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The relative age effect in the Gaelic Athletic Association (GAA): A mixed methods approach

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Background: Background: In the Gaelic Athletic Association (GAA), Talent Academies (TAs) and senior teams cater for high-performing players. However, only two previous studies have quantified the relative age effect (RAE; i.e., a selection bias favouring those born near the beginning of the cut-off date) in these cohorts. Additionally, no studies have explored stakeholder understanding of the RAE using qualitative methods. Aim: This study aimed to: (a) quantify the RAE in TAs and senior teams, and (b) investigate stakeholder perspectives of the talent development environment, providing practical insight into the RAE. Methods: A mixed methods sequential explanatory study design was employed. Phase one involved a retrospective analysis of longitudinal data for the frequency and distribution of births using TA (n = 12,445) and senior (n = 8,752) players. Phase two comprised two focus groups of key stakeholders [coaches (n = 4) and Talent Development Leaders (n = 4)] at TA and senior level. Results: Analysis revealed a significant difference between TA birth quarter (BQ) distributions compared with expected distributions (P < 0.001; BQ1 = 30.4% vs. BQ4 = 17.6%), whereas at senior level, there were no significant differences observed (χ2 (df = 3) = 3.812, P = 0.282). In phase two, inductive analysis revealed three higher-order themes: (a) understanding of the RAE, (b) selection criteria, and (c) player characteristics. Conclusion: The GAA are encouraged to reflect on the practice of chronological age band grouping, investigate possible solutions to limit the effects of the RAE, and offer support programmes to educate key stakeholders.
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Science and Medicine in Football
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The relative age effect in the Gaelic Athletic
Association (GAA): a mixed methods approach
Jamie R. Queeney, Adam L. Kelly, Padraig McGourty & Peter Horgan
To cite this article: Jamie R. Queeney, Adam L. Kelly, Padraig McGourty & Peter Horgan (2022):
The relative age effect in the Gaelic Athletic Association (GAA): a mixed methods approach,
Science and Medicine in Football, DOI: 10.1080/24733938.2022.2096918
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Published online: 10 Jul 2022.
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The relative age eect in the Gaelic Athletic Association (GAA): a mixed methods
Jamie R. Queeney
, Adam L. Kelly
, Padraig McGourty
and Peter Horgan
Gaelic Athletic Association, Meath GAA Centre of Excellence, Dublin 3, Ireland;
Centre for Life and Sport Sciences (Class), Faculty of Health,
Education and Life Sciences, Birmingham City University, Birmingham, West Midlands, UK;
Department of Health and Nutritional Sciences, Atlantic
Technological University, Sligo, Ireland
Background: Background: In the Gaelic Athletic Association (GAA), Talent Academies (TAs) and senior
teams cater for high-performing players. However, only two previous studies have quantied the relative
age eect (RAE; i.e., a selection bias favouring those born near the beginning of the cut-o date) in these
cohorts. Additionally, no studies have explored stakeholder understanding of the RAE using qualitative
Aim: This study aimed to: (a) quantify the RAE in TAs and senior teams, and (b) investigate stakeholder
perspectives of the talent development environment, providing practical insight into the RAE.
Methods: A mixed methods sequential explanatory study design was employed. Phase one involved
a retrospective analysis of longitudinal data for the frequency and distribution of births using TA
(n = 12,445) and senior (n = 8,752) players. Phase two comprised two focus groups of key stakeholders
[coaches (n = 4) and Talent Development Leaders (n = 4)] at TA and senior level.
Results: Analysis revealed a signicant dierence between TA birth quarter (BQ) distributions compared
with expected distributions (P < 0.001; BQ1 = 30.4% vs. BQ4 = 17.6%), whereas at senior level, there were
no signicant dierences observed (χ2 (df = 3) = 3.812, P = 0.282). In phase two, inductive analysis
revealed three higher-order themes: (a) understanding of the RAE, (b) selection criteria, and (c) player
Conclusion: The GAA are encouraged to reect on the practice of chronological age band grouping,
investigate possible solutions to limit the eects of the RAE, and oer support programmes to educate
key stakeholders.
Accepted 28 June 2022
Gaelic games; RAE; talent
identification; selection
criteria; player development;
coach decision making
The Gaelic Athletic Association (GAA) is the sporting orga-
nisation that governs Gaelic football and hurling, with
Gaelic football the most popular sport on the Island of
Ireland (Teneo Sport and Sponsorship Index 2020.). The
basic unit is the club, of which there are 2,066 aliated,
with 314,420 registered players (GAA 2022). At the repre-
sentative (Inter County) level, Talent Academies (TAs) and
senior teams provide over 12,000 high-performing players
with additional and enhanced player development pro-
grammes (GAA 2014).
In order to produce the next gen-
eration of senior players, key stakeholders (i.e., full-time
sta, coaches, and practitioners) look towards TAs to oer
developmental pathways for players to reach the highest
levels and prepare them for the demands of future com-
petitions (Mountjoy et al. 2008; Stambulova 2016).
Although TAs are a national programme, overseen by the
GAA, counties operate independently based on their own
unique philosophies and cultures, and while guidelines
require them to hold TAs from U14 to U17, some have
started the selection process at the U12/13 age groups in
recent years (Cuthbert 2018.).
In the GAA, competitions are organised across all age groups
using a xed cut-o date of January 1
, whereby players com-
pete within the annual age grade corresponding to their year of
birth. While this grouping strategy is common, the variation in
births within a given year, coupled with each player’s individual
stage of development, can lead to physical, psychological,
emotional and performance imbalances (Musch and Grondin
2001; de la Rubia et al. 2020), which may also be inuenced by
individual, task and environmental constraints (Wattie et al.
2015). These imbalances are often revealed as a selection bias
leading to a larger proportion of players who’s birth dates are
from the early months of the year being selected, and is widely
acknowledged as the Relative Age Eect (RAE) (Cobley et al.
2009). To quantify the extent of the RAE in sport, the observed
birth distributions are numerically categorised into birth quar-
ters (BQs) which correspond to the number of players born at
a particular time of the year (i.e., BQ1 = rst three months of the
selection year vs. BQ4 = last three months of the selection year).
CONTACT Jamie R. Queeney Gaelic Athletic Association, Meath GAA Centre of Excellence, Dunganny, Trim Co. Meath, C15
VWF4, Ireland
© 2022 Informa UK Limited, trading as Taylor & Francis Group
There are several hypothesised explanations for the manifesta-
tion of the RAE in sport. While it has been suggested that
growth and maturation is a contributing factor (Cobley et al.
2009), playing experience coupled with an athletes cognitive,
emotional, behavioural, motor, and social development are
more likely to be the underlying causes (Romann et al. 2020).
