Title: Ranking football teams with AHP and TOPSIS methods

Authors: Reza Kiani Mavi; Neda Kiani Mavi; Leila Kiani

Addresses: Department of Industrial Management, Faculty of Management and Accounting, Qazvin Branch, Islamic Azad University (IAU), Nokhbegan Street, Qazvin, 34185-1416, Iran. ' Department of Physical Education and Sport Science, Faculty of Management and Accounting, Qazvin Branch, Islamic Azad University (IAU), Nokhbegan Street, Qazvin, 34185-1416, Iran. ' Department of Science, Faculty of Engineering, Miyaneh Branch, Islamic Azad University (IAU), Zeinabiieh Street, Miyaneh, 53158-36511, Iran

Abstract: Managers continually seek improved methods to measure the performance of their organisations because they are committed to improve efficiency and effectiveness in their operating units. The sporting performance of professional football teams has often been assessed considering their results in the major regular competition, namely the national league. On the other hand, ranking teams is a multi-criteria decision-making (MCDM) problem. Therefore by taking data for the season 1999/2000 from Haas et al. (2004) we study the efficiency of football teams in the German Bundesliga by MCDM techniques. Based on the analytic hierarchy process (AHP) and the technique for order preferences by similarity to ideal solution (TOPSIS), this paper applies an MCDM approach to evaluate the performance of football teams in the German Bundesliga. The non-parametric Spearman test of relationship (rs) and the Kendall's Tau test (τ) of correlation verify the results of DEA and TOPSIS.

Keywords: analytical hierarchy process; AHP; multicriteria decision making; MCDM; sport; TOPSIS; order preference; similarity; ideal situations; football teams; managers; performance measurement; efficiency; effectiveness; operating units; sporting performance; professional football; match results; sporting competitions; national leagues; German Bundesliga; football leagues; Germany; professional football; association football; Spearman's rank correlation coefficient; Spearman's rho; Charles Spearman; non-parametric measures; Kendall's tau coefficient; measured quantities; non-parametric hypothesis tests; statistical dependence; data rankings; Maurice Kendall; decision sciences; risk management.

DOI: 10.1504/IJDSRM.2012.046620

International Journal of Decision Sciences, Risk and Management, 2012 Vol.4 No.1/2, pp.108 - 126

Received: 18 Mar 2011
Accepted: 27 Nov 2011

Published online: 02 May 2012 *

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