Young soccer players’ selection: associations with the relative age effect and physical fitness variablesABSTRACT
The study aimed to identify the association of the effect of relative age and physical fitness variables with the approval status of 363 young soccer athletes. Binary logistic regression was used to test the association between approval status and birth quartile and factorial ANOVA to evaluate the effect of category, selection status, and the interaction effect between both in height, 20m linear run and jump height. A total of 95 players were selected. When combining the under-11 and under-13 categories, those born in the first quartile of the year had a 5.37 more chance of being selected (95%CI 1.35-21.41; p=0.017) than those born in the last quartile. The effect of relative age was associated with the selection of players in the younger categories.
Keywords:
Soccer; Adolescent; Birth registration; Athletic performance
RESUMO
O estudo objetivou identificar a associação do efeito da idade relativa e variáveis de aptidão física com o status de aprovação de 363 jovens atletas de futebol. Regressão logística binária foi utilizada para testar a associação entre status de aprovação e quartil de nascimento e ANOVA fatorial para avaliar o efeito da categoria, status de seleção e o efeito de interação entre ambos na altura, corrida linear de 20m e altura do salto. Foram selecionados 95 jogadores. Ao combinar as categorias sub-11 e sub-13, os nascidos no primeiro quartil do ano tiveram 5,37 mais chances de serem selecionados (IC95% 1,35-21,41; p=0,017) do que nascidos no último quartil. O efeito da idade relativa mostrou-se associado à seleção de jogadores nas categorias mais jovens.
Palavras-chave:
Futebol; Adolescente; Registro de nascimento; Desempenho atlético
RESUMEN
El estudio tuvo como objetivo identificar la asociación del efecto de las variables de edad relativa y aptitud física con el estado de aprobación de 363 jóvenes deportistas de fútbol. Se utilizó regresión logística binaria para probar la asociación entre el estado de aprobación y el cuartil de nacimiento y ANOVA factorial para evaluar el efecto de la categoría, estado de selección y la interacción entre ambos sobre la altura, carrera lineal de 20m y altura del salto. Se seleccionaron 95 jugadores. Al combinar las categorías menores de 11 y de 13, los nacidos en el primer cuartil tuvieron 5,37 más posibilidades de ser seleccionados (IC95% 1,35-21,41; p=0,017) que los nacidos en el último. El efecto de la edad relativa se asoció con la selección de jugadores en las categorías más jóvenes.
Palabras-clave:
Fútbol; Adolescente; Registro de nacimiento; Rendimiento atlético
INTRODUCTION
Athletes' trajectories and progressions across a variety of sports does not guarantee that athletes recruited in the early years into the academy will have a higher success rate than those recruited later during adolescence (Mostaert et al., 2022; Durandt et al., 2011; Grossmann and Lames, 2015). Studies involving youth soccer that have investigated players' trajectories and coaches' selection decisions agree that high achievers during childhood and early adolescence may not develop into successful senior professionals (Grossmann and Lames, 2015; Dugdale et al., 2021).
In this regard, both objective and subjective measurements have been used to discriminate among young players with higher potential to become professionals. A variety of anthropometric measurements and physical field tests, including vertical and horizontal jumps, sprints, repeated sprint ability, handgrip strength, aerobic capacity, and psychological evaluations, have been frequently investigated (Massa et al., 2022). While subjective assessments may be contentious, they are sometimes deemed advantageous as seasoned coaches and scouts possess the expertise to evaluate characteristics that are challenging to quantify (Leyhr et al., 2021). Selections decisions appear also based on players' ability to fit in with the requirements of the organization (Rothwell et al., 2022) and are also affected by cognitive bias (Johnston and Baker, 2020).
Notably, these parameters become increasingly important in young players where differences in growth and maturity lead to performance disparities and opportunities (Costa et al., 2023). Thus, being born earlier in their selection year is more likely to success in sports that require or prioritize these attributes (Parr et al., 2020). This overrepresentation of players born in the early months of the year is referred to as the Relative Age Effect (RAE). Recent studies show that RAE persist at professional and youth soccer levels, nevertheless, even if the prevalence of RAE decreases as age increases (Brustio et al., 2018; Lupo et al., 2019; Morganti et al., 2023). Consequently, these gaps create unequal opportunities and competition presence according to chronological age (Pérez-González et al., 2021). The selection bias limits the possibility of potentially selecting talented athletes born late in the year and may result in premature de-selection and dropout (Delorme et al., 2010).
