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10th EAI International Conference on Simulation Tools and Techniques

Research Article

PageRank Approach to Ranking Football Teams’ Network

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1145/3173519.3173533,
        author={Boren Wang and Zongwei Luo},
        title={PageRank Approach to Ranking Football Teams’ Network},
        proceedings={10th EAI International Conference on Simulation Tools and Techniques},
        publisher={ACM},
        proceedings_a={SIMUTOOLS},
        year={2018},
        month={8},
        keywords={pagerank; social network; football team ranking},
        doi={10.1145/3173519.3173533}
    }
    
  • Boren Wang
    Zongwei Luo
    Year: 2018
    PageRank Approach to Ranking Football Teams’ Network
    SIMUTOOLS
    ACM
    DOI: 10.1145/3173519.3173533
Boren Wang1,*, Zongwei Luo1
  • 1: Southern University of Science and Technology, Shenzhen, China
*Contact email: wangbr@mail.sustc.edu.cn

Abstract

Football is one of the world’s most favored sports with a huge amount of data that one could inspect, analyze and reach interesting conclusions. In this paper we analyze such football data made available through collecting via world football matches.. Our goal is to rank the teams not just based on directmatch result, but also considering team relationship. For this purpose, we apply the PageRank algorithms with restarting mechanismto a graph built from the games. Several statistics such as matches wining and goals scored are combined in different metrics with 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 yet more meaningful rankings comparable to the official ranking.

Keywords
pagerank; social network; football team ranking
Published
2018-08-02
Publisher
ACM
http://dx.doi.org/10.1145/3173519.3173533
Copyright © 2017–2025 ACM
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