European Financial and Accounting Journal 2024, 19(2):1-19 | DOI: 10.18267/j.efaj.286

Numbers Beyond the Pitch: A Conceptual Review Concerning the Impact of Data Analysis on Football Club Valuation

Tudor Oprisor1, George-Silviu Cordos1
1 Babes-Bolyai University of Cluj-Napoca, Faculty of Business, Department of Business, Horea Street 7, 400174 Cluj-Napoca, Romania

This article investigates how data analytics is revolutionizing how football clubs are valued. Previously, valuations were based on biased opinions and past financial results, which often resulted in errors and missed chances. Data analytics offers a more impartial method that considers elements including player worth, brand power, fan involvement, and online presence. The article delves into specific methodologies employed in data-driven valuations, highlighting their advantages over traditional methods. The article – structured as a literature review – showcases how various stakeholders benefit from this approach. Club owners gain a more reliable way to assess assets, while players and agents leverage data for contract negotiations. The article uses existing studies to delineate elements of data analysis which are prone to be included in valuation models. The article highlights the drawbacks of data-driven valuations, such as data reliability and the difficulty in quantifying intangible elements. It advocates for a hybrid strategy that balances data analysis with the judgment of human experts. Additionally, the article outlines the potential of data analytics for valuing intangible assets and making analytics more common in football, paving the way for a sports industry that is more competitive and driven by data.

Keywords: Data Analysis; Football; Metrics; Valuation.
JEL classification: M41, Z23

Published: December 30, 2024  Show citation

ACS AIP APA ASA Harvard Chicago Chicago Notes IEEE ISO690 MLA NLM Turabian Vancouver
Oprisor, T., & Cordos, G. (2024). Numbers Beyond the Pitch: A Conceptual Review Concerning the Impact of Data Analysis on Football Club Valuation. European Financial and Accounting Journal, 19(2), 1-19. doi: 10.18267/j.efaj.286
Download citation
  • BibTeX (.bib)
  • Bookends (.ris)
  • EasyBib (.ris)
  • EndNote (.enw)
  • EndNote 8 (.xml)
  • ISI WoS (.isi)
  • Medlars (.medlars)
  • Mendeley (.ris)
  • MODS (.xml)
  • Papers (.ris)
  • RefWorks (.txt)
  • RefManager (.ris)
  • RIS (.ris)
  • MS Word (.xml)
  • Zotero (.ris)
    • Open full article

