9th inning for home batters (relative to the away batters), and a more noticeable downtick in doubles and triples. This is almost surely a function of the fielders playing differently.
The HR rates are a bit more difficult to figure out. Whereas each batting slot is not that much biased in terms of chance of getting a walk or hit, when it comes to HR, that’s not the case. So, in order to properly do this analysis, we’d have to account for at least the batting order, if not the actual identity of the players involved.
In any case, I have the full data, by inning, by home/away, by score, by base/out states, by starter/relief, by day/night, (but not by player identity or batting lineup) so feel free to make some suggestions below, and let’s see what we can all learn.
Wednesday, October 19, 2011
By , 08:10 PM
This thread, which hopefully Tango will stick, will be about manager mistakes in the WS. Hence the title of the thread!
It didn’t take very lone, IMO. With no outs in the top of the first, hit and run with Kinsler on 1st and Andrus at the plate. I’ve never seen the research, but I have always suspected that the hit and run was rarely a good strategy. If it were, it would be used a lot more. There is not a whole lot of game theory to it - it’s not like managers are going to pitch out every time a runner reaches base in order to thwart the hit and run.
Basically you have a batter forced to swing at some bad pitches, which is what happened in this case, and you have a runner who is vulnerable if the batter misses. Now, I hate the hit and run with a slow runner on first base, since if the batter misses, he is like 50% likely to be thrown out, the number depending on the speed of the runner and his jump.
In this case, Kinsler is an excellent base stealer but apparently he did not get a good jump as he was thrown out by a mile. A bugaboo of mine is when a runner does not get a great jump just because the hit and run is on and he expects the ball to be put in play. He should be doing the exact same thing he does when he attempts a steal. He should assume the batter is not going to make contact…
Great stuff from Matt.
***
Related articles:
http://www.tangotiger.net/walkbonds.html
Giants on the road:
http://www.tangotiger.net/walkbondschart.html
Giants at home:
http://www.tangotiger.net/walkbondschart2.html
That was done back in 2002. It probably is due for an update, though we’ve got a great table in The Book.
Tuesday, October 18, 2011
By , 12:29 PM
I realize that lots of people have chimed in or lurked a little with regard to the data presented about starters and relievers pitching in the later innings, especially the 9th, and that the data can be confusing. In an effort to summarize an analysis of the data, here is what it suggests:
If managers and coaches can tell whether a starting pitcher is “on” in any given day based on how he has pitched in the early and middle innings, we should see gradually increasing performance in the later innings, relative to a starter’s overall performance. IOW, if we look at all starters who pitch the 7th, we should see a collective excellent performance in 1-6 (otherwise they would not be allowed to continue). We do. We see a wOBA against of .322 (23 points better than their seasonal wOBA) in innings 1-6 (and presumably a low pitch count and few runs allowed) when they are allowed to start the 7th. Presumably their managers and coaches are thinking or saying, “He is pitching well, and his stuff is good today. We’ll let him start the 7th - at least.”
Since a pitcher’s overall wOBA against is a combination of days when his stuff is good and his stuff is bad, we should see better than average performance in inning 7. We see, however, a wOBA against of .354 while these pitchers’ overall wOBA is .345, which is almost exactly what we would expect the 3rd time through the order.
So it seems that managers and coaches are not able to tell that their stuff is good that day and they will continue to pitch particularly well, since they don’t. In fact, if they had let these pitchers pitch the 7th when they were pitching horribly in 1-6, they would have had to pitch the same in the 7th as they did when they were pitching exceptionally well in 1-6, since the two samples have to average to their overall seasonal numbers. IOW, if they are overall .345 and they pitch at .354 the third time through the order in the 7th, when they have been pitching great in 1-6, they have to also pitch at .354 when they are pitching badly in 1-6, since we expect .354 overall!
For inning 8, we should see the same phenomenon but even stronger. Since pitch counts are higher and short relievers are now readily available, we should see a manager only let his starter start the 8th when he has pitched even better in 1-7 and the manager believes that he is really “on” that day. He has to be even more “on” than in the 7th inning since his pitch count is higher and short relievers can now come in to pitch. In fact, going into the 8th inning, these pitchers who are allowed to pitch the 8th have pitched at a .297 level in innings 1-7! Surely they are “on”! So we expect his 8th inning performance to be really better than their overall performance. While it is true that these guys who are allowed to pitch the 8th have been even better in 1-7 than pitchers who were allowed to pitch the 7th, it turns out that in inning 8, these guys once again, like the 7th, pitch at their expected seasonal levels. They were at .345 in the 8th and they were .343 pitchers overall. Again, given that they were pitching the 3rd or 4th time through the order, that is about what we would expect, if there were no predictive value associated with their prior innings. Remember these numbers, like the .345, are adjusted for the pool of batters in that inning.