Thus, considering that little is known about the relationship between RAE and other physical fitness variables in young soccer players, especially Brazilians adolescents (Amatori et al., 2024), the present study aims to identify the association of RAE and height, 20-meter linear sprint test and jump height with young soccer players selection.
MATERIALS AND METHODS
Study design and ethics
A cross-sectional study was conducted using secondary data obtained from a male soccer development club in a city in southern Brazil. This refers to a club that develops young athletes and frequently produces players who are transferred to major professional teams in the country. The selection process is consistently conducted by professionals in the field of Physical Education within the club, focusing on technical, tactical, and physical criteria related to the identification of athletes for professional development, ranging from the younger categories up to the under-17 level. All data was collected by the club's specialized team and analyzed by the university's team of researchers. The Research Ethics Committee of the Universidade Federal de Pelotas under protocol number 5.868.803 approved the study.
Participants
A total of 365 adolescents participated in the club selection process in the year 2022. For this study, inclusion criteria were not previously defined as the analysis model and study design do not meet these criteria. All young people received by the club for selection tests were potentially accepted for the study. Participants with incomplete registration forms, i.e., those without information on birth month or information on the final selection status in the club's selection process, were excluded of the data base. For this reason, two subjects were excluded from the analyses and the final sample was composed for 363 participants who were divided into four age categories: under-11, under-13, under-15, and under-17.
Procedures
Data were obtained from the players registration forms, which included information such as date of birth (information for RAE calculation), approval status in the club selection process, height, and the results of physical performance field tests: maximum 20-meter sprint and jump height. The anthropometric measurements and physical fitness field tests were conducted at the sports club under the supervision of the coordination team. It's noteworthy that all tests and measurements were consistently performed in the same location to ensure uniformity and consistency in the data collection process.
Relative age effects
The players were divided into quartiles based on their date of birth within each year: the first quartile represented those born between January and March, the second quartile between April and June, the third quartile between July and September, and the fourth and last quartile between October and December (Barnsley et al., 1985).
Anthropometric assessment
Height was measured with the individuals barefoot, in an upright position and the head positioned in the Frankfurt horizontal plane, using a stadiometer (Filizolla®, Brazil). The choice of this variable was due to the characteristics of the sport and its importance in game actions, such as: disputes for possession of the ball and shots on target.
Maximum 20-meter sprint
The maximum sprint was measured in a 20-meter linear sprint test. For this purpose, photocells (Multisprint, Hidrofit®) were positioned on the field at 0 and 20 meters (test-retest reproducibility with r=0.890). As the participants were unfamiliar with the tests, they received prior guidance on how to perform the sprint. All participants were wearing soccer cleats.
Jump height
To measure jump height (cm) at a contact mat (Jump System®, Nova Odessa, Brazil), the Countermovement Jump (CMJ) was used. The participants were barefoot and placed their hands on their waists (test-retest reproducibility with r=0.930). Two jump attempts were made, and the highest result was recorded.
Statistical analysis
The analyses were conducted using the statistical package Stata, version 16.0. After checking the normality of the data using the Shapiro-Wilk test, descriptive statistics were applied, presenting the mean and standard deviation (SD) for height and physical performance measures and ANOVA was performed to compare these variables according to athlete categories. The Chi-square test for heterogeneity was used to compare the proportion of selected players by birth quartile. Logistic regression with odds ratio and confidence interval (95% CI), was used to test the association between selected status and each birth quartile. The means of height and physical performance measures between RAE categories were also presented and ANOVA was also performed. Due to the sample size, for this analysis, the categories were grouped into under-11 + under-13, and under-15 + under-17. A factorial ANOVA was performed separately for height, sprint, and jump to evaluate the effect of category, selection status effect, and the interaction effect between category and selection status. Post-hoc contrasts with Bonferroni's multiple comparisons test were subsequently conducted to explore significant differences between specific groups. All analyses were stratified by category. The significance level was set at 5%.
