Physical attractiveness and monetary success in German Bundesliga

Abstract

That attractive people are more successful has been proved for many areas of life in the past. However, the effects of the attractiveness of professional athletes have not been examined yet. This is surprising as it is comparatively simple to measure the actual performance of this group of people and to control their performance in statistical models. In the study, 438 professional football players were examined who played in the 18 teams of the German Bundesliga in 2007 and 2008. It was analyzed how their facial and bodily attractiveness influence their market value. Bodily attractiveness was operationalized using the Body Mass Index, facial attractiveness was measured using the Truth of Consensus Method. Statistical analysis shows that both facial and bodily attractiveness have considerable effects on a player’s market value even if his actual performance is controlled.

Notes

1. Walster et al., ‘Importance of Physical Attractiveness’; Grammer, Signale der Liebe [Signals of Love].

2. Gangestad and Thornhill, ‘Evolutionary Psychology of Extra-pair Sex’; Thornhill and Gangestad, ‘Human Fluctuating Asymmetry’; Thornhill et al., ‘Female Orgasm and Male Fluctuating’.

3. Langlois et al., ‘Maxims or Myths of Beauty’; Shackelford et al., 2000; Thornhill et al., ‘Female Orgasm and Male Fluctuating’.

4. Elder, ‘Marriage Mobility’; Marwick, ‘Beauty in History’; Udry and Eckland, ‘Benefits of Being Attractive’.

5. However, it is also the case – on the other side of the coin, as it were – that attractive individuals run a significantly higher risk of separation (Feingold, ‘Matching for Attractiveness’; White, ‘Physical Attractiveness’); furthermore, men whose contact with young and attractive women is, as a result of their job, more intense than the average (such as college professors) likewise have a disproportionately high risk of divorce (Kanazawa and Still, ‘Teaching and Marriage’).

6. Solnick and Schweitzer, ‘Influence of Physical Attractiveness’.

7. Hamermesh and Parker, ‘Beauty in the Classroom’; Klein and Rosar, ‘Das Auge hört mit! [The Eye is Also Listening!]’.

8. Biddle and Hamermesh, ‘Beauty, Productivity, and Discrimination’; Cash et al. ‘Sexism and “Beautyism”’; Frieze et al., ‘Attractiveness in Management’; Hamermesh and Biddle, ‘Beauty and the Labor’; Harper, ‘Beauty, Stature and Labour’; Hosoda et al., ‘Effects of Physical Attractiveness’.

9. Reingen and Kernan, ‘Social Perception and Interpersonal Influence’; DeShields et al., ‘Purchase Decisions’.

10. Efran and Patterson, ‘Voters Vote Beautiful’; Berggren et al., ‘Looks of a Winner’; King and Leigh, Beautiful Politicians; Klein and Rosar, ‘Physische Attraktivität und Wahlerfolg’; Klein and Rosar ‘Deutschland reif für Kanzlerin’; Klein and Rosar ‘Sie oder Er?’; Rosar, ‘Fabulous Front-Runners’; Rosar et al., ‘Frog Pond Beauty Contest’; Rosar et.al., ‘Magic Mayors’.

11. Deseran and Chung, ‘Appearance and Role-taking’; Mace, ‘The “overt-bluff” shoplifter’; Steffensmeier and Terry, ‘Deviance and Respectability’.

12. Downs and Lyons, ‘Links Between Attractiveness and Judgements’; Efran, ‘Effect of Physical Appearance’; Esses and Webster, ‘The Canadian Criminal Code’.

13. Langlois et al., ‘Maxims or Myths of Beauty?’.

14. Langlois et al., ‘Infant Attractiveness’.

15. Langlois et al., ‘Maxims or Myths of Beauty?’.

16. McCabe, ‘Facial Proportions’.

17. Anderson et al., ‘Who Attains Social Status?’; Dion and Berscheid, ‘Physical Attractiveness Among Children’; Krantz, ‘Physical attractiveness and popularity’; Rost, ‘Attraktive Grundschulkinder’; Vaughn and Langlois, ‘Social Competence in Preschool Children’.

18. Baugh and Parry, ‘Physical Attractiveness and Grade Point’; Landy and Sigall, ‘Beauty is Talent’; Maisonneuve and Bruchon-Schweitzer, Le corps et la beauté, 52; Rost, ‘Attraktive Grundschulkinder’.

19. Clifford and Walster, ‘Attractiveness on Teacher Expectations’; Dion et al., ‘What is Beautiful is Good’; Dunkake et al., ‘Schöne Schüler, schöne Noten? [Good Looks, Good Grades?]’; Ross and Salvia, ‘Attractiveness in Teacher Judgments’.

