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Using graph theory to predict NCAA tournament outcomes

SocratesJedi (986460) writes | more than 2 years ago

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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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