Organisational efficiency of national football leagues in Europe

ABSTRACT

Research question: National football leagues are organisations with multidimensional and idiosyncratic objectives according to one train of thought among the theories of organisational management. Starting from this standpoint, the paper aims at providing an analytical framework for empirically assessing sport leagues organisational performance across several European countries and comparing them in terms of their organisational efficiency.

Research methods: The novelty consists in using at league level a methodology – a Data Envelopment Analysis – which has been confined so far to the study of club efficiency in the existing literature. The league sample is limited to 36 observable leagues out of 55 UEFA member leagues over 2010–2015 due to data paucity.

Results and findings: Efficiency scores, checked with several robustness tests, exhibit a scattered efficiency across European football leagues. Part of the observed inefficiency is linked to decreasing returns to scale, the rest being due to purely inefficient management. The paper also provides a delineation of peer efficiency groups for each league under evaluation.

Implications: There is a managerial recommendation to use peer groups as international benchmarks for improving football leagues’ efficiency. Benchmarking best practices may assist the less well-performing leagues in signalling to them which other leagues’ experience could be an example to follow on their path toward organisational improvement.

KEYWORDS:

• Performance mesaurement
• data envelopment analysis
• European football leagues
• efficiency
• organisations

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 Since the United Kingdom is represented by four leagues for England, Scotland, Northern Ireland and Wales, GDP and population for those leagues are taken from the Office for National Statistics: https://www.ons.gov.uk/search?q=regional+gva.

2 FIFA Big Count provides data only for the years 2000 and 2006. A linear extrapolation was used to estimate the value of this variable throughout the period of analysis.

3 Several sources of information were used to collect final tables of the 55 UEFA member leagues over the 2008-2015 period of time: wikipedia.fr, transfermarkt.de, soccerway.com, mondedufoot.fr and footballdatabase.eu. This cross-check process ensures the data reliability.

4 These indexes are based on the results of each association’s clubs in the five previous UEFA Champions League and Europa League seasons. Details about the calculation of these indexes’ awarding points system can be found on line, see: http://www.uefa.com/memberassociations/uefarankings/country/index.html.

5 We are grateful to an anonymous reviewer for calling attention on those researches.

6 The efficiency criterion was selected in this study to control the heterogeneity of the development potential of the football product on the country and to identify potential for optimization for a given organisation thanks to a better trade-off between conflicting goals.

7 This under-sampling of failure has been verified with a Student test comparing FIFA rating (the performance of national football teams) for missing leagues and those selected in M1 to M7 samples. The significant difference (p-value inferior to .0001) between the subgroups confirms that only the most important leagues survive the data collection selective process for the seven models.