IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i22p3554-d1520736.html
   My bibliography  Save this article

Assessing Overall Performance of Sports Clubs and Decomposing into Their On-Field and Off-Field Efficiency

Author

Listed:
  • Don Galagedera

    (Department of Econometrics and Business Statistics, Monash Business School, Monash University, 900 Dandenong Road, Caulfield, VIC 3145, Australia)

  • Joan Tan

    (Department of Econometrics and Business Statistics, Monash Business School, Monash University, 900 Dandenong Road, Caulfield, VIC 3145, Australia)

Abstract

Generally, playing group management performance and financial management performance of sports clubs are assessed separately. We adopt a non-parametric methodology to assess overall performance, first conceptualising overall management as a production process comprising two serially linked subprocesses, namely, playing group management and financial management. Thereafter, we decompose overall performance to obtain estimates of performance at the subprocess level. Through this procedure, it is possible to determine whether a sports club’s on-field performance or off-field performance or both may contribute towards its inefficiency, if any, in overall management. Further, a model is developed to determine targets for inefficient clubs to become overall efficient. The method is applied to 18 clubs in the Australian rules football league. In the 2021 season, the results reveal that on-field performance, on average, is better than off-field performance, and variability in off-field performance is higher than that of on-field performance. The observed overall management inefficiency is mainly due to inefficiency in financial management. Results are robust to the weighting scheme adopted in the overall efficiency configuration.

