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1.
PLoS One ; 13(8): e0201795, 2018.
Artigo em Inglês | MEDLINE | ID: mdl-30089178

RESUMO

The main objective of this research was to determine the existence of relative age effect (RAE) in five European soccer leagues and their second-tier competitions. Even though RAE is a well-known phenomenon in professional sports environments it seems that the effect does not decline over the years. Moreover, additional information is required, especially when taking into account second-tier leagues. Birthdates from 1,332 first-tier domestic players from France, England, Spain, Germany and Italy and birthdates from 1,992 second-tier domestic players for the 2014/2015 season were taken for statistical analysis. In addition to standard statistical tests, the data were analyzed using econometric techniques for count data using Poisson and negative binomial regressions. The results obtained confirmed a biased distribution of birthdates in favor of players born earlier in the calendar year. For all of the five first-tier soccer leagues there was an unequal distribution of birthdates (France χ2 = 40.976, P<0.001; England χ2 = 21.892, P = 0.025; Spain χ2 = 24.690, P = 0.010; Germany χ2 = 22.889, P = 0.018; Italy χ2 = 28.583, P = 0.003). The results for second-tier leagues were similar (France χ2 = 46.741, P<0.001; England χ2 = 27.301, P = 0.004; Spain χ2 = 49.745, P<0.001; Germany χ2 = 30.633, P = 0.001; Italy χ2 = 36.973, P<0.001). Econometric techniques achieved similar results: estimated effect of month of birth, i.e., long-term RAE on players' representativeness, is negative (statistically significant at the 1% level). On average, one month closer to the end of the year reduces the logs of expected counts of players by 6.9%. Assuming this effect as linear, being born in the month immediately before the cut-off date (i.e., December/August), reduces the logs of expected counts of players by approximately 75.9%. Further, ID (index of discrimination, that is, the ratio between the expected counts of players born in the middle of the first and the twelfth month of the selection year) is 2.13 and 2.22 for the first- and second-tier, respectively. In other words, in the top five European first-tier and second-tier leagues, one should expect the number of players born in the first month of the calendar year to be twice the number of those born in the last month. The RAE in the second-tiers is the same as in the first-tiers, so it appears that there is no second chance for later born players. This reduces the chances to recover talented players discarded in youth simply because of lower maturity.


Assuntos
Atletas , Futebol , Fatores Etários , Europa (Continente) , Humanos , Modelos Econométricos , Análise de Regressão
2.
PLoS One ; 12(8): e0182827, 2017.
Artigo em Inglês | MEDLINE | ID: mdl-28806751

RESUMO

Like many sports in adolescence, junior hockey is organized by age groups. Typically, players born after December 31st are placed in the subsequent age cohort and as a result, will have an age advantage over those players born closer to the end of the year. While this relative age effect (RAE) has been well-established in junior hockey and other professional sports, the long-term impact of this phenomenon is not well understood. Using roster data on North American National Hockey League (NHL) players from the 2008-2009 season to the 2015-2016 season, we document a RAE reversal-players born in the last quarter of the year (October-December) score more and command higher salaries than those born in the first quarter of the year. This reversal is even more pronounced among the NHL "elite." We find that among players in the 90th percentile of scoring, those born in the last quarter of the year score about 9 more points per season than those born in the first quarter. Likewise, elite players in the 90th percentile of salary who are born in the last quarter of the year earn 51% more pay than players born at the start of the year. Surprisingly, compared to players at the lower end of the performance distribution, the RAE reversal is about three to four times greater among elite players.


Assuntos
Atletas , Hóquei , Adolescente , Fatores Etários , Humanos , Renda , Análise de Regressão , Adulto Jovem
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