Alternative ranking measures to predict international football results

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Demartino, Roberto Macrì, Egidi, Leonardo, Torelli, Nicola
Format: Preprint
Published: 2024
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866910746585071616
author Demartino, Roberto Macrì
Egidi, Leonardo
Torelli, Nicola
author_facet Demartino, Roberto Macrì
Egidi, Leonardo
Torelli, Nicola
contents Over the last few years, there has been a growing interest in the prediction and modelling of competitive sports outcomes, with particular emphasis placed on this area by the Bayesian statistics and machine learning communities. In this paper, we have carried out a comparative evaluation of statistical and machine learning models to assess their predictive performance for the 2022 FIFA World Cup and for the 2023 CAF Africa Cup of Nations by evaluating alternative summaries of past performances related to the involved teams. More specifically, we consider the Bayesian Bradley-Terry-Davidson model, which is a widely used statistical framework for ranking items based on paired comparisons that have been applied successfully in various domains, including football. The analysis was performed including in some canonical goal-based models both the Bradley-Terry-Davidson derived ranking and the widely recognized Coca-Cola FIFA ranking commonly adopted by football fans and amateurs.
format Preprint
id arxiv_https___arxiv_org_abs_2405_10247
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Alternative ranking measures to predict international football results
Demartino, Roberto Macrì
Egidi, Leonardo
Torelli, Nicola
Applications
Over the last few years, there has been a growing interest in the prediction and modelling of competitive sports outcomes, with particular emphasis placed on this area by the Bayesian statistics and machine learning communities. In this paper, we have carried out a comparative evaluation of statistical and machine learning models to assess their predictive performance for the 2022 FIFA World Cup and for the 2023 CAF Africa Cup of Nations by evaluating alternative summaries of past performances related to the involved teams. More specifically, we consider the Bayesian Bradley-Terry-Davidson model, which is a widely used statistical framework for ranking items based on paired comparisons that have been applied successfully in various domains, including football. The analysis was performed including in some canonical goal-based models both the Bradley-Terry-Davidson derived ranking and the widely recognized Coca-Cola FIFA ranking commonly adopted by football fans and amateurs.
title Alternative ranking measures to predict international football results
topic Applications
url https://arxiv.org/abs/2405.10247