Pesquisa Operacional (2012) 32(1): 21-29 © 2012 Brazilian Operations Research Society Printed version ISSN 0101-7438 / Online version ISSN 1678-5142 www.scielo.br/pope A DEA MODEL WITH A NON DISCRITIONARY VARIABLE FOR OLYMPIC EVALUATION Jo˜ ao Carlos C.B. Soares de Mello * , Lidia Angulo-Meza and F´ abio Gomes Lacerda Received December 10, 2009 / Accepted February 15, 2011 ABSTRACT. In recent years, a lot of work has been done dealing with alternative performance rankings for the Olympic Games. Almost all of these works use Data Envelopment Analysis (DEA). Generally speaking, those works can be divided into two categories: Pure rankings with unitary input models and relative rankings with classical DEA models; both output oriented. In this paper we introduce an approach taking into account the number of athletes as a proxy to the country investment in sports. This number is an input for a DEA model, and the other input is the population of the country. We have three outputs, the number of gold, silver and bronze medals earned by each country. Contrary to the usual approach in the literature, our model is not output oriented. It is a non-radial DEA model oriented to the “number of athletes” input, as our goal is not a countries’ ranking. We intend to analyse whether the number of athletes competing for each country accords with the number of won medals. For this analysis, we compare each country with its benchmarks. The Decision Making Units (DMU) are all the countries participating in the Beijing Olympic Games, including those that did not earn a single medal. We use a BCC model and we compare each DMU’s target with the number of athletes who have won, at least one medal. Keywords: Data Envelopment Analysis, olympic games, sport evaluation. 1 INTRODUCTION Performance evaluation has been widely studied in sport for the last 25 years (Nevill et al., 2008). In the case of the Olympic Games the rank of the nations is traditionally carried out with the so- called Lexicographic Multicriteria Method (Lins et al., 2003). In this very paper the drawbacks of the Lexicographic Method are pointed out and a new ranking is suggested. There are already some other approaches using Data Envelopment Analysis (Charnes et al., 1978). The very first one was proposed by Lozano et al. (2002). They used population and GNP as inputs and the medals as outputs. In a similar approach, Lins et al. (2003) built a new *Corresponding author Departamento de Engenharia de Produc ¸˜ ao, Universidade Federal Fluminense. E-mail: jcsmello@pq.cnpq.br