Suggested Citation

  • Don Galagedera & Joan Tan, 2024. "Assessing Overall Performance of Sports Clubs and Decomposing into Their On-Field and Off-Field Efficiency," Mathematics, MDPI, vol. 12(22), pages 1-25, November.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:22:p:3554-:d:1520736
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/22/3554/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/12/22/3554/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chen, Yao & Cook, Wade D. & Zhu, Joe, 2010. "Deriving the DEA frontier for two-stage processes," European Journal of Operational Research, Elsevier, vol. 202(1), pages 138-142, April.
    2. Thanasis Bouzidis, 2018. "On-field Performance Assessment in Football: Applying the Connected Network Data Envelopment Analysis Model," Discussion Paper Series 2018_12, Department of Economics, University of Macedonia, revised Dec 2018.
    3. 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.
    4. Sonia Aviles-Sacoto & Wade D Cook & Raha Imanirad & Joe Zhu, 2015. "Two-stage network DEA: when intermediate measures can be treated as outputs from the second stage," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(11), pages 1868-1877, November.
    5. Adler, Nicole & Yazhemsky, Ekaterina, 2010. "Improving discrimination in data envelopment analysis: PCA-DEA or variable reduction," European Journal of Operational Research, Elsevier, vol. 202(1), pages 273-284, April.
    6. Papahristodoulou, Christos, 2006. "Team Performance in UEFA Champions League 2005-06," MPRA Paper 138, University Library of Munich, Germany.
    7. A. Charnes & W. W. Cooper, 1962. "Programming with linear fractional functionals," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 9(3‐4), pages 181-186, September.
    8. Liang Liang & Feng Yang & Wade Cook & Joe Zhu, 2006. "DEA models for supply chain efficiency evaluation," Annals of Operations Research, Springer, vol. 145(1), pages 35-49, July.
    9. Dyson, R. G. & Allen, R. & Camanho, A. S. & Podinovski, V. V. & Sarrico, C. S. & Shale, E. A., 2001. "Pitfalls and protocols in DEA," European Journal of Operational Research, Elsevier, vol. 132(2), pages 245-259, July.
    10. Timothy Anderson & Gunter Sharp, 1997. "A new measure of baseball batters using DEA," Annals of Operations Research, Springer, vol. 73(0), pages 141-155, October.
    11. Hofler, Richard A. & Payne, James E., 1997. "Measuring efficiency in the National Basketball Association1," Economics Letters, Elsevier, vol. 55(2), pages 293-299, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Galagedera, Don U.A., 2019. "Modelling social responsibility in mutual fund performance appraisal: A two-stage data envelopment analysis model with non-discretionary first stage output," European Journal of Operational Research, Elsevier, vol. 273(1), pages 376-389.
    2. Dan Li & Yanfeng Li & Yeming Gong & Jiawei Yang, 2021. "Estimation of bank performance from multiple perspectives: an alternative solution to the deposit dilemma," Journal of Productivity Analysis, Springer, vol. 56(2), pages 151-170, December.
    3. Chih-Hai Yang & Hsuan-Yu Lin & Chiang-Ping Chen, 2014. "Measuring the efficiency of NBA teams: additive efficiency decomposition in two-stage DEA," Annals of Operations Research, Springer, vol. 217(1), pages 565-589, June.
    4. Wang, Derek D. & Ren, Yaoyao, 2024. "Accuracy of Deterministic Nonparametric Frontier Models with Undesirable Outputs," European Journal of Operational Research, Elsevier, vol. 315(2), pages 596-612.
    5. Chen, Kun & Zhu, Joe, 2020. "Additive slacks-based measure: Computational strategy and extension to network DEA," Omega, Elsevier, vol. 91(C).
    6. L-J Kao & C-C Lu & C-C Chiu, 2011. "The training institution efficiency of the semiconductor institute programme in Taiwan—application of spatiotemporal ICA with DEA approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(12), pages 2162-2172, December.
    7. Yu, Shasha & Lei, Ming & Deng, Honghui, 2023. "Evaluation to fixed-sum-outputs DMUs by non-oriented equilibrium efficient frontier DEA approach with Nash bargaining-based selection," Omega, Elsevier, vol. 115(C).
    8. Ang, Sheng & Liu, Pei & Yang, Feng, 2020. "Intra-Organizational and inter-organizational resource allocation in two-stage network systems," Omega, Elsevier, vol. 91(C).
    9. Torben Tiedemann & Tammo Francksen & Uwe Latacz-Lohmann, 2011. "Assessing the performance of German Bundesliga football players: a non-parametric metafrontier approach," 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. 19(4), pages 571-587, December.
    10. AGRELL, Per & HATAMI-MARBINI, Adel, 2011. "Frontier-based performance analysis models for supply chain management; state of the art and research directions," LIDAM Discussion Papers CORE 2011069, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    11. Yang, Fuxia & Yang, Mian, 2015. "Analysis on China's eco-innovations: Regulation context, intertemporal change and regional differences," European Journal of Operational Research, Elsevier, vol. 247(3), pages 1003-1012.
    12. Wang, Weijiao & Xu, Fei & Chu, Junfei & Dong, Yanhua & Yuan, Zhe, 2025. "Determining the equilibrium efficient frontier by proportional frontier shifting for data envelopment analysis with fixed-sum outputs," Omega, Elsevier, vol. 130(C).
    13. Vincenzo Patrizii & Anna Pettini & Giuliano Resce, 2017. "The Cost of Well-Being," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 133(3), pages 985-1010, September.
    14. Peykani, Pejman & Seyed Esmaeili, Fatemeh Sadat & Pishvaee, Mir Saman & Rostamy-Malkhalifeh, Mohsen & Hosseinzadeh Lotfi, Farhad, 2024. "Matrix-based network data envelopment analysis: A common set of weights approach," Socio-Economic Planning Sciences, Elsevier, vol. 95(C).
    15. Kao, Ling-Jing & Lu, Chi-Jie & Chiu, Chih-Chou, 2011. "Efficiency measurement using independent component analysis and data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 210(2), pages 310-317, April.
    16. Dariush Khezrimotlagh & Wade D. Cook & Joe Zhu, 2021. "Number of performance measures versus number of decision making units in DEA," Annals of Operations Research, Springer, vol. 303(1), pages 529-562, August.
    17. Huang, Chin-wei & Ho, Foo Nin & Chiu, Yung-ho, 2014. "Measurement of tourist hotels׳ productive efficiency, occupancy, and catering service effectiveness using a modified two-stage DEA model in Taiwan," Omega, Elsevier, vol. 48(C), pages 49-59.
    18. Tatiana Bencova & Andrea Bohacikova, 2022. "DEA in Performance Measurement of Two-Stage Processes: Comparative Overview of the Literature," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 5, pages 111-129.
    19. Eskelinen, Juha, 2017. "Comparison of variable selection techniques for data envelopment analysis in a retail bank," European Journal of Operational Research, Elsevier, vol. 259(2), pages 778-788.
    20. Chu, Junfei & Dong, Yanhua & Yuan, Zhe, 2024. "An improved equilibrium efficient frontier data envelopment analysis approach for evaluating decision-making units with fixed-sum outputs," European Journal of Operational Research, Elsevier, vol. 318(2), pages 592-604.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jmathe:v:12:y:2024:i:22:p:3554-:d:1520736. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.