Abstract:The relative age effect (RAE) is a statistical bias observed across sport contexts and consists of a systematic skewness in birth date distribution within an annual-age cohort. In soccer, January 1st is the common cut-off date when categorizing players in competitions according to their chronological age, which potentially disadvantages those within the cohort who were born later in the year. Thus, relatively older soccer players in their cohort can be favored in talent identification, selection, and developme… Show more
“…Nevertheless, the difference in sample selection (i.e., the first one considering the Italian national teams and the second one considering the Italian national teams) may partially explain these results. On the other hand, data corroborated previous results underlined as RAE disappears from youth to senior level [ 20 , 24 ].…”
Section: Discussionsupporting
confidence: 90%
“…While the RAE is well documented in male football, whereby a consistent and pervasive RAE exists, especially in the youth age groups [ 14 , 18 , 19 ], its presence remains inconclusive in females [ 17 , 21 ]. More specifically, the RAE seems mixed depending on contextual factors such as sociocultural context (i.e., depth of competition, attraction level and country-specific differences) [ 22 ], age groups [ 20 ], competition levels [ 23 ], playing positions [ 20 ], and historical moment [ 24 ]. For example, there was a significant difference in quartile distributions across elite German national teams [ 25 ] (i.e., Q1~31% vs. Q4~21%).…”
Section: Introductionmentioning
confidence: 99%
“…Similarly, high-level senior French players did not present the RAE [ 26 ] whereas players born near the selection date in Italy were about 1.62 times more likely to reach the high-level tiers [ 27 ]. Likewise, when considering Women’s Football World Cup rosters (years between 2008–2019), the RAE effect sizes have been identified only in the U17 and U20 tournaments but not in senior tournaments [ 20 , 24 ]. In particular, for the Under 17 and 20 age groups, a RAE was observed (i.e., Q1~33% vs. Q4~20%), especially when considering midfielders (i.e., Q1~37% vs Q4~17%) [ 20 ].…”
This study aimed to evaluate youth-to-senior transition and the relative age effect in Italian female football national teams. Birthdate data of 774 female players selected for Under 17 (N = 416), 19 (N = 265) and National Senior team (N = 93) were analysed. The youth-to-senior transition rate was determined by the number of youth players competing in the Senior National team (and vice versa), whilst birth quarter (Q) distributions with a chi-square goodness-of-fit test. Only 17.4% of youth players were able to be selected for the Senior National team, whereas 31.2% of the players reached the high-senior level without being selected for youth age groups. Data revealed a skewed birth date distribution in Under 17 and 19 teams (on average, Q1 = 35.6% vs Q4 = 18.5%) but not in the Senior National team. Youth players born in Q1 were two times more likely to be selected than in Q4. In Under 17, goalkeepers, defenders, and midfielders of Q1 players were overrepresented. However, Q4 players recorded higher conversion rates than Q1 (Q1 = 16.4% vs. Q4 = 25.0%). National youth experience may not be a prerequisite for being selected at the senior level. Moreover, this confers a higher probability of playing in the National Senior team than players not selected in youth rosters.