Additionally, the popularity of the sport, playing numbers, and
competition level are all thought to enhance the existence of
the RAE (Musch and Grondin 2001). Furthermore, it has been
suggested that key decision makers and social agents (i.e.,
Parents, coaches and athletes) inuence the selection imbal-
ances observed in team sports, which have been explained
through theoretical models such as Matthew, Pygmalion and
Galatea eects (Hancock et al. 2013).
The RAE was rst explored in a sporting context in a study of
adult Canadian ice hockey players (n = 715), where Barnsley
et al. (1985) discovered that 61.8% of players were born in the
rst six months of the year, with players being twice as likely to
be born in BQ1 compared to BQ4. Since then, numerous studies
have assessed the frequency and impact of the RAE in team
sports such as volleyball (Rubajczyk and Rokita 2020), basket-
ball (Gonçalves and Carvalho 2021), handball (Schorer et al.
2013), Australian rules football (Coutts et al. 2014; Tribolet
et al. 2019), rugby league (Till et al. 2010; Cobley et al. 2014),
rugby union (Kelly et al. 2021a), and soccer (Del Campo et al.
2010; Dugdale et al. 2021). While such studies highlight the
signicance of the RAE, it was commonly more pronounced at
youth levels becoming less signicant at senior levels (Musch
and Grondin 2001; Helsen et al. 2005). The decreasing RAE at
senior levels may be explained by theories (e.g., reversal eects
of relative age and the underdog hypothesis) that suggest
relatively younger players who are initially disadvantaged,
eventually catch-up (and potentially overtake) their relatively
older peers through developing sport-specic skills over the
long term (Gibbs et al. 2012; McCarthy et al. 2016). However,
not all studies of the RAE have shown a reversal of the selection
bias of players as they transition through the development
pathway. In particular, the RAE was found to be persistent
across senior professional competitions in both the Australian
Rules football talent development pathway (Tribolet et al. 2019)
and elite German soccer (Götze and Hoppe 2021).
To the author’s knowledge, only two studies have investi-
gated the RAE across the Gaelic games playing population. In
their study of U13 to U20 players (n = 2,194), Campbell et al.
(2012) showed BQ1s were signicantly overrepresented
whereas BQ4s were signicantly underrepresented across all
age groups (BQ1 = 30.3% vs. BQ4 = 17.6%). Likewise, Power
et al. (2012) revealed a RAE in U14 to U16 TA players (n = 115),
which favoured relatively older youth (BQ1 = 38.2% vs.
BQ4 = 16.5%). While these studies highlight the existence of
the RAE during a single season in GAA TAs, there is a need to
examine the phenomenon over several years, as well as includ-
ing senior levels, in order to capture trends in player develop-
ment and selection policies at varying levels (Schorer et al.
2020). Moreover, since qualitative research is yet to exist in
this context, coupling longitudinal data with key stakeholder
perspectives will help capture the mechanisms of the RAE
throughout the GAA player pathway. Given the technical, tac-
tical, physical, and psychosocial requirements of GAA
competitions, it is possible that key stakeholders are inuenced
by certain player characteristics during the selection phase that
may exacerbate the RAE in Gaelic football and hurling
(Campbell et al. 2012; Power et al. 2012). However, much of
the current literature focuses on quantitative descriptions of
the RAE, with few studies employing qualitative or mixed
method approaches to enhance our understanding of the fac-
tors which may contribute to the bias in selecting players born
during the earliest stages of the year (Baker et al. 2020;
Turnnidge and Kelly 2021; Kelly et al. 2021e). Of the qualitative
studies that do exist, it has been shown that key decision
makers in rugby union may contribute to the onset of the
RAE by selecting players with advanced physical characteristics
and, therefore, place a greater emphasis on performance-
related outcomes (e.g., winning) rather than creating develop-
mental opportunities for those with long-term potential (Lewis
et al. 2015). Therefore, as key decision makers in the GAA, the
views of coaches and other stakeholders are crucially important
in order to gain an understanding of the individual talent
development policies employed, and whether any inuencing
factors exist which may exacerbate the RAE and thus, aect the
player development experience.
Given the absence of studies in the GAA which highlight
the frequency of the RAE through longitudinal analysis, and
the need to better understand key stakeholder experiences
throughout youth and senior Gaelic football and hurling, this
study employed a mixed method approach. Specically, the
aims of the study were twofold: (a) to explore the prevalence
of the RAE in GAA Talent Academies and senior teams, and
(b) to explore key stakeholder perspectives and experiences
of the talent development environment in order to provide
a level of practical insight into the RAE. Based on ndings
from similar research (e.g., Campbell et al. 2012; Power et al.
2012), it was hypothesised that the RAE would be present
within the TA cohort and reduce in eect throughout each
age group and become less signicant at senior level.
The second phase of the study would seek to explore key
stakeholder (i.e., coaches and talent development leads)
experiences of the talent development environment which
may help inform current and future TA structures, as well as
oer practical guidance to organisational decision makers in
an attempt to improve player and key stakeholder
Research design
Given the absence of a longitudinal, mixed method approach
to better understand the RAE throughout youth and senior
Gaelic football and hurling, a sequential explanatory
research design (Creswell et al. 2003) was applied to this
current study using retrospective analysis of longitudinal
data. Specically, two successive phases of data collection
and analysis were adopted. Phase one involved the collec-
tion and analysis of existing data sets of birth distributions in
GAA TA and senior cohorts. Phase two included the collec-
tion and analysis of qualitative information through focus
groups from key stakeholders (e.g., coaches and Talent
Development Leaders
) within the GAA, in order to provide
a level of practical insight and understanding of the RAE
through the lens of those closely involved in the talent
development pathway.
In line with Collins et al. (2019) suggested approach to talent
development research, a pragmatic approach was adapted
throughout this study. Often associated with mixed method
studies, pragmatism is a research paradigm based on the idea
that researchers should use the philosophical or methodologi-
cal approach that best matches the particular problem under
investigation (Tashakkori et al. 1998). Such an approach oers
a degree of exibility to the study design (Creswell and Clark
2017), where the main focus is on the consequences of the
study, in particular the research questions, rather than the
methodology used.
Phase one: quantitative analysis
Following institutional (University College Dublin) and organi-
sational (Gaelic Athletic Association and Gaelic Players
Association) ethical approval, secondary datasets of both TA
Gaelic football and hurling male players aged 13 to 17 years
(n = 12,445) and senior male players (n = 8,752) were analysed.
