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Thursday, October 09, 2008
By , 10:03 PM
OK, he’s not really a manager, but he certainly could be one. In fact, I think that he is as smart, knowledgeable, and experienced as most managers in baseball. Don’t get me wrong. I am not, by any means, touting his qualifications to be a good manager. Only that he seems to me to have to have the mindset of a typical manager. And I think that most baseball insiders would agree with me on that.
In the bottom of the 7th, with the pitcher’s spot coming up, there is a runner on first and no outs. At first Manuel had Dobbs in the on-deck circle ready to pinch hit. Then when Ruiz, the batter, reaches base, he decides to pinch hit Taguchi, obviously to bunt. Let’s set aside for a second that that is a bad play by Manuel for the following reason: As I have said a million (maybe only a thousand) times here and in other forums, when there is the possibility of the sacrifice bunt, your ONLY edge is if the defense does not know whether you are going to bunt or not. Once you give it away, one, the bunt almost always decreases your WE, and two, if you don’t bunt (but still give it away), the defense can play back, thus reducing the batter’s chance of a hit. But that is not the issue here.
The person I am referring to, the “faux manager” analyzes the situation. (I am paraphrasing.) He says, “I would not have bunted there. First of all, you have the best pinch hitter in baseball in Dobbs. Second of all, it is the 7th inning and you have a one-run lead - you want to play for the big inning and not one run.”
O.K.
In the top of the 8th, with 1 out, and no one on, Madson is pitching to Manny. This “manager,” says, “The right strategy, I would think, is to throw him inside fastballs. We’ll see (what Madson does).”
Honestly, I think that this person is a perfect proxy for a typical manager. Do me a favor (not directed towards anyone in particular). The next time I or anyone else criticize a manager’s decision-making process, please don’t tell me, “But the manager knows things that you don’t.” Please. Ever.
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Comments • 2008/10/10
Wednesday, October 08, 2008
winClass n next3 regr3 over500 reg500
0.378 26 0.458 0.451 19% 13%
0.429 157 0.478 0.472 35% 29%
0.476 265 0.489 0.490 45% 43%
0.522 311 0.507 0.509 57% 57%
0.571 144 0.530 0.528 70% 71%
0.617 39 0.572 0.547 95% 85%
From 1969-1971, the Expos had a .404 record. I put them in the “.400-.450” win class. (That’s an average of .429 for all the teams in that class, which is the second line in the chart, under the “winClass” column.) From 1972-1974, they had a .476 win%. That’s a close match to similar teams (actually, .478, under the “next3’ column). Teams in their win class (the .400-.450 win class) ended up with a 3-yr win% of over .500 35% of the time (that’s the “over500” column).
If we regress their win percentage 60% toward the mean, we end up with the reg3 column (that’s win% times .4 plus .3). As we can see, a pretty strong match, except for the really, really good teams. If we take their win%, times 3, minus 1, you get the reg500 column. Again, a decent match.
So, the 2006-08 Pirates, with a win% of .416, is expected from 2009-11 to have a .466 record, with a 25% chance of having at least a .500 record over those three years.
Now this is cool. Forget Dan Rather, Keith Olbermann, and whoever else Nate has met. Stephen Colbert? Guest-speaker to the President’s dinner? Wittiest man in America? A one-time presidential candidate? That’s really cool. Nate looked nervous, unlike his very calm demeanor with the other guys. Must be tough to be sparring with a comedian as sharp as Colbert. Colbert was pretty good to Nate. Nate had one good line where he tried to put a baseball analogy to the race for presidency, likening Obama to the Rays, that we’re in the 9th inning down by 2, and Palin was just picked off first base. Must feel great to make a funny guy like Colbert laugh.
Nate has Obama with an 89% win expectancy as of today. Bottom of the 9th, 1 out, down by 2 is a 96% chance of winning. Down by one though is a 90% chance. So, that’s where we are in the race. Bottom of the 9th, 1 out, down by 1 run, McCain batting, Obama pitching.
Tuesday, October 07, 2008
UPDATE: Pujols wins. Poll question modified to select SECOND best player. Further information below.
Justin gives us a best-of-breed. He also applies my revised positional adjustments, which, as of today, are these:
+1.25 C
+0.75 SS
+0.25 2B/3B/CF
-0.75 LF/RF
-1.25 1B
-1.75 DH ... Should be -2.25, but then I add in 0.50 for the DH penalty of how hard it is to hit off the bench.
Monday, October 06, 2008
Nice list.
Bill James, in what will surely be an article to appear in the next Gold Mine, looks at the issue of whether the Power or Finesse pitchers perform better in the post-season. He does his typically enjoyable study of matched pairs, where he proceeds to select 100 power pitchers and 100 finesse pitchers (they match in a variety of ways, except in K and BB). They match up quite well in the categories he selected. He also notes:
But the power pitchers had averaged 183 strikeouts, 76 walks; the finesse pitchers had averaged 107 strikeouts, 57 walks. The two groups were nearly even in terms of home runs allowed (a few more for the power pitchers), but the finesse pitchers had given up, on average, 18 more hits. 18 more hits, 19 less walks, one less homer. . .the same results overall.
As you guys know, I’m big on simply doing K minus BB, per PA. And just looking at the bolded part, you can see that I think the two groups are biased. I responded:
Very enjoyable study.
If you look at the BABIP (batting average on balls in play, or H minus HR divided by PA minus BB, K, HBP, HR), I think you will find that the finesse pitchers ended up with a BABIP of 10 or 12 points better. Or, probably a bit more lucky than the power pitchers that year. So, I think the study is biased in that while the component ERA may come out as equal for the two groups, the component ERA of the power pitchers is more indicative of the true talent.
