Wednesday, March 14, 2012

Using Graph Theory To Predict NCAA Tournament Outcomes

Some problems I see. Disclaimer: I know there's a margin of error here as the author said, and I know my observations will be based largely on anecdotal evidence, making it inferior. But if sports were so easy to predict there would be no sports gambling.

- That's probably too far for Belmont; a #14 has only ever gotten as far as the Sweet 16, twice (Cleveland State '86, Chattanooga '97). Lowest seed to make an Elite 8 is Missouri in 2002 as a #12 . Belmont is actually going to be one of the more popular upset picks, but they would have to upset two far superior teams twice in 3 days.

- It's a bit too "chalk". #1 seeds generally survive the first two games (undefeated against #16's, 55-14 v. #8's, 59-6 v. #9's), but the #2's have it worse (only four losses v. #15's, but 58-21 v. #7's and 29-21 v. #10's). I know two #12's, a #13 and a #14 doesn't seem like "chalk" but historically it's much more likely that we'll see more #5-7 or #10-11's. To have only one #2 not make the Elite 8 and all the #1's would be almost unheard of.

- A #12 always beats a #5, but three of them doing so in one year would seem unlikely, as they're only 39-89 overall.

- Some of the other first round matchups seem a bit improbably. It has every #6 and every #7 winning, for example.

Source: http://rss.slashdot.org/~r/Slashdot/slashdotScience/~3/pAq1a_aplY8/using-graph-theory-to-predict-ncaa-tournament-outcomes

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