RESULTS
Out of the total 363 adolescents who participated in the club selection process, 34 (9.4%) were registered for the under-11 category, 76 (20.9%) for the under-13 category, 130 (35.8%) for the under-15 category, and 123 (33.9%) for the under-17 category (Table 1). Table 1 also presents the description of the stature and physical performance of all players who underwent the tests.
Mean and standard deviation of height and physical performance measures among the analyzed categories.
Ninety-five adolescents were approved in the club selection process, representing 26.2% of the total players who participated in the selection. Among them, 21 were in the under-11 category (61.8%), 24 in the under-13 category (31.6%), 33 in the under-15 category (25.4%), and 17 in the under-17 category (13.8%). Figure 1 presents the distribution of birth quartiles among the selected players in each category.
Distribution of birth quartile among selected individuals according to analyzed categories.
For the under-11 category, 47.6% of the selected players were born in the first quartile of the year and 4.8% in the last quartile. Among the players selected for the under-13 category, the majority were born in the first quartile (54.2%), while 8.3% in the last quartile of the year. For the under-15 category, the distribution was 33.3%, 21.2%, 18.2%, and 27.3%, while for the under-17 category; it was 23.5%, 29.4%, 35.3%, and 11.8% for quartiles 1 to 4, respectively.
Table 2 presents the odds ratios and 95%CI of the association between selection status and birth quartile. It can be observed that when evaluating the entire sample, adolescents born in the first quartile had 2.14 times higher odds of being selected (95%CI 1.06-4.32; p=0.033) compared to those born in the fourth quartile. When stratifying by category, the association remained significant only for the younger players in the under-11 and under-13 categories, where players born in the first quartile of the year had 5.37 times higher odds of being selected (95%CI 1.35-21.41; p=0.017) compared to those born in the last quartile.
According to Table 3, that presented the differences in height and performance measures between the RAE categories, maintaining the same category groupings (under-11+under-13 and under-15+under-17) due to the sample size. No statistically significant differences were observed, it is possible to observe that these measures did not differ according to birth quartiles.
Differences in height and physical performance measures between the RAE categories, for all sample and clustered by category.
According to Figure 2, which describes the mean and 95%CI of the sprint, jump height, and height variables among selected and non-selected individuals in the selection process, it can be observed that the selected individuals in the under-15 and under-17 categories were faster than the non-selected individuals. For the under-15 category, the mean 20-meter sprint time was 3.31 seconds (95%CI 3.22-3.40) among the selected players and 3.44 seconds (95%CI 3.38-3.50) among the non- selected players (p=0.023). For the under-17 category, the respective times were 3.09 seconds (95%CI 3.02-3.16) among the selected players and 3.22 seconds (95%CI 3.17-3.26) among the non- selected players (p=0.024). The factorial ANOVA results show that sprint times differed significantly between categories (p<0.001) and, in general, according to approval status (p=0.001). However, no interaction effect was observed between category and approval status (p=0.985). As observed in Figure 2, height did not differ according to approval status within each category analyzed. According to the factorial ANOVA, this variable differs between categories (p<0.001), but not differ according to approval status (p=0.262). The interaction test does not indicate interaction between category and approval status (p=0.141).
Mean and 95% confidence interval of sprint, jump, and height variables between selected and non-selected individuals in the selection. Note: White symbols indicate selected participants and black symbols indicate non-selected participants. *p<0.05.
Regarding jump height, the categories that showed significant differences were the under-13 and under-17, with the selected individuals having a higher jump. For the under-13 category, the mean jump height was 24.62 cm (95%CI 22.61-26.62) for the selected players and 22.37 cm (95%CI 21.17-23.57) for the non- selected players (p=0.044), while for the under-17 category; it was 34.09 cm (95%CI 31.47-36.71) and 30.27 cm (95%CI 29.17-31.36), respectively (p=0.010). According to factorial ANOVA, the jump height differed between categories (p<0.001), but did not differ according to approval status (p=0.084). The p-value for the interaction effect (p=0.035) indicates that the effect of selection status (selected and non- selected) on the jump variable differs between different categories of athletes. The post-hoc analysis demonstrates that the biggest difference observed was between the categories under -17 vs. under-11 (mean: 10.20; IC95%: 7.16-13.25; p<0.001), followed by categories under -17 vs. under -13 (mean: 8.69; IC95%: 6.20-11.18; p<0.001), under -15 vs. under -11 (mean: 7.36; IC95%: 4.53-10.19; p<0.001), under -15 vs. under -13 (mean: 5.85; IC95%: 3.62-8.07; p<0.001), and under -17 vs. under -15 (mean: 2.84; IC95%: 0.54-5.14; p=0.007). Just the comparison between the under -13 vs. under -11 categories did not show any significant difference.
