Ronailde Braga Guerra*

ronailde.braga@usp.br

Jaqueline Freitas de Oliveira Neiva**

jaquelineneiva@usp.br

Marcelo Massa***

mmassa@usp.br

Paulo Henrique de Araújo Guerra+

paulo.guerra@usp.br

Rogério Honda++

rog_honda@hotmail.com

*Bacharela em Ciências da Atividade Física

pela Escola de Artes, Ciências e Humanidades

da Universidade de São Paulo (EACH-USP).

Licenciada em Educação Física

pela Universidade Cruzeiro do Sul.

Especialista em laboratório no Centro de Estudos

e Práticas de Atividades Físicas da EACH - USP

**Doutora e Mestre em Ciências

pela Escola de Educação Física e Esporte

da Universidade de São Paulo (EEFE-USP)

Educadora na Escola de Artes, Ciências e Humanidades

da Universidade de São Paulo (EACH-USP)

Membro do Grupo de Estudos e Pesquisas

em Capacidades e Habilidades Motoras (GEPCHAM- EACH -USP)

Membro do Laboratório de Comportamento Motor (LACOM - EEFE-USP)

***Doutor e Mestre em Educação Física

pela Escola de Educação Física e Esporte

da Universidade de São Paulo (EEFE-USP)

Professor Associado da Universidade de São Paulo (USP)

na Escola de Artes, Ciências e Humanidades (EACH-USP)

Curso de Educação Física e Saúde (EFS-USP)

Membro do Grupo de Pesquisa em Adaptações Biológicas

ao Exercício Físico - GABEF/USP.

Licenciado em Educação Física
Doutor em Ciências pela USP

+Docente Adjunto do curso de Medicina

da Universidade Federal da Fronteira Sul, câmpus Chapecó (SC)

++Graduado e Educação Física

Mestre em Ciências da Atividade Física

pela Escola de Artes, Ciências e Humanidades

da Universidade de São Paulo (EACH-USP)

Docente na Universidade Paulista

(Brasil)

Reception: 08/22/2022 - Acceptance: 09/04/2023

1st Review: 03/27/2023 - 2nd Review: 07/07/2023

Accessible document. Law N° 26.653. WCAG 2.0

Suggested reference: Guerra, R.B., Neiva, J.F. de O., Massa, M., Guerra, P.H. de A., & Honda, R. (2024). Relative Age Effect in Individual Sports. Systematic Review. Lecturas: Educación Física y Deportes, 28(308), 186-205. https://doi.org/10.46642/efd.v28i308.1529

 

Abstract

    Relative Age Effect (RAE) refers to the influence that month birth could have over the performance of people born in the same year. Most RAE studies indicate that individuals born in the first quartiles of a given year may present biological, physical, cognitive, psychological advantages over those who were born in the last months of the same year. Such variations could affect performance, leading to overestimation of observed results at the evaluation time. Although RAE had become a well-studied phenomenon, few is known about the prevailing studies methodological characteristics, as well as the breakthroughs over the theme, particularly, in individual sports. Thus, this systematic review investigated the state of art of RAE in individual sports. Results reveal RAE was found among athletes of individual sports; most studies described RAE in individual sports, nevertheless, few established relations between RAE and other variables (i.e. anthropometry, technical performance.) besides the quarter of birth. Findings indicate most RAE studies in individual sports focus their methodologies and results on describing athletes’ percentage born in each quartile of the year. Therefore, the theme requires a new approach, focused on the relation of RAE with sports talent identification and athlete development processes in individual sports.

    Keywords: Relative age effect. Individual sports. Talent identification. Athlete development.

 

Resumo

    Efeito da Idade Relativa (EIR) refere-se à influência que o mês de nascimento teria na performance de pessoas nascidas no mesmo ano. A maioria dos estudos sobre EIR indicam que indivíduos nascidos no primeiro quartil de um dado ano podem apresentar vantagens biológicas, físicas, cognitivas e psicológicas sobre nascidos nos últimos meses do mesmo ano. Tais variações afetariam a performance, levando à superestimação dos resultados observáveis no período de avaliação. Embora o EIR tornado um fenômeno bem estudado, pouco se sabe sobre as características metodológicas dos estudos prevalentes, bem como sobre os avanços a respeito do tema, especialmente em esporte individuais. Assim, esta revisão sistemática investigou o estado da arte do EIR nos esporte individuais. Os resultados revelaram que o EIR foi encontrado entre atletas de esportes individuais; a maioria dos estudos descreveu o EIR nos esportes individuais, contudo, poucos estabeleceram correlações entre o EIR e outras variáveis (como antropometria, performance técnica) além do trimestre de nascimento. Os achados indicam que metodologias e resultados da maioria dos estudos focam em descrever o percentual de atletas nascidos em cada trimestre do ano. Portanto, o estudo do tema requer uma abordagem voltada à relação do EIR com a identificação de talentos esportivos e com o processo de desenvolvimento dos atletas em esportes individuais.

