Archive for the 'Statgeekery' Category

Note: This post was originally published at College Basketball at Sports-Reference, S-R's College Hoops site, so when you're done reading, go over and check it out!

Just how unlikely is this year's Final Four of Kentucky, UConn, Virginia Commonwealth, and Butler?

Well, going by one measure, the odds of it happening were 0.00003% -- only two entries (out 5.9 million) correctly picked the four teams in ESPN.com's Bracket Challenge. But I decided to see how this year's improbable group matched up against other inexplicable Final Fours since the tournament expanded to 64 teams in 1985. Here were the Final Fours with the highest average seed # since then:

Aside from 2011, two other years stand out at the top of the list: 2000, when two 8-seeds crashed the Final Four, and 2006, when no #1 seeds made it (but George Mason did). In terms of pre-tournament likelihood, how do those years stack up to 2011?

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2010-11 NBA power rankings through the games played on March 24, 2011:

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With Derrick Rose's 2011 MVP looking like a foregone conclusion, it seems only natural to compare his campaign to that of Allen Iverson in 2001, the year another popular guard won the MVP despite not being the game's most talented player.

Here's the numerical tale of the tape for A.I. and D-Rose, with Rose extrapolated to 82 team games: (Glossary)

Statistically, the two players are incredibly comparable. If you translate Iverson from the 103.0 league-ORtg environment of 2001 to the league ORtg of 107.1 in 2011, his ORtg/%Poss/DRtg becomes 110.5/33.8/103.0, production that is basically equivalent to Rose's after adjusting for usage.

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Note: This post was originally published at College Basketball at Sports-Reference, S-R's College Hoops site, so when you're done reading, go over and check it out!

Watching Texas and Pitt destroy my bracket for what seems like the fifth or sixth time in the last 10 years, I was compelled to ask: is it just perception, or do Rick Barnes' and Jamie Dixon's teams always significantly underachieve in the NCAA Tournament?

Luckily, I can answer that question two ways. The first is to look at every NCAA Tourney game since the field expanded to 64 teams in 1985, and measure the probability of a team winning any game based on the seeds of the two teams involved. The logistic regression formula, based on 1,686 games (including Sunday's results), is this:

Expected W% ~ =1 / (1 + EXP(0.1738176 * Seed Diff))

Where Seed Diff is simply the team's seed # minus the opponent's seed #. For instance, when a 4-seed plays a 5-seed, as Texas did Sunday, their seed difference is (4 - 5) = -1, which yields an expected win % of 54.3%. And when a 1-seed (like Pitt) plays an 8-seed (like Butler), the seed difference is -7, giving an expected W% of 77.1%.

Anyway, add all up of these expected wins for every coach's NCAA career, compare to his actual wins, and you can see which coaches have disappointed the most over their post-1985 careers:

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2010-11 NBA power rankings through the games played on March 17, 2011:

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Using Ken Pomeroy's ratings and the log5 formula, I set up a Monte Carlo Simulation and ran the 2011 NCAA Tournament 10,000 times. Here was the most likely bracket:

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2010-11 NBA power rankings through the games played on March 10, 2011:

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I would have written a full summary of my trip to the MIT Sloan Sports Analytics Conference last week, but A) I've been sick this week, and B) the guys at TrueHoop had it covered so well that my efforts would be totally extraneous:

• MIT Sloan Sports Analytics Conference bullets (Tim Varner)
• Malcolm Gladwell and player development (Michael Schwartz)
• The "Data Holy Grail" (Brett Hainline)
• The problem with macho decisions in hoops (Zach Harper)
• Basketball brains diagnose the Heat (Tom Haberstroh)
• Sports and Labor panel addresses broader issue of NBA profit (Graydon Gordian)
• Is sports franchise ownership a hobby for the rich? (Harper)
• The duller side of the statistical cutting edge (Rob Mahoney)
• Sounding the whistle on referee analytics (Kevin Arnovitz)
• How much trouble is early foul trouble? (Brian Robb)
• Gut vs. data in NBA decision making (Sebastian Pruiti)
• Bullets from the basketball analysis panel (Scott Sereday)
• Brain mapping: the future of scouting (Beckley Mason)
• A championship four years in the making (Ryan DeGama)
• Mark Cuban hopes to lose and, lose badly, someday (Varner)
• Player evaluation and motion capture technology (Bret LaGree)
• Dynamic Efficiency, the Nash Equilibrium, and Kobe as an undershooter (Devin Kharpertian)
• Futurism and coaching (Mason)
• Social media and the business of sports (Schwartz)
• The heart of sports (Henry Abbott)
• Almost clever (Ethan Sherwood Strauss)

It was such a blast to meet those guys, btw. You haven't lived until you've been out partying with stat geeks until 2:30 AM.

I'd be remiss if I didn't also link to Kevin Pelton's recap at Basketball Prospectus:

Recapping Sloan: Two Key Issues

And don't forget Ben Morris' summary at Skeptical Sports Analysis. Or Deadspin's "Dispatches From Dorkapalooza".

Finally, you can read all of the tweets I sent out as I covered the panels live via the Basketball-Reference Twitter stream:

Basketball Reference (bball_ref) on Twitter

Let me know if I'm forgetting anybody's recap/summary, and I'll add them to the list.

The close-game struggles of this year's Miami Heat are nothing if not well-documented. A 5-13 record in games decided by 5 or fewer points has become the team's defining stat, far surpassing LeBron James' gaudy all-around numbers or the scoring brilliance of Dwyane Wade. As far as the mainstream media is concerned, it is now assumed this team will choke until they prove otherwise.

As statheads, we typically detest this sort of cliched, pseudo-psychological nonsense. Part of the sabermetric orthodoxy is to deny the existence of "clutch skills", or at least to minimize them relative to overall factors that impact every minute of the game. But with the Heat so dominant in blowouts and so vulnerable in close games, perhaps there is something to the old sportswriter aphorisms about certain teams being unable to close the deal when the margin gets tight.

As mentioned earlier, Miami is 5-13 (.278) in games decided by 5 points or fewer, while they sport a sterling 38-7 (.844) mark in games decided by 6 or more points. The Heat now have the biggest differential in NBA history between wpct in games decided by 6+ pts and games decided by 5 or fewer:

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You can follow my tweets from the MIT Sloan Sports Analytics Conference at the BBR Twitter feed:

Basketball Reference (bball_ref) on Twitter

Also, you can follow everyone's tweets by searching for the #ssac tag.