20. Schnabel, ‘Grundkonzept “Sportliche Leistung”’, 33.

21. For a general overview, see: Grammer, Signale der Liebe [Signals of Love]; Renz, Schönheit – Eine Wissenschaft [The Science of Beauty]; in relation to the specific purposes of this study, see also: Klein and Rosar, ‘Physische Attraktivität und Wahlerfolg [Physical Attractiveness and Electoral Success]’; Rosar et al., ‘Frog Pond Beauty Contest’.

22. Köhler, ‘Physische Attraktivität und Persönlichkeitsmerkmale’‚ 140ff.

23. Cunningham, ‘Physical in Physical Attractiveness’; Cunningham et al., ‘What Do Women Want?’; Cunningham et al., ‘Perception of Female Physical Attractiveness’; Henss, ‘Beurteilerübereinstimmung [Interrater Agreement]’; Henss, Spieglein an der Wand [Mirror, Mirror on the Wall]; Iliffe, ‘Preferences in Feminine Beauty’.

24. Rosar et al., ‘Frog Pond Beauty Contest’, 67.

25. Maner et al., ‘Sexually Selective Cognition’.

26. Dermer and Thiel, ‘When Beauty May Fail’; Dion et al., ‘What is Beautiful is Good’; Eagly et al., ‘What is Beautiful is Good’; Feingold, ‘Good-looking People’; Miller, ‘Attractiveness in Impression Formation’.

27. Dabbs and Stokes, ‘Beauty is Power’; Dion and Berscheid, ‘Physical Attractiveness Among Children’; Hartnett et al., ‘Determinants of Personal Space’; Hatfield and Sprecher, Mirror, Mirror; Langlois et al., ‘Maxims or Myths of Beauty?’; Marwick, ‘Beauty in History’; Mulford et al., ‘Opportunity and Success in Everyday Exchange’; Ritter et al., ‘Adults’ Responses’; White and Langlois, ‘Baby Beautiful’.

28. Rosar et al., ‘Frog Pond Beauty Contest’ 67.

29. Bassili, ‘The Attractiveness Stereotype’; Grammer, Signale der Liebe [Signals of Love], 169.

30. Rosar et al., ‘Frog Pond Beauty Contest’ 68.

31. Rosar et al., ‘Frog Pond Beauty Contest’, 67f.

32. Football players who moved between the 18 teams during the 2007/2008 season are allocated to the team for which they played last. It was necessary to exclude football players who ended their career after the 2007/2008 season as, by announcing their intention to retire, they no longer had any market value.

33. Cf. www.transfermarkt.de. The transfer value is the value for which a club is prepared to sell a player and for which at least one other club is prepared to buy that player. It is estimated by the registered users of the transfermarkt forum as part of the market value analysis. In the ideal case, the estimated market value can predict the transfer value that is subsequently realised. However, it must be assumed that the market value analysis does not take account of the remaining contract time and strategic considerations by purchasers – for example to weaken competitors. When estimating market value on transfermarkt, registered users must follow a set of guidelines which defines the crucial evaluation criteria of net asset value and future prospects. User amendments to the market value are not applied immediately after submission; they must first be reviewed by administrators and data managers. The forum relies on the principle that, given a sufficiently large number of estimates, taking an average must give a realistic figure. In this it has certain similarities to the academic concept of finding truth through discourse.

34. It would, of course, be desirable to base the analyses on actual transfer fees paid and on player salaries, rather than on the market values. However, this is not possible as the sample size is too small. This is in part because the number of transfers for which a transfer fee is paid in an individual season is comparatively low. It is also due to the fact that, on the whole, clubs do not produce generally accessible data on the salaries of their players and, in some cases, non-disclosure agreements are signed regarding the level of transfer fees paid, too. It is therefore only in exceptional cases that we know how much a professional footballer earns, and occasionally the value of the transfer fee cannot be determined either. Nevertheless, the market value of a football player is – as far as this can be checked – a very reliable proxy variable for illustrating the proportional differences between professional footballers in terms of salary and transfer fees: on 28 May 2008, SportBILD-Online published the current annual salaries of the players in the starting squad of the national football team for the 2008 European championship (SportBILD-Online 2008). There is a correlation between these salaries and the market value of the players at the end of the 2007/2008 Bundesliga season, r = 0.74 (p = 0.000; N = 26). In the 2008 summer break, a transfer fee was paid in relation to a total of 96 footballers who transferred either between the 18 clubs which played in the German Bundesliga in 2007/2008, from these 18 clubs to clubs in other leagues, or from clubs in other leagues to these 18 clubs. The transfer fees paid are known for 91 of these 96 football players. There is a correlation between these and the market value of the players at the end of the 2007/2008 Bundesliga season, r = 0.91 (p = 0.000; N = 91).

35. Cf. www.fussballdaten.de.

36. Cf. www.kicker.de.

37. On the 28th matchday, the game between 1. FC Nürnberg and VfL Wolfsburg had to be abandoned. It was replayed on a different day. Selection of players for the abandoned game was taken into account as was selection of players for the replay.