    Unitermos: Efeito da idade relativa. Esportes individuais. Identificação de talentos. Desenvolvimento de atletas.

 

Resumen

    El efecto de la edad relativa (EER) se refiere a la influencia que podría tener el mes de nacimiento sobre el rendimiento de las personas nacidas en el mismo año. La mayoría de los estudios de la EER indican que los individuos nacidos en los primeros cuartiles de un año determinado pueden presentar ventajas biológicas, físicas, cognitivas y psicológicas sobre aquellos que nacieron en los últimos meses del mismo año. Tales variaciones podrían afectar el desempeño, llevando a una sobreestimación de los resultados observados en el momento de la evaluación. Aunque la EER se ha convertido en un fenómeno bien estudiado, poco se sabe sobre las características metodológicas predominantes de los estudios, así como sobre los avances sobre el tema, particularmente, en los deportes individuales. Así, esta revisión sistemática investigó el estado del arte de la EER en deportes individuales. Los resultados revelan que se encontró EER entre atletas de deportes individuales; la mayoría de los estudios describieron la EER en deportes individuales, sin embargo, pocos establecieron relaciones entre la EER y otras variables (ej. antropometría, rendimiento técnico...) además del trimestre de nacimiento. Los hallazgos indican que la mayoría de los estudios EER en deportes individuales centran sus metodologías y resultados en describir el porcentaje de atletas nacidos en cada cuartil del año. Por lo tanto, el tema requiere un nuevo enfoque, centrado en la relación de la EER con los procesos de identificación de talento deportivo y desarrollo de atletas en deportes individuales.

    Palabras clave: Efecto de la edad relativa. Deportes individuales. Identificación de talento. Desarrollo del deportista.

 

Lecturas: Educación Física y Deportes, Vol. 28, Núm. 308, Ene. (2024)

---

 

Introduction 

 

    Individuals grouping by age range usually occur in order to ensure equality of opportunities, similar development, and fair competition between children and teenagers (Barnsley, Thompson, & Legault, 1992; Carli, Luguetti, & Ré, 2009; Massa et al., 2014; Mujika et al., 2009; Pacharoni, Aoki, Costa, Moreira, & Massa, 2014; Vaeyens, Philippaerts, & Malina, 2005). Hence, birth date is used throughout the main stages of human development and growth process, subdividing children and teenagers by age groups, taking as reference chronological age and a limit date - usually the birth year.

 

    Since 1980 in the sports environment several studies investigated if birth month could mean an advantage for children and teenagers born in the same year but in different quartiles. (Barnsley, Thompson, & Barnsley, 1985; Barnsley et al., 1992; Cobley, Schorer, & Baker, 2008; Costa et al., 2012; Edgar, & O’Donoghue, 2005; Mujika et al., 2009; Schorer, Tirp, Steingröver, & Baker, 2016)

 

    In this sense, most studies seem to indicate young people born in the first months of the year, when compared to same-age athletes’ but born in the last months, could have their performance positively favored by higher levels of growth and biological maturation, higher stages of cognitive development, larger experience repertoire due to longer lifetime and greater acquired competence. Such phenomenon is described as Relative Age Effect (RAE). (Delorme, Boiché, & Raspaud, 2010; Helsen, Starkes, & Winckel, 2000; Helsen, Winckel, & Williams, 2005; Hirose, 2009; Mujika et al., 2009; Pacharoni et al., 2014; Schorer, Baker, Büsch, Wilhelm, & Pabst, 2009)

 

    The remarkable presence of RAE is found in studies in soccer. In Hirose’s study (2009), 58.8% of Japanese soccer players were born in the first quartile of the year while only 24% of the Tokyo population was born in such period. A recent study with 341 youth soccer players (under 10-20 years) of a top-level Brazilian soccer club, found that 47.5% of athletes were born in the first quartile of the year, 25.5% in the second, 18.2% in the third and only 8.8% were born in the last quartile of the year. (Massa et al., 2014)

 

    Although historically RAE studies in soccer are predominant, studies with individual sports such as tennis (Pacharoni et al., 2014), triathlon (Werneck, Lima, Coelho, Matta, & Figueiredo, 2014), taekwondo (Albuquerque et al., 2012) and others have presented and highlighted the RAE investigation relevance to sports development. However, regarding the scope and characteristics of RAE studies in individual sports, no systematic review was found.

