A comprehensive review of data envelopment analysis (DEA). Approach in sports

Zahoor Ul Haq Bhat, Sultana D, Qaiser Farooq Dar

Abstract


Data Envelopment Analysis (DEA) is a deterministic mathematical programming technique, evaluates the performance and benchmarking of decision-making units (DMUs) with several inputs and outputs. DEA, in addition to public and private sectors, finds application in the sports setting. As a result, a significant number of papers have been published that determine the athletic/economic/managerial efficiency by DEA in various games. In this paper, we present an extensive study on the application of various models of DEA in the following games: Baseball, Basketball, Cricket, Cycling, Football, Golf, Handball, Olympics, and Tennis. It is found that DEA identified the sources of inefficiency in different team and individual games by means of benchmarking analysis and provided possible directions for improvement.    


Keywords


Data Envelopment Analysis; Sports; Efficiency; Decision Making Units

Full Text:

PDF

References


Amin, G. R. & Sharma, S. (2017). Cricket team selection using data envelopment analysis. European Journal of Sport Science, 14(S1), 369–376.

Anderson, T. R. (2004). Benchmarking in sports bonds or ruth: Determining the most dominant baseball batter. In Cooper, W. W., Seiford, L. M. & ZhuIn, J. (Eds.) Handbook on Data Envelopment Analysis, pp. 443–454.

Anderson, T. R. & Sharp, G. P. (1997). A new measure of baseball batters using DEA. Annals of Operations Research, 73, 141–155.

Avkiran, N. K. (1999). An Application Reference for Data Envelopment Analysis in Branch Banking: helping the novice researcher. International Journal of Bank Marketing, 17(5), 206–220.

Banker, R. D., Charnes, A., & Cooper, W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 30(9), 1078–1092.

Barros, C. P., Assaf, A. & Sa-Earp, F. (2010). Brazilian football league technical efficiency : A Simar and Wilson approach. Journal of Sports Economics, 11(6), 641–651.

Barros, C. P. & Garcia-del-Barrio, P. (2011). Productivity drivers and market dynamics in the Spanish first division football league. Journal of Productivity Analysis, 35(1), 5–13.

Barros, C. P. & Leach, S. (2006). Performance evaluation of the English Premier Football League with data envelopment analysis. Applied Economics, 38(12), 1449–1458.

Boscá, J. E., Liern, V., Martínez, A., & Sala, R. (2009). Increasing offensive or defensive efficiency ? An analysis of Italian and Spanish football. Omega, 37(1), 63–78.

Calôba, G. M. T Lins, M. P. E. (2006). Performance assessment of the soccer teams in Brazil using DEA. Pesquisa Operacional, 26(3), 521–536.

Charnes, A. & Cooper, W. (1962). Programming With Linear fractional Functionals. Naval Research Logistics, 9(3–4), 181–186.

Charnes, A., Cooper, W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429–444.

Chen, W.-C. & Johnson, A. L. (2010). The dynamics of performance space of Major League Baseball pitchers 1871 – 2006. Annals of Operations Research, 181(1), 287–302.

Chitnis, A. & Vaidya, O. (2014). Performance assessment of tennis players: Application of DEA. Procedia - Social and Behavioral Sciences, 133, 74–83.

Churilov, L. & Flitman, A. (2006). Towards fair ranking of Olympics achievements: the case of Sydney 2000. Computers and Operations Research, 33(7), 2057–2082.

Coelli, T. J. et al. (2005) An Introduction to Efficiency and Productivity Analysis.

Cooper, W. W., Ruiz, L., & Sirvent, I. (2009). Selecting Non-zero Weights to Evaluate Effectiveness of Basketball Players With DEA. European Journal of Operational Research, 195(2), 563–574.

Djordjević, D. P., Vujošević, M., & Martić, M. (2015). Measuring efficiency of football teams by multi-stage dea model. Technical Gazette, 22(3), 763–770.

Doble, M. (1995). Measuring And Improving Technical Efficiency In Uk Post Office Counters by DEA. Annals of Public and Cooperative Economics, 66(1), 31–64.

Douvis, I. T. & Barros, C. P. (2008). Comparative Analysis of football efficiency among two small european countries: portugal and greece. Choregia, 4(1), 6-31.

emrouznejad, A. & Yang, G. (2018). A survey and analysis of the first 40 years of scholarly literature in DEA : 1978-2016. Socio-Economic Planning Sciences, 61, 4–8.

Espitia-Escuer, M. & García-Cebrián, I. (2006). Performance in sports teams: results and potential in the professional soccer league in Spain. Management Decision, 44(8), 1020–1030.

