<p>In this study we describe several diagnostic methods for Generalized Estimating Equations approach. The principal idea behind generalized estimating equations is to generalize and extend the usual likelihood score equation for a generalized linear model by including the covariance matrix of the clustered responses. The advantage of generalized estimating equations is that we do not need to specify the whole response distribution, only the mean structure and, with the aim to increase efficiency, the covariance structure consisting of a working correlation matrix along with the variance function defining the mean–variance relationship. The paper investigates, from a methodological point, to the identification of the best subset of variables, considering the link between the coefficient of determination and Wald Statistics. Some diagnostic measures and a simulated envelope for checking the adequacy of GEE method will be presented. In particular, diagnostic measures are considered and applied to a dataset to assess the impact that some economic-financial variables have on the points made by football teams participating in the Series A League.</p>