Open Access Journal Article

Did the UEFA Champions League winners start in an easy group?

by Antonio Avila-Cano a orcid  and  Francisco Triguero-Ruiz b,* orcid
Department of Economic Theory and Economic History, University of Málaga, Málaga, Spain
Department of Languages and Computer Sciences, University of Málaga, Málaga, Spain
Author to whom correspondence should be addressed.
JEA  2024, 71; 3(3), 71;
Received: 6 July 2023 / Accepted: 17 September 2023 / Published Online: 15 September 2024


Competitive balance indicates the degree of control participating teams have over a sports competition. Supporters look for excuses to justify their team’s defeat and the triumph of their rivals. If the competition has required a preliminary qualifying group stage, they will argue that the winning team was in an "easy group" from the start, and their team was unlucky to be in a "difficult group". It is therefore of interest to determine what is an "easy group" and what is a "difficult group". This is directly related to the concept of competitive balance. We have a wide range of indices to measure competitive balance. We will use the Distance to Competitive Balance, a standardized index that complies cardinality property. The perfectly unbalanced distribution is the truncated cascade, which allows the maximum value of concentration to be obtained. We focus our attention on the UEFA Champions League, before and after competition, and we measure the competitive balance of the qualifying stage groups between the 1999/2000 and 2022/2023 seasons. The composition of the UEFA Champions League groups seems to be balanced and has no influence on which team will be the champion. A highly competitive group will be more "difficult" in terms of qualifying than a highly concentrated one. Supporters say that their team was unlucky to be in a “difficult” group, but the data does not prove them right.

Copyright: © 2024 by Avila-Cano and Triguero-Ruiz. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (Creative Commons Attribution 4.0 International License). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.


Ministerio de Ciencia e Innovación (Spain) (PID2020-114309GB-I00)

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ACS Style
Avila-Cano, A.; Triguero-Ruiz, F. Did the UEFA Champions League winners start in an easy group?. Journal of Economic Analysis, 2024, 3, 71.
AMA Style
Avila-Cano A, Triguero-Ruiz F. Did the UEFA Champions League winners start in an easy group?. Journal of Economic Analysis; 2024, 3(3):71.
Chicago/Turabian Style
Avila-Cano, Antonio; Triguero-Ruiz, Francisco 2024. "Did the UEFA Champions League winners start in an easy group?" Journal of Economic Analysis 3, no.3:71.
APA style
Avila-Cano, A., & Triguero-Ruiz, F. (2024). Did the UEFA Champions League winners start in an easy group?. Journal of Economic Analysis, 3(3), 71.

