Archive for the 'Statgeekery' Category

2010-11 NBA power rankings through the games played on November 18, 2010:

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The Miami Heat have been under fire recently for dominating weak foes and losing close games against good teams. The conventional wisdom is that this reveals a major gap in Miami's armor -- they just can't close the deal against stronger opponents.

Is this really true, though? And does it even matter?

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After five straight improbable comeback victories, I thought now would be a good time to post some Win Probability graphs from the Utah Jazz's recent winning streak. For those curious, the method for WP comes from an old Ed Küpfer post at APBRmetrics, and the play-by-play records come from ESPN.com (or FoxSports.com, in the case of Jazz-Heat and Jazz-Bobcats). All WP is from the perspective of Utah, and the numbers at the bottom of the WP graphs represent the minutes remaining in the game.

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2010-11 NBA power rankings through the games played on November 11, 2010:

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Which players are playing better or worse than we would have expected so far this season? Well, let's look at each player's actual Statistical Plus/Minus (SPM) in 2011 vs. what the simple projection system would have predicted their SPM to be. The overachievers:

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See also: #16-20, #21-25, #26-31

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

With the 2010-11 NCAA basketball season technically commencing this week, let's return to these rankings...

15. Connecticut Huskies (+14.16 SRS)

Record: 682-312 (.686)
Prominent Coaches: Jim Calhoun
Best NCAA Finish: Won NCAA Championship (1999, 2004)

Two national titles in the last 12 years makes up for a mediocre first half of the 1980s under Dom Perno, as the leadership of Calhoun has transformed Storrs into an unlikely national hoops hotbed. And to think that it all started with Scott Burrell & Tate George...

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Not sure if I want to make this the new BBR Rankings method or return to maximum likelihood, but these are your team schedule-adjusted offensive & defensive ratings so far in 2011 (negative = good for defenses):

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A somewhat non-basketball-related dispatch from Tango and The Book Blog: Brian MacDonald has written a paper applying Dan Rosenbaum et al's adjusted plus/minus theory to hockey players.

To which I say... Finally! I've been waiting for someone to use that methodology on the sport that popularized the plus/minus stat in the first place. Even though the standard errors are huge (especially for goalies, whose impacts are difficult to disentangle from teammates because they rarely leave the ice), it's still encouraging to see the effort be made.

For now, I'm still partial to the great Tom Awad's Goals Versus Threhold (GVT) as my go-to NHL metric (download the all-time spreadsheet here), but MacDonald's work could have implications for hockey statheads for years down the road. Nice work!

It's that time of year again... Time to plug a ton of projected numbers into a computer, simulate the NBA schedule thousands of times, and see what kind of predictions it spits out. This year I ran three sets of 2,500 simulated seasons -- one based on statistical plus/minus (the raw version of which I posted here, but also adjusted for team using past franchise & coaching histories), one based on Win Shares (using the Simple Projection System method), and one based on a heavily regressed-to-the-mean version of last year's Simple Ratings (not so much for prediction purposes, but as an experiment to see how well the "dumbest" possible projections fare vs. complex methods). To see the individual minutes and ratings that went into these projections, click here.

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In the realm of APBRmetrics, perhaps no stat has as many alternate versions (many under essentially the same confusingly interchangeable name) as "Assist Ratio/Rate". All theoretically attempt to measure passing ability, but each version has its own quirks and biases. Today I want to compare all of the versions I can think of, and show a leaderboard (minimum 500 MP) for each to get a better feel for what each is measuring, starting with...

Assist-to-Turnover Ratio

(Assists / Turnovers)

The granddaddy of all assist-based rate stats, this metric is a mainstay whenever the mainstream media is trying to assess ballhandling and/or passing ability. Obviously it assumes that the positive value of an assist is equal in magnitude to the negative value of a turnover, which isn't necessarily true, and from a functional perspective it rewards turnover avoidance more than passing because as long as you keep the denominator low, even a few cheap assists will give you a decent ATO. While its ease of calculation has made it popular, you can see some of ATO's extreme flaws by looking at the 2009-10 positional leaders:

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