DISCUSSION
In order to identify the associations between relative age and physical fitness variables with the selection of young soccer players, the present study found RAE in younger players, specifically in the under-11 and under-13 categories. Among the older players, the selected individuals were faster in sprint performance; and in the under-13 and under-17 categories, they had higher jump performance. According to the literature, understanding the extent of RAE and the magnitude of age-related biases in these assessments is particularly important to support a more efficient and fair athlete selection strategy (Leyhr et al., 2021).
Approximately 80% of the selected players in the under-11 and under-13 categories were born in the first half of the year, demonstrating a significant RAE for this age group. A similar study conducted in 2016 also found RAE in the under-13 category, but in a different manner than what was found in this study: also found this effect in older players in the under-17 category (Marques et al., 2019). Previous studies report that the extent of RAE decreases with increasing age, especially after puberty (Sierra-Díaz et al., 2017; Doncaster et al., 2020). This overrepresentation of older athletes remains high from early to mid-adolescence and decreases but may still be present in older age groups and even adulthood (Doyle and Bottomley, 2018).
Among the older players (under-15 and under-17), RAE was not observed. However, in these categories, the sprint performance was superior among the selected players. In this regard, a study observed that athletes selected to continue playing for a Spanish soccer academy during the next age category performed better in the agility test when compared to non-selected players (Augste and Lames, 2011). The study by Castillo et al. (2019) also found better performance in the 10m and 30m sprint test in under-16 players selected for a Spanish elite soccer academy when compared to non-selected players, while Bidaurrazaga-Letona et al. (2019) found no differences in the physical fitness test values. However, selection criteria may vary according to age category, which may explain why some studies find an association and others do not (Bidaurrazaga-Letona et al., 2019). Even so, sprint speed is an essential component of physical fitness for playing soccer (Faude et al., 2012) and has been shown as one of the most discriminating variables for predicting which players soccer clubs will select for their teams (Fortin-Guichard et al., 2022).
Regarding jump performance, the participants in the under-13 and under-17 categories who were selected had better performance compared to those who were not selected. Additionally, the interaction effect between selection status and category was significant for jump height. This finding suggests that the influence of lower-limb power on selection may vary depending on the athlete’s age group. While selected players in the under-13 and under-17 groups showed superior jumping performance, this was not evident in the younger or intermediate categories, which may reflect age-specific priorities or developmental stages considered in talent selection. Consistent with our findings, Deprez et al. (2015) showed that players aged eight to 18 who signed a professional contract had higher jumping performance than players who did not achieve professional status. Associated with this, Gonaus and Muller (2012) also reported better jumping performance in those players aged 14 to 17 who were subsequently called up to a national youth team. In contrast, some research has shown that sprint and jump performance does not determine the professional career of young soccer players (Castillo et al., 2018; Martinez-Santos et al., 2016).
We did not identify height as a variable associated with soccer player selection. Other authors also did not identify an association between selected and unselected players (Bidaurrazaga-Letona et al., 2019; Castillo et al., 2019). Furthermore, for the under-13 and under-17 categories, we found a different pattern than the initial hypothesis, i.e., we would expect taller players to be selected for the team. The literature is still unclear about anthropometry variables: while Mala et al. (2020) suggest that anthropometric and body composition indicators are important factors affecting specific attributes of soccer players, and report that, generally, taller, more muscular and with less body fat soccer players have more advantages, especially during growth and maturation, Deprez et al. (2015) highlight that anthropometry values (such as height) may not be useful for discriminating between players who have achieved a professional contract and those who have not. Although height significantly differed between age categories, it did not discriminate between selected and non-selected players in any specific category, suggesting that coaches may prioritize other physical or technical attributes over anthropometry during selection.
