Document Type: Research Paper


Department of Industrial Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran


Football is one of the most popular and exciting sports fields throughout the world. Today, in addition to the result, the number of goals and points, attraction and quality of the played matches are important for club management staff, coaching staff, the players and especially the fans. Beside number of goals, there are different criteria such as successful passes, attacks, defenses, tackles and etc. can determine the quality of matches. Therefore, in this survey, researchers consider the quality of World Cup 2014 football matches. For this purpose, after the review on research literature, the quality criteria of football matches are determined. Afterward, related data of each criterion are extracted. Then, the DEA common weight analysis (DEA-CWA) is used in order to evaluate and rank the quality of competitions. Results show that the match between the national teams of Argentina and Nigeria was elected as the highest-quality match in Brazil's 2014 World Cup first round.


Main Subjects

Arabzad, S. M., Ghorbani, M., & Shahin, A. (2013). Ranking players by DEA the case of English Premier League. International Journal of Industrial and Systems Engineering15(4), 443-461.

Arabzad, S. M., Ghorbani, M., & Shirouyehzad, H. (2014). A new hybrid method for seed determination in sport competitions: the case of European Football Championship 2012. International Journal of Industrial and Systems Engineering17(3), 259-274.

Arabzad, S. M., Tayebi Araghi, M. E., Sadi-Nezhad, S., & Ghofrani, N. (2014). Football match results prediction using artificial neural networks; the case of Iran Pro League. Journal of Applied Research on Industrial Engineering1(3), 159-179.

Boscá, J. E., Liern, V., Martínez, A., & Sala, R. (2009). Increasing offensive or defensive efficiency? An analysis of Italian and Spanish football. Omega37(1), 63-78.

Calôba, G. M., & Lins, M. P. E. (2006). Performance assessment of the soccer teams in Brazil using DEA. Pesquisa Operacional26(3), 521-536.

Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European journal of operational research2(6), 429-444.

Chitnis, A., & Vaidya, O. (2014). Performance assessment of tennis players: Application of DEA. Procedia-Social and Behavioral Sciences133, 74-83.

de Mello, S., Baptista, J. C. C., Meza, L. A., & Silva, B. B. D. (2008). Some rankings for the Athens Olympic Games using DEA models with a constant input. Investigação Operacional28(1), 77-89.

Douvis, I., & Barros, C. P. (2008). Comparative Analysis of Football Efficiency Among Two Small European Countries: Portugal and Greece. Choregia4(1).

Hosseinzadeh Lotfi, F., Jahanshahloo, G. R., & Memariani, A. (2000). A method for finding common set of weights by multiple objective programming in data envelopment analysis. Southwest Journal of Pure and Applied Mathematics [electronic only]2000(1), 44-54.

Jahanshahloo, G. R., Memariani, A., Lotfi, F. H., & Rezai, H. Z. (2005). A note on some of DEA models and finding efficiency and complete ranking using common set of weights. Applied mathematics and computation166(2), 265-281.

Kao, C. (2010). Malmquist productivity index based on common-weights DEA: The case of Taiwan forests after reorganization. Omega38(6), 484-491.

Kern, A., Schwarzmann, M., & Wiedenegger, A. (2012). Measuring the efficiency of English Premier League football: A two-stage data envelopment analysis approach. Sport, Business and Management: an International Journal, 2(3), 177-195.

Kornbluth, J. S. H. (1991). Analysing policy effectiveness using cone restricted data envelopment analysis. Journal of the Operational Research Society42(12), 1097-1104.

Liu, F. H. F., & Peng, H. H. (2008). Ranking of units on the DEA frontier with common weights. Computers & Operations Research35(5), 1624-1637.

 Makuei, A., Alinezhad, A., KIANI, M. R., & Zohrehbandian, M. (2008). A goal programming method for finding common weights in DEA with an improved discriminating power for efficiency.

Roll, Y., Cook, W. D., & Golany, B. (1991). Controlling factor weights in data envelopment analysis. IIE transactions23(1), 2-9.

Shannon, C. E. (1948). A mathematical theory of communication (parts I and II). Bell System technical journal, 379-423.

Soleimani-Damaneh, J., Hamidi, M., & Sajadi, H. (2011). Evaluating the performance of Iranian football teams utilizing linear programming. American Journal of Operations Research1(02), 65.

Tiedemann, T., Francksen, T., & Latacz-Lohmann, U. (2011). Assessing the performance of German Bundesliga football players: a non-parametric metafrontier approach. Central European Journal of Operations Research19(4), 571-587.

Valério, R. P., & Angulo-Meza, L. (2013). A data envelopment analysis evaluation and financial resources reallocation for Brazilian olympic sports. WSEAS Transactions on Systems12(12), 627-636.

Wang, Y. M., Luo, Y., & Lan, Y. X. (2011). Common weights for fully ranking decision making units by regression analysis. Expert Systems with Applications38(8), 9122-9128.