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Relative Age Effect Among Elite Youth Male Soccer Players Across the United States Ajit Korgaokar, Richard S. Farley, Dana K. Fuller & Jennifer L. Caputo.

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Presentation on theme: "Relative Age Effect Among Elite Youth Male Soccer Players Across the United States Ajit Korgaokar, Richard S. Farley, Dana K. Fuller & Jennifer L. Caputo."— Presentation transcript:

1 Relative Age Effect Among Elite Youth Male Soccer Players Across the United States Ajit Korgaokar, Richard S. Farley, Dana K. Fuller & Jennifer L. Caputo Department of Health and Human Performance, Middle Tennessee State University, Murfreesboro, TN Abstract The relative age effect (RAE) in sports is an asymmetry in birthdate distribution where an overrepresentation of athletes born earlier in the cohort and an underrepresentation of athletes born later in the cohort exists. Despite a wealth of literature on RAE, few studies have examined U.S. soccer players. Purpose: To determine the existence of a RAE among elite youth male soccer players competing in the United State Soccer Developmental Academy (USSDA) during the season. Methods: Player birthdates (u15/u16 n = 1,724; u17/u18 n = 1,494) were collected from the USSDA website and compared to the birthdate distribution for the general population. Player birthdates were organized into quartiles (Q1-Q4) based upon the U.S Soccer Academy competition year of January 1 st –December 31 st. Results: The data revealed a RAE among the u15/u16 age group indicating a preference for the selection of the oldest in the cohort. An overrepresentation of players was observed in Q1 (34%) and an underrepresentation in Q4 (20%). The birthdate distribution for the first (56%) and second (44%) halves of the season showed significant differences, exhibiting a bias against the selection of boys born between July and December in the u15/u16 age group. No RAE was observed among the u17/u18 age group when analyzed into quartiles or by halves of the competition year. The largest number of players was represented in Q4 (28%) with the lowest in Q2 (19%), and the majority of the players were born in the second half of the competition year (54%) compared to the first half (46%). Conclusion: The current research indicated that the youngest in elite soccer across the U.S. are disadvantaged when organized into cohorts. Future research should focus on key factors contributing to RAEs in youth soccer. Structural changes designed to reduce or eliminate RAEs should be examined, evaluated, and implemented where appropriate. Purpose To determine the existence of a RAE among elite youth male soccer players competing in the United State Soccer Developmental Academy (USSDA) during the season.. Hypothesis: A significant RAE would be present among this group of elite level youth soccer players, indicating a bias against the selection of soccer players born late in the cohort Methodology Participants Amateur elite youth male soccer players competing in the u15/16 ( n = 1,724) and u17/18 ( n = 1,494) age groups in the USSDA during the season were included in this study. For the 2012/2013 season, 80 of the highest level youth clubs across the country were selected to participate in the Academy league. The league was comprised of 3 conferences (East, Central, and West) and 7 divisions. Any male player within the specified birthdate range was eligible to tryout for an Academy team regardless of place of residence or citizenship. Procedures The birthdate for each player was collected from the individual team web pages from the USSDA web site (www.academy.demosphere.com). The birthdates of each player were compared to the birthdates of males in the general U.S. population born during the same years as the players. The birthdate range for the 2012/2013 USSDA player was from The census birthdates were collected from the Center for Disease and Control and Prevention (CDC) vital statistics reports, which was retrieved from the CDC website (www.cdc.gov/nchs/vitalstats.htm). The birthdates for the players and males in the general population were organized into quartiles based upon the USSDA competition year of January 1 st –December 31 st. All birthdates were coded as follows: Q1 = January-March, Q2 = April- June, Q3 = July- September and Q4 = October-December. In addition, half-season analyses were conducted, where the first half of the season was the combination of Q1 and Q2 and the second half of the season was Q3 and Q4 Statistical Analyses A series of chi-square ( χ 2) goodness-of-fit tests were used to determine differences between the observed birth in the cohort and the expected birth month distributions for the births of males born in the U.S. from (the same years as the players). The dependent variable for each analysis was the frequency of soccer players born in each quartile per age group. The level of significance was set at p <.05. Statistically significant chi-square ( χ 2) values were used to calculate an effect size w statistic to determine the strength of the RAE. Post-hoc analyses were conducted for w values ≥ 0.1. Lastly, for statistically significant chi-square ( χ 2) values, standardized residuals were used to determine which observed birthdate quartiles differed from the expected distribution (Turnnidge, Hancock, Côté, 2012). A value of ≥ 1.96 indicated an overrepresentation of births in the quartile and a value of ≤ indicated an underrepresentation of births in the quartile (Sheskin, 2003). Conclusion In summary, the current research indicated that the youngest in elite soccer across the U.S. are disadvantaged when organized into cohorts. Future research should focus on key factors contributing to RAEs in youth soccer. Structural changes designed to reduce or eliminate RAEs should be examined, evaluated, and implemented where appropriate. Birth Quartiles for the u15/16 and u17/18 USSDA Boys’ Age Groups Results The chi-square analysis indicated a statistical difference between the observed and expected quartile distributions for all of the age groups, indicating significant RAEs: (u15/16) χ 2 (3, n = 1724) = 90.26, p <.001 and (u17/18) χ 2 (3, n = 1494) = 34.17, p <.001. When compared to the general population birth distribution, the chi-square test and the post hoc analyses revealed an overrepresentation of players born at the beginning of the cohort and an underrepresentation of players born at the end of the selection year for u15/16 age group. The standardized residuals for the u15/16 age group showed an overrepresentation of players born in Q1 and an underrepresentation of players born in Q2 and Q4. Among the players in the u17/18 age group, the chi-square analyses revealed an underrepresentation of players born toward the middle of the selection year and an overrepresentation of players born at the beginning and the end of the selection year. In the u17/18 age group, the standardized residuals indicated an overrepresentation of players born in Q1 and Q4 and an underrepresentation


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