Thus, determining the main characteristics that may influence the specific competence of soccer players is a complex process (Reilly et al., 2000), mainly because soccer is a multifactorial sport in which success is conditioned by the interaction of multiple characteristics, including anthropometry, body composition, somatotype, physical and physiological factors, as well as soccer-specific skills (Castillo et al., 2018). Therefore, more information is needed to improve the process of identifying athletes and to establish specific characteristics of talented players who progress in the sport in order to optimize talent development programs. These findings reinforce the complexity of player selection, highlighting that not only the individual variables but also their interaction with age category may be relevant to understanding which players are more likely to be selected.
Despite contributing to a better understanding of the selection of young soccer players and its practical implications, the present study has some limitations that need to be discussed. Due to the sample size, the categories had to be grouped, and it was not possible to assess the effect of each category individually. We also did not measure biological maturation, as it is considered to exist and operate independently of relative age.
The RAE played an important role in defining selection procedures in youth soccer, where early-born players at the under-11 and under-13 levels had an increased likelihood of being selected, thus highlighting the presence of inequalities in opportunities to develop. Then, contrarily to expectations (i.e., RAE long-term developmental effects), when players grow up (under-15 and under-17 level), the influence of RAE on the selection procedure decreased. Moreover, our study revealed that players' linear speed (under-15 and under-17 level) and lower limb muscle power (under-13 and under-17 level) are variables that differentiate selected and non-selected players.
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FUNDING
None.
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DATA AVAILABILITY
Not applicable.
REFERENCES
-
Amatori S, Pintus A, Corsi L, Bensi R, Zanini L, Rocco V, et al. Chronological age, relative age, pubertal development, and their impact on countermovement jump performance in adolescent football players: an integrative analysis. Heliyon. 2024;10(17):e36879. http://doi.org/10.1016/j.heliyon.2024.e36879 PMid:39281445.
» http://doi.org/10.1016/j.heliyon.2024.e36879 -
Augste C, Lames M. The relative age effect and success in German elite U-17 soccer teams. J Sports Sci. 2011;29(9):983-7. http://doi.org/10.1080/02640414.2011.574719 PMid:21604225.
» http://doi.org/10.1080/02640414.2011.574719 - Barnsley RH, Thompson AH, Barnsley PE. Hockey success and birthdate: the relative age effect. Phys Educ Recreat J. 1985;51:23-8.
- Bidaurrazaga-Letona I, Lekue JA, Amado M, Gil SM. Progression in youth soccer: selection and identification in youth soccer players aged 13-15 years. J Strength Cond Res. 2019;33(9):2548-58. PMid:28394831.
-
Brustio PR, Lupo C, Ungureanu AN, Frati R, Rainoldi A, Boccia G. The relative age effect is larger in Italian soccer top-level youth categories and smaller in Serie A. PLoS One. 2018;13(4):e0196253. http://doi.org/10.1371/journal.pone.0196253 PMid:29672644.
» http://doi.org/10.1371/journal.pone.0196253 -
Castillo D, Los Arcos A, Martinez-Santos R. Aerobic endurance performance does not determine the professional career of elite youth soccer players. J Sports Med Phys Fitness. 2018;58(4):392-8. http://doi.org/10.23736/S0022-4707.16.06436-7 PMid:27441912.
» http://doi.org/10.23736/S0022-4707.16.06436-7 -
Castillo D, Pérez-González B, Raya-González J, Fernández-Luna A, Burillo P, Lago-Rodríguez Á. Selection and promotion processes are not associated by the relative age effect in an elite Spanish soccer academy. PLoS One. 2019;14(7):e0219945. http://doi.org/10.1371/journal.pone.0219945 PMid:31339926.
» http://doi.org/10.1371/journal.pone.0219945 -
Costa JC, Borges PH, Ramos-Silva LF, Weber VMR, Moreira A, Ronque ERV. Body size, maturation and motor performance in young soccer players: relationship of technical actions in small-sided games. Biol Sport. 2023;40(1):51-61. http://doi.org/10.5114/biolsport.2023.110749 PMid:36636197.
» http://doi.org/10.5114/biolsport.2023.110749 -
Delorme N, Boiche J, Raspaud M. Relative age and dropout in French male soccer. J Sports Sci. 2010;28(7):717-22. http://doi.org/10.1080/02640411003663276 PMid:20480428.