These age groups were chosen as they represent the entire
formal GAA pathway, including the initial entry phase to the TA
programme (i.e., U14), the subsequent TA annual age groups
(i.e., U15, U16, and U17), and the transitional phase between
youth and senior level (i.e., U18+); all of which are crucial stages
in the player development process (Lidor et al. 2021).
Data for all TA players between 2013 and 2019 were obtained
from the GAA’s player monitoring database (Fusionsport 2021).
Simultaneously, senior player data between 2017 and 2020
were obtained directly from the Gaelic Players Association,
the ocial representative body for all senior players.
Birthdates for all players were categorised into the following
quartiles based on the annual cut-o dates for the GAA com-
petitions: (a) BQ1 = January to March, (b) BQ2 = April to June, (c)
BQ3 = July to September, and (d) BQ4 = October to December.
Players were then further categorised based on the following
age groupings: (a) U14 (n = 3,118), (b) U15 (n = 4,276), (c) U16
(n = 3,296), (d) U17 (n = 1,755), and (e) senior (n = 8,752). To
compare observed BQ distributions with those of the general
population (i.e., national norms), male births between the years
1980 and 2005 (n = 42,772) were obtained from the Central
Statistics Oce (2021) and Northern Ireland Statistics And
Research Agency (2021), which reected the birth distributions
of the youngest to oldest players contained in this sample
(BQ1 = 24.8%, BQ2 = 25.5%, BQ3 = 25.7%, BQ4 = 23.9%).
Data analysis
Chi-square goodness of t tests were used to analyse the
observed age grouping BQ distributions with the expected
BQ distributions based on the national norms. To determine
the likelihood of a player from a particular BQ being repre-
sented, odds ratios (ORs) and 95% condence intervals (CIs)
were calculated, with BQ4 used as the reference group (i.e., BQ1
vs. BQ4, BQ2 vs. BQ4, and BQ3 vs. BQ4). A higher OR indicated
an increased frequency of players born in a particular quartile
compared to the reference quartile (BQ4) and were considered
signicant when the CI range was ≤1.00. Finally, to determine
the eect size, Cramer’s V was calculated and interpreted as
either small (≥0.06), medium (≥0.17), or large (≥0.29), based on
guidelines for degrees of freedom (df = 3) (Kim 2017). Results
were considered signicant where P < 0.05. All statistical ana-
lyses were performed using Microsoft Excel (Microsoft,
Redmond, WA, USA).
Phase two: qualitative analysis
Focus group participants were recruited from
a convenience sampling of TA and senior coaches (male
n = 4; experience mean 12.75 years) and Talent
Development Leaders (TDLs) (male n = 4; experience
mean 15.25 years).
The sample of coaches recruited con-
sisted of U14 Gaelic football (n = 1), U17 Gaelic football
(n = 2), and senior Gaelic football (n = 1), which repre-
sented the beginning (U14), middle (U17), and senior
stages of the GAA player pathway. TDLs were recruited
from both GAA codes (football n = 2; hurling n = 2) and
represented a broad geographical demographic, in order
to provide an accurate understanding of the unique struc-
tures within counties of dierent playing levels in Ireland.
Participant characteristics are provided in Table 1.
Two focus groups were held remotely via Microsoft Teams
(Microsoft, Redmond, WA, USA). Focus groups were selected
as the primary research method as they allowed for the
conguration of both groups with participants who were
capable of providing in depth nuanced discussions on the
specic research topic (Greenbaum 1998). Two semi-
structured interview schedules were developed using open-
ended probing questions, which would explore the topic of
the study from both the coach and TDLs perspectives (See
appendix A). Both focus groups comprised questions around
participant knowledge of the RAE, the type of player
sought, and methods used during talent identication
phases in TAs and senior teams, and whether a player’s
birth month was a signicant factor during nal selection
decisions (e.g., “Do you think birthdate can inuence some-
one’s chances of being selected?, What is the basis for
selection at each age grade?).
Table 1. Focus group participant characteristics.
(Years) Gender County ID
Academy Coach (Under 14) 12 M Tier 2 FB Coach 4
Academy Coach (Under 15) 8 M Tier 2 FB Coach 3
Academy Coach (Under 17) 6 M Tier 1 FB Coach 2
Senior Coach 25 M Tier 1 FB Coach 1
TD Leader 12 M Tier 1 Dual TDL1
TD Leader 18 M Tier 1 H TDL2
TD Leader 15 M Tier 2 FB TDL3
TD Leader 16 M Tier 2 FB TDL4
Data analysis
Data were analysed manually using inductive content ana-
lysis, following the four staged framework described by
Bengtsson (2016): (a) decontextualization, (b) recontextua-
lization, (c) categorisation, and (d) compilation. After read-
ing both transcripts, segments of transcriptions were
separated into meaning units which were further con-
densed in either a descriptive or interpretive way and
assigned codes related to the overall study aim.
Generated codes were then collated and reviewed against
the meaning units to determine if all aspects of the study
aim have been met. By repeatedly reading the transcripts
and analysing how the meaning units and codes t with
emerging themes, higher and lower-order themes were
developed based on commonly observed trends relevant
to the research questions.
Methodological rigor
In order to ensure eective qualitative research practices,
the researchers reviewed the eight criteria as proposed by
Tracy (2010) (worthy topic, rich rigor, sincerity, credibility,
resonance, signicant contribution, ethical, and meaningful
coherence), which contributed to rigor in the study. This
study was commissioned by the GAA who identied it as an
area that would provide the organisation with additional
information on player and coach development practices.
Further, as this was, to the author’s knowledge, only the
third study of the RAE in the GAA, and the rst to use
a qualitative methodology, it was considered a worthy
topic. The collection and analysis of large data sets, and
importantly the use of two focus groups using participants
with contrasting perspectives of player development,
ensured the study met the criteria for rich rigor. Sincerity
was embraced throughout the research process whereby
the lead author endeavoured to remain unbiased during
focus group discussions, to ensure he did not inuence
the nature of the responses received. Additionally, the accu-
racy of both the quantitative data, and the reections from
multiple stakeholder experiences, ensured a credible
research design was used. The nature of the ndings high-
lighted the reality of talent selection practices within the
GAA, and these ndings may resonate with the reader
through their past or current experiences. In addition, this
study may advance knowledge of the reader on the extent
of the RAE in both youth and senior cohorts, as well as the
factors that inuence this. This knowledge may also help
inform future organisational structures, in order to enhance
the player development experiences in GAA pathways and,
therefore, the study signicantly contributes to current litera-
ture and applied practice. Due to the large volume of player
data, the majority of which pertained to players who were
under the age of eighteen, appropriate ethical procedures
were followed at all times. Subsequently, procedural ethics
were adhered to that protected the identity of both players
in the data set and participants partaking in focus group
discussions. Finally, ensuring meaningful coherence, this
study achieved its stated goals and interconnected each
stage of the research process so as to accomplish the
intended outcomes.
