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Individual and team efficiency: a case of the National Hockey League

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  • Josef Jablonsky

    (Prague University of Economics and Business)

Abstract

The paper aims at the evaluation of efficiency in sports. Many articles are dealing with the application of data envelopment analysis (DEA) models in this area. They are mainly oriented on efficiency evaluation of teams and not the individual players. On the contrary, the main aim of this paper is to combine both approaches and investigate the relation between individual efficiency of the players and the efficiency of the teams. The first step is the evaluation of individual efficiencies, and the second one is its aggregation into the teams' performance within a competition (League). The idea is to evaluate the efficiency of individual players in certain positions and explore how the individual efficiencies contribute to the efficiency of the teams. Individual efficiency is measured using traditional radial and slacks-based measure DEA models. Team efficiency is derived in several ways—traditional DEA models with the variables describing the true achievements of the teams, parallel DEA models that consider all positions and players, and actual results of the teams in the League, which is the true performance of the team. The study is based on the Canadian-American National Hockey League (NHL) statistics in 2019/2020. The results of the analysis are compared and discussed. They show that the true performance of the team is not always directly dependent on individual performances of the members of the team.

Suggested Citation

  • Josef Jablonsky, 2022. "Individual and team efficiency: a case of the National Hockey League," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(2), pages 479-494, June.
  • Handle: RePEc:spr:cejnor:v:30:y:2022:i:2:d:10.1007_s10100-021-00775-0
    DOI: 10.1007/s10100-021-00775-0
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    References listed on IDEAS

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    1. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    2. Li, Yongjun & Wang, Lizheng & Li, Feng, 2021. "A data-driven prediction approach for sports team performance and its application to National Basketball Association," Omega, Elsevier, vol. 98(C).
    3. S Lozano & G Villa & F Guerrero & P Cortés, 2002. "Measuring the performance of nations at the Summer Olympics using data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(5), pages 501-511, May.
    4. Isidoro Guzmán & Stephen Morrow, 2007. "Measuring efficiency and productivity in professional football teams: evidence from the English Premier League," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 15(4), pages 309-328, November.
    5. Josef Jablonsky, 2018. "Ranking of countries in sporting events using two-stage data envelopment analysis models: a case of Summer Olympic Games 2016," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(4), pages 951-966, December.
    6. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    7. José L. Ruiz & Diego Pastor & Jesús T. Pastor, 2013. "Assessing Professional Tennis Players Using Data Envelopment Analysis (DEA)," Journal of Sports Economics, , vol. 14(3), pages 276-302, June.
    8. Cooper, W.W. & Ruiz, José L. & Sirvent, Inmaculada, 2009. "Selecting non-zero weights to evaluate effectiveness of basketball players with DEA," European Journal of Operational Research, Elsevier, vol. 195(2), pages 563-574, June.
    9. Gerçek Budak & İmdat Kara & Yusuf Tansel İç & Refail Kasımbeyli, 2019. "New mathematical models for team formation of sports clubs before the match," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 27(1), pages 93-109, March.
    10. Kao, Chiang, 2009. "Efficiency measurement for parallel production systems," European Journal of Operational Research, Elsevier, vol. 196(3), pages 1107-1112, August.
    11. Paulo Reis Mourao, 2016. "Soccer transfers, team efficiency and the sports cycle in the most valued European soccer leagues – have European soccer teams been efficient in trading players?," Applied Economics, Taylor & Francis Journals, vol. 48(56), pages 5513-5524, December.
    12. Min Yang & Yuqi Wei & Liang Liang & Jingjing Ding & Xianmei Wang, 2021. "Performance evaluation of NBA teams: A non-homogeneous DEA approach," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 72(6), pages 1403-1414, June.
    13. Tone, Kaoru, 2002. "A slacks-based measure of super-efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 143(1), pages 32-41, November.
    14. Tone, Kaoru, 2001. "A slacks-based measure of efficiency in data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 130(3), pages 498-509, May.
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