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Activity Number: 227
Type: Contributed
Date/Time: Monday, August 4, 2014 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics in Sports
Abstract #313512 View Presentation
Title: The Perfect Bracket: Machine Learning in NCAA Basketball
Author(s): Sara Stoudt*+ and Loren Santana and Ben S. Baumer
Companies: Smith College and Smith College and Smith College
Keywords: sports ; basketball ; R ; machine learning ; ensemble method

Warren Buffett's 1 billion dollar prize for the perfect 2013 - 2014 NCAA bracket and Kaggle's March Machine Learning Madness competition increased the stakes of predicting this year's tournament results. Adding to the core data given by the Kaggle competition of team wins and loses since 1995 - 1996, we gather other team data to allow for more flexibility and options for modeling. We investigate different ensemble methods in R that contain strategies such as a modified PageRank algorithm, decision trees, neural networks, among others to predict probabilities of different match-ups and create a bracket for this season. We discuss strengths and weaknesses of our approach.

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