The results of both phases of the research design are
presented hereafter in sequential order. Phase one outlines
statistical analysis conducted on the TA and senior second-
ary data sets. Phase two presents an overview of the
themes obtained during the focus group discussions.
Phase one
Descriptive statistics, including the frequency and distribution
of BQs at each age group, are presented in Table 2. When all
age groups were taken together, the chi-squared (χ
) goodness
of t test indicated that the proportion of players in each BQ
included in the TA sample was signicantly skewed compared
to the expected distributions based on national norms, with
a small eect size (χ
(3) = 402.133, P < 0.001). Signicant ORs
showed how players who were selected to TAs were more likely
to be born earlier in the year, with a greater likelihood of being
born in BQ1 or BQ2 compared to BQ4. Specically, a TA player
was almost 1.7 times more likely to be born in BQ1 (1.67; 95% CI
1.55–1.79) and 1.5 times more likely to be born in BQ2 (1.49;
95% CI 1.38–1.60) when compared to BQ4. With regard to the
senior level, the RAE was less pronounced (i.e., BQ1 = 25.3% vs.
BQ4 = 23.1%), with no signicant dierences between the
observed and expected BQ distributions
(df = 3) = 3.812,
P = 0.282).
Table 2. Analysis of birth-date distributions by BQ amongst TA and senior GAA players.
Cohort BQ1 (%) BQ2 (%) BQ3 (%) BQ4 (%) Total χ
(df = 3) P Cramer’s V Effect size BQ1 vs. BQ4 OR (95% CI)
U14 TA 898
3118 55.784 0.004 0.08 Small 1.44
(1.25, 1.67)
U15 TA 1323
4276 157.731 0.005 0.11 Small 1.72
(1.52, 1.94)
U16 TA 1057
3296 158.957 0.003 0.13 Small 1.93
(1.67, 2.23)
U17 TA 504
1755 51.60 0.003 0.10 Small 1.53
(1.26, 1.86)
U14-U17 TA 3782
12,445 402.133 <0.001 0.10 Small 1.67
(1.55, 1.79)
Senior 2214
8752 3.812 0.282 0.01 N/A 1.06
(0.97, 1.15)
BQ1: January – March, BQ2: April – June, BQ3: July- September, BQ4: October–December. χ
= chi-square value, df = degrees of freedom for χ
. p-value = level of
statistical significance for χ2.
Phase two
Inductive analysis of the data highlighted three higher-order
themes: (a) participants had little understanding of the con-
founding eects of the RAE, (b) consistent player identication
and selection criteria were absent, and (c) preferred player
characteristics at each age group were explored. Seven lower-
order themes were included in these high-order-themes, which
are presented in Table 3 alongside sample quotations in order
to illustrate the analysis process.
RAE understanding
Participants reported the RAE as a concept which they were
broadly aware of, however, during trial periods and the playing
season as a whole, it was rarely considered as part of the talent
identication, selection, and development process:
I’d be wrong to say that when we were doing trials at U14 that I knew
the ages or the dates of the month. We didn’t to be honest” (Coach 2).
I wouldn’t know the [player’s] date of births within the year, not with
Talent Academies, no” (Coach 3).
Although an understanding of the RAE was limited, some coa-
ches explained that recently they have begun to develop their
knowledge on its signicance in player development, although
it was not until they had left their roles within TAs that they
chose to educate themselves further:
It was always something I was conscious of but not in Talent
Academies. But when I went back to my club, I was certainly more
conscious of it” (Coach 1).
Player identification and selection criteria
There was mixed evidence on the existence and implementa-
tion of prescribed selection criteria, with coaches required to
collaborate with their fellow coaches to make key player selec-
tion decisions. For instance, one TA coach suggested that it is
often his own observation and instinct as a coach which form
the opinion on whether a player meets the desired standards of
a TA player:
No, there isn’t. There isn’t a prescribed set of criteria that we would
work to or try to identify players from, it’s very much observation
and instinct in relation to yourself to say look, can they play ball?”
(Coach 2).
Additionally, one TDL noted that while selection criteria had
previously existed in his county, there is a need for universal
selection criteria in GAA TAs, as decisions are now often left to
coaches when deciding the type of player to be selected:
We would have written down selection criteria but the more we’re
looking at it, it’s probably the coaching eye, word of mouth, obser-
vation of players in their clubs and school environment. Would it be
helpful to have an outline at various age levels? I think it would be
because it is evolving all the time” (TDL 2).
However, one TDL revealed the benets to having a set of
criteria within their TA teams, as it ensured a level of consis-
tency annually, as well as reduced potential conict situations
when it came to player selection decisions:
We had ve criteria and the lads [coaches] that we have back
every year know the process, you know, but we trust them to pick
the right lads. The process is important because parents come with
an email, so you have to have a procedure or process to go back to
when the problems arise” (TDL 1).
Interestingly, although TDLs explained that they had an aware-
ness of, and in some cases clearly dened selection criteria in
their TAs, this was not the unanimous feeling amongst coaches
who felt that key decisions are the responsibility of individual
Player characteristics
Participants stated that depending on the age group they were
associated with, the desired player qualities should be reected
in the level at which they play. For example, at U14/15/16,
participants emphasised several qualities such as technical,
tactical, team play and coachability, however, as they pro-
gressed to U17 level, a more balanced player was preferred:
At U14/ 15 you are looking at technical ability and skill set (Coach 4).
At 14/15/16 its technical ability and tactical decision-making ability,
team play ability, coachability (TDL 1).
We would have said once we took the U16 squad and are a year out
from minor [U17], you’re really looking at the more rounded player
and their application in terms of the whole buy in” (Coach 4).
And it just kind of all in terms of what we were looking for at that
age [U17], you are looking for the better players in terms of ability”
(Coach 3).
At senior level, participants described the need for players to
possess advanced levels of physicality and skillset due to the
increased demands and responsibilities required at that level:
You have to look at it from a physical hardware point of view of
nowadays. Have they the capacity to train at an elite level? The
capacity where a guy who might look spectacular and have a great
club championship, and is known by his physical attributes, he just
might not be able to play elite football (Coach 1).
While it was revealed that players are selected based on several
characteristics and behaviours (e.g., coordination, decision-
making, athleticism, coachability, tactical, technical, and team
play ability), and although there was some evidence of
a prescribed selection criteria amongst TDLs, this was not com-
municated directly to coaches. Additionally, a player’s physical
ability was not revealed to be a decisive factor during selection
opportunities, particularly at TA level and, therefore, as partici-
pants were unaware of a player’s date of birth and the overall
concept of the RAE, it cannot be assumed that they purposely
selected chronologically older players.
