Talent and/or Popularity: What Does It Take to Be a Superstar?

Abstract

We show that both talent and popularity significantly contribute to stars' market values in German soccer. The talent-versus-popularity controversy on the sources of stardom goes back to Rosen (1981) and Adler (1985). All attempts to resolve the controversy empirically face the difficulty of accurately identifying talent. In professional sports, rank-order tournaments help in ascertaining talent. Analyzing a team setting, we use 20 different performance indicators to estimate a player's talent according to his ability to increase the team's winning probability. (JEL J31, J44, L83)The phenomenon of Superstars, wherein small numbers of people earn enormous amounts of money and dominate the activities in which they engage, seems to be increasingly important in the modern world (Rosen 1981, 845).

The effect of talent disparity on team productivity in soccer

“…4 Alternatively, we could use salary data to proxy talent. However, we refused this approach as both a player's talent and his popularity influence salaries in German soccer (Franck & Nüesch, 2007). 5 We are grateful to an anonymous referee for raising this issue.…”

“…8 Other performance statistics -like flick success rate, tackling success rate, shots off target, shots hitting the woodwork, blocked shots, fouls, hands, balls caught by the goalkeeper, or balls dropped by the goalkeeper -do not significantly affect the team's winning probability. For further information about the team production estimates, see Franck and Nüesch (2007). 9 Summary statistics revealed that goalkeepers received higher average performance statistics than defenders, midfielders, or attackers, even though various studies show that they receive the lowest salaries on average (e.g.…”

“…Before a player's performance index can be ascertained, the marginal contribution of each statistic to the team's winning percentage must be determined. 6 Analyzing the results of 1530 games of the Bundesliga using the same data, Franck and Nüesch (2007) showed that the following statistics significantly influence the final score of a match (coefficients as weights in parentheses): number of goals (1) and assists (1) scored 7 ; pass success rate (1.082); cross success rate (0.676); dribbling success rate (0.419); shots on target (0.217); red cards (À0.287); yellow cards (À0.072); clearances, blocks, and interceptions (0.010); and the saves-to-shots ratio by the goalkeeper (3.791). 8 The productivity index of a player is measured by the sum of each player's seasonal statistics multiplied by the marginal value of the corresponding variable.…”

Temporal variations in technical efficiency: evidence from German soccer

“…Unfortunately, that data is not available for most of the years we include in our analysis. In another study Franck and Nüesch (2007) use as a proxy for individual salaries-as opposed to team wage bills-the individual players' market values as published by www.transfermarkt.de and by Kicker soccer magazine. That data too is available only for a rather short sub-period of our investigation (since the beginning of the 1995/1996 season).…”

Influences on sponsorship deals in NASCAR: indirect evidence from time on camera

“…Knowing that multiple mediocre performances do not add up to the quality found in one great performance (Rosen 1981) magnifies the importance of finding these superstars. Hamlen (1991Hamlen ( , 1994 and Kruger (2005) analyze this in vocal musical talent and Franck and Nüesch (2010) analyze both talent and popularity in German soccer to see what it takes to be a superstar. Our data provide a unique opportunity to study the value of both performance and celebrity on superstar status by analyzing NASCAR drivers.…”