An application of Google’s PageRank to NFL rankings

Laurie Zack; Ron Lamb; Sarah Ball

doi:10.2140/involve.2012.5.463

An application of Google’s PageRank to NFL rankings

Laurie Zack
, Ron Lamb
, Sarah Ball

Mathematics and Statistics

High Point University

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

We explain the PageRank algorithm and its application to the ranking of football teams via the GEM method. We then modify and extend the GEM method with the addition of more football statistics to look at the possibility of using this method to more accurately rank teams. Lastly, we compare both methods by aggregating each statistical ranking using the cross-entropy Monte Carlo algorithm.

Original language	English
Pages (from-to)	463-471
Number of pages	9
Journal	Involve
Volume	5
Issue number	4
DOIs	https://doi.org/10.2140/involve.2012.5.463
State	Published - Jan 1 2012

Keywords

linear algebra
PageRank algorithm
ranking football teams

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10.2140/involve.2012.5.463

Cite this

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abstract = "We explain the PageRank algorithm and its application to the ranking of football teams via the GEM method. We then modify and extend the GEM method with the addition of more football statistics to look at the possibility of using this method to more accurately rank teams. Lastly, we compare both methods by aggregating each statistical ranking using the cross-entropy Monte Carlo algorithm.",

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An application of Google’s PageRank to NFL rankings

Abstract

Keywords

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