 

    Thus, and considering the implications of RAE over athletes’ formation programs and talent development, this study aimed to present the state of the art of RAE in individual sports by means of a systematic review.

 

Methods 

 

    This systematic review was conducted in accordance with Preferred Reporting Items for Systematic Reviews and Meta-analysis Statement - PRISMA. (Moher, Liberati, Tetzlaff, Altman, & The PRISMA Group, 2009)

 

Eligibility criteria 

 

    Cross-sectional and longitudinal studies over RAE in athletes of individual sports - regardless of their modality, age range, and/or competition level - were included. Open-access articles in English, Portuguese, or Spanish with no restriction in regard to publication period were assessed. Thereby, studies reporting only team sports, non-athlete participants, not RAE-related, non-research papers (such as editorial letters, expanded abstracts and etc.), or in a language different from those aforementioned were excluded.

 

Searches for potential studies and selection process 

 

    In February 2018, searches for potential studies were carried out in five electronic databases (Web of Science, PubMed, Scielo, PsycINFO, and SPORTDiscus). Previous identification of terms/descriptors in all databases was performed. The resulting electronic search strategy applied in all databases search fields except PubMed is as follows: (((((("relative age effect" OR "effect of relative age")) AND (("Athletics" OR "Archery" OR "Badminton" OR "Boxing" OR "Canoe Slalom Kayak" OR "Canoe Sprint Kayak" OR "Canoe Sprint" OR "Cycling BMX" OR "Cycling Mountain Bike" OR "Cycling Road" OR "Cycling Track" OR "Diving" OR "Equestrian Dressage" OR "Equestrian Eventing" OR "Equestrian Jumping" OR "Fencing" OR "Golf" OR "Gymnastics Artistic" OR "Judo" OR "Modern Pentathlon" OR "Rowing" OR "Sailing" OR "Shooting" OR "Swimming" OR "Table Tennis" OR "Taekwondo" OR "Tennis" OR "Trampoline" OR "Triathlon" "Weightlifting" OR "Wrestling Freestyle" OR " Wrestling Greco-Romano" OR "Rowing")))))). To avoid potential losses, manual searches also were performed in reference lists.

 

    Processes of identification and removal of inter-databases duplicates, title and abstracts screening of original studies were performed by two independent researchers. Abstracts of all selected titles including discordant cases were examined. If doubt remained, the article was read in its entirety to determine whether it should be or not included. Agreement between researchers’ selection was measured by the Kappa index (0.897; p<0.001).

 

Data extraction and assessment 

 

    The following data were extracted from the included studies: sport modality, sample’s location, size, age, and sex, study procedures, variables analyzed, and RAE’s findings. A researcher extracted the data and summarized them into an electronic spreadsheet. Based on the eligibility criteria, a second researcher evaluated the data extraction spreadsheet. Once this is a descriptive review, it was decided not to make methodological/risk of bias assessments of studies.

 

Results 

 

    Initial search retrieved 243 titles from which 27 studies were selected. Twelve titles from references lists were added, totaling 39 studies. After a full assessment, four studies were excluded for not meeting the eligibility criteria (Figure 1). The main data from the 35 selected studies are summarized in Table 1.

 