The aims of the study were twofold: (a) to explore the
prevalence of the RAE in GAA Talent Academies and senior
teams, and (b) to explore key stakeholder perspectives and
experiences of the talent development environment in
order to provide a level of practical insight into the RAE. It
was hypothesised that the RAE would be present within the
TAs, reducing in successive years and eventually becoming
less signicant at senior level (Cobley and Til 2017). Phase
Table 3. Higher- and lower-order themes describing participant perceptions of the RAE.
themes Low-order themes Sample quotations
of implications
Emerging interest in
I have much more awareness of it now than I did when I was actually stuck in the middle of it, if that makes sense. It probably wasn’t something that was really considered when I was
coaching the U15/16/17 Academies’ (Coach 3).
‘I would have read a bit on it over the last 12 months, and I have a fairly good understanding of it at this point’ ” (Coach 2).
Selection criteria Coaches judgment
Selection matrix
It [selection] is probably the coaching eye, word of mouth, observation of players in their clubs and school environment. Would it be helpful to have an outline at various age levels? I think it
would be because it is evolving all the time(TDL 2).
I don’t think there is a selection criteria. I think it is a kind of collective where you work closely with your selectors but there is no criteria. You are just ticking the boxes for technical skills
and athleticism mainly (Coach 2).
Would it be helpful to have an outline at various age levels? I think it would be because the thing [player development] is evolving all the time’ (TDL 2).
Players ability
of characteristics
And it’s just kind of all in terms of what we were looking for. Look at that age, you are looking for the better players in terms of ability’ (Coach 2).
At 14/15/16 it’s technical ability and tactical decision-making ability, team playability, coachability. And we go into the physical fitness a little bit, but if a guy is lacking this, we
understand that we can get that done through the development process (TDL 1).
one revealed that in each annual age group at TA level,
there was an over-representation of players born in the
early stages of the year compared to those born later in
the year (i.e., U14-17 BQ1 = 30.4% vs. BQ4 = 17.6%).
However, at senior level the RAE was less pronounced,
with results indicating an even distribution of birthdates
(i.e., BQ1 = 25.3% vs. BQ4 = 23.1%). These ndings are
consistent with both previous studies of the RAE in the
GAA by Campbell et al. (2012) and Power et al. (2012),
who observed similar eects in their TA sample cohort.
Indeed, these ndings partially support our initial hypoth-
esis. The second phase of the study explored key stake-
holder (i.e., coaches and full-time employee) perspectives
and experiences of the talent development environment in
order to provide a level of practical insight into the RAE.
Findings revealed that key stakeholders had a limited
understanding of the RAE and how it impacted key player
selection decisions. Additionally, the implementation of
a prescribed selection criteria was found to be inconsistent,
with coaches often required to use their own experience
and judgment when making key selection decisions. Finally,
participants described several player characteristics pre-
ferred during the identication and selection phases of TA
and senior teams in the GAA.
Regarding the quantitative ndings, despite the RAE being
signicant throughout the TA sample, it did not decline as
expected since it remained consistent between the U14 and
U17 age groups, before levelling o somewhere between U17
and senior. These ndings are contrary to previous RAE litera-
ture in youth sport (Doncaster et al. 2020; Dugdale et al. 2021;
Lidor et al. 2021), where results indicated that it was common
for the RAE to decrease with age, however, some studies do
support the continued presence of the RAE throughout the
player pathway up to and including senior professional level
(Tribolet et al. 2019; Götze and Hoppe 2021). One suggestion
for this ongoing selection bias is that the selection practices of
key stakeholders in GAA TAs continues to favour ‘older’ players
later in the development pathway, despite physical advantages
becoming less pronounced (Dugdale et al. 2021). It could also
be suggested that coaches adopt a continuous preference to
selecting physically dominant players or perhaps demonstrate
a loyalty to those players who they had initially selected earlier
in the development pathway ahead of those on the periphery
of the squad (Cripps et al. 2016). Coaches revealed that they
sought for a more ‘well-rounded player’ at older age grades
which may highlight that the physical attributes of players
continue to inuence the selection process and are, therefore,
of some importance. Coupling this with the acknowledgement
that participants were broadly unaware of player date of births
before and during selection opportunities, enhances the like-
lihood of a strong bias towards selecting those born in BQ1 or
BQ2. Further, the lack of a consistent selection criteria suggests
that coaches select players based on their own intuition and
experience and are therefore more likely to make personal
decisions on a players future talent (Roberts et al. 2021).
However, further research is required to better understand
how the initial entry into TAs (i.e., U14) has a knock-on eect
of relative age in subsequent age groups (i.e., U15, U16,
and U17).
The results of phase one of this study were further sup-
ported by the inclusion of a qualitative design, where the
perspectives of key decision makers (coaches and TDLs) were
explored in the context of the RAE revealing several interesting
ndings. First, coaches had little knowledge of the concept of
the RAE (i.e., RAE understanding). Second, coaches did not
consider nor were they aware of player birth dates during the
selection process at TA or senior level (i.e., player ID and selec-
tion criteria). Finally, the type of player preferred by participants
across the various age groups was revealed, where those pos-
sessing several qualities, characteristics, and behaviours (e.g.,
technical, tactical, team play ability, attitude, physical hardware,
and coachability) were deemed preferable. These ndings
would seem to support those of the quantitative analysis
where the strong selection bias (i.e., RAE) was observed across
all teams at TA level in particular. Despite signicant experi-
ence, the absence of an understanding of the RAE amongst
participants is somewhat surprising, even within the amateur
environment of the GAA. Although it might be reasonable to
assume that participants should be aware of the mechanisms of
the RAE (Helsen et al. 2012), ndings justify why player birth
dates were not considered, as the relevance of such informa-
tion may not have been fully understood. As previously men-
tioned, ndings revealed that participants identify and select
players based on several characteristics and behaviours across
each of the age groups. However, as they were unaware of
player birth dates, it cannot be assumed that they purposely
selected those who were chronologically older. Subconsciously,
coaches may be inuenced by a players technical or physical
ability and, therefore, their selection is deemed automatic
based on these qualities (Helsen et al. 2000). Nevertheless, it
is important to recognise that social and psychological factors
may also contribute to the onset of the RAE (Doncaster et al.
2020), and should be considered as part of a holistic selection
process (Kelly et al. 2021b). Further, while skill levels are an
important quality for GAA players to possess, their perceived
ability may be enhanced by their physical size and therefore
coaches may be (un)consciously biased towards selecting those
who are physically superior to their teammates (Delorme et al.
