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## Using Graph Theory To Predict NCAA Tournament Outcomes91

New submitter SocratesJedi writes "Like many technically-minded people, I don't have a lot of time to keep up with sports. Nevertheless, trying to predict the outcome of the NCAA men's basketball tournament is a fun activity to share with friends, family and colleagues. This year, I abandoned my usual strategy of quasi-randomly choosing teams and instead modeled the win-loss history of all Division I teams as a weighted network. The network included information from 5242 games played during the 2011-2012 season. From this, teams came be ranked using tools from graph theory and those rankings can be used to predict tournament outcomes. Without any a priori information, this method accurately identified all the #1 seeds in the top 5 best teams. It also predicts that at least one underdog, Belmont (#14 seed), will reach the Elite Eight. Although the ultimate test will be how well it predicts tournament outcomes, initial benchmarks suggest 70-80% accuracy would not be unreasonable."
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## Using Graph Theory To Predict NCAA Tournament Outcomes

• #### 70-80%? (Score:2, Informative)

by Anonymous Coward on Tuesday March 13, 2012 @09:15AM (#39337703)

Okay, you can get 50% accuracy just by flipping a coin.
If you go with "the higher seed wins", you get to 85% or so. Color me unimpressed.

• #### Re:70-80%? (Score:5, Informative)

on Tuesday March 13, 2012 @09:20AM (#39337755) Journal

And my numbers are off. In 2011, 43 times out of 63, the lower seed won for about a 68% win rate.

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