Study/Year	Sport	Country	Sample size	Sex	Age	Variables analyzed	RAE* (detected)
Giacomini (1999)	Tennis	United States	600	F / M	< 14 to < = 18	Birthdate / Sex / Performance (ranking)	Among males in younger divisions
Edgar & O’Donoghue (2005)	Tennis	Various	448 senior / 476 junior	F / M	Junior: 13 to 17/senior: not informed	Birthdate / Sex / Age (Senior-Junior) /Birth place (country) / Performance (winners)	Among both genders and competition levels
Abel & Kruger (2007)	Nascar	United States	1,054	not informed	not informed	Birthdate / Performance (winners)	Yes
Medic et al. (2007)	Masters sports	United States	1,160 / 24,831 (2 studies)	not informed	35 to 96	Birthdate / Performance (record setting and participation rate)	Among the firsts years of 5-year category for athlete's performance and participation
O’Donoghue (2009)	Tennis	Various	Variable (5th out of 6 studies)	F / M	born after 1984	Birthdate / Sex / Performance (ranking / competition level/ Grand slam conquered)	Evidence for inverse RAE (6 years of a 25-years cohort study)
Medic et al. (2009)	Masters swimming / track and field	United States	35,814 / 1,509 (2 studies)	F / M	35 to 101	Birthdate / Sex / Performance (participation rate/record setting) / Sport	Across gender, from 4th life decade and in track and field and swimming
Delorme & Raspaud (2009)	Shooting sports	France	132,538	F / M	> 11 to > 20	Birthdate/Sex /Performance(ranking) /Age category /Membership discontinuance	Among males / inverse  RAE in 15-17y category
Medic et al. (2009)	Master sports	Various	4,820	not informed	35 to 96	Age / Year category (5 years range) / Sport / Performance (participation rate)	Among track and field, and swimming athletes / not for weightlifting and rowing
Loffing et al. (2010)	Tennis	Various	1,027	M	not informed	Birthdate / Handedness / Performance (ranking)	Not among left-handed
Medic et al. (2011)	Masters swimming	United States	2,596	F / M	25 to 77	Birthdate / Performance (participation rate)	Yes
Albuquerque et al. (2012)	Taekwondo	Various	291	F / M	not informed	Birthdate / Sex	No
Costa et al. (2013)	Swimming	Portugal	7,813	F / M	12 to 18	Birthdate /Sex / Age category /Performance (ranking)	Among males
Albuquerque et al. (2013)	Judo	Various	1,738	not informed	not informed	Birthdate / Weight category	Among Heavy Weight / Half-Heavy: over-representation in third quarter
Ribeiro et al. (2013)	Tennis	Various	924	F / M	13 to 26	Birthdate / Sex / Performance (category ranking)	Among 14 and 18 years categories
Agricola et al. (2013)	Tennis	Various	239	M	13-14	Birthdate / Sex / Performance (ranking)	Among males
Werneck et al. (2014)	Triathlon	Various	111	F / M	Average age 28	Birthdate / Sex / Anthropometry / Performance (Olympic medals)	Among males /Relates to winning medal
Delorme (2014)	Boxing	France	6,167 amateur / 354 professional	F / M	12 to 18	Birthdate / Sex / Age category / Weight category	inverse RAE among 18-18+ male category
Pacharoni et al. (2014)	Tennis	Various	800	M	12 to 18	Birthdate / Age category / Performance (Top 100 / category)	Stronger among younger divisions
O’Donoghue (2014)	Tennis	Various	116	F / M	born before 1/1/85 or on or after this date	Birthdate / Sex / Player style (net points) Period / Generation (due to court changes)	May affect male players style
Albuquerque et al. (2014)	Wrestling	Various	3,938	F / M	not informed	Birthdate / Sex / Fighting style (Freestyle / Greco-roman) / Performance (medals)	Among males / in all styles / among freestyle medalists
Edginton et al. (2014)	Boxing	Various	388	M	17 to 35 / Average 24 (SD 3.3)	Birthdate / Weight category / Birthplace (country) / Performance (medals)	Among medal-winning men’s amateur boxing
Baker et al. (2014)	Skiing, figure skating and gymnastics.	Various / Canada	29,983 / 1,114 (2 studies)	F / M	born in 1970 or later	Birthdate/Sex/Performance (intern. compet.)/Sport/Category (Junior-Senior)	Among most ski sports across sexes / atypical RAE for female gymnastics
Hollings, et al. (2014)	Track and field	Various	2,924	F / M	16 to 19	Birthdate / Sex / Sport /Performance (ranking) / Category (Junior-Juvenile)	Stronger among younger division and males
Albuquerque et al. (2015)	Judo	Various	2,427	F / M	not informed	Birthdate / Sex / Weight category	Among male heavyweight athletes and medalists
Hancock et al. (2015)	Female gymnastics	Canada	921	F	under-15 / over-15	Birthdate / Performance (competition level)	Among under-15 / inverse RAE among over-15
Romann & Cobley (2015)	Athletic sprinting	Swiss	7,761	M	aged 8-15	Age / Exact decimal age / Birthdates / Performance (sprint times across 8 to 15 y)	Across childhood to youth (small to large) / could be removed by adjustments
Müller et al. (2015)	Alpine Ski Racing.	Austria	2,878	F / M	7 to 11 and 12 to 15	Birthdate / Sex / Age category (Kids- Teenager Cups) / Performance (ranking)	Among youngest division
Ulbricht et al. (2015)	Tennis	Germany	120,851	M	11 to 17	Birthdate / Age category / Performance (ranking) / Physical fitness / Motor skills	Among higher competitive levels ( no difference in physical characteristics)
Mueller et al. (2016)	Various sports	Various	899	F / M	17.1 years (SD 0.77, range 14.9-18.3).	Birthdate / Sex / Performance (medals) / Sport capacities required / Anthropometry	Among male athletes in strength and endurance-related sports
Gorski et al. (2016)	Alpine Skiers	Swiss	2,469	F / M	11 to 19	Birthdate/Sex/Performance (high/low level)/Age categ./Phys. fitness/Motor skills	Influenced by performance level among female
Saavedra-García et al. (2016)	Athletics	Spain	3,313	F / M	16 to absolute category	Birthdate / Sex / Age category / Performance (ranking) / Sport	Among all athletes / less evident for females in age category analysis
Brazo-Sayavera et al. (2017)	Track and field	Spain	29,045	F / M	14 to 17	Birthdate / Sex / Performance (selected or not)	Stronger for males and younger (U15) / no evidence for older female (U17)
Moreira et al. (2017)	Tennis	Various	2,481	M	13 to 18	Birth month / Birth year / Performance (scores)	Among all players / Birth year contributed more to their scores
Ferreira et al. (2017)	Swimming	Various	978	F / M	Average 23.1 ± 3.9	Birthdate / Sex / Birthplace (continent)	Among female and Asian athletes
Cobley et al. (2018)	Swimming	Australia	6,014	F / M	12 to 18	Birthdate / Sex / Style	Among earlier age-groups / Apparent inverse RAE by 17-18 y

