On the Élö–Runyan–Poisson–Pearson Method to Forecast Football Matches

José Daniel López-Barrientos, Damián Alejandro Zayat-Niño, Eric Xavier Hernández-Prado, Yolanda Estudillo-Bravo

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

This is a work about football. In it, we depart from two well-known approaches to forecast the outcome of a football match (or even a full tournament) and take advantage of their strengths to develop a new method of prediction. We illustrate the Élö–Runyan rating system and the Poisson technique in the English Premier League and we analyze their accuracies with respect to the actual results. We obtained an accuracy of 84.37% for the former, and 79.99% for the latter in this first exercise. Then, we present a criticism of these methods and use it to complement the aforementioned procedures, and hence, introduce the so-called Élö–Runyan–Poisson–Pearson method, which consists of adopting the distribution that best fits the historical distribution of goals to simulate the score of each match. Finally, we obtain a Monte Carlo-based forecast of the result. We test our mechanism to backcast the World Cup of Russia 2018, obtaining an accuracy of 87.09%; and forecast the results of the World Cup of Qatar 2022.

Original languageEnglish
Article number4587
JournalMathematics
Volume10
Issue number23
DOIs
StatePublished - 1 Dec 2022

Keywords

  • English Premier League
  • inverse transform method
  • Poisson forecasting method
  • Qatar 2022
  • recursive distributions
  • Russia 2018
  • Élö–Runyan rating system

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