Here is one account, here is Levitt’s account of another round. In the latest he did very well indeed. Out of 900 or so contestants, I am hearing reports that he finished about #25, some sources are saying as high as #10. The pointer is from Scott Cunningham, tell us more if you know more.
So how many dimensions does intelligence have? Some top chess players, such as Etienne Bacrot, are switching into poker for the higher pay, though I suspect Levitt’s move is temporary rather than permanent.
Addendum: Here is Levitt’s account.
The series isn’t over yet:
that’s only the beginning of the story. The main point is that when
LeBron James got the ball against San Antonio’s defense, the Cavaliers
managed to get a good shot an alarming percentage of the time. There
were a smattering of offensive fouls, certainly. And a couple of times
James forced a pass that was picked off.
I watched 50
possessions, between the two games. Eight times (nine if you count a
pretty amazing Tim Duncan block of Anderson Varejao) the Spurs forced
the Cavaliers into a turnover, an offensive foul, or a truly difficult
shot. Trusting my observations, that means the Cavaliers had
good looks 84% of the time. Seems like a high number against any team,
but especially San Antonio.
Of course the Lucas critique is relevant; the numbers don’t mean that Cleveland can replicate those shots at will. The betting markets are giving Cleveland about twenty percent. Matt Yglesias offers numbers on offensive and defensive efficiency, and writes of the coming blowout. I’m picking San Antonio in six.
In the prestigious Linares chess tournament Carlsen met the following top-rated players: Veselin Topalov, Viswanathan Anand, Peter Svidler, Alexander Morozevich, Levon Aronian, Peter Leko, and Vassily Ivanchuk (replacing Teimour Radjabov). With the significantly lowest ELO rating, he achieved a 2nd place (on tiebreaks) with 7.5 points after 4 wins, 7 draws and 3 losses, and an ELO performance of 2778.
Magnus, born in Norway November 30, 1990, may be the greatest chess prodigy of all time. He is arguably ahead of the pace of either Fischer or Kasparov.
Back when I was Tyler’s colleague (and Alex’s professor), Tyler and I shared a pair of season tickets to the then Washington Bullets. We’d sit in the stands and discuss how we would run things if we were the general manager. Now older and wiser, I’d like to offer suggestions for how to improve the league.
1. Re-seed after each round of the playoffs. I’m pretty sure the majority of other pro sports do this and it makes sense. Keep the best teams in the longest, save the best match-ups for last. I know it might cause some extra days off and lengthen the already long playoffs but……
2. Shorten the regular season. Modern NBA basketball is a brutal sport. 82 games is a grind and a half. What shall we say? 60? 70 at the most. This leaves room for the extra time re-seeding might take, makes the games that are played more important, and reduces the potential for injury.
3. Make the draft lottery a true lottery. The tanking in the Greg Oden derby was hideous. Let every team that misses the playoffs (or better yet, every team in the league) have an equal shot in the lottery. Eliminate the lottery-created incentives to lose. And regarding the possibility that the rich would just get richer, that would actually be a plus.
4. Make the finals 2-2-1-1-1 not 2-3-2. Again, the shorter season gives us more time for travel days and the current 2-3-2 is just unfair. Stat boy can check me but I am pretty sure no home team has ever won all three of those middle games.
Am I missing anything?
As a response to Justin Wolfers and Joseph Price, the NBA financed a study supposedly showing there is no racial bias in refereeing. Here is a WSJ analysis of that study. Here is part of what they found:
Columbia University statistician Andrew Gelman, who has blogged
about the Wolfers-Price study and participated in a conference call
with Segal and me, said, “What the statistics tell you is that there’s
a pattern in the data that’s not explainable by chance.” University of
California-Irvine statistician Hal Stern told me the NBA’s study “can’t
be said to disprove the Price-Wolfers analysis.”
the NBA’s study didn’t include players who weren’t called for any
fouls, making Segal’s results “suspect,” according to Mr. Gelman. Mr.
Fluhr responded, “I’m not sure if you’re looking at non-calls, it would
affect the data.” He added that Segal had the data necessary to
incorporate such players, but didn’t consider the data relevant,
instead only focusing on foul calls. Messrs. Wolfers and Price included
all players who appeared in the games they examined.
The NBA does promise to examine non-calls and redo some of the results. I do not think we have yet gotten to the bottom of this, but my "haven’t read anything but the initial study" intuition (and Steve Levitt’s comments; see also Voxbaby) is that the result of bias will hold up.