38. The football magazine kicker has a reporter assigned to each Bundesliga team, who monitors every game of that team in the stadium in the role of expert. After the game, the reporter for the home team and the reporter for the away team come to an agreement on the grades for each individual player to be assessed.

39. If a player is played for less than 20 min, they are only awarded a grade by the kicker reporters if the footballer in question has nonetheless had a crucial influence on the game. As a rule, however, no grade is given, as the duration of play – in the opinion of the editorial team – is not sufficient for a valid assessment of performance. However, if the time is not sufficient for an assessment of performance, it should be the case that a player can neither be praised nor blamed. His performance profile for the game in question is thus neutral. For this reason, players whose performance was not assessed by the kicker reporters because their duration of play was too short have been allocated a neutral grade of 3.5 for the relevant game.

40. IMPIRE AG runs the Bundesliga database (cf. www.bundesliga-datenbank.de), which was previously also marketed under the name ran database. Each Bundesliga game is monitored by four specially trained game observers (scouts), two of whom sit in the stadium. This means that statistics on each player are gathered live. More than 2000 events are recorded per game. Each individual action of the player, i.e. each pass, each tackle, each foul, each shot at goal, each goal and so on, is documented. Yellow and red cards are verified after the game in discussion with the referee. Selected live data, in the form of a ticker or statistics, are made available to all customers, such as TV stations, online services and print media, as well as to football clubs and professional associations, in real time during the game. Following the game, the matches are once more analysed in detail and coded by specialist editors from IMPIRE AG using video recordings. So, for example, in the case of goals, there are 19 distinct information details: goal scorer, assist, head/foot, attacking side, counterattack yes/no, etc. The data for each player on each matchday is summarised in the standard player rating point system. In the process, different events are calculated using standardised criteria to give an overall score. There is a general and a position-related scorecard for each player. The general scorecard distinguishes between 28 score criteria. For example, for each goal scored by the player himself he receives +100 points, for each penalty converted he receives +50 points, for a major error in front of an opponent’s goal he receives –100 points and for each yellow or red card he receives –75 points. The position-related scorecards contain distinct criteria for goal (8 criteria), defender (8 criteria), midfielder (7 criteria) and forward (5 criteria). For example, a defender receives +20 points for a successful tackle, while a midfielder receives +15 points and a forward receives +5 points for a successful tackle on the ground and +3 points for a successful header tackle. There are no set limits on the overall score in either a positive or negative direction. It is only limited by the fact that there cannot be an infinite number of events within one game of football.

41. Grammer, Signale der Liebe [Signals of Love]; Renz, Schönheit – Eine Wissenschaft [The Science of Beauty].

42. Of course, we are aware that the Body Mass Index in the specific context of this study also indicates superior athletic ability: having more muscles can imply a higher level of physical fitness and should moreover be a direct advantage when tackling on the football pitch. However, in the empirical analyses reported in the next section this aspect will be moderated by the indicators of athletic performance with the result that it can be disregarded when interpreting the effects of Body Mass Index on the market value.

43. The height and weight of these players were also collected for the same reason.

44. Patzer, The Physical Attractiveness Phenomena, 17.

45. cf. Grammer et al., ‘Darwinian aesthetics’; Henss, ‘Beurteilerübereinstimmung [Interrater Agreement]’; Henss Spieglein an der Wand [Mirror, Mirror on the Wall]; Iliffe, ‘Preferences in Feminine Beauty’.

46. Henss, Spieglein an der Wand [Mirror, Mirror on the Wall], 308.

47. Here and below, only those raters are included who evaluated all the photographs that were presented to them.

48. At this point we would like to express our sincere thanks to Respondi AG. Without the generous support of Respondi AG, the study would not have been possible in the present format.

49. The photographs of the players were presented to the raters sorted by team, with each rater only getting to see the players from one individual team, selected at random. Within the team blocks, the sequence in which the photographs were presented was likewise determined at random and reset for each rater.

50. It was nevertheless possible, of course, that the raters might recognise the footballers to be evaluated, and that this recognition, together with a correspondingly positive or negative attitude towards the player’s team, could have an influence on the attractiveness score. For this reason, for each photograph the rater was asked whether the individual depicted was familiar and what his name was. However, the individual depicted was correctly identified in only 42 of a total of 9888 measurements (0.4%), so this aspect can be completely disregarded.

51. The arithmetic mean is 20.43 and the median is 20.00. The minimum is 14 and the maximum is 26. The standard deviation is 3.57.