Once again, managers simply cannot tell whether their starters are “on” or not, or perhaps there is no such thing as being “on.”
What about inning 9? Again, we should see the same phenomenon, but even stronger than inning 7 and 8. Pitchers who are allowed to pitch the 9th pitched at .283 in 1-8. This time we do see better than expected pitching in the 9th! Starters who pitch the 9th not only show exceptional performance in 1-8, but they continue to some extent that exceptional performance in the 9th. They are .330 in the 9th even though they are .342 pitchers overall. They do around 13 points better than expected (the 4th time through the order, pitchers typically do 1 point worse than overall). How can they all of a sudden do that in the 9th but not at all in the 8th or the 7th? Surely managers just don’t let any starter pitch the 7th and 8th yet all of a sudden they decide that only starters who are “on” that day will pitch the 9th? That makes no sense!
So what is the explanation? It is simple once we look at how wOBA is recorded in different score situations (whether the batting team is tied, up by a little, up by a lot, down by a little, or down by a lot). As it turns out, even if the actual quality of the pitching (and hitting) is the same, the wOBA can change radically because of the approach of the batters, pitchers, and fielders, depending on the score in the 9th (or later) inning only and because the wOBA weights are based on average values (across all innings) of the various events. In fact, we see that for all pitchers in the 9th, including relievers, who actually pitch an overwhelming majority of 9th innings of course, wOBA is much lower when the pitching team is ahead by 2 or more runs, and much higher when the game is tied or the pitching team is ahead by only one run or is losing. This is evident from looking only at the relievers, who aren’t pitching the 9th inning because they are “on” that day. They are pitching the 9th because they are primarily closers or late inning relievers in general. And please remember, when I say that wOBA is lower in games where the pitching team is ahead by a lot and higher when the game is close or they are losing, I mean relative to the pool of batters and the quality of the pitchers in that “bucket.”
So, for example, if in blowouts, the average pitcher (reliever and starter) is a .350 pitcher and the batters are average, then we might see a wOBA of .330 (20 points lower than expected). If in close games, the average pitcher is a .320 (again, with average batters), we might see a wOBA of .340, 20 points higher than expected.
Here are the numbers in the 9th inning for all pitchers based on score differential of the pitching team. I’ll only use score differentials when the pitching team is winning so we can use home and road numbers (the numbers for when the pitching team is losing are similar to when the game is close). Look at the pattern. It is obvious. The first number is the wOBA adjusted for the batting pool. The numbers in parentheses are the seasonal talent levels of the pool of pitchers in that bucket. Remember these numbers are for all pitchers, which are mostly relievers of course, since 90% or so of all PA in the 9th inning are pitched by relievers.
Up 4 or more runs: .325 (.337)
Up 3: .305 (.318)
Up 2: .304 (.318)
Up 1: .318 (.317)
Tied: .356 (.330)
When up by 2 or more runs, wOBA for all pitchers is around 13 points lower than “expected” (seasonal numbers).
When up by 1, it is 1 point higher.
When tied, it is 26 points higher!
So that still doesn’t explain why all of a sudden in the 9th inning, we see starters doing exceptionally well. It does if you know this one important fact: Most of the time that a starter pitches in the 9th, he is pitching with a large lead. In fact, 76% of the time that a starter pitches in the 9th his team is ahead by 2 runs or more. 55% of the time, his team is ahead by 4 or more runs. Only 9% of the time that a starter pitches in the 9th is the game tied, which is when wOBA is the highest by far, for all pitchers.
Contrast that to relievers. Only 48% of the time do they pitch with a 2 or more run lead, 27% of the time their team has a 4 or more run lead, and 13% of the time they pitch when the game is tied. They also pitch considerably more often than starters when their team is losing, The wOBA is also quite high in games (in the 9th of course) in which the pitching team is losing.