*RAE: Relative age effect. Source: Authors

 

Studies characteristics 

 

    Studies dates ranged from 1999 to 2018. Throughout this period, exponential growth in individual sports RAE studies’ is observed. Only one study before 2000 was retrieved (Giacomini, 1999). In the following decade (2000 to 2009) seven more were retrieved whereas 27 ones were retrieved from 2010 until February 2018.

 

    Studies sample size ranged from 111 to 132,538. Samples’ age ranged from 7 to 101 years. Nevertheless, seven studies (Abel, & Kruger, 2007; Albuquerque et al., 2012, 2013, 2014, 2015; Edgar, & O’Donoghue, 2005; Loffing, Schorer, & Cobley, 2010) not informed such data or informed them partially. Five other studies not informed participants’ age clearly, indicating their birth year cutoff point (Baker, Janning, Wong, Cobley, & Schorer, 2014; O’Donoghue, 2009, 2014) or not pointing out their limits’ ages.(Hancock, Starkes, & Ste-Marie, 2015; Saavedra-García, Gutiérrez-Aguilar, Sa-Marques, & Fernández-Romero, 2016) As well as age, the samples’ sex was not clearly informed in four studies.(Abel, & Kruger, 2007; Albuquerque et al., 2013; Medic, Starkes, & Young, 2007; Medic, Young, Starkes, Weir, & Grove, 2009) Most studies analyzed both sexes (n=23; 66%). Seven studies had male samples and one had female participants exclusively. (Hancock et al., 2015)

 

    Except for one (Albuquerque et al., 2012), all studies detected RAE, whether in the whole sample or only in part of it, depending on the variable analyzed. Some studies reported reverse or atypical RAE. (Cobley et al., 2018; Delorme, 2014; Delorme, & Raspaud, 2009; Hancock et al., 2015; O’Donoghue, 2009)

 

    Half of the studies (n=18; 51%) used data exclusively from world and/or international championships, such as the Olympic Games. Hence, most athletes’ nationality was not specified. All other studies but one in Australia (Cobley et al., 2018) took place in countries of North America and Europe.