52. The minimum is 0.72, the maximum is 0.87 and the standard deviation is 0.04. As the literature offers a range of criticisms regarding the use of Cronbach’s α as a measure of correlation between assessments (cf. Hassebrauck, ‘Beurteilung der physischen Attraktivität [The Evaluation of Physical Attractiveness]’; Hönekopp, ‘Beauty in the Eye’; and the fundamental statements on reliability measures in Asendorpf and Wallbott, ‘Maße der Beobachtungsübereinstimmung [Measures of Observer Agreement]’ and in Shrout and Fleiss, ‘Intraclass Correlations’), we also determined the intraclass correlation. This was on average 0.34, i.e. just a third of the overall variation in judgement that can be observed can be attributed to the raters, with two thirds being ascribed to the photographs evaluated. This can be interpreted to the effect that the attractiveness judgements were first and foremost determined by the individuals depicted in the photographs and only to a lesser extent by the idiosyncratic taste of the raters.

53. Football players who are not included in the population of the study were not taken into account in calculating the statistical figures. The same applies to the illustration in Figure 1.

54. Braun et al., Beautycheck; Grammer, Signale der Liebe [Signals of Love]; Renz, Schönheit – Eine Wissenschaft [The Science of Beauty].

55. for the method cf. Bryk and Raudenbush, Hierarchical Linear Models; Hox, Multilevel Analysis; Snijders and Bosker, Multilevel Analysis.

56. With increasing age, retirement draws unavoidably closer. The market value is expected to decrease accordingly.

57. The effect of ethnocentric prejudices on the market value of a footballer cannot be ruled out. Players with apparently Northern European physiognomy should in that case have an advantage compared to players who look Mediterranean, players with an Asian complexion and players with a black African appearance. The characteristic of ethnic appearance was therefore incorporated into the dummy coding in the analysis models, with a Northern European appearance forming the reference category. Classification of the players in terms of their ethnic appearance was carried out by the author of the study.

58. Forwards are the stars of any football team and goalkeepers only come into view when their team is in a critical situation. The effect of playing position on market value due to a visibility effect – in the same way as the Attractiveness Attention Boost – cannot be ruled out. For this reason, the playing position was incorporated into the dummy coding in the analysis models. The position of goalkeeper forms the reference category.

59. Wealthy teams are in a better position to recruit top quality football players than poorer teams. In the case of a footballer who plays for a wealthy team, however, this in turn can lead to an increase in market value due to the inversion of the argument, namely that he must be good because he is playing for a wealthy team. Like the market values of the individual players, the market values of the clubs were sourced from the transfermarkt website and have been added to the data-set in increments of millions of euro.

60. The effect of the prestige of a club on the market value of a footballer under contract with that club cannot be ruled out. The prestige of a club might best be measured in terms of its past sporting successes. For this reason, the ranking of the clubs in the Bundesliga table at the end of each of the previous 10 seasons has been coded. If a club has won the German championship it is allocated a value of 18, if it is in second place it is allocated a value of 17, and so on. Clubs that were relegated to the 2nd division or a regional league during the period were allocated a value of zero for the respective season. Finally, the point values for each club were calculated to give a mean score. A higher mean should indicate a club with greater prestige.

61. The lowest Body Mass Index was 19.75 and the highest was 26.59. The average Body Mass Index was 23.35 and the standard deviation was 1.13.

62. For more detail on the statistical parameters see the last paragraph in Section 2.

63. Having been played in 28 matches, he is one of the most regular players. In the footballer performance score he came 2nd with a value of 4.46 and in the Impire performance score he was likewise in 2nd place with a value of 279.93.

64. What Franck Ribéry would look like were it not for the consequences of the car accident can be easily checked by searching on the Internet for photographs of François Ribéry. François Ribéry is currently under contract with the French football club Calais RUFC and is Franck Ribéry’s younger brother. The family resemblance between the brothers is striking.

65. Nevertheless, the findings appearing in relation to Franck Ribéry do give rise to further contemplation. The ‘Ribéry Effect’ could simply be what it appears at first sight, namely an individual outlier. However, the effect could also indicate a systematic correlation acting in the background. On the one hand, it is conceivable that, under particular circumstances, scars resulting from injuries – scars are generally considered to be manly in any case – could have the effect of increasing prestige. At least one current study by Burris et al. (2009) points in this direction. On the other hand, however, it could indicate a sort of Ugliness Premium, a mirror image of what is known as the Beauty Penalty. Wilson and Eckel (2006) used experimental studies of game theory to show that attractive individuals who disappoint the (often inflated) expectations placed on them are sanctioned more stringently than less attractive individuals. If, with a reversal of the signs, something comparable happens at the other end of the attractiveness scale, then unattractive individuals whose performance surpasses the expectations placed on them must be able to count on a disproportionately high level of reward. The extent to which these considerations are empirically sustainable cannot be investigated due to the foundation of the data used here.

66. The calculations also took account of the 46 professional footballers who were not part of the population or who transferred between the 18 teams of the German Bundesliga during the season. On this subject, see Section 2.