2009; Delorme and Raspaud 2009; Meylan et al. 2010).
These results are concerning for those responsible for orga-
nisational and competition structures within the GAA.
Specically, somewhere during the transition phase (i.e., U17
to senior), players who once represented the majority (BQ1s
and BQ2s) are disappearing from the elite pathway. While it is
evident that relatively younger players are ‘catching-up’ with
their relatively older peers, possibly through the creation of
a competitive environment with their older teammates (Gibbs
et al. 2012; McCarthy et al. 2016), the current status of older
players is a cause for reection for the GAA. Although ndings
have shown that relatively older players tend to be recruited
into talent development pathways at youth levels, it seems
they comprise a greater percentage of those who fail to suc-
ceed at senior levels (Kelly et al., 2022). Moreover, it should be
determined whether these players are leaving the game com-
pletely or returning to a lower playing level with their clubs,
since long-term participation at any level should be priority for
TAs when recruiting young players. Thus, although the RAE
may have important implications on the immediate outcomes
and short-term opportunities for relatively younger players,
they could also have a detrimental eect on the long-term
outcomes for relatively older players (Turnnidge and Kelly
Nevertheless, the underrepresentation of relatively younger
players across all stages of the GAA TA system is a more press-
ing issue for the GAA as these players may not have the
opportunity to experience a high-performance training envir-
onment which may enhance their overall development in the
long term. Due to the decline in physical and developmental
advantages, those chronologically younger players (i.e., BQ1s &
BQ2s) who are selected to GAA TAs may eventually develop
superior abilities which will elevate them above their older
peers (Votteler and Höner 2014; Cumming et al. 2018), how-
ever, if they are not provided with the opportunity to ourish,
they may never reach their full potential as young players. This
may suggest that as time goes on, young players who are less
mature will drop out of the GAA entirely, as they are not as
successful, motivated, or fullled by the playing experience any
longer (Stracciolini et al. 2016).
Future research directions
Following on from the presented ndings, considerations for
future research are provided for key stakeholders when
attempting to alleviate the causes and eects of the RAE (see
Figure 1). Strategies such as age and anthropometric banding
(MacDonald et al. 2009), birthday-banding (Kelly et al. 2020),
multi-squads (Musch and Grondin 2001), RAE quotas (Barnsley
and Thompson 1988), and delayed selection practices (Cobley
et al. 2019) have all been proposed as alternatives to the
common chronological age-based systems and appear to
address the mechanisms of the RAE and create a positive player
development environment (Webdale et al. 2020). However,
there are currently no studies in Gaelic football or hurling that
has designed, implemented, and evaluated these potential
solutions. Thus, future research is encouraged to apply these
possible solutions in order to better understand how to reduce
the RAE and create settings that are more appropriate across
the GAA.
The ndings from this study are novel as it is the rst to
simultaneously investigate the RAE in GAA TA and senior
player cohorts, while incorporating data from key decision
makers in talent identication and selection procedures,
advancing previous studies by Campbell et al. (2012) and
Power et al. (2012). Interestingly, in the decade since the
publication of these studies little change has been intro-
duced at an organisational or local level in the GAA, as
current ndings continue to highlight a signicant RAE in
all TA age groups. Thus, future research is warranted to
observe and inform contemporary practices throughout
the GAA to ensure key stakeholders better understand the
RAE through education (Grossmann and Lames 2013), are
provided with clear selection criteria with markers of poten-
tial over performance (Kelly et al. 2021c), and ensure player
characteristics are recognised as holistic and long-term
focussed (Kelly et al. 2021d).
A unique element of this study was the inclusion of
a qualitative component that complimented the ndings
of the quantitative phase. While the data retrieved was
invaluable to the study, the sample size of coaches and
TDLs reected only a small proportion of those who are
actively coaching and supporting GAA TA programmes
across Ireland and may not provide an overall assessment
of specic practices, cultures and traditions within each
individual county, which may have inuenced the ndings.
It is also worth noting that qualitative ndings may only be
relevant to Gaelic football coaches as the cohort used in
this sample did not include any hurling representatives,
although the inclusion of hurling TDLs contributed to the
quality of the study.
Coach education programmes should aim to upskill key personnel on the existence and potential
disadvantages of the RAE.
Acknowledge the presence of the RAE in its playing cohorts and actively reflect on the current practice
of grouping players according to chronologocal age bands.
Examine possible RAE strategies that may promote positive player experiences in its pathways.
Explore the RAE from the perspectives of several other key stakeholders, such as players, parents,
coaches, and administrators, to determine the extent of their influence on the RAE.
With the RAE becoming less prominent at senior level, longtitudinal research is required to track,
analyse, and report on individual player progress throughout the GAA player development pathway.
Figure 1. Future research directions for GAA stakeholders.
This study was strengthened by the large sample size of
21,197 TA and senior players, which was comprised of up to
eight years of retrospective data. One limitation to this long-
itudinal approach was the possibility that players appeared
more than once in the dataset in subsequent years (i.e., U16
and U17). Additionally, it is possible that players in the TA
sample were represented in the senior cohort once they had
progressed through the TA system however, removing dupli-
cates was beyond the scope of this study due to the absence of
player identities. Nevertheless, it accurately depicts those who
have competed at each TA and senior annual age group across
these seasons. Finally, although in line with previous studies of
the RAE (i.e., Rubajczyk and Rokita 2020; Dugdale et al. 2021),
the comparison of both the TA and senior player samples with
the general population birth rates and not the specic Gaelic
games playing population is a limitation. Future studies should
seek to compare playing samples with the overall participation
pool (e.g., comparing the birth quartiles of under 14 TA players
with those of all under 14 players in Gaelic games) to investi-
gate the possibility of whether coaches recruit players from an
already biased RAE pool.
This study is the rst to quantify the RAE in both codes
(Gaelic football and hurling) across every county participat-
ing in GAA Talent Academy and senior grades, while seeking
to explore key stakeholder perceptions and understanding
of the RAE. Analysis revealed a signicant and ongoing
selection bias exists in the GAA TA pathway (i.e., U14
U17), while at senior level, no such bias was found. Focus
group discussions revealed three higher-order themes: (a)
participants had little knowledge of the confounding eects
of the RAE, (b) player identication and selection criteria
were absent, and (c) preferred player characteristics at
each age group were explored. This study provides key
stakeholders in the GAA with useful data on the RAE within
its cohorts, as well as oering a clearer understanding of the
selection practices currently implemented. In the immediate
future, further collaboration may be required between the
GAA and researchers to investigate potential strategies that
may reduce the RAE and promote positive player experi-
ences within their respective teams.
