Abstract:The purpose of this study was to investigate the relative age effect and the age of peak performance of women's football players who participated in the Olympic Games from 1996 to 2016. Methods: Birth dates, playing positions, and nationality of all players registered in women's football competition in the Olympic Games (1996 to 2016) were collected. All data used in this study were obtained from the official website of the Federation Internationale de Football Association (www.fifa.com). The sample size of th… Show more
“…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 ]. Differently, Andrew et al [ 21 ] found no RAE in UEFA European tournaments of U17, U19, and senior age groups between 2019–2022, whilst Barreira et al [ 28 ] reported no RAE in Olympic tournaments between 1996–2016. On the other hand, the few analyses on the national academy talent system (i.e., Swiss and U.S.) showed that the RAE is dependent by competition levels [ 29 , 30 ].…”
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.
“…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 ]. Differently, Andrew et al [ 21 ] found no RAE in UEFA European tournaments of U17, U19, and senior age groups between 2019–2022, whilst Barreira et al [ 28 ] reported no RAE in Olympic tournaments between 1996–2016. On the other hand, the few analyses on the national academy talent system (i.e., Swiss and U.S.) showed that the RAE is dependent by competition levels [ 29 , 30 ].…”
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.
“…However, the finding indicates that relatively early-born players are over-represented among youth team players in the big clubs, as well as among senior teams in the big leagues. Among female international players, a quite recent study reported small, insignificant effects in Olympic tournaments since 1996 [ 63 ]. Sedano et al [ 57 ] had previously reported a clear effect among Spanish national teams; however, their sample was combined from U17, U19, U21, and senior players, with a rather small total N of 232.…”
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 development. The aim of the current study was to investigate the variations in RAE in male and female international youth world-cup tournaments (U17 and U20) in the period from 1997–2019 and in international senior world-cup-tournaments from 2006–2019. A total of 20,401 soccer players participating in 47 different tournaments were analyzed. The birthdate distributions were categorized into four quartiles (January-March, Q1; April-June, Q2; July-September, Q3; October-December, Q4) and compared to a uniform distribution using Chi-square analysis with Cramer’s V (Vc) as a measure of effect size. Based on the existing data concerning RAE in elite junior and senior soccer, it was hypothesized that: (I) the RAE is present in youth soccer world cup tournaments but is stronger in male players than in female players; (II) the younger the soccer players, the stronger the RAE; and (III) the RAE in world cup soccer tournaments has strengthened over time. All these hypotheses were supported by the data; novel findings included that the effect has now entered women’s soccer, and in men’s soccer it persists into senior world cup tournaments. Thus, a strong RAE bias occurs in selection among elite soccer players competing in international world cup tournaments.
“…Next, we calculated the coefficient of variation (CV) and mean age for each player before dividing the players into three groups: pre-peak age (<23 years old), peak age (23–27 years old), and post-peak age (>27 years old) ( Table 1 ). Given that peak age studies in women’s football are almost non-existent we based the peak age dichotomization on 1) the study by Barreira et al (2021) reporting a peak age of approximately 25 years old, and 2) studies on male elite players showing peak age band between 25–27 years old ( Dendir, 2016 ). We also felt extending this age band to include ages 23–25 years was appropriate due to the league being comparatively young in comparison to the men’s league.…”
Introduction: The fluctuation of external match load throughout a season is influenced by several contextual factors. While some, have been deeply analysed in men’s football literature, information is lacking on how other contextual elements, such as player’s age or experience, may affect the match-to-match variability of locomotor activities. In fact, aging has been described as a multifactorial process with the potential to affect human performance. The aim of this study is to assess if the variability of match locomotor performances fluctuates according to the players’ age.Methods: 59 female players from four top-level clubs were divided into three age groups and monitored during two seasons using GPS APEX (STATSports, Northern Ireland), with a sampling frequency of 10Hz, in 150 official matches to determine the coefficient of variation (CV) of full-match and 1-min peak locomotor demands of total distance (TD), high-speed running distance, sprint distance (SpD), accelerations, and decelerations. To test whether there was a group effect of age on match-to-match variability we used a one-way ANOVA with CV% as the independent variable.Results: CV values of full match variables ranged from 3.8% to 27.8%, with total distance (3.8%) in the peak age group and SpD (27.8%) in the pre-peak age group. Similarly, CV values of 1-min peaks ranged from 4.1% (post-peak group) in TD to 22.3% (peak group) in SpD.Discussion: The main finding was that there were no significant differences between the different age groups in the metrics analysed although trends indicate less variability in the post-peak age group.
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