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| I'm an NL fan, but the fact that the AL has been stronger for the past several years is inescapable. The AL is ahead in interleague play so far in 2009, and (thank you to Rob Neyer for printing these totals), in the past 4 years, the AL has been:
149-103 (2008)
137-115 (2007)
154-98 (2006)
136-116 (2005)
in interleague play. In terms of winning percentages, that's .591, .543, .611, and .540, for an overall total of .571. This is very, very statistically significant. The AL is stronger, deal with it.
The more interesting question, though, is WHY the AL is stronger. Before we start harping on about DHs and smart executives, let's look at some telling numbers.
Year Average AL Team Salary Average NL Team Salary
2009 $93.3M $84.3M
2008 $96.9M $83.1M
2007 $92.8M $73.7M
2006 $83.7M $72.4M
2005 $75.5M $70.9M
(I got each year from a different source, but in any given year, the AL & NL numbers are from the same source. They're not exact, there are different ways of measuring this, I know, I know. Take them as rough estimates, I don't care.)
The obvious reaction to this is: well of COURSE the AL does better, their average salaries are noticeably higher. And certainly yes, that does give them an edge. I'm going to do some crude analysis to show you that it does partially explain the results.
Here's another table. This one shows the difference in average salary computed from the info above, and, courtesy of FanGraphs, the price of a marginal win, from 2005-2008.
Year Salary Difference Price of a Marginal Win
2008 $13.8M $4.5M
2007 $19.1M $4.1M
2006 $11.3M $3.7M
2005 $4.6M $3.4M
If we divide salary difference by marginal win price, we find that the difference in expected win totals between the average AL & NL teams should be 3.07, 4.66, 3.05, and 1.35, equivalent to season winning percentage differences of .019, .029, .019, and .008.
These are the differences we'd expect against average competition. In interleague play, you have above average teams playing against below average teams (in aggregate). So, the difference in winning percentages should actually be magnified a bit. This is quite a large expected difference in performance, but it still explains less than half of the AL's success. If you compute a z-score for the 2005-2008 results using this information, regardless of what assumptions you make, you're going to get something more than a couple standard deviations from the expected results. Thus, there's something else going on here.
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| Is this libel? I don't think so.There is a non-zero probability that Raul Ibanez has taken steroids.
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| The Young/Harris for Garza/Bartlett Trade RevisitedI wrote a year and a half ago that the Rays fleeced the Twins on this deal. The main points were:
-Garza's a solid above-average starter
-Young is really not that valuable
-Bartlett is better than Harris, because his defense is way better than most people realize
Garza and Young have been exactly what any reasonable person could've predicted they'd be. Well above average and well below average, respectively. In 2008, Bartlett and Harris were roughly comparable, Bartlett playing good defense but being a little more pedestrian with the bat. So yes, advantage: Rays.
But wait, look at what Bartlett's done so far in 2009! He's .379/.424/.572, with 12 stolen bases, in 40 games! Now I'm sure he's going to regress, but it's getting to the point where this sample is a little too big and too extreme to just ignore. He's certainly not a .379 hitter, but there's a good chance that he's become a legitimately competent one. And if that's the case, this is getting into Bagwell-for-Andersen territory.
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| Sending Runners From 3rdI've never seen or heard this discussed before, but when it hit me, it seemed so obvious. Imagine that you're the 3rd base coach in the following two situations, both early in a game:
1. Player A is on 3rd, with 1 out. Player B hits a fly ball to left field which is about to be caught. You believe there is probability p that if player A tries to score, he'll make it safely.
2. Player A is on 2nd, with 2 outs. Player B lines a single into left field. You believe that there is probability p that if player A tries to score, he'll make it safely.
The question is: in order for you to send the runner home, does p have to be equally high in both situations? That is, should you be equally aggressive in sending the runner in the two situations? The answer is NO! You should be less aggressive in situation 2. Why? It's actually pretty simple, once you frame it the right way.
If you send the runner, there are two possible outcomes. Either he scores and the inning continues, or he's out and the inning ends. If you do not send the runner, he remains on 3rd and the inning continues. In scenario 2, you get an additional benefit from the inning continuing: you have another runner on base! This increases the average number of runs that you'd score in the rest of the inning. The safe option of holding the runner is now more desirable than it was in scenario 1. If you're not satisfied with the basic intuitive explanation, here's the math behind it.