1. At senior grade, counties eld only one team in Gaelic football and
hurling, while within the Talent Academy system counties may eld
multiple teams in each age group (U14-U17) in both playing codes.
2. In this study, Talent Development Leader refers to full time employ-
ees of the GAA who are responsible for the organisation and imple-
mentation of player and coach development programmes (Talent
Academies) in their counties.
3. In this instance, experience refers to the number of years the TDL
has been employed within the GAA and has had oversight over his
counties Talent Development Programme. Coaches experience has
been quantied by the number of years they have been actively
coaching within the GAA at any level.
Disclosure statement
No potential conict of interest was reported by the author(s).
The author(s) reported there is no funding associated with the work fea-
tured in this article.
Jamie R. Queeney
Adam L. Kelly
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Appendix A: Interview guide
Focus Group Interview Guide
Question Probe Purpose
Please tell me about your coaching background. Past/ Current
How many years Academy/ senior experience have you?
(1) How do you identify talented players for your team?
(2) What attributes/Characteristics do you look for when choosing
players at U14/U17/Senior?
(3) Is there a prescribed criteria for selecting players in your County?
(4) How many selection opportunities (trials) do you hold at each age
grade? How long do you need to observe an athlete for in order to
identify them as talented?
(5) Is there an awareness of the relative age effect (RAE) among
Length of time coaching/ employed in
Experience of coaches
Are we selecting or identifying
Can they be measured?
Why do you look for those traits?
Do you have a criteria?
Who selects players?
Are team selection decisions based
on birthdate, height, weight, and/or
Ongoing or immediate (ie trials)?
Loyalty to players from U14-U17?
If so, does this affect selection for
your team?
Are you aware of the players Dates of
Births in your squad?
Is it necessary in your opinion?
To place all future responses in context
Establish current performance/
coaching level
Specific, preferably measurable, factors
or attributes that coaches use to
predict talent
Are coaches willing to sacrifice short
term success for long term gain?
Is TID inclusive and offer many
opportunities to progress to elite level
Assess the prior knowledge of RAE in
GAA coaches
ResearchGate has not been able to resolve any citations for this publication.
Full-text available
The purpose of this study was to adopt the Personal Assets Framework (PAF) to examine the immediate, short-term, and long-term developmental outcomes associated with relative age effects (RAEs) in male cricket. As such, this study was comprised of three aims: (a) examine the birth quarter (BQ) distribution of players throughout the England and Wales Cricket Board (ECB) national talent pathway (i.e., Regional U15, Regional U17, England U19, England Lions, England T20, England ODI, and England Test; n = 1800; immediate timescale), (b) explore the youth-to-senior transitions based on BQ and skill-set (i.e., batters and bowlers; short-term timescale), and (c) analyse the average number of games played at senior levels based on BQ and skill-set (i.e., long-term timescale). A chi-square goodness of fit test, Cramer’s V, odds ratios, and 95% confidence intervals were used to compare the BQ distributions of each cohort against the expected BQ distributions. In the immediate timescale, results showed that relatively older players were overrepresented throughout all the youth levels (p < 0.05, V = 0.16–0.30), whereas there were no differences at senior levels (p > 0.05, V = 0.05–0.15). In the short-term timescale, when the senior cohorts were compared to the expected BQ distributions based on the Regional U15 cohort, relatively younger players were more likely to transition from youth to senior levels (p < 0.05, V = 0.22–0.37). In the long-term timescale, relatively older batters were selected for more games (p < 0.05, V = 0.18–0.51), whereas relatively younger bowlers were selected for more games (p < 0.05, V = 0.17–0.39). Moving forward, it is important for researchers and practitioners to better understand how (bi)annual-age grouping shapes developmental outcomes in across different timescales (i.e., immediate, short-term, and long-term), as well as consider alternative grouping strategies and RAE solutions.
Full-text available
Relative age effects (RAEs) appear consistently prevalent throughout the youth basketball literature. However, the selection into and successful transition out of a national talent pathway in basketball is yet to be explored. Thus, the primary aim of this study was to explore the influence of relative age, gender, and playing time based on the selection into the Regional Talent Hubs and Basketball England youth teams (U16, U18, and U20) and the successful transition into the England National Senior Teams. Participants who were selected into the male (n = 450) and female (n = 314) Basketball England Talent Pathway were allocated into one of three cohorts: (a) Regional Talent Hubs (U12 to U15; n = 183), (b) England National Youth Teams (U16, U18, and U20; n = 537), and (c) England National Senior Teams (n = 44). A chi-square test was used to compare the birth quarter (BQ) distributions of each cohort against the expected distributions, with a Cramer’s V (Vc) used to interpret effect sizes. Odds ratios (OR) and 95% confidence intervals were also calculated to compare the likelihood of each BQ being represented. Males revealed significant RAEs across both the Regional Talent Hubs (p < 0.001, Vc > 0.29, OR = 10) and England National Youth Teams (p < 0.001, Vc > 0.17, OR = 3.1). In comparison, females only had significant RAEs in the Regional Talent Hubs (p < 0.001, Vc > 0.29, OR = 2.3). Despite RAEs being prevalent throughout youth levels, there were no significant differences in the BQ distribution based on playing time and those who made the successful transition to the England National Senior Teams. These findings demonstrate the potential mechanisms of RAEs in basketball, as well as the impetus to explore more equitable competition structures within the England Basketball Talent Pathway.
Full-text available
One of the environmental variables associated with early talent development and the achievement of a high level of proficiency in sport is the relative age effect (RAE). The purpose of our study was threefold: (a) to calculate the RAE in young Israeli athletes (ages 14–18 years); (b) to examine how the athletes perceived this effect, if the effect indeed exists; and (c) to compare the RAE findings of this study with those of two previous studies on elite male (Lidor et al., 2010 ) and female (Lidor et al., 2014 ) Israeli ballplayers. Participants in the current study were 1,397 athletes (390 females and 1,007 males) who competed in five individual (gymnastics, judo, swimming, tennis, and track and field) and five team (basketball, soccer, team handball, volleyball, and water polo) sports. Data on the RAE, as well as on a number of aspects associated with this effect as perceived by the athletes, were collected via two closed questions. Data analyses showed that the RAE was found to be significant among the male athletes in four sports—swimming, basketball, soccer, and team handball; those who were born early in the year had a higher representation in these sport programs. However, this effect was not found to be significant in the female athletes. Most of the female and male athletes did not think that their birth date influenced their athletic success. However, a large portion of those who were born in the first quarter of the year (Q1) and the second quarter of the year (Q2) among the male athletes felt that they exhibited stronger abilities in the sports program compared to their peers who were born in the third and fourth quarters of the year (Q3 and Q4, respectively). The data of the current study provide additional support for the use of an “open door” approach to accepting children to sport programs by policymakers and coaches in Israel.
