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

José Daniel López-Barrientos (), Damián Alejandro Zayat-Niño, Eric Xavier Hernández-Prado and Yolanda Estudillo-Bravo
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José Daniel López-Barrientos: Facultad de Ciencias Actuariales, Universidad Anáhuac México, Naucalpan de Juárez 52786, Mexico
Damián Alejandro Zayat-Niño: Facultad de Ciencias Actuariales, Universidad Anáhuac México, Naucalpan de Juárez 52786, Mexico
Eric Xavier Hernández-Prado: Facultad de Ciencias Físico-Matemáticas, Benemérita Universidad Autónoma de Puebla, Puebla 72000, Mexico
Yolanda Estudillo-Bravo: Facultad de Ciencias Físico-Matemáticas, Benemérita Universidad Autónoma de Puebla, Puebla 72000, Mexico

Mathematics, 2022, vol. 10, issue 23, 1-29

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.

Keywords: Élö–Runyan rating system; Poisson forecasting method; inverse transform method; recursive distributions; English Premier League; Russia 2018; Qatar 2022 (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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