“…Nevertheless, the difference in sample selection (i.e., the first one considering the Italian national teams and the second one considering the Italian national teams) may partially explain these results. On the other hand, data corroborated previous results underlined as RAE disappears from youth to senior level [ 20 , 24 ].…”
Section: Discussionsupporting
confidence: 90%
“…While the RAE is well documented in male football, whereby a consistent and pervasive RAE exists, especially in the youth age groups [ 14 , 18 , 19 ], its presence remains inconclusive in females [ 17 , 21 ]. More specifically, the RAE seems mixed depending on contextual factors such as sociocultural context (i.e., depth of competition, attraction level and country-specific differences) [ 22 ], age groups [ 20 ], competition levels [ 23 ], playing positions [ 20 ], and historical moment [ 24 ]. For example, there was a significant difference in quartile distributions across elite German national teams [ 25 ] (i.e., Q1~31% vs. Q4~21%).…”
Section: Introductionmentioning
confidence: 99%
“…Similarly, high-level senior French players did not present the RAE [ 26 ] whereas players born near the selection date in Italy were about 1.62 times more likely to reach the high-level tiers [ 27 ]. Likewise, when considering Women’s Football World Cup rosters (years between 2008–2019), the RAE effect sizes have been identified only in the U17 and U20 tournaments but not in senior tournaments [ 20 , 24 ]. In particular, for the Under 17 and 20 age groups, a RAE was observed (i.e., Q1~33% vs. Q4~20%), especially when considering midfielders (i.e., Q1~37% vs Q4~17%) [ 20 ].…”
This study aimed to evaluate youth-to-senior transition and the relative age effect in Italian female football national teams. Birthdate data of 774 female players selected for Under 17 (N = 416), 19 (N = 265) and National Senior team (N = 93) were analysed. The youth-to-senior transition rate was determined by the number of youth players competing in the Senior National team (and vice versa), whilst birth quarter (Q) distributions with a chi-square goodness-of-fit test. Only 17.4% of youth players were able to be selected for the Senior National team, whereas 31.2% of the players reached the high-senior level without being selected for youth age groups. Data revealed a skewed birth date distribution in Under 17 and 19 teams (on average, Q1 = 35.6% vs Q4 = 18.5%) but not in the Senior National team. Youth players born in Q1 were two times more likely to be selected than in Q4. In Under 17, goalkeepers, defenders, and midfielders of Q1 players were overrepresented. However, Q4 players recorded higher conversion rates than Q1 (Q1 = 16.4% vs. Q4 = 25.0%). National youth experience may not be a prerequisite for being selected at the senior level. Moreover, this confers a higher probability of playing in the National Senior team than players not selected in youth rosters.
“…A statistically significant difference was found between the groups of quarters. In another study (Pedersen et al, 2022) on male football players who participated in the under-17 World Cup between 1997-2019, the number of football players born in the first quarter of the same year was higher than the number of football players born in other quarters.…”
This present study aims to examine the phenomenon of the relative age effect among football players based on birth year and the positions they played in Turkish professional leagues. A total of 3622 professional football players from Turkish Super League, Spor Toto 1stLeague, 2ndLeague and 3rd League were included in the study. The players were divided into 4 different quarters with 3-month intervals and 2 different half-terms with 6-month intervals starting from January. The data of the second half of the 2021-2022 football season were used in the research. The data of the study were obtained from the official and open-access web pages of the Turkish Football Federation and Transfermarkt. With the chi-square test, the distribution of the football players according to birth months, positions and leagues and the frequency distribution differences between the groups were analyzed. SPSS 22 statistical package program was used to analyze data and the significance level was accepted as p
“…The relative age effect (RAE) refers to differences in athlete selection that are related to subtle age differences between athletes, such that differences in time of year of the athletes’ births differ within a given age year group (Helsen et al, 2012; Musch & Grondin, 2001; Pedersen, et al, 2022). For example, in Japan, April is the cutoff month for division play because schools begin in April.…”
We investigated recent trends in relative age effect (RAE) findings of top-level female soccer players in Japan, using data from the 2016 to 2020 seasons. We conducted two main analyses: (a) An examination of RAE for all registered players in the Japan Women’s Soccer League (Nadeshiko League) from 2016 to 2020; and (b) an examination of RAE of newly registered players in the league from 2017 to 2020. In the first analysis, we found a significant difference between the number of players born in Q1 (April–June) versus Q4 (January–March), with the number of players born in Q1 greater and with the ratio between these groups ranging from 1.5 to 1.7. In the second analysis, we found a significant relationship between Q1 and Q4 for the 2017 season alone. However, the Q1/Q4 ratio ranged from 1.4 to 1.9, and the semester ratio of S1 (Q1 + Q2))/S2 (Q3 + Q4) ranged from 1.2 to 1.3, suggesting a birth month bias. Thus, there was a RAE in female soccer players playing recently in Japan’s top-level leagues; and the size of the effect did not change significantly across recent seasons.
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