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If you send the runner in scenario 1, you get (on average) 1+X runs for the rest of the inning if you're successful, and 0 if you're unsuccessful. X is the average number of runs you'd score starting with 2 outs and nobody on. If you do not send the runner, you get (on average) Y runs, where Y is the average number of runs you'd score starting with 2 outs and a runner on 3rd.
If you send the runner in scenario 2, you get (on average) 1+X' runs for the rest of the inning if you're successful, and 0 if you're unsuccessful. X' is the average number of runs you'd score starting with 2 outs and a runner on 1st. If you do not send the runner, you get (on average) Y' runs, where Y' is the average number of runs you'd score starting with 2 outs and runners on 1st and 3rd.
So, in scenario 1, you have the following expected #s of runs (p is the probability of success if you send the runner):
Send runner: p(1+X) + (1-p)0 = p(1+X)
Don't send: Y
In scenario 2:
Send runner: p(1+X') + (1-p)0 = p(1+X')
Don't send: Y'
So, the benefit of sending the runner in scenario 1 is p(1+X)-Y, and the benefit in scenario 2 is p(1+X')-Y'. What we want to know is whether or not the two benefits are equal. If we set p(1+X)-Y = p(1+X')-Y' and do some algebra, it works out to:
(Y'-Y) = p(X'-X).
If the left side is greater, that would mean that the benefit of sending the runner is higher in situation 1. But look back at what X, X', Y, and Y' are. There's no reason that Y'-Y and X'-X should be significantly different. Both of them roughly represent the probability of a runner scoring from 1st with 2 outs. However, when p is close to 1, the decision is very easy, you send the runner. It's only a tough decision for middle values of p, where the values of sending & not sending are close. But for middle values of p, it's very obvious that the above requirement is not satisfied. The left side is significantly greater, and thus the benefit of sending the runner home when there's nobody else on base is much, much higher.
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The lesson here? If there are two outs and you have a trailing runner on base, or especially two trailing runners, you should be MUCH LESS WILLING to send runners home from third. I have never seen this addressed anywhere, and I strongly suspect that major league 3rd base coaches are largely unaware of it. I have (many times) seen a 2-out single with runners on 1st and 2nd, only to witness the 3rd base coach foolishly send the lead runner home with a low chance of success, rather than let the next batter hit with the bases loaded.
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| Fantasy Baseball: My teams, and some insightsI'm in three leagues this year. One is rotisserie, the other two are head-to-head. None of them use the standard 5x5 categories.
One of the H2H leagues is particularly bizarre: the stats are OBP, SLG, R, RBI, SB, ERA, WHIP, Saves, K/9, Quality Starts, with no weekly innings requirement. Apparently, I was the only person in the league to realize that nabbing all the best relievers and drafting zero starting pitchers would pretty much guarantee a win in 4 out of 5 pitching categories every week. Once I got Papelbon and Nathan in rounds 4 and 5, I had that pretty much locked up. Instead of trying to get a balanced offense, stacking in 2-3 categories would assure me a win nearly every week. I decided to neglect the two power categories and focus on drafting low-power guys with good OBP/R/SB. Since everyone loves power guys, the players I was targeting were available pretty late. The lesson here is: if your league uses bizarre categories, figure out a good way to exploit it.
I noticed a trend with a lot of fantasy player rankings and average draft positions: people tend to be overvaluing last year's results. Guys coming off of a single down year were extremely undervalued. David Ortiz, Victor Martinez, and Michael Young come to mind. Conversely, players who had surprisingly good years in 2008 were overvalued. Josh Hamilton, Ian Kinsler, and Nate McLouth come to mind. I'd include Alexei Ramirez, but honestly, he wasn't even that great in 2008.
My strange draft strategy in the bizarre H2H league made it tougher to get players common to all three of my teams, so I do not have a single trifecta. However, I have the following players on two of my three teams:
Miguel Cabrera
Prince Fielder
David Ortiz
Curtis Granderson
Chone Figgins
Bobby Abreu
Joe Nathan
David Price
Jonathan Broxton
Clayton Kershaw
Jason Motte
Hong-Chih Kuo
Cabrera was mostly a function of my draft position in the first round. When I'm drafting closers, I go for ability, not for any ridiculous projection of how many saves they'll get. I took Kuo not for saves, obviously, but because he's a nice extra piece to put into my pitching staff if I want ERA/WHIP improvement (with a few Ks). Ortiz and Abreu become much more valuable when your league includes OBP.
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