» http://doi.org/10.1080/02640411003663276 -
Deprez DN, Fransen J, Lenoir M, Philippaerts RM, Vaeyens R. A retrospective study on anthropometrical, physical fitness, and motor coordination characteristics that influence dropout, contract status, and first-team playing time in high-level soccer players aged eight to eighteen years. J Strength Cond Res. 2015;29(6):1692-704. http://doi.org/10.1519/JSC.0000000000000806 PMid:26010800.
» http://doi.org/10.1519/JSC.0000000000000806 -
Doncaster G, Medina D, Drobnic F, Gomez-Diaz AJ, Unnithan V. Appreciating factors beyond the physical in talent identification and development: insights from the FC Barcelona sporting model. Front Sports Act Living. 2020;2:91. http://doi.org/10.3389/fspor.2020.00091 PMid:33345082.
» http://doi.org/10.3389/fspor.2020.00091 -
Doyle J, Bottomley P. Relative age effect in elite soccer: more early-born players, but no better valued, and no paragon clubs or countries. PLoS One. 2018;13(2):e0192209. http://doi.org/10.1371/journal.pone.0192209 PMid:29420576.
» http://doi.org/10.1371/journal.pone.0192209 -
Dugdale JH, Sanders D, Myers T, Williams AM, Hunter AM. Progression from youth to professional soccer: A longitudinal study of successful and unsuccessful academy graduates. Scand J Med Sci Sports. 2021;31(Suppl 1):73-84. http://doi.org/10.1111/sms.13701 PMid:33871087.
» http://doi.org/10.1111/sms.13701 -
Durandt J, Parker Z, Masimla H, Mike Lambert M. Rugby-playing history at the national U13 level and subsequent participation at the national U16 and U18 rugby tournaments. S Afr J Sports Med. 2011;23(4):103-5. http://doi.org/10.17159/2078-516X/2011/v23i4a321
» http://doi.org/10.17159/2078-516X/2011/v23i4a321 -
Faude O, Koch T, Meyer T. Straight sprinting is the most frequent action in goal situations in professional football. J Sports Sci. 2012;30(7):625-31. http://doi.org/10.1080/02640414.2012.665940 PMid:22394328.
» http://doi.org/10.1080/02640414.2012.665940 -
Fortin-Guichard D, Huberts I, Sanders J, van Elk R, Mann DL, Savelsbergh GJP. Predictors of selection into an elite level youth football academy: a longitudinal study. J Sports Sci. 2022;40(9):984-99. http://doi.org/10.1080/02640414.2022.2044128 PMid:35212615.
» http://doi.org/10.1080/02640414.2022.2044128 -
Gonaus C, Muller E. Using physiological data to predict future career progression in 14- to 17-year-old Austrian soccer academy players. J Sports Sci. 2012;30(15):1673-82. http://doi.org/10.1080/02640414.2012.713980 PMid:22917159.
» http://doi.org/10.1080/02640414.2012.713980 -
Grossmann B, Lames M. From talent to professional football: youthism in German football. Int J Sports Sci Coaching. 2015;10(6):1103-14. http://doi.org/10.1260/1747-9541.10.6.1103
» http://doi.org/10.1260/1747-9541.10.6.1103 -
Johnston K, Baker J. Waste reduction strategies: factors affecting talent wastage and the efficacy of talent selection in sport. Front Psychol. 2020;10:2925. http://doi.org/10.3389/fpsyg.2019.02925 PMid:31998188.
» http://doi.org/10.3389/fpsyg.2019.02925 -
Leyhr D, Bergmann F, Schreiner R, Mann D, Dugandzic D, Höner O. Relative age-related biases in objective and subjective assessments of performance in talented youth soccer players. Front Sports Act Living. 2021;3:664231. http://doi.org/10.3389/fspor.2021.664231
» http://doi.org/10.3389/fspor.2021.664231 -
Lupo C, Boccia G, Ungureanu AN, Frati R, Marocco R, Brustio PR. The beginning of senior career in team sport is affected by relative age effect. Front Psychol. 2019;10:1465. http://doi.org/10.3389/fpsyg.2019.01465 PMid:31293489.
