Tag Archives: Bracketology

Predicting the Madness: 2013 Upset Edition

For the past two years, I have worked on a model that predicts NCAA Tournament upsets using the gospel of tempo-free basketball stats, the Four Factors. Over that time, the model has gone a perfect six for six in predicting … Continue reading

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Survival of the Fittest: A New Model for NCAA Tournament Prediction

(Editor’s note: You can see the model’s 2012 1-68 rankings here and full bracket here) Every year, millions of Americans tune in to watch the NCAA Men’s Basketball Tournament, colloquially known as March Madness. And every year, millions participate in Bracket Pools, where … Continue reading

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2012 NCAA Survival Model Full Rankings

Below is my full Survival Model rankings for the NCAA tournament in 2012. The numbers are tough to interpret, but they represent the relative risk of failing (losing) at a given time period. Lower numbers represent better chances to advance:

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Predicting NCAA Tournament Upsets: The Importance of Turnovers and Rebounding

For the past two years, I have attempted to systematically predict First Round NCAA Tournament upsets using a dataset of match-ups from 2004 onward. Last year, I improved the model by adding opponent Four Factors data, and the model correctly … Continue reading

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Quantifying Intangibles: A New Way to Predict the NCAA Tournament

By John Ezekowitz Each March, college basketball fans looking for help in filling out their NCAA Tournament brackets can go one of two ways: the quantitative, algorithmic route used effectively by sites like Ken Pomeroy and TeamRankings, or the “expert … Continue reading

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The NCAA Tournament Network

By John Ezekowitz and Ben Blatt Now that the bracket is out and fans everywhere are busy trying to find that perfect upset, a lot of attention will be paid rightly to projecting ahead. We thought, however, that it might … Continue reading

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Predicting First Round NCAA Tournament Upsets: New and Improved

By John Ezekowitz (Ed Note: Please use our updated model and predictions for 2012, found here) This time last year, I attempted to create a logistic model that would predict those first round NCAA Tournaments that everyone loves so much. … Continue reading

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Predicting NCAA Tournament Upsets: Favorite Vulnerability

By John Ezekowitz On Tuesday, I looked at predicting upsets in the NCAA Tournament. Today I’m looking at which favorites are vulnerable to upsets. Again, I created a database of NCAA Tournament favorites’ tempo-free stat profiles using KenPom.com’s invaluable data.  … Continue reading

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March Madness for (Statistically Inclined) Dummies

Author note: This article originally appeared on the old HSAC blog around this time last year, back when I was a wee freshman (I am now a no-less-wee sophomore). But because that blog has been lost to the ages, and … Continue reading

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Predicting NCAA Tournament Upsets: The Underdogs

By John Ezekowitz A few weeks ago, when I started analyzing the effects of tempo on NCAA Tournament upsets, I got a crazy idea: what if I could find a model that would predict factors of successful underdogs? I’ve always … Continue reading

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