Espitia-escuer, M. & García-cebrián, L. I. (2010). Measurement of the efficiency of football teams in the champions league. Managerial and Decision Economics, 31(6), 373–386.

Espitia-Escuer, M. and García-Cebrián, L. I. (2004) ‘Measuring the efficiency of spanish first-division soccer teams’, Journal of Sports Economics, 5(4), 329–346.

Farrell, M. . (1957). The Measurement of Productive. Journal of the Royal Statistical Society, 120(3), 253–290.

Flégl, M. (2014). Performance Analysis During the 2014 FIFA World Cup Qualification. The Open Sports Sciences Journal, 7(1), 183–197.

Fried, H. O., Lambrinos, J., & Tyner, J. (2004). Evaluating the performance of professional golfers on the PGA , LPGA and SPGA tours. European Journal of Operational Research, 154(2), 548–561.

García-Sánchez, I. M. (2007). Efficiency and effectiveness of Spanish football teams : a three-stage-DEA approach. Central European Journal of Operations Research, 15(1), 21–45.

Glass, A. J. & Kenjegalieva, K. (2015). Game , set and match : evaluating the efficiency of male professional tennis players. Journal of Productivity Analysis, 43(2), 119–131.

Gonzalez-Gomez, F. & Picazo-Tadeo, A. J. (2010). Can we be satisfied with our football team ? evidence from spanish professional football. Journal of Sports Economics, 11(4), 418–442.

Gutierrez, O. & Ruiz, J. L. (2013a). Data envelopment analysis and cross-efficiency evaluation in the management of sports teams: The Assessment of Game Performance of Players in the Spanish Handball League. Journal of Sport Management, 27(3), 217–229.

Gutierrez, O. & Ruiz, J. L. (2013b). Game performance versus competitive performance in the world championship of handball 2011. Journal of Human Kinetics, 36(1), 137–147.

Guzmán, I. & Morrow, S. (2007). Measuring efficiency and productivity in professional football teams : evidence from the English Premier League. Central European Journal of Operations Research, 15(4), 309–328.

Haas, D. J. (2003a). Productive efficiency of english football teams-a data envelopment analysis approach. Managerial and Decision Economics, 24(5), 403–410.

Haas, D. J. (2003b). Technical efficiency in the major league soccer. Journal of Sports Economics, 4(3), 203–215.

Haas, D., Kocher, M., & Sutter, M. (2004). Measuring efficiency of german football teams by data envelopment analysis. Central European Journal of Operations Research, 12(3), 251–268.

Howard, L. W. & Miller, J. L. (1993). Fair pay for fair play: estimating pay equity in professional baseball with data envelopment aanalysis. The Academy of Management Journal, 36(4), 882–894.

Jardin, M. (2009). Efficiency of French football clubs and its dynamics. Munich Personal RePEc Archive, (19828). https://mpra.ub.uni-muenchen.de/19828/1/MPRA_paper_19828.pdf

Kang, J. H., Lee, Y. H., & Sihyeong, K. (2007). Evaluating management efficiency of korean professional baseball teams using data envelopment analysis (DEA). Journal of Sport and Health Science, 5, 125–134.

Kern, A., Schwarzmann, M., & Wiedenegger, A. (2012). Measuring the efficiency of English Premier League football. Sport, Business and Management: an International Journal, 2(3), 177–195.

Kulikova, L. I. & Goshunova, A. V. (2014). Efficiency measurement of professional football clubs: a non-parametric approach. Life Science Journal, 11(11), 117–122.

Lee, B. & Worthington, A. (2013). A note on the “linsanity” of measuring the relative efficiency of national basketball association (NBA) guards. Applied Economics, 45(29), 4193–4202.

Lei, X., Li, Y., Xie, Q., & Liang, L. (2015). Measuring Olympics achievements based on a parallel DEA approach. Annals of Operations Research, 226(1), 379–396.

Lewis, H. F., Lock, K. A., & Sexton, T. R. (2009). Organizational capability , efficiency , and effectiveness in Major League Baseball: 1901 – 2002. European Journal of Operational Research, 197(2), 731–740.

Lewis, H. F., Sexton, T. R., & Lock, K. A. (2007). Player salaries, organizational efficiency & competitiveness in major league baseball. Journal of Sports Economics, 8(3), 266–294.

Li, Y., Liang, L., Chen, Y., & Morita, H. (2008). Models for measuring and benchmarking olympics achievements. Omega, 36(6), 933–940.