Full-text available
A common practice in youth rugby union is to group players based on (bi)annual age with fixed cut-off dates. The overrepresentation of players born at the start of the cut-off date and the underrepresentation of players born toward the end of the cut-off date are termed relative age effects (RAEs). The aim of this study was to examine RAEs during entry into professional and international rugby union pathways in England, as well as comparing them to their respective senior cohort: U15 Regional Academy Player ( n = 1,114) vs. Senior Professional Player ( n = 281) and U16–23 England Academy Player ( n = 849) vs. Senior International Player ( n = 48). Chi-square (χ ² ) analysis compared birth quarter (BQ) distributions against expected distributions. Odds ratios and 95% confidence intervals compared the likelihood of a BQ being selected. Findings revealed a significant overrepresentation of relatively older players compared with their relatively younger peers within both youth cohorts ( P < 0.001; BQ1 = 42.5% vs. BQ4 = 9.6%; BQ1 = 36.5% vs. BQ4 = 15.2%). In comparison, there was no significant difference in the BQ distributions within both senior cohorts. Further, BQ4s were 3.86 and 3.9 times more likely to achieve senior professional and international levels than BQ1s and BQ2s, respectively. It is suggested that relatively younger players may have a greater likelihood of achieving expertise following entry into a rugby union talent pathway due to benefitting from more competitive play against relatively older counterparts during their development (e.g., reversal effects; the underdog hypothesis). Moreover, possible solutions (e.g., age and anthropometric banding; playing-up and playing-down) are discussed to encourage practitioners and policy makers to create the most appropriate learning environment for every player.
Full-text available
Relative age effect (RAE) is considered to bias the selection of young athletes and a cause of exclusion of many participants. The goal of the study was to unveil the effects of the birth quarter on physical performances and a set of psychological constructs in the age groups corresponding to the specialization years. A set of surveys with cross-sectional data collected from 2015 to 2019 in youth basketball was used. Three hundred and twenty-seven Brazilian players (127 females, 100 males), mean age 14.0 years, participated in the study. Counter-movement jump, line-drill, yoyo intermittent test, achievement goals, motivation for deliberate practice, and enjoyment were measured. Bayesian multilevel regression was performed. RAE was observed but its advantages did not persist and did not differentiate the players in the variables under scrutiny. The only predictor of athletic and psychological outcomes was chronological age. The initial advantage that triggered the coaches' decision to select individual players disappears during the specialization years. Coaches must overcome the superficial observation of young athletes based only on age groups and actual performances, avoiding hasty decisions that, unlike RAE, last in time and cannot be reversed.
Full-text available
Significant structural, developmental and financial constraints exist in Scottish soccer that may predicate a different approach to talent identification and development. To our knowledge, no published reports exist evaluating the prevalence of the relative age effect (RAE) in Scottish soccer players. Consequently, the aim of this study was to investigate the prevalence of the RAE among varied playing levels and ages of male Scottish youth soccer players. Birthdates of male youth players (n = 1,230) from U10-U17 age groups and from playing levels: ‘Amateur’ (n = 482); ‘Development’ (n = 214), and; ‘Performance’ (n = 534), alongside a group of male Scottish senior professional players (n = 261) were recorded and categorised into quartiles (Q1 = Jan-Mar; Q2 = Apr-Jun; Q3 = Jul-Sep; Q4 = Oct-Dec) and semesters (S1 = Jan-Jun; S2 = Jul-Dec) from the start of the selection year. Birthdates were analysed for: (a) each playing level, and; (b) each age group irrespective of playing level. For the varied playing levels examined, a RAE was evident in ‘Development’ and ‘Performance’ playing levels only at youth level. When examining each age group, a RAE was observed in U12-U17 players only. While there was a slight asymmetry favouring Q1 born senior professional players, the RAE was not present within this group of our sample. Results from our study suggest that a bias in selecting individuals born earlier in the selection year may exist within male soccer academy structures, but not at amateur level. The asymmetry favouring chronologically older players at youth but not professional level questions the efficacy of this (un)conscious bias within male Scottish soccer players.
Full-text available
The relative age effect (RAE) is associated with (dis)advantages in competitive sports. While the RAE in elite male soccer reveals a skewed birthdate distribution in relation to a certain cut-off date, research of RAE in elite female soccer is affected by small number of samples and conflicting results. The purpose of this study was to investigate the RAE in elite adult German soccer regarding gender and competition level. The sample comprised 680 female and 1,083 male players of the two top German leagues during the 2019/20 season and German national teams (A-Team to Under 19). Differences between the observed and expected birthdate distributions were analyzed using chisquare statistics and effect sizes followed by calculating odds ratios. Results showed a statistically significant RAE with small effect size across all players included for both genders (female players: P < 0.001, W = 0.16, male players: P < 0.001, W = 0.23). The identified RAE was based on an over-representation of players born at the beginning of the year. According to gender and competition level, RAEs were more pronounced in German male soccer. While significant RAEs were found among males in the first two leagues (first league: P < 0.001, W = 0.19, second league: P < 0.001, W = 0.26), the RAE of females was more pronounced in the second league (first league: P = 0.080, W = 0.16, second league: P = 0.002, W = 0.20). The analysis of RAE regarding the national teams revealed a statistically significant RAE with large effect size for only the youngest investigated age group of male players (Under 19: P = 0.022, W = 0.52). Our data show an RAE in female and male German adult soccer, which could be accompanied by a loss of valuable elite players during the youth phase of the career. Consequently, the pool of talented players at the adult level would be limited.
Relative age effects (RAEs) are independent of specific cutoff dates that can vary from country to country. However, the consequences of changing the selection cutoff dates within a national sport organization are unknown. Further, the transition from international youth to senior representation is yet to be explored in rugby union. Thus, the aims of this article were twofold: Study 1 compared the birth quarter (BQ) distributions of the England Rugby Football Union (RFU) under-18 representatives based on September to August and January to December selection cutoff dates. Study 2 explored the BQ distributions within the RFU international development pathway through analyzing the under-18, under-20, and senior representatives, as well as the BQ distributions of youth players who were subsequently capped at senior level. Chi-square analysis was used to compare BQ distributions in each sample against expected distributions. Results revealed a corresponding shift of a skewed birthdate distribution favoring chronologically older players that was mediated by specific cutoff dates (p < 0.05). Moreover, whilst RAEs were present within both youth cohorts (p < 0.05), it was not apparent at the senior level (p > 0.05). Furthermore, during the transition from international youth to senior representation, more chronologically older players were successfully capped.