 

    For most studies, online databases were the main source of athletes’ data such as age (age, birthdates, and birth month or birth year), performance indicators (federations’ ranking, medals and prizes conquest, participation rates, competition levels, and others.) and sex. If applicable, studies analyzed the weight and age categories of the sport separately (n=15; 43%). Six studies (17%) analyzed physical and motor data as anthropometry (Müller, Hildebrandt, Schnitzer, & Raschner, 2016; Werneck et al., 2014), physical fitness and motor skills (Gorski, Rosser, Hoppeler, & Vogt, 2016; Ulbricht, Fernandez-Fernandez, Mendez-Villanueva, & Ferrauti, 2015), players’ style (O’Donoghue, 2014), and handedness. (Loffing et al., 2010)

 

Discussion 

 

    Given this systematic review purpose, RAE’s presence in individual sports was found in 34 of the 35 studies analyzed. Results were statistically significant, whether fully or partially - meaning RAE was detected only in a given sample’s subgroup as early age group or in a certain category. Evidence for inverse RAE was also presented.

 

    Most studies verified RAE in individual sports by analyzing athletes’ birthdates distribution within year quartiles. This has been a traditional formula for RAE detection since the first studies (Dudink, 1994). Although some studies persisted in reproducing such formula, expansion, and diversity of variables analyzed are observed throughout the timeline, especially among those individual sports where RAE was most investigated across the time, such as tennis, whose ten retrieved studies ranged from 1999 to 2017 (Table 2). Supposedly, tennis researchers improved their study designs accordingly to RAE’s new findings and hypothesis in that sport.

 

Study	Age	Variables analyzed	RAE* (detected)
Tennis (N=10)
Ulbricht et al. (2015)	11 to 17	Birthdate / Age category / Performance (ranking) /Physical fitness / Motor skills	Among higher competitive levels                                                            (no difference in physical characteristics)
Pacharoni et al. (2014)	12 to 18	Birthdate / Age category / Performance (Top 100 / category)	Stronger among younger divisions
Agricola et al. (2013)	13-14	Birthdate / Sex / Performance (ranking)	Among males
Moreira et al. (2017)	13 to 18	Birth month / Birth year/ Performance (scores)	Among all players / Birth year contributed more to their scores.
Edgar, & O’Donoghue (2005)	Junior: 13 to 17/senior: not informed	Birthdate / Sex / Age (Senior-Junior) /                                                         Birthplace (country) / Performance (winners)	Among both genders and competition levels
Ribeiro et al. (2013)	13 to 26	Birthdate / Sex / Performance (category ranking)	Among 14 and 18 years categories
Giacomini (1999)	< 14 to £ 18	Birthdate / Sex / Performance (ranking)	Among males in younger divisions
O’Donoghue (2009)	born after 1984	Birthdate / Sex / Performance (ranking / competition level/ Grand slam conquered)	Evidence for "reverse RAE" (6 years of a 25-years cohort study)
O’Donoghue (2014)	born before 1/1/85 or on or after this date	Birthdate / Sex / Player style (net points) Period / Generation (due to court changes)	May affect male players style
Loffing et al. (2010)	not informed	Birthdate / Handedness / Performance (ranking)	Not among left-handed
Fighting sports (N=6)
Delorme (2014)	12 to 18	Birthdate / Sex / Age category / Weight category	reverse RAE among 18-18+ male category
Edginton et al. (2014)	17 to 35 / Average 24 (SD 3.3)	Birthdate / Weight category / Birthplace (country) / Performance (medals)	Among medal-winning men’s amateur boxing
Albuquerque et al. (2012)	not informed	Birthdate / Sex	No
Albuquerque et al. (2013)	not informed	Birthdate / Weight category	Among Heavy Weight /                                                                               Half-Heavy: over-representation in third quarter
Albuquerque (2014)	not informed	Birthdate / Sex / Fighting style (Freestyle / Greco-roman) / Performance (medals)	Among males / in all styles / among freestyle medalists
Albuquerque et al. (2015)	not informed	Birthdate / Sex / Weight category	Among male heavyweight athletes and medalists.
Athletic sports (N=5)
Romann, & Cobley (2015)	aged 8-15	Age / Exact decimal age / Birthdates / Performance (sprint times across 8 to 15y)	Across childhood to youth (small to large) /                                                 could be removed by adjustments
Brazo-Sayavera et al. (2017)	14 to 17	Birthdate / Sex / Performance (selected or not)	Stronger for males and younger (U15) /                                                    no evidence for older female (U17)
Hollings et al. (2014)	16 to 19	Birthdate / Sex / Sport /Performance (ranking) / Category (Junior-Juvenile)	Stronger among younger division and males
Saavedra-García et al. (2016)	16 to absolute category	Birthdate / Sex / Age category / Performance (ranking) / Sport	Among all athletes / less evident for females in age category analysis
Werneck et al. (2014)	Average age 28	Birthdate / Sex / Anthropometry / Performance (Olympic medals)	Among males /Relates to winning medal
Master sports (N=4)
Medic, Young,  & Medic (2011)	25 to 77	Birthdate / Performance (participation rate)	Yes
Medic et al. (2007)	35 to 96	Birthdate / Performance (record setting and participation rate)	Among the firsts years of 5-year category for athlete's performance and participation
Medic et al. (2009)	35 to 96	Age / Year category (5 years range) / Sport / Performance (participation rate)	Among track and field, and swimming athletes / not for weightlifting and rowing
Medic et al. (2009)	35 to 101	Birthdate / Sex / Performance (participation rate/record setting) / Sport	Among gender, from 4th life decade and in track and field and swimming
Swimming (N=3)
Costa et al. (2013)	12 to 18	Birthdate / Sex / Age category / Performance (ranking)	Among males
Cobley et al. (2018)	12 to 18	Birthdate / Sex / Style	Among earlier age-groups / Apparent reverse RAE by 17-18y
Ferreira et al. (2017)	Average 23.1 ± 3.9	Birthdate / Sex / Birthplace (continent)	Among female and Asian athletes
Alpine sports (N=2)
Müller et al. (2015)	7 to 11 and 12 to 15	Birthdate / Sex / Age category (Kids- Teenager Cups) / Performance (ranking)	Among youngest division
Gorski et al. (2016)	11 to 19	Birthdate/Sex/Performance (high/low level)/ Age categ./Phys. fitness/Motor skills	Influenced by performance level among female
Artistic sports (N=2)
Hancock et al. (2015)	under-15 / over-15	Birthdate / Performance (competition level)	Among under-15 / reverse RAE among over-15
Baker et al. (2014)	born in 1970 or later	Birthdate / Sex /Performance (intern. compet.) / Sport / Category (Junior-Senior)	Among most ski sports across sexes / atypical RAE for female gymnastics
Non-physical sports (N=2)
Delorme, & Raspaud (2009)	> 11 to > 20	Birthdate / Sex / Performance (ranking) / Age category / Membership discontinuance	Among males / "reverse RAE" in 15-17y category
Abel, & Kruger (2007)	not informed	Birthdate / Performance (winners)	Yes
Various sports (N=1)
Mueller et al. (2016)	17.1 years (SD 0.77, range 14.9-18.3).	Birthdate / Sex / Performance (medals) / Sport capacities required / Anthropometry	Among male athletes in strength and endurance-related sports