Li, Y., Lei, X., Dai, Q., & Liang, L. (2015). Performance evaluation of participating nations at the 2012 London Summer Olympics by a two-stage data envelopment analysis. European Journal of Operational Research, 243(3), 964–973.

Lozano, S., Villa, G., Guerrero, F., & Cortés, P. (2002). Measuring the performance of nations at the Summer Olympics using data envelopment analysis. Journal of the Operational Research Society, 53(5), 501–511.

de Mello, J. C. C. B. S., Meza, L. A., & da Silva, B. B. (2008). Some rankings for the Athens Olympic Games using DEA models with a constant input. Investigacao Operacional, 28(1), 77–89.

Miceli, T. J. & Volz, B. D. (2012). Debating immortality : application of data envelopment analysis to voting for the baseball hall of fame. Managerial and Decision Economics, 33(3), 177–188.

Pyatunin, A. V., Vishnyakova, A. B., Sherstneva, N. L., Mironova, S. P., Dneprov, S. A., & Grabozdin, Y. P. (2016). The economic efficiency of european football clubs – data envelopment analysis (DEA) approach. International Journal of Environmental and Science Education, 11(15), 7515–7534.

Radovanović, S., Radojičić, M., Jeremić, V., & Savić, G. (2013). A novel approach in evaluating efficiency of basketball players’, Management. Journal for Theory and Practice Management, 67, 37–45.

Ramón, N., Ruiz, J. L., & Sirvent, I. (2012). Common sets of weights as summaries of DEA profiles of weights: With an application to the ranking of professional tennis players. Expert Systems with Applications, 39(5), 4882–4889.

Ribeiro, A. S. & Lima, F. (2012). Portuguese football league efficiency and players â€TM wages. Applied Economics Letters, 19(6), 599–602.

Rogge, N. & Puyenbroeck, T. Van (2012). Performance evaluation of Tour de France cycling teams using data envelopment analysis. Working Paper https://lirias.kuleuven.be/retrieve/232046

Ruiz, J. L., Pastor, D., & Pastor, J. T. (2013). Assessing professional tennis players using data envelopment analysis (DEA). Journal of Sports Economics, 14(3), 276–302.

Sala-Garrido, R., Liern Carrión, V., Martinez Esteve, A., et al. (2009). Analysis and Evolution of Efficiency in the Spanish Soccer League (2000/01 - 2007/08). Journal of Quantitative Analysis in Sports, 5(1), doi:10.2202/1559-0410.1143

Santín, D. (2014). Measuring the technical efficiency of football legends: who were Real Madrid’s all‐time most efficient players?. International Transactions in Operational Research, 21(3), 439–452.

Sexton, T. & Lewis, H. F. (2003). Two-Stage DEA: An application to major league baseball. Journal of ProductivityAnalysis, 19(2–3), 227–249.

Singh, S. (2011). Measuring the performance of teams in the Indian premier league. American Journal of Operations Research, 1(3), 180–184.

Soleimani-Damaneh, J., Hamidi, M., & Sajadi, N. (2011). Evaluating the performance of iranian football teams utilizing linear programming. American Journal of Operations Research, 1(2), 65–72.

Sueyoshi, T., Ohnishi, K., & Kinase, Y. (1999). A benchmark approach for baseball evaluation. European Journal of Operational Research, 115(3), 429–448.

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 Research, 19(4), 571–587.

Villa, G. & Lozano, S. (2016). Assessing the scoring efficiency of a football match. European Journal of Operational Research, 255(2), 559–569.

Wu, J., Zhou, Z., & Liang, L. (2010). Measuring the performance of nations at beijing summer olympics using integer-valued DEA model. Journal of Sports Economics, 11(5), 549–566.

Yang, C. H., Lin, H. Y., & Chen, C. P. (2014). Measuring the efficiency of NBA teams: additive efficiency decomposition in two-stage DEA. Annals of Operations Research, 217(1), 565-589.

Yang, F., Ling, L., Gou, Q., & Wu, H. (2009, December). Olympics performance evaluation and competition strategy based on data envelopment analysis. In 2009 International Conference on Computational Intelligence and Software Engineering (pp. 1-4). IEEE.

Zambom-Ferraresi, F., García-Cebrián, L. I., & Lera-López, F. (2017). Sports results measurement and efficiency in UEFA champions league. Athens Journal of Sports, 291–312.

Zambom-Ferraresi, F., Lera-lópez, F., & Iráizoz, B. (2017). And if the ball does not cross the line?. A comprehensive analysis of football clubs' performance. Applied Economics Letters, 24(17), 1259–1262.


Refbacks

  • There are currently no refbacks.