    References

    1. Ahmed, N., 2022. Understanding Sports Data Analytics Simplified. Hevo Data. Available from: <https://hevodata.com/learn/sports-data-analytics>. [15 March 2024].
    2. Amir, E., Livne, G., 2005. Accounting, Valuation and Duration of Football Player Contracts. Journal of Business Finance & Accounting, 32(3-4), 549-586. DOI: 10.1111/j.0306-686x.2005.00604.x. Go to original source...
    3. AnalyiSport, 2021. How Football Clubs Use Data to Sign Players. AnalyiSport. Available from: <https://analyisport.com/insights/how-football-clubs-use-data-to-sign-players>. [15 March 2024].
    4. Brandsen Sports, 2023. The Game-Changer: Data Analytics in Football. LinkedIn. Available from: <https://www.linkedin.com/pulse/game-changer-data-analytics-football-brandsen-sports-c5zje>. [15 March 2024].
    5. Chauhan, D., Khairnar, A., 2020. Multivariate Model - An Optimal Method for Valuing Football Clubs? Aranca. Available from: <https://www.aranca.com/knowledge-library/articles/investment-research/multivariate-model-an-optimal-method-for-valuing-football-clubs>. [15 March 2024].
    6. Deloitte, 2024. Deloitte Football Money League 2024. Deloitte. Available from: <https://www2.deloitte.com/uk/en/pages/sports-business-group/articles/deloitte-football-money-league.html>. [15 March 2024].
    7. Dougramaji, M., 2023. Data Analytics in football: How LFC Used Data to Gain the Edge. Rockborne. Available from: <https://rockborne.com/graduates/blog/data-analytics-in-football-lfc>. [15 March 2024].
    8. Fantinel, P., 2023. Evaluating Football Players. DAIN Studios. Available from: <https://dainstudios.com/insights/evaluating-football-players>. [15 March 2024].
    9. Franceschi, M., Brocard, J. F., Follert, F., Gouguet, J. J., 2023. Determinants of football players' valuation: A systematic review. Journal of Economic Surveys, 38(3), 577-600. DOI: 10.1111/joes.12552. Go to original source...
    10. GameInsight, 2023. The Rise of Data Analytics in Football: How Big Data is Transforming the Beautiful Game. GameInsight. Available from: <https://gameinsight.sport/data-analytics-football-transforming-game>. [15 March 2024].
    11. Gulbrandsen, A. M., Gulbrandsen C. M., 2011. Valuation of Football Players: A Complete Pricing Framework. Master's thesis, Norwegian School of Economics. Available from: <http://hdl.handle.net/11250/169019>. [15 March 2024].
    12. 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). DOI: 10.1177/2158244021989257. Go to original source...
    13. Harper, J., 2021. Data experts are becoming football's best signings. BBC News. Available from: <https://www.bbc.com/news/business-56164159>. [15 March 2024].
    14. Ikwechegh, J., 2020. Valuation of Sports Organizations: Football Clubs? LinkedIn. Available from: <https://www.linkedin.com/pulse/how-football-clubs-valued-jerry-nnochiri-ikwechegh>. [15 March 2024].
    15. Katerova, L., 2023. How Big Data & Analytics Improve Football Performance. B EYE. Available from: <https://b-eye.com/blog/how-big-data-analytics-improve-football-performance>. [15 March 2024].
    16. Kim, Y., Bui, K. H. N., Jung, J. J., 2019. Data-driven exploratory approach on player valuation in football transfer market. Concurrency and Computation: Practice and Experience, 33(3). DOI: 10.1002/cpe.5353. Go to original source...
    17. Laidig, D., 2018. Building a System for Assessing Player Value. American Soccer Analysis. Available from: <https://www.americansocceranalysis.com/home/2018/9/10/building-a-system-for-assessing-player-value>. [15 March 2024].
    18. Lichtenthaler, U., 2020. Mixing data analytics with intuition: Liverpool Football Club scores with integrated intelligence. Journal of Business Strategy, 43(1), 10-16. DOI: 10.1108/jbs-06-2020-0144. Go to original source...
    19. Mark, A., 2023. What Marketers Can Learn From Football Analytics. CVE. Available from: <https://controlvexposed.com/what-data-driven-marketers-can-learn-from-football-analytics>. [15 March 2024].
    20. Markham, T., 2013. What is the Optimal Method to Value a Football Club? SSRN Electronic Journal. DOI: 10.2139/ssrn.2238265. Go to original source...
    21. McHale, I. G., Holmes, B., 2023. Estimating transfer fees of professional footballers using advanced performance metrics and machine learning. European Journal of Operational Research, 306(1), 389-399. DOI: 10.1016/j.ejor.2022.06.033. Go to original source...
    22. Müller, O., Simons, A., Weinmann, M., 2017. Beyond crowd judgments: Data-driven estimation of market value in association football. European Journal of Operational Research, 263(2), 611-624, DOI: 10.1016/j.ejor.2017.05.005. Go to original source...
    23. Page, M. J. et al., 2021. PRISMA 2020 explanation and elaboration: updated guidance and exemplars for reporting systematic reviews, BMJ, 372, DOI: 10.1136/bmj.n160. Go to original source...
    24. Pykes, K., 2022. Sports Analytics: How Different Sports Use Data Analytics. DataCamp. Available from: <https://www.datacamp.com/blog/sports-analytics-how-different-sports-use-data-analysis>. [15 March 2024].
    25. Quansah, T., Frick, B., Lang, M., Maguire, K., 2021. The Importance of Club Revenues for Player Salaries and Transfer Expenses-How Does the Coronavirus Outbreak (COVID-19) Impact the English Premier League? Sustainability, 13(9), 5154. DOI: 10.3390/su13095154. Go to original source...
    26. Scarfe, R., Singleton, C., Telemo, P., 2021. Extreme Wages, Performance, and Superstars in a Market for Footballers. Industrial Relations: A Journal of Economy and Society, 60(1), 84-118. DOI: 10.1111/irel.12270. Go to original source...
    27. Schroer, A., 2024. Sports Analytics: What It Is, How It's Used. Built In. Available from: <https://builtin.com/big-data/big-data-companies-sports>. [15 March 2024].
    28. SciSports, 2021. State of the football analytics industry in 2021. SciSports. Available from: <https://www.scisports.com/state-of-the-football-analytics-industry-in-2021>. [15 March 2024].
    29. Segner, M., 2023. How TOCA Football Achieved Their Data Quality GOOOOOOAL! Monte Carlo. Available from: <https://www.montecarlodata.com/blog-how-toca-football-achieved-their-data-quality-goal>. [15 March 2024].
    30. Slater, M., 2022. How do you value a football club? The Athletic. Available from: <https://theathletic.com/3068619/2022/11/22/how-do-you-value-a-football-club>. [15 March 2024].
    31. Totime, J., 2023. Data Analytics Revolutionizing Football Contract Negotiations. LinkedIn. Available from: <https://www.linkedin.com/pulse/data-analytics-revolutionizing-football-contract-negotiations>. [15 March 2024].
    32. Trichard, T., 2021. What are the main determinants of professional soccer players wages? An Examination of the top 5 European Leagues. Adam Smith Business School, University of Glasgow. Available from: <https://www.researchgate.net/publication/354859802_What_are_the_main_determinants_of_professional_soccer_players_wages_An_Examination_of_the_top_5_European_Leagues>. [15 March 2024].
    33. Tunaru, R. S., Viney, H. P., 2010. Valuations of Soccer Players from Statistical Performance Data. Journal of Quantitative Analysis in Sports, 6(2). DOI: 10.2202/1559-0410.1238. Go to original source...
    34. WDSportz, 2024. Uncovering Hidden Patterns: A Look at the Role of Data Analytics in Player Recruitment. WDSportz. Available from: <https://wdsportz.com/uncovering-hidden-patterns-a-look-at-the-role-of-data-analytics-in-player-recruitment>. [15 March 2024].
    35. Yaldo, L., Shamir, L., 2017. Computational Estimation of Football Player Wages. International Journal of Computer Science in Sport, 16(1), 18-38. DOI: 10.1515/ijcss-2017-0002. Go to original source...

    This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.


    Return to the content