Thanks to Chris Masse for the pointer.
I wouldn’t have thought so, but Justin Wolfers, writing with Joseph Price, says maybe yes:
…during the 13 seasons from 1991 through 2004, white referees called fouls at a greater rate against black players than against white players…[the authors] found a corresponding bias in which black officials called fouls more frequently against white players, though that tendency was not as strong.
Here is the paper. The effect is big enough that an all-white team would, all other things equal, win two extra games over the course of an 82-game season. A panel of three independent experts has judged that the Wolfers-Price analysis is more convincing than a David Stern-sanctioned rebuttal that no bias is present.
The NYT web site is slow this morning, try back later if the first link is giving you trouble.
Wall Street is about to launch a new way to trade professional athletes the way you trade stocks. A piece of Tiger, anyone?
Here is further information.
Let’s consider a power supplier with market power and zero marginal cost. Capacity suffices for ten units but five units are sold at p = 10; selling more would lower profits. Now, using carbon offsets, bribe the fifth buyer to stay out of the market, say by walking to work rather than flying his jetpack. Even better, just shoot him.
The company has two options. It can stick with selling four units and raise price. Or it could drop price a bit and pick up a fifth buyer again. Hard to say what will happen. Alternatively, if buyers stand along a continuum, is there a general proof one way or the other?
Rather than bribing the fifth buyer to walk, invest the "carbon offsets" money in building a nice comfy sidewalk. In principle all buyers could walk on this new path.
It is then easy to see how the power company might lower price and expand to six units or more. Otherwise they might lose all their customers.
A key question is the cost structure of the alternative clean technology. Non-scalable technologies, with little potential for expansion, are the least likely to backfire and least likely to lead to more dirty power. Scalable technologies, such as the sidewalk, are most likely to backfire and make the world dirtier. They require a bigger competitive response on the part of the dirty power supplier. (At least in the short run this is true, in the longer run the scalable technology might eliminate dirty power altogether.)
This counterintuitive conclusion is one reason why we have economic models.
The head of the largest birth clinic in the [German] city of Kassel, Rolf Kliche, estimates that births at his hospital will be up by 10 to 15 percent, which he described as a "minor sensation" given the usually stable birth statistics.
Here is the story, via Jason Kottke.
He [Amaechi] writes that the pros play the game for a lot of reasons–money, fame,
groupies, self-esteem–but that very few NBA players love basketball.
"The fan sitting at home … wants us to love the game like he does," he
writes. "If he knew why we really play the game, for the most part, he
might not love the game. He might not even watch it." The average fan,
gay or straight, will probably find that contention more troubling than
a former player’s homosexuality.
Here is more.
I never knew you all had such a pent-up demand to discuss matters gay. Having read through 110 plus comments, I am now more inclined to see genetic correlations — rooted in the human mind rather than the body — with athletic achievement (NB: I don’t agree with all the "genetic" claims in the thread, by any means).
Most of all, I am struck by how few former male athletes have come out of the closet. That would seem to adjust for "the locker room effect" and "the endorsement effect," as explained in my original post. Once an athlete is retired, those factors shouldn’t matter much.
I also noticed that Amaechi signed a book contract about being gay in the NBA. He was a pretty feeble player, and quite nerdy, more here. How large was his book advance? 50K or 100K is not a bad guess. I’ve known plenty of gay guys who would self-identify for much less; the fact that so few former male athletes have done so is striking.
The Bears winning the coin toss made them 0.5% more likely to win…
When the Bears took an 8 point lead, the market still viewed the Colts as the favorite to win.
The not-so-famous John Amaechi, former NBA player, has come out and admitted publicly he is gay. I am struck that he is (only) "the sixth professional male athlete from one of the four major U.S. sports — basketball, baseball, football, hockey — to openly discuss his homosexuality."
Those are scant numbers, why? I see a few hypotheses:
1. There aren’t so many gay professional athletes, maybe because guys play college ball to get women.
2. Even the not-so-famous earn endorsement income, at some level or another, or at least hope to, and that implies a mainstream image.
3. Fans don’t want to see gay players, or at least they do not want to know too explicitly about sexuality in that manner. Major league sports are about numbers of fans, not the possibly intense minority loyalties that could be generated if a major star came out of the closet.
I put most of the weight on #2. When it comes to #4, my sense is that the teammates often know or suspect who is gay, even if it is not publicly admitted.
Keep in mind it is relatively easy to measure performance in sports. The real lesson is that employer-driven discrimination is no longer the dominant model.