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PageRank Approach to Ranking National Football Teams

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arxiv 1503.01331 v2 pith:YA5FGJYB submitted 2015-03-04 cs.SI

Verica Lazova , Lasko Basnarkov This is my paper · ORCID
classification cs.SI
keywords footballworldapproachchampionshipsdataduringgamesgraph
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The Football World Cup as world's favorite sporting event is a source of both entertainment and overwhelming amount of data about the games played. In this paper we analyse the available data on football world championships since 1930 until today. Our goal is to rank the national teams based on all matches during the championships. For this purpose, we apply the PageRank with restarts algorithm to a graph built from the games played during the tournaments. Several statistics such as matches won and goals scored are combined in different metrics that assign weights to the links in the graph. Finally, our results indicate that the Random walk approach with the use of right metrics can indeed produce relevant rankings comparable to the FIFA official all-time ranking board.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Player-Team Heterogeneous Interaction Graph Transformer for Soccer Outcome Prediction

    cs.LG 2025-07 conditional novelty 6.0 of 10

    HIGFormer predicts soccer match outcomes by jointly modeling player-player event interactions and team-team historical win rates with a heterogeneous graph transformer and graph convolution network.

  2. Football is becoming more predictable; Network analysis of 88 thousands matches in 11 major leagues

    physics.soc-ph 2019-08 conditional novelty 6.0 of 10

    Match outcomes in 11 major European football leagues became more predictable between 1993 and 2019, while team inequality rose and home advantage declined.

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