*RAE: Relative age effect. Source: Authors

 

    Dudink (1994) highlighted social and psychological factors as often ignored or underestimated in organized sports, where talent is considered predominantly in terms of physical skills. For this reason, it is interesting to note that in a chronological analysis, the third and the fourth retrieved studies investigated RAE in unlikely publics: NASCAR racers and Master athletes, respectively (Abel, & Kruger, 2007; Medic et al., 2007). Attempting to eliminate physical skills demands (NASCAR) and maturation advantages (Masters Sports) from the equation, both studies yet detected RAE.

 

    In Masters Sports, athletes are separated into 5-year age categories. Therefore, RAE was found comparing athletes in the first years of a 5-year age category with athletes in its last years. Aging process and lack of motivation in athletes in the last years’ category were pointed as factors that possibly influence RAE in Masters Sports. As for the NASCAR study, its results extended RAE for a sport that does not rely on superior strength or increased size (Abel, & Kruger, 2007), but brought no hypothesis for such a result.

 

    Aligned with the non-physical sports investigation, Delorme, & Raspaud (2009) detected RAE among young male athletes in shooting sports, pushing researchers to look over exogenous factors, such as parental authorization and sport migration driven by failure in other sports.

 

    The relation between RAE and physical variables such as athletes’ physical fitness, anthropometric and motor skills were verified by six studies (Gorski et al., 2016; Loffing et al., 2010; Müller et al., 2016; O’Donoghue, 2014; Ulbricht et al., 2015; Werneck et al., 2014). All of them were carried out in the last decade, indicating that researchers moved from the assumption of maturation process influence over RAE to stating its real correlation. Ulbricht et al. (2015) detected RAE among higher competitive level tennis players, but no differences in their physical characteristics. An approach to motor skills reveals RAE not influenced left-handed male tennis players (Loffing et al., 2010) but may affect tennis senior players’ style since play style is developed during junior years. (O’Donoghue, 2014)

 

    Despite that, most studies (n=29; 83%) mainly described the percentage of athletes born in each year quartile and its relation to athletes’ performance data, revealing the scarcity of studies that have advanced to an in-depth understanding of RAE in face of growth, development, maturation, performance and talent identification processes in individual sports.

