Measuring the Technical Efficiency of Hockey Players: Empirical Evidence from Czech Hockey Competition
Vol.16,No.2(2022)
Ice hockey is a very popular sport in the Czech Republic. Nowadays, hockey player efficiency analysis is a useful tool that helps sports managers with player selection, team composition and team performance evaluation. The literature offers only a limited number of scientific studies that deal with the evaluation of the efficiency of hockey players or clubs. The aim of this research is to use data envelopment analysis to help Czech hockey clubs, managers and coaches to evaluate the efficiency of their players. This research evaluates the technical efficiency of Czech hockey players using three data envelopment analysis models, ranks the best players based on their super-efficiency scores, and then tries to uncover the main sources of player inefficiency. The models are empirically applied to players playing in the Tipsport extraliga in the 2021/22 season. The evaluation used in this paper attempts to incorporate greater objectivity into decision making and thus may be an important step in developing a systematic methodology for evaluating hockey players.
sport; ice hockey; efficiency; inefficiency; data envelopment analysis
Andersen T. R., & Sharp, G. P. (1997). A new measure for baseball hitters using DEA. Annals of Operations Research, 73(0), 141–155. http://dx.doi.org/10.1023/A:1018921026476
Andersen, P., & Petersen, N. C. (1993). A procedure for ranking efficient units in data envelopment analysis. Management Science, 39(10), 1261–1264. https://doi.org/10.1287/mnsc.39.10.1261
Avkiran, N. K. (2006). Productivity analysis in the services sector with data envelopment analysis. University of Queensland Business School.
Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 30(9), 1078–1092. https://doi.org/10.1287/mnsc.30.9.1078
Bedford, A., & Baglin, J. (2009). Evaluating the performance of an ice hockey team using interactive phases of play. IMA Journal of Management Mathematics, 20(2), 159–166. http://dx.doi.org/10.1093/imaman/dpn019
BPA sport marketing a.s. (2022). Statistiky: Tipsport elh: Hokej.cz - web českého hokeje. Retrieved 20 November, 2022. Available from https://www.hokej.cz/tipsport-extraliga/stats-center?season=2021&competition=6877&team=&age=&state=&timeFrom=&yearFrom=&yearTo=&position=
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429–444. https://doi.org/10.1016/0377-2217(78)90138-8
Collier, T., Johnson, A. L., & Ruggiero, J. (2011). Measuring Technical Efficiency in Sports. Journal of Sports Economics, 12(6), 579–598. https://doi.org/10.1177/1527002510391582
Cooper, W. W., Ruiz, J. 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. https://doi.org/10.1016/j.ejor.2008.02.012
Cooper, W. W., Ramón, N., Ruiz, J. L., & Sirvent, I. (2011). Avoiding large differences in weights in cross-efficiency evaluations: application to the ranking of basketball player. Journal of centrum cathedra: The Business and Economics Research Journal, 4(2), 197–215. http://dx.doi.org/10.7835/jcc-berj-2011-0058
Cooper, W. W. (2011). Handbook on data envelopment analysis. Springer.
Dlouhý, M., Jablonský, J., & Zýková, P. (2018). Analýza obalu dat. Professional Publishing.
Espitia-Escue, M., & García-Cebrián, L. Í. I. (2004). Masuring the Efficiency of Spanish First-Division Soccer Teams. Journal of Sports Economics, 5(4), 329–346. https://doi.org/10.1177/1527002503258047
eSports.cz, s.r.o. (2022). Hokej - Onlajny. Retrieved 1 November, 2022. Available from https://www.onlajny.com/hokej
Farrell, M. J. (1957). The measurement of productive efficiency. Journal of the Royal Statistical Society, 120(3), 253–281. https://doi.org/10.2307/2343100
Fizel, J. L., & D’Itri, M. (1996). Estimating managerial efficiency: The case of college basketball coaches. Journal of Sport Management, 10(4), 435–445. https://doi.org/10.1123/jsm.10.4.435
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. https://doi.org/10.1016/S0377-2217(03)00188-7
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. https://doi.org/10.1007/s10100-007-0034-y
Guzmán-Raja, I., & Guzmán-Raja, M. (2021). Measuring the efficiency of football clubs using data envelopment analysis: Empirical evidence from Spanish professional football. SAGE Open, 11(1), 1–13. https://doi.org/10.1177/2158244021989257
Haas, D. J. (2003). Productivity efficiency of English football teams: A data envelopment analysis approach. Managerial and Decision Economics, 24(5), 403–410. https://doi.org/10.1002/mde.1105
Haas, D. J., Kocher, M. G., & Sutter, M. (2004). Measuring efficiency of German football teams by data envelopment analysis. Central European Journal of Operations Research and Economics, 12, 251–268.