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  1. Avila-Cano, A., Owen, P. D., & Triguero-Ruiz, F. (2023). Measuring competitive balance in sports leagues that award bonus points, with an application to rugby union. European Journal of Operational Research, S0377221723001133.
  2. Avila-Cano, A., Ruiz-Sepulveda, A., & Triguero-Ruiz, F. (2021). Identifying the Maximum Concentration of Results in Bilateral Sports Competitions. Mathematics, 9(11), 1293.
  3. Avila‐Cano, A., & Triguero‐Ruiz, F. (2023). On the control of competitive balance in the major European football leagues. Managerial and Decision Economics, 44(2), 1254–1263.
  4. Coates, D., Humphreys, B. R., & Zhou, L. (2014). Reference-Dependent Preferences, Loss Aversion, and Live Game Attendance. Economic Inquiry, 52(3), Article 3.
  5. Collins, C., & Humphreys, B. R. (2022). Contest Outcome Uncertainty and Fan Decisions: A Meta-Analysis. Journal of Sports Economics, 23(6), 789–807.
  6. Csató, L. (2023). Club coefficients in the UEFA Champions League: Time for the shift to an Elo-based formula (arXiv:2304.09078). arXiv.
  7. Eckard, E. W. (2017). The Uncertainty-of-Outcome Hypothesis and the Industrial Organization of Sports Leagues: Evidence from U.S. College Football. Journal of Sports Economics, 18(3), Article 3.
  8. El-Hodiri, M. and Quirk, J. (1971). The economic theory of a professional sport league. Journal of Political Economy, 79 (6), pp. 1302-1319.
  9. Fort, R., & Maxcy, J. (2003). “Competitive Balance in Sports Leagues: An Introduction”. Journal of Sports Economics, 4(2), Article 2.
  10. Fort, R., & Quirk, J. (1995). Cross-Subsidization, Incentives, and Outcomes in Professional Team Sports Leagues. Journal of Economic Literature, 33(3), 1265–1299.
  11. Frick, B., Quansah, T. K., & Lang, M. (2023). Talent concentration and competitive imbalance in European soccer. Frontiers in Sports and Active Living, 5.
  12. Gayant, J. P., & Le Pape, N. (2012). How to account for changes in the size of Sports Leagues? The Iso Competitive Balance Curves. Economics Bulletin, 32(2), 1715–1723. I2-P165. pdf.
  13. Gayant, J. P., & Le Pape, N. (2015). The metrics of competitive imbalance. In W. Andreff (Ed.), Disequilibrium sports economy: Competitive imbalance and budget constraints (pp. 104–130). Edward Elgar Publishing.
  14. Gerrard, B., & Kringstad, M. (2021). The multi-dimensionality of competitive balance: Evidence from European football. Sport, Business and Management: An International Journal, ahead-of-print(ahead-of-print), Article ahead-of-print.
  15. Horowitz, I. (1997). The Increasing Competitive Balance in Major League Baseball. Review of Industrial Organization, 12(3), 373–387.
  16. Koning, R. H. (2009). Sport and measurement of competition. De Economist, 157 (2), 229-249. 10.1007/s10645-009-9113-x
  17. Kringstad, M., & Gerrard, B. (2004). The concepts of competitive balance and uncertainty of outcome. In G. T. Papanikos (Ed.), The economics and management of mega athletic events: Olympic Games, professional sports and other essays (pp. 115–130). Athens Institute For Education and Research.
  18. Larsen, A., Fenn, A. J., & Spenner, E. L. (2006). The Impact of Free Agency and the Salary Cap on Competitive Balance in the National Football League. Journal of Sports Economics, 7(4), 374–390.
  19. Neale, W. C. (1964). The Peculiar Economics of Professional Sports. The Quarterly Journal of Economics, 78(1), Article 1.
  20. Owen, P. D., Ryan, M., & Weatherston, C. R. (2007). Measuring Competitive Balance in Professional Team Sports Using the Herfindahl-Hirschman Index. Review of Industrial Organization, 31(4), 289–302.
  21. Quirk, J. and Fort, R. (1992). Pay dirt: The business of professional team sports. Princeton University Press, Princeton, NJ (1992).
  22. Rottenberg, S. (1956). The Baseball Players’ Labor Market. Journal of Political Economy, 64(3), Article 3.
  23. Schmidt, M.B. and Berri, D.J. (2001). Competitive balance and attendance: The case of major league baseball. Journal of Sports Economics, 2 (2), pp. 145-167.
  24. Szymanski, S. (2003). The Economic Design of Sporting Contests. Journal of Economic Literature, 41(4), 1137–1187.
  25. Triguero-Ruiz, F., & Avila-Cano, A. (2019). The distance to competitive balance: A cardinal measure. Applied Economics, 51(7), 698–710.
  26. Triguero-Ruiz, F., & Avila-Cano, A. (2023). On competitive balance in the group stage of the UEFA Champions League*. Scottish Journal of Political Economy, 70(3), Article n/a.
  27. UEFA. (2019). Club coefficients | UEFA Coefficients |
  28. Utt, J., & Fort, R. (2002). Pitfalls to Measuring Competitive Balance With Gini Coefficients. Journal of Sports Economics, 3(4), 367–373.