PurposeThe main goal of this paper is to evaluate the players' contribution and economic value in the soccer industry. Media visibility records provide us with comparable metrics to identify talent… Click to show full abstract
PurposeThe main goal of this paper is to evaluate the players' contribution and economic value in the soccer industry. Media visibility records provide us with comparable metrics to identify talent and make hiring decisions – these records can jointly capture sport (on-field) skills and other attractive (off-field) abilities.Design/methodology/approachThis paper presents a valuation method that applies media visibility appraisals to estimate “theoretical values” of the transfer fees paid for hiring soccer players. The estimations are performed by analysing the evolution over time of the media exposure of about 5,000 individuals of more than 200 clubs.FindingsThe study’s empirical results reveal that, along with sport performance, the players' media status also affects their economic valuation, which explains why the clubs – in search of greater economic returns – fiercely compete for the most popular players. The paper also identifies the main factors determining the players' economic value. In predicting the players' transfer fees, some variables are statistically significant: individual media visibility, media visibility share of the player within his team, contract duration, status of the hiring team, years of experience, player's age at the end of the contract and the domestic league of the hiring team.Originality/valueProfessional sports provide reliable measures on individuals' performance that may help in the hiring process of workers. This paper identifies gifted soccer players while taking into account their skills as media leaders and the economic implications. Insofar as players' talents determine their teams' sport and economic achievements, the transfer fees paid for players must then be seen as a crucial factor. Measuring individual talent and being able to translate this talent into productivity levels entail serious methodological and empirical challenges.
               
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