I estimate that the 10-12 estimated difference in BABIP to be roughly worth 0.20-0.30 in ERA, thereby giving you a perfect match for the post-season difference.
***
We can even try to estimate FIP, and I get a 38 point difference, in favor of the K pitchers. So, I don’t think that we really have a matched pair of pitchers here. The idea behind matched pairs is that you can match on everything, except the thing you are looking at. And the plan is to make sure not to bias the two groups. But, I think Bill does have a biased group of pitchers. The FIPs aren’t close to matching, the BABIP don’t match, and what is more indicative in the future is a pitcher’s FIP not his ERA. And his BABIP is the least indicative, but it makes up a substantial part of ERA, one of James’ indicators.
In any case, I really enjoyed the study, and it would be an ideal study by simply introducing one extra parameter (FIP or BABIP) into the equation.
David compares THT, Chone, PECOTA, and ZiPS.
Saturday, October 04, 2008
By , 09:16 PM
Sometimes you can get an idea as to how well a manager actually “understands” the game. To wit:
Jerry Manuel says:
“You don’t see a lot of guys that have statistical numbers play well in these championship series,” Manuel said. “What you see is usually the little second baseman or somebody like that carries off the M.V.P. trophy that nobody expected him to do. That’s because he’s comfortable in playing that form of baseball, so therefore when the stage comes, it’s not a struggle for him.”
I pity the poor Met fans.
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Comments • 2008/10/09
Friday, October 03, 2008
Colin provides his data for easy access, along with his intro article.
Thursday, October 02, 2008
By , 07:04 PM
Here is an SI,com article by John Donovan (I don’t know who he is). In it, he says:
Still, there are smart ways to pick the teams that will fare best in the playoffs. Nate Silver and the hard-thinkers over at Baseball Prospectus have looked at tons of data and come up with a formula that identifies the three main characteristics of a successful playoff team. They are:
1. Pitchers that strike out batters.
2. A stud closer.
3. A good defense.
You might notice there’s no mention of home runs or the ability to squeeze a guy to second with one out against a left-hander. There’s not anything in there about crafty managers or experience or a versatile bench, either. Momentum? History? Don’t even bother. Speed? Pssh. Clutchness? Please, save it.
I say, “Poppycock!”
Unless I am somehow living in an upside down universe, the last time I looked, a post-season series was 5 or 7 games of two teams playing 9 innings of baseball. There is a starting pitcher, 8 more fielders, 9 batters in the lineup, right? 3 outs per inning per team? Or are there a different set of rules that I am not aware of?
I have no doubt that if you ran various regressions on playoff success and team parameters you might come up with all kinds of goofy things. Without getting into a discussion about the merits of using regression analysis for this type of analysis (of which I am woefully not qualified to do anyway), the team that has the best chance of success in the playoffs is the team that has the best team!
Duh!
And how do we determine the best team? Uh, let’s see, the same way we do it for any other game or games. The team with the best expected run differential is the best team. Period. How do we estimate or determine that (the team with the best expected run differential)? Well, the starter goes 6 or 7 innings. Then 2 or 3 relief pitchers come in. Then we throw in the defense. That comprises the runs allowed. Yes, I know that the closer tends to pitch more in the post-season. That shouldn’t be too hard to model in our “runs allowed” formula should it? I also know that the closer has a leverage of around 2.0 so we have to “double” his contribution. The setup guy or guys might have leverages of 1.5 or so, so we adjust their contribution accordingly. And yes, I know that they only use 3 or 4 starters per series and that each starter pitches more than the next one in line. Thank you for reminding me, though. I might have accidentally added up the contributions of 5 equal starters per team.
Now the offense, Let’s see. Hmmmm. RC or lwts (or OTS if you must), including base running and base stealing for each player on the team, prorated by their expected playing time? Did I miss anything?
Done. We now know which teams have the best chance of winning each game and thus each series. Oh, and home field advantage for each game. Thank you for reminding me again.
Pitchers who strike out the most batters? Well, no duh they tend to be the best pitchers. How about pitchers who walk the fewest batters? And pitchers who give up the fewest HR? How about pitchers with the lowest BABIP? Oops, no, that is mainly luck.
No, how about the team with the BEST pitchers. Maybe that will work in the post-season. It tends to work in the regular season. Oh, I forgot - there is magic fairy dust in the air in the post-season.
Best defense? Again, no duh! But would you want a +10 defense or a +15 offense. Uh, I’ll take the +15 defense, thank you ever much.
A stud closer? What, not a bad closer?
Here is my list:
Best offense (including base running)
Best defense (including pitching, closers, etc.)
Combined
This whole idea of what makes post-season teams good is pure nonsense (again, other than the fact that we know that a team only needs 3 or 4 pitchers and that they will use their closer more, etc.). Did I say that it is nonsense?
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Comments • 2008/10/06
Long-time reader Mike has his thesis posted on my site:
The home advantage has been consistently demonstrated across a number of sports, but conclusive evidence of the origin of the home advantage has yet to be found. One factor thought to contribute to the home advantage is familiarity; the home team is more familiar with their stadium and playing field and thus should have an advantage in competition. To isolate this variable, we compared the records of teams in their last year at a stadium, where familiarity should be high, with their records their first year in a new stadium, where familiarity should be low. Professional baseball, hockey, football, and basketball data from the four major U.S. leagues were examined. Results showed no differences in home winning percentage between a team’s high-familiarity season and its following low-familiarity season, suggesting that familiarity does not play a major role in the home advantage.
Here is my first stab at trying to describe Situational Wins. Please provide comments, especially as it pertains to readability. I will then make the necessary modifications, and I’ll submit it to THT for publication for the general public to consume.
Wednesday, October 01, 2008
Sweet.
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Comments • 2008/10/02
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Tuesday, September 30, 2008
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