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New mathematical models for team formation of sports clubs before the match

Author

Listed:
  • Gerçek Budak

    (Adana Science and Technology University)

  • İmdat Kara

    (Başkent University)

  • Yusuf Tansel İç

    (Başkent University)

  • Refail Kasımbeyli

    (Anadolu University)

Abstract

Coaches of sports clubs aim to form the team that optimally determines the roles of positions before the match. These types of decisions are referred to as the team formation problem, and they are critical for the sports industry in the financial sense. Finding the optimal solution to the team formation problem is more difficult without the use of systematical approaches, as the number of players and their past performance records have increased substantially in recent years. In this paper, we discuss previous studies on the team formation problems of sports clubs and outline the deficiencies of their results in real-life decision processes. Then, we propose two new formulations that address coaches’ preferences in the decision-making process. A real-life application of the proposed models is displayed for a volleyball team that participates in the first division of the Turkish Volleyball League.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:cejnor:v:27:y:2019:i:1:d:10.1007_s10100-017-0491-x
    DOI: 10.1007/s10100-017-0491-x
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    References listed on IDEAS

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    1. Madjid Tavana & Farshad Azizi & Farzad Azizi & Majid Behzadian, 2013. "A fuzzy inference system with application to player selection and team formation in multi-player sports," Sport Management Review, Taylor & Francis Journals, vol. 16(1), pages 97-110, January.
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    3. Tavana, Madjid & Azizi, Farshad & Azizi, Farzad & Behzadian, Majid, 2013. "A fuzzy inference system with application to player selection and team formation in multi-player sports," Sport Management Review, Elsevier, vol. 16(1), pages 97-110.
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    Cited by:

    1. 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.

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