» http://doi.org/10.3389/fpsyg.2019.01465 -
Mala L, Maly T, Cabell L, Hank M, Bujnovsky D, Zahalka F. Anthropometric, body composition, and morphological lower limb asymmetries in elite soccer players: a prospective cohort study. Int J Environ Res Public Health. 2020;17(4):1140. http://doi.org/10.3390/ijerph17041140 PMid:32053926.
» http://doi.org/10.3390/ijerph17041140 -
Marques PRR, Pinheiro ES, Coswig VS. Efeito da idade relativa sobre a seleção de atletas para as categorias de base de um clube de futebol. Rev Bras Ciênc Esporte. 2019;41(2):157-62. http://doi.org/10.1016/j.rbce.2018.03.034
» http://doi.org/10.1016/j.rbce.2018.03.034 -
Martinez-Santos R, Castillo D, Los Arcos A. Sprint and jump performances do not determine the promotion to professional elite soccer in Spain, 1994–2012. J Sports Sci. 2016;34(24):2279-85. http://doi.org/10.1080/02640414.2016.1190460 PMid:27238422.
» http://doi.org/10.1080/02640414.2016.1190460 -
Massa M, Moreira A, Costa RA, Lima MR, Thiengo CR, Marquez WQ, et al. Biological maturation influences selection process in youth elite soccer players. Biol Sport. 2022;39(2):435-41. http://doi.org/10.5114/biolsport.2022.106152 PMid:35309527.
» http://doi.org/10.5114/biolsport.2022.106152 -
Morganti G, Kelly AL, Apollaro G, Pantanella L, Esposito M, Grossi A, et al. Relative age effects and the youth-to-senior transition in Italian soccer: the underdog hypothesis versus knock-on effects of relative age. Sci Med Footb. 2023;7(4):406-12. http://doi.org/10.1080/24733938.2022.2125170 PMid:36103671.
» http://doi.org/10.1080/24733938.2022.2125170 -
Mostaert M, Vansteenkiste P, Pion J, Deconinck FJA, Lenoir M. The importance of performance in youth competitions as an indicator of future success in cycling. Eur J Sport Sci. 2022;22(4):481-90. http://doi.org/10.1080/17461391.2021.1877359 PMid:33446072.
» http://doi.org/10.1080/17461391.2021.1877359 -
Parr J, Winwood K, Hodson-Tole E, Deconinck FJA, Hill JP, Teunissen JW, et al. The main and interactive effects of biological maturity and relative age on physical performance in elite youth soccer players. J Sports Med. 2020;2020:1-11. http://doi.org/10.1155/2020/1957636
» http://doi.org/10.1155/2020/1957636 -
Pérez-González B, León-Quismondo J, Bonal J, Burillo P, Fernández-Luna A. The new generation of professional soccer talent is born under the bias of the RAE: relative age effect in international male youth soccer championships. Children. 2021;8(12):1117. http://doi.org/10.3390/children8121117 PMid:34943315.
» http://doi.org/10.3390/children8121117 -
Reilly T, Williams AM, Nevill A, Franks A. A multidisciplinary approach to talent identification in soccer. J Sports Sci. 2000;18(9):695-702. http://doi.org/10.1080/02640410050120078 PMid:11043895.
» http://doi.org/10.1080/02640410050120078 -
Rothwell M, Stone J, Davids K. Investigating the athlete-environment relationship in a form of life: an ethnographic study. Sport Educ Soc. 2022;27(1):113-28. http://doi.org/10.1080/13573322.2020.1815690
» http://doi.org/10.1080/13573322.2020.1815690 -
Sierra-Díaz MJ, González-Víllora S, Pastor-Vicedo JC, Serra-Olivares J. Soccer and relative age effect: a walk among elite players and young players. Sports. 2017;5(1):5. http://doi.org/10.3390/sports5010005 PMid:29910365.
» http://doi.org/10.3390/sports5010005
Edited by
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Editors:
Leonardo Alexandre Peyré Tartaruga, André Ivaniski Mello, Jhennifer Luiza Machado Pimenta.
Data availability
Not applicable.
Publication Dates
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Publication in this collection
10 Nov 2025 -
Date of issue
2025
History
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Received
12 Apr 2024 -
Accepted
19 Aug 2025
