A Generalized Estimating Equation in Longitudinal Data to Determine an Efficiency Indicator for Football Teams
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Over the years football has attracted enormous interest from various fields of study, attracting attention both for its sporting and social aspects. Professional business operators consider football an important industry with enormous potential both in terms of its size and growth, and also because of indirect benefits due to the popularity gained by investors and management of football teams. The focus of the analysis has been on what characterizes most football clubs, and determines their particular economic and financial needs. The aim of this paper is to establish an efficiency measurement for football team financial resource allocation. In particular, we analysed the impact that the income statement, Net equity and Team value variables have on the points achieved by football teams playing in “Serie A” championship (Italian league). The method used in our study is a generalized estimating equation (GEE) for longitudinal count data. In addition we consider a coefficient of determination in the GEE approach based on Wald Statistics, and we propose a modified Mallow’s Cp for choosing the best model. Finally we propose an AFRSport index based on the differences between observed and theoretical points, in order to identify those teams that efficiently employ their financial resources.
KeywordsFinancial indicator Generalized estimating equations Best subset CP Mallows
We would like to thanks the anonymous referee for carefully reading our manuscript and for giving such constructive comments which substantially helped improving the quality of the paper.
- Forrester, D., & Simmons, R. (2002). Outcome uncertainty and attendance demand in sport: The Case of English soccer. Journal of the Royal Statistical Society: Series D (The Statistician),51(2), 229–241.Google Scholar
- Hardin, J., & Hilbe, J. (2003). Generalized estimating equations. London: Chapman and Hall.Google Scholar
- Hawkins, D. M., & Wixley, R. A. J. (1986). A note on the transformation of Chi squared variables to normality. The American Statistician,40, 296–298.Google Scholar