Chapter 25: Further Reading

Foundational Texts

Szymanski, S. (2015). Money and Soccer: A Soccernomics Guide. Nation Books. A rigorous economic analysis of professional soccer, covering revenue models, competitive balance, and the financial dynamics of the transfer market.
Kuper, S., & Szymanski, S. (2018). Soccernomics (5th ed.). Nation Books. The most accessible introduction to the economics of soccer, blending data analysis with narrative to explain why the transfer market behaves as it does.
Dobson, S., & Goddard, J. (2011). The Economics of Football (2nd ed.). Cambridge University Press. A comprehensive academic treatment of football economics, including chapters on player valuation, wage determination, and competitive balance.

Herm, S., Callsen-Bracker, H.-M., & Kreis, H. (2014). "When the Crowd Evaluates Soccer Players' Market Values: Accuracy and Evaluation Attributes of an Online Community." Sport Management Review, 17(4), 484--492. Examines the accuracy of Transfermarkt crowd-sourced valuations and the attributes that drive market value assessments.
Muller, 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. Develops machine learning models for player valuation, demonstrating that data-driven estimates outperform crowd-sourced valuations in predicting actual transfer fees.
Ruijg, J., & van Ophem, H. (2015). "Determinants of Football Transfers." Applied Economics Letters, 22(1), 12--19. Econometric analysis of the factors driving transfer fees, including age, performance, nationality, and contract length.

Poli, R., Ravenel, L., & Besson, R. (various years). CIES Football Observatory Monthly Reports. The CIES provides the most comprehensive ongoing quantitative analysis of the global transfer market, including their proprietary valuation algorithm.
Deloitte. Annual Review of Football Finance. The definitive annual financial analysis of European football, essential for understanding the macroeconomic context in which transfer decisions are made.
UEFA. Club Licensing Benchmarking Report. Annual publication providing aggregate financial data across European football, enabling benchmarking of individual club finances against industry norms.

UEFA (2022). Club Licensing and Financial Sustainability Regulations. The regulatory framework governing club finances in European competition, replacing the original FFP regulations with a cost-control approach.
Flanagan, C. (2013). "A Tricky European Fixture: An Assessment of UEFA's Financial Fair Play Regulations and Their Compatibility with EU Law." The International Sports Law Journal, 13(1), 55--66. Legal analysis of FFP's compatibility with EU competition law.
Peeters, T., & Szymanski, S. (2014). "Financial Fair Play in European Football." Economic Policy, 29(78), 343--390. Rigorous economic analysis of FFP's intended and unintended consequences, including its effects on competitive balance.

Biermann, C. (2019). Football Hackers: The Science and Art of a Data Revolution. Blink Publishing. Profiles data-driven recruitment at clubs including Brentford, FC Midtjylland, and others, providing narrative context for the analytical approaches discussed in this chapter.
Anderson, C., & Sally, D. (2013). The Numbers Game. Penguin Books. Includes analysis of the transfer market's inefficiencies and the potential for data-driven recruitment to exploit them.

Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. The standard econometrics textbook, covering the regression methods used in hedonic pricing models and transfer fee analysis.
Angrist, J. D., & Pischke, J.-S. (2014). Mastering Metrics: The Path from Cause to Effect. Princeton University Press. Accessible treatment of causal inference methods relevant to measuring the impact of transfers and wage policies on sporting outcomes.

McKinney, W. (2022). Python for Data Analysis (3rd ed.). O'Reilly Media. Essential reference for implementing the data manipulation and analysis workflows described in the code examples.
Geron, A. (2022). Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow (3rd ed.). O'Reilly Media. Practical guide to the machine learning techniques (gradient boosting, random forests, neural networks) used in advanced valuation models.

Transfermarkt (transfermarkt.com). The largest crowd-sourced player valuation database, widely used as a benchmark in academic and industry research.
CIES Football Observatory (football-observatory.com). Research center producing regular quantitative analysis of the transfer market, player valuations, and club finances.
Swiss Ramble (blog). Detailed financial analysis of individual club accounts, providing granular insight into how transfer spending and wage costs affect club finances.
The Transfer Price Index (various academic publications). Research project tracking inflation-adjusted transfer spending over time, enabling meaningful historical comparisons.