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

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...

Full description

Saved in:
Bibliographic Details
Published in:Mathematics (Basel) 2022-12, Vol.10 (23), p.4587
Main Authors: López-Barrientos, José Daniel, Zayat-Niño, Damián Alejandro, Hernández-Prado, Eric Xavier, Estudillo-Bravo, Yolanda
Format: Article
Language:English
Subjects:
Accuracy
Algorithms
Analysis
Competitions
English Premier League
Football
Forecasts and trends
Hypotheses
inverse transform method
Mexico
Poisson forecasting method
Prediction theory
Random variables
recursive distributions
Russia 2018
Soccer
Tournaments & championships
Élö–Runyan rating system
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:2227-7390
2227-7390
DOI:10.3390/math10234587