The Determinants of International Football Success: A Panel Data Analysis of the Elo Rating*

Abstract

Objectives. This article investigates the determinants of football 1 success at the international level. We introduce three innovations as (a) we apply the model developed by Bernard and Busse (2004) to football, (b) we consider a wide panel of countries over a 33-year period, and (c) we supplement FIFA's classification with the Elo rating system. Methods. We estimate a dynamic panel model using Blundell and Bond's (1998) system-generalized method of moments (GMM) estimator. Results. The results are robust to several sensitivity analyses, showing that economics, demographics, weather, geography, and football institutions are good indicators of football success at the international level. Besides, the Elo rating is a better alternative indicator than the FIFA ranking. Conclusions. The Elo rating may be used in the academic works that wish to analyze football success over a long period of time.

A football player rating system

“…For women, the rankings are formed in this way since their introduction in 2003 (FIFA 2020a). Yet in 2013, Lasek et al (2013) found that an Elo-based system for team performance prediction works best and outperforms the one used by FIFA for Men's National Teams at that time; the same claim has been made by Gásquez & Royuela (2016). The FIFA / Coca-Cola World Ranking for Men's National Teams has been based on the Elo calculation method not until August 2018 (FIFA 2020b).…”

Managing sporting success and economic efficiency in the professional football: Identification of determinant factors through the academic literature

“…Several authors have treated the management of or sporting football success (Guzmán and Morrow, 2007;Gásquez and Royuela, 2016;Pyatunin et al, 2016;Carmichael et …”

“…Sport is one of the most diverse business industries in the world, having a massive global effect (Parks and Quarterman, 2003;Gásquez and Royuela, 2016). It has been practically an integral part of mankind since the founding of the first social organizations (Sportcal, 2016), being considered as a productive sector with multidisciplinary characteristics that has become a complex phenomenon influencing the society due to its enormous dimensions and heterogeneity (AEA, 2002).…”

“…Additionally, football creates, far beyond the economic impact, also social benefits, as follows (Parks and Quarterman, 2003;Commission of the European Communities, 2007;KPMG Sports, 2015;BMWi and BISp, 2015;Gásquez and Royuela, 2016 It is clear, that football is not any longer just a sport that is focused on the sporting success, but rather it has turned into a business with a high economic impact and a significant contribution to the GDP (KPMG Sports, 2015). Football clubs are nowadays much more than being just a simple sport organization, as they have turned into complex business units (Pyatunin et al, 2016;Bács, 2014;Guzmán and Morrow, 2007).…”

Prediction Model for the Africa Cup of Nations 2019 via Nested Poisson Regression

“…In this article the Elo ranking (see http://en.wikipedia.org/wiki/World_Football_Elo_Ratings) is preferably considered instead of the FIFA ranking (which is a simplified Elo ranking since July 2018), since the calculation of the FIFA ranking changed over time and the Elo ranking is more widely used in football forecast models. See also (Gásques and Royuela, 2016) for a discussion on this topic and a justification of the Elo ranking. At the time of this analysis the composition and the line ups of the teams have not been announced and hence the two other covariates are not available.…”