 

    As aforementioned, social factors in organized sports are often ignored (Dudink, 1994). This can be verified by the low attention given to athletes’ birthplaces. Only three studies considered this item as an important variable to analyze (Edgar, & O’Donoghue, 2005; Edginton, Gibson, & Connelly, 2014; Ferreira et al., 2017). Although not exclusively related to individual sports, Côté et al. (2006) pointed out that contextual factors associated with birthplace contribute more influentially to the achievement of an elite level of sports performance than relative age. However, the author states that these factors are independent in their influences on expertise development. It is worth noting to remember that half of the studies (n=18; 51%) used data exclusively from world and/or international championships, generally analyzing athletes from worldwide as a homogenous population. Thus, future studies of RAE in individual sports should explore such variable.

 

    For female athletes, RAE in individual sports was less evident. Six studies detected RAE in their female sample, either exclusively or together with their male sample. Gorski et al. (2016) stated that the high popularity of a sport could increase competition between athletes at the very early stages of their careers, driving towards a boosted RAE. Stronger RAE for males is often attributed to the higher number of athletes competing, taking to higher pressure on selection processes (Müller, Hildebrandt, & Raschner, 2015). However, such statements are not enough to assume the absence of RAE in the female universe of individual sports, and hence ignore it. On the contrary, studying this scenario could bring other comprehensions of RAE impacts on individual sports, such as the one found by Hancock et al. (2015), where inverse RAE was present among over-15-year gymnastics.

 

    Evidence of inverse RAE was found in four more studies (Cobley et al., 2018; Delorme, 2014; Delorme, & Raspaud, 2009; O’Donoghue, 2009). Before proceeding, it is important to stress that inverse RAE means an over-representation of athletes born in the third or fourth quartile of the year, and an under-representation of those born in the first or second ones. A similar effect was labeled as ‘atypical’ by Baker et al. (2014) since the highest percentage of the female gymnastics athletes sample was born in the second quartile whilst RAE default is the highest percentage born in the first one.

 

    The analysis of the studies of RAE in individual sports allows stating that critical variables that could help explain RAE manifestation were not included in their designs. Studies considering relations between RAE and sexual maturation, hormonal index, stature's speed peak, bone maturation, creativity, decision-making, and other variables were not observed.

RAE descriptive studies suggesting young people born in the first months of the year have advantages throughout selection and promotion talent processes usually infer that their more advanced growth and biological maturation degree, higher cognitive development stage, larger experiences repertoire due to longer lifetime and higher acquired competence could boost their performance when compared to those born in last months of the same year. Since most studies of RAE in individual sports did not take into account such variables, their results are quite limited to background RAE understanding.

 

    Therefore, is fundamental that future research on RAE in individual sports cover a larger set of critical variables, which supports an in-depth and integrated explanation of RAE's phenomenon.

 

Conclusion 

 

    Through this systematic review, it was sought to comprehend and present the range of variables analyzed in RAE studies in order to establish if such variables, as well as study designs and their findings, are appropriate to be used as reliable scientific support by coaches and their peers.

 

    Furthermore, by spotlighting RAE complexity it was intended to help out prevent its occurrence, as an outcome of a better athletes' evaluation and follow-up throughout their career development. That stated, the review results lead to the following conclusions:

 

    RAE is present in individual sports, although not in the studies’ whole samples but mostly in its subgroups.

 

    Most studies investigated only the percentage distribution of athletes born in each quartile of the year, collecting their data - especially athletes’ birthdates - mainly from websites of sports committees, federations, or from sports teams/clubs files. Mostly, their findings confirm RAE presence in individual sports, however, bring no breakthroughs or help explain RAE relations with other variables which are part of athletes’ developing process context.

 

    Few studies investigated and tested which are the real relations between RAE and growth, development, maturation and performance variables. When designing this sort of study, researchers’ approach to sports facilities and training process on a long-term basis is fundamental, so they can interact with the data collection process. The lack of such approach explains the scarcity of studies with the design upper mentioned.

 

    These systematic review findings reveal the theme problematic and reinforce the importance of new studies aiming to verify the relation of RAE with sports talent identification and development processes in individual sports.

 

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Lecturas: Educación Física y Deportes, Vol. 28, Núm. 308, Ene. (2024)