Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Phylourny: Predicting the Knock-out-phase of Tournaments via Phylogenetic Methods by example of the UEFA EURO 2020

View ORCID ProfileBen Bettisworth, View ORCID ProfileAlexandros Stamatakis
doi: https://doi.org/10.1101/2021.06.24.449715
Ben Bettisworth
1Computational Molecular Evolution Group, Heidelberg Institute for Theoretical Studies
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Ben Bettisworth
Alexandros Stamatakis
1Computational Molecular Evolution Group, Heidelberg Institute for Theoretical Studies
2Institute for Theoretical Informatics, Karlsruhe Institute of Technology
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Alexandros Stamatakis
  • For correspondence: alexandros.stamatakis@h-its.org
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Data/Code
  • Preview PDF
Loading

Abstract

The prediction of knock-out tournaments represents an area of large public interest and active academic as well as industrial research. Here, we leverage the computational analogies between calculating the so-called phylogenetic likelihood score used in the area of molecular evolution and efficiently calculating, instead of approximating via simulations, the exact per-team winning probabilities, given a pairwise win probability matrix P. We implement and make available our method as open-source code and deploy it to calculate the winning probabilities for all teams participating at the knock-out phase of the UEFA EURO 2020 football tournament. We use three different P matrices to conduct predictions, two inferred via our own simple method and one computed by experts in the field. According to this expert P matrix which we trust most, we find that the most probable final is France versus England and that England has a slightly higher probability to win the title. The ability to efficiently and exactly compute winning probabilities, apart from improving and accelerating predictions, might allow for the development of novel methods to compute P.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Amongst all unimportant subjects, football is by far the most important. Pope John Paul II

  • https://cme.h-its.org/exelixis/resource/download/phylourney-data.tar.bz2

  • https://github.com/computations/phylourny

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted June 25, 2021.
Download PDF
Data/Code
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Phylourny: Predicting the Knock-out-phase of Tournaments via Phylogenetic Methods by example of the UEFA EURO 2020
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Phylourny: Predicting the Knock-out-phase of Tournaments via Phylogenetic Methods by example of the UEFA EURO 2020
Ben Bettisworth, Alexandros Stamatakis
bioRxiv 2021.06.24.449715; doi: https://doi.org/10.1101/2021.06.24.449715
Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
Citation Tools
Phylourny: Predicting the Knock-out-phase of Tournaments via Phylogenetic Methods by example of the UEFA EURO 2020
Ben Bettisworth, Alexandros Stamatakis
bioRxiv 2021.06.24.449715; doi: https://doi.org/10.1101/2021.06.24.449715

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Bioinformatics
Subject Areas
All Articles
  • Animal Behavior and Cognition (4382)
  • Biochemistry (9591)
  • Bioengineering (7090)
  • Bioinformatics (24856)
  • Biophysics (12600)
  • Cancer Biology (9956)
  • Cell Biology (14349)
  • Clinical Trials (138)
  • Developmental Biology (7948)
  • Ecology (12105)
  • Epidemiology (2067)
  • Evolutionary Biology (15988)
  • Genetics (10925)
  • Genomics (14738)
  • Immunology (9869)
  • Microbiology (23659)
  • Molecular Biology (9484)
  • Neuroscience (50856)
  • Paleontology (369)
  • Pathology (1539)
  • Pharmacology and Toxicology (2681)
  • Physiology (4013)
  • Plant Biology (8657)
  • Scientific Communication and Education (1508)
  • Synthetic Biology (2394)
  • Systems Biology (6433)
  • Zoology (1346)