Ramón Sala

The Spanish Football Crisis

Abstract This article analyses the economic results of Spanish professional football teams using data collected over the past few years. These data differ substantially from the information presented in the annual reports of the “Liga de Fútbol Profesional” (Spanish professional football league), which are obtained from the initial budgets elaborated each season. Special attention is paid to the two most important teams in the Spanish league: Real Madrid and FC Barcelona. The results of this research show that Spanish football has the same problems as those evidenced by the Italian and English football leagues and, therefore, requires similar solutions in order to be able to survive in forthcoming years.

RANKING DECISION MAKING UNITS BY MEANS OF SOFT COMPUTING DEA MODELS

This paper presents a method for ranking a set of decision making units according to their level of efficiency and which takes into account uncertainty in the data. Efficiency is analysed using fuzzy DEA techniques and the ranking is based on the statistical analysis of cases that include representative situations. The method enables the removal of the sometimes unrealistic hypothesis of a perfect trade-off between increased inputs and outputs. This model is compared with other DEA models that work with imprecise or fuzzy data. As an illustration, we apply our ranking method to the evaluation of a group of Spanish seaports, as well as teams playing in the Spanish football league. We compare the results with other methods and we show that our method enables a total ranking of the seaports, and that the ranking of football teams is found to be more consistent with final league positions.

Updating input–output matrices: assessing alternatives through simulation

A problem that frequently arises in economics, demography, statistics, transportation planning and stochastic modelling is how to adjust the entries of a matrix to fulfil row and column aggregation constraints. Biproportional methods in general and the so-called RAS algorithm in particular, have been used for decades to find solutions to this type of problem. Although alternatives exist, the RAS algorithm and its extensions are still the most popular. Apart from some interesting empirical and theoretical properties, tradition, simplicity and very low computational costs are among the reasons behind the great success of RAS. Nowadays computer hardware and software have made alternative procedures equally attractive. This work analyses, through simulation, the performance of RAS and some minimands when matrix coefficients vary following different schemes of change. Results suggest RAS algorithm as the best option when variations in coefficients are proportional to their size, while the method based on minimizing squared differences is seen to be the best alternative when the standard deviations of variations are either constant, variable, or an inverse function of matrix entries.

Fuzzy Linear Programming in Practice: An Application to the Spanish Football League

FLP problems are perhaps one of the most and best studied topics of Soft Computing, and are among the most fruitful in applications and in theoretical and practical results. Areas of application of FLP problems are many and varied and in fact suppose an extraordinary example of technology transfer in action. In this paper, Fuzzy Linear Programming models are applied to the European football game in which the inherent uncertainty of the parameters relating to the football teams in the Spanish Football League serve to establish these models and so optimize the returns of the investments made to maintain a high quality competition. In this context, fuzzy DEA models are established which provide teams predictions as to their efficiency score. At the end of the study we offer some experiments using data from the Spanish Football League 2006/07.

A Portfolio Problem with Uncertainty

In this paper we present two models for cash flow matching with an uncertain level of payments at each due date. To solve the problem of minimising the initial investment we use the scenario method proposed by Dembo, and the robust optimisation method proposed by Mulvey et al. We unify these optimisation methods in a general co-ordinated model that guarantees a match under every scenario. This general model is also a multi-objective programming problem. We illustrate this methodology in a problem with several scenarios.