Football players’ career and wage profiles

ABSTRACT

The objective of this article is to look over football players’ career path, from lower leagues to the first league, and the associated wage profile. The information comes from a Portuguese longitudinal matched employer–employee data set defining several career events according to players’ movement across football clubs and across professional and semi-professional leagues. Our identifying strategy relies on coach changes to reduce the potential bias resulting from players’ moves between clubs. The estimated first-difference wage equations indicate that players can expect a wage premium when they get transferred to new clubs in higher leagues or a wage penalty when moving to lower leagues. Players who stay in the same club after the club being relegated can also expect a wage penalty.

KEYWORDS:

• Wages
• football players
• careers
• wage premium

JEL CODES::

• J31
• J44
• M51
• Z22

Acknowledgements

We thank the conference participants at Druid Academy Conference in Aalborg, North American Society for Sport Management Conference in Austin, Association for Public Economic Theory in Lisbon, and European Conference in Sport Economics in Esbjerg for valuable comments. We also thank Mário Centeno and Miguel Torres Preto for suggestions. This work was partially supported by the Portuguese Foundation for Science and Technology (PTDC/EGE-ECO/101493/2008, PTDC/EGE-ECO/118070/2010 and PTDC/IIM-ECO/5123/2012). We are also thankful to the Portuguese Ministry of Labor and Social Solidarity for giving us access to the data used in this research.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

¹ For a review on sport labour markets, see Kahn (2000), Rosen and Sanderson (2001) and Frick (2007). See Siegfried and Sanderson (2006), Sloane (2006) and Bryson, Frick, and Simmons (2015) on the relevance of sport economics. See also Franck and Nüesch (2011), Ribeiro and Lima (2012) and Bachan, Reilly, and Witt (2014) on football efficiency; and Ruijg and Van Ophem (2015) on transfers between clubs.

² See the discussion on the issue of symmetric versus asymmetric learning in Schönberg (2007) and Pinkston (2009). Several models integrate learning about worker’s ability, human capital accumulation and job assignment, as in Gibbons and Waldman (1999, 2006). We argue that information about players’ performance is publicly available to all clubs and, in addition, job assignment within clubs is not an issue.

³ As in Jovanovic (1979), we assume the club lowers player’s wage in order to make him quit (a ‘disguised layoff’).

⁴ It does not guarantee that we will reduce all the bias to make an argument of causality. A new coach can be due to several reasons. Possibly the two most important reasons for a coach leave the club is team’s performance and the recognition that part of it is the coach’s merit or responsibility. If club’s performance is higher than expected, coaches can expect new invitations to manage new teams with more resources and economic capabilities. If the results are lower than the expected, coaches can be seen as responsible for those results and are dismissed or do not see their contract renewed.

⁵ The third League comprises three regional leagues and the fourth League includes seven regional leagues. Since 2013 there are just three national levels: two professional levels and one semi-professional level with eight leagues (10 clubs each).

⁶ We could also include players’ schooling level among the variables analysed, but the variable proved to be subject to coding errors (contrary to what happens generally to other industries in the data set); frequently, we would find the same player moving up or down his schooling level. Moreover, we can assume that schooling is not a relevant form of human capital accumulation for football players, since their physical, technical and tactical skills are partly innate and partly developed throughout their career at football clubs and academies and not at school. There is no evidence that this kind of human capital accumulation play a role in the wage process since the numbers of years completed in school are very low and almost common to all players. In the pooled data, 70.34% completed at most 9 years of schooling; 28.37% completed high-school; and only 1.29% hold a college degree.

Additional information

Funding

This work was partially supported by the Portuguese Foundation for Science and Technology (PTDC/EGE-ECO/101493/2008, PTDC/EGE-ECO/118070/2010 and PTDC/IIM-ECO/5123/2012).