Hadley, L., Poitras, M., Ruggiero, J., & Knowles, S. (2000). Performance evaluation of National Football League teams. Managerial and Decision Economics, 21(2), 63–70. http://dx.doi.org/10.1002/1099-1468(200003)21:2<63::AID-MDE964>3.0.CO;2-O
Halkos, G., & Tzeremes, N. (2012). Evaluating professional tennis players’ career performance: A Data Envelopment Analysis approach. MPRA Paper 41516. University Library of Munich.
Jablonský, J. (2016). Ranking models in Data Envelopment Analysis. Trendy v podnikání, 6(4), 36–42.
Jablonský, J. (2021). Individual and team efficiency: a case of the National Hockey League. Central European Journal of Operations Research, 30(2), 479–494. https://doi.org/10.1007/s10100-021-00775-0
Jablonský, J., & Dlouhý, M. (2015). Modely hodnocení efektivnosti a alokace zdrojů. Professional Publishing.
Kahane, L. H. (2005). Production Efficiency and Discriminatory Hiring Practices in the National Hockey League: A Stochastic Frontier Approach. Review of Industrial Organization, 27(1), 47–71. http://dx.doi.org/10.1007/s11151-005-4400-4
Kian, I. (2009). Profitability and marketability efficiency of large banks-an application of
data envelopment analysis. Journal of Business, 96(9), 101–113.
Kirschstein, T., & Liebscher, S. (2018). Assessing the market values of soccer players - a robust analysis of data from German 1. and 2. Bundesliga. Journal of Applied Statistics, 46(7), 1336–1349. https://doi.org/10.1080/02664763.2018.1540689
Kuosmanen, T. (1998). Efficiency of Hockey Teams in NHL. Helsinki School of Economics and Business Administration.
Mazur, M. (1994). Evaluating the relative efficiency of baseball players. In A. Charnes, W. W. Cooper, A. Lewin, & L. Seiford (Eds.), Data envelopment analysis: Theory, methodology and applications (pp. 369-391). Kluwer.
Palafox-Alcantar, P. G., & Vargas-Hernández, J. G. (2015). Measuring the efficiency of the 32 franchises in the NFL during the 2014 season. Journal of Sports Economics & Management, 5(1), 37–53.
Porter, P. K., & Scully, G. W. (1982). Measuring managerial efficiency: The case of baseball. Southern Economic Journal, 48(3), 642–650. https://doi.org/10.2307/1058656
PWC. (2015). Ice Hockey National Team Performance Model. PricewaterhouseCoopers
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 Applica-tions, 39(5), 4882–4889. https://doi.org/10.1016/j.eswa.2011.10.004
Ruggiero, J., Hadley, L., & Gustafson, E. (1996). Technical efficiency in major league baseball. In J. Fizel, E. Gustafson & L. Hadley (Eds.), Baseball economics: Current research (pp. 191-200). Westport, CT: Praeger.
Suk, Y. K. (2014). Selecting the Batters of National Baseball Squad using Data Envelopment Analysis. Journal of the Korea Academia-Industrial cooperation Society, 15(1), 165–172. https://doi.org/10.5762/kais.2014.15.1.165
Weissbock, J., Viktor, H. L., & Inkpen, D. (2013). Use of Performance Metrics to Forecast Success in the National Hockey League. ECML/PKDD
Zak, T. A., Huang, C. J., & Siegfried, J. J. (1979). Production efficiency - Case of professional basketball. The Journal of Business, 52(3), 379–392. https://doi.org/10.1086/296053
Zambom-Ferraresi, F., García-Cebrián, L. I., Lera-López, F., & Iráizoz, B. (2015). Performance evaluation in the UEFA Champions League. Journal of Sports Economics, 18(5), 448–470. https://doi.org/10.1177/1527002515588135
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Copyright © 2023 Studia sportiva