And that is why starters seems to pitch so well in the 9th. It is not that they are really pitching well. It is just that the way wOBA is figured it understates what is really happening (the weights of the events are not correct, and other things probably occur more often, like sac bunts and IBBs) in the 9th inning of games in which starters tend to pitch (close games, not losing) presumably because of the approach of the batters, fielders, and pitchers. Again, we know that the low wOBA against for starters in the 9th has nothing to do with the starting pitchers themselves because we see that when the pitching team is ahead by a lot with a reliever in the game, the wOBA is just as low. Again, it is just that starters tend to pitch in the 9th when they are leading by 2 or more and relievers tend to pitch the 9th when their teams are losing or the game is close.
In fact, when we look at games in which the score is close, the starters’ wOBA against is around the same as the relievers (relative to their overall wOBA against) and when the pitching team is ahead by a lot, the starters’ wOBA against is also the same as the relievers’. No difference. Starters and relievers pitch the same in the 9th relative to their true talent. Starters do not pitch well despite having pitched exceptionally well in innings 1-8.
A simple but perfectly apt analogy would be this:
Let’s say that during the day wOBA was 10 points higher than at night, given the same pool of batters. And let’s say that pitchers with blond hair pitched mostly at night and pitchers with brown or black hair pitched mostly during the day. What would we find? We would find that blond haired pitchers appeared to pitch a lot better (by almost 10 points) than dark haired pitchers. This would be an illusion. We would find of course that blonds during the day pitched the same as brunettes during the day and that both groups also pitched the same at night.
In this case, starters are blondes and relievers are brunettes and night games are games in which the pitching team is ahead by a lot and day games are games in which the score is close or the pitching team is losing.
So, there does NOT appear to be any predictive value to pitchers who have pitched great in 1-6 or 1-7 or 1-8 AND their manager considering them to be “on” that day (I presume) and thus leaving them in the game. We only saw that in the 9th inning anyway, and it was an illusion created by the fact that starters tend to pitch when they are ahead by a lot and ANY pitcher will have a low wOBA against, presumably because of a non-typical approach by batters, pitchers, and fielders, and relievers tend to pitch in closer games (or losing games) when ANY pitcher will have a high wOBA against, again, presumably because of a non-typical approach by batters, pitchers, and fielders.
I hope I have explained this well…
Thursday, October 13, 2011
As you know, I think 4-pitch walks (intentional or not) are against the spirit of the game. The idea of called balls was to act as an incentive for the pitcher to throw strikes at the batter. But, sometimes, the pitcher/manager believes that it is better to throw all those balls than to let the batter get a strike. Hence, against the spirit of the game.
Now, what if the batter makes life a bit tougher for the pitcher? The pitcher throws two intentional balls, and on the third one, the batter swings through. The count is now 2-1. Does the pitcher still walk the batter? Since an IBB is usually a very close to break-even decision, intentionally giving back .05 runs by the batter by swinging through on a pitch must cancel out that advantage. But, as we can figure, the defense is still going to throw an intentional ball 3.
Now what? At 3-1, the defense is going to throw ball 4. The batter can’t swing again, as he’d be giving up another .07 runs. But, suppose he does. Suppose he swings through at an intentional ball to put it at 3-2. Then what? What do you think the defense is going to do?
Similarly, what if the batter intentionally swings through on the first pitch, to put himself in a 0-1 hole. What do you think the defense is going to do?
Tuesday, October 11, 2011
Max Marchi weighs in with a great article. Read it all. This is the conclusion:
I looked at games played in the past 20 years, thanks to the invaluable Retrosheet data. I selected all the instances in which the starting pitcher has completed eight innings giving up one run at most. These should be the circumstances when the manager can believe his starter “has it” and can complete the game.
I removed the games in which the offense had provided the pitcher more than three runs. Thus, we are dealing with situations in which the game is still on the line, and the manager should be trying to maximize his chances. (In a blowout the skipper’s choices could be dictated by having to rest the bullpen or wanting to try a young arm.)
The games were then split in two groups: Games with the starter beginning the ninth (STARTER) and games with a reliever beginning the ninth (CLOSER).
Here’s how the two groups fared, with more than 1,000 games represented in each group.
runs percentage
allowed CLOSER STARTER
0 76 74
1 14 16
2 7 5
3 2 3
4+ 0 1
Looking at the numbers above, the decision on whether leaving the starter in or removing him appears as a coin flip. However, the above table can suffer from selection bias, with three possible sources of bias coming to my mind.
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