Application of PageRank Algorithm to Division I NCAA men’s basketball as bracket formation and outcome predictive utility

Author:

Matthews Nicole R.1,McClain Andrew1,Smith Chase M.L.2,Tennant Adam G.3

Affiliation:

1. Business and Engineering Center, University of Southern Indiana, University Boulevard, Evansville, IN, USA

2. Assistant Professor of Sport Management, Health Professions Center, University of Southern Indiana, University Boulevard, Evansville, IN, USA

3. Assistant Professor Engineering, Business and Engineering Center, University of Southern Indiana, University Boulevard, Evansville, IN, USA

Abstract

This article examines the use of the PageRank algorithm to rank the teams and predict team performance in the tournament. This method has the potential to be utilized as an alternative method to choose tournament participants, as opposed to the traditional ranking and seeding process currently employed by the NCAA. PageRank allows for the consideration of all games played during the regular season (average of 5832 games per season) and for customizable performance weights in the prediction. The PageRank algorithm is a viable tool in predicting tournament outcomes due to depth and extensiveness of the data. The PageRank analysis helped to predict over half of the tournament game outcomes correctly in 2014-2018 and produced an average bracket score of 81.8 points out of 192 possible over the same 5 years.

Publisher

IOS Press

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Algorithm Analysis of Trade Gravity Model Based on PageRank Algorithm;2023 International Conference on Electronics and Devices, Computational Science (ICEDCS);2023-09-22

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