Dissertation

Is there a difference between 10-11 year old football
players in grassroots football in the West Yorkshire
region, born in the 1st and 2nd quartile compared to
participants born in the 3rd and 4th quartile of a relative
age grouping in relation to the development of self-
regulatory skills?
James Thomas Dunn
Leeds Beckett University, Carnegie Facility
Submitted in part fulfilment of the degree of ‘Sport Coaching’

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I confirm that this major independent study constitutes my own
work
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……………………………………………………………………………..
I confirm that the text of the submission does not exceed the
upper word limit of 10,000 words
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Is there a difference between 10-11 year old football players in grassroots
football in the West Yorkshire region, born in the 1st and 2nd quartile compared
to participants born in the 3rd and 4th quartile of a relative age grouping in
relation to the development of self-regulatory skills?
Acknowledgments
The project has been supported throughout by Chris Low, a senior lecturer at
Leeds Beckett University in BSc Sports Coaching.

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Table of Contents
List of Tables ........................................................................................................... 4
List of Figure............................................................................................................ 5
List of Appendices .................................................................................................. 6
List of abbreviations ............................................................................................... 7
Abstract.................................................................................................................... 8
Introduction: ............................................................................................................ 9
Literature Review: ................................................................................................. 12
What is the Relative Age effect?.............................................................................. 12
What ages are affected by the Relative Age effect? ................................................ 13
What is affected by the Relative Age effect?............................................................ 15
What psychological characteristics do development models explain under 11’s
possess?................................................................................................................. 16
What are self-regulatory skills?................................................................................ 19
Is there an advantage in being younger?................................................................. 21
Are self-regulatory skills affected by the Relative age effect? .................................. 21
Methodology.......................................................................................................... 26
The Sample............................................................................................................. 26
Data Collection........................................................................................................ 26
Procedure................................................................................................................ 27
Data Analysis .......................................................................................................... 29
Logistic regression analysis..................................................................................... 29
Ethical Considerations............................................................................................. 30
Results ................................................................................................................... 31
Logistic binary regression........................................................................................ 40
Discussion ............................................................................................................. 45
Principle findings ..................................................................................................... 45
Limitation of the study.............................................................................................. 46
Comparisons and differences with past studies....................................................... 47
Implications of research findings.............................................................................. 50
Recommendations................................................................................................... 52
Conclusion............................................................................................................. 53
Bibliography .......................................................................................................... 55

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List of Tables
Table 1.1: Thompson (2012) – Data Findings……………………………………14
Table 1.2: Simmons and Paull (2001) – Data Findings…………………………23
Table 1.3: Carling et al., (2009) – Data Findings………………...………………23
Table 1.4: Schorer et al., (2008) – Data Findings…………….…………………23
Table 1.5: Toering et al., (2009) – Data Findings……………..…………………24
Table 1.6: Toering et al., (2011) – Logistic regression analysis………………..24
Table 2.0: Participants in quartile one scores……………………………………31
Table 2.1: Average scores for participants in quartile one……………………..32
Table 2.2: Participants in quartile two scores……………………………………33
Table 2.3: Average scores for participants in quartile two……………………..34
Table 2.4: Average scores for participants in quartile one and two……………34
Table 2.5: Participants in quartile three scores………………………………….35
Table 2.6: Average scores for participants in quartile three……………………36
Table 2.7: Participants in quartile four scores…………………………..……….37
Table 2.8: Average scores for participants in quartile four…………………….38
Table 2.9: Average scores for participants in quartile three and four…………39
Table 3.0: Difference between quartile one/two and three/four averages……40
Table 3.1: Chi square results……………………………………………………...42
Table 3.2: Coefficients of the model………………………………………………42
Table 3.3: Wald Statistics………………………………………………………….43

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List of Figure
Figure 1.0: Schorer et al., 2008 – Relative Age Effect…………………………13
Figure 1.1: Three levels of psycho-behavioural skill development……………...19
Figure 1.2: Histogram of results…………………………………………………..44

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List of Appendices
Appendix 1: Self-regulatory Questionnaire……………………………………...61
Appendix 2: Participant information sheet and consent form…………………66
Appendix 3: Player information sheet and assent form………………………..69
Appendix 4: Gatekeeper information sheet and consent form………………..72
Appendix 5: Progress report forms………………………………………………75

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List of abbreviations
Abbreviation Stands for
RAE Relative Age Effect
β Beta Value
Final Word Count: 9,915

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Abstract
The purpose of this project was to examine the relationship between early and
late borns, to explore any significant differences between participants born at
the start and the end of a relative age grouping, in regards to the development
of self-regulatory skills: the process of participants controlling their thoughts,
feelings and actions. This has been stimulated due to current literature in the
area focusing more predominantly on the physical aspect of young player
development as oppose to the psychological. Additionally, literature has failed
to investigate the effects of relative age grouping in samples younger than 12,
which fails to acknowledge the changes that can take place in children before
this age. The study aimed to use this information to contribute to the findings
that could lead to an improvement of training programmes and practices by
raising awareness across coaching to the benefit of all stakeholders.
Thirty-two ten to eleven year old participants from grassroots football clubs in
West Yorkshire, England were selected to complete a questionnaire. The
questionnaire covered a range of topics including, planning, self-monitoring,
effort, self-efficacy, evaluation and reflection. A logistic binary regression
analysis highlighted that participants scoring high on self-monitoring and effort,
were most likely to belong to the second half of an age grouping (OR = 2.70).
The cause, being suggested as the need for relatively young participants to
compensate for any physical difference.

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Introduction:
The focus on youth football and the pressure on clubs to identify and develop
talent early has increased dramatically over recent years (Stratton et al., 2004).
The physique of players have been identified as a major factor in talent
identification. To date, self-regulation in relation to the relative age effect has
had limited research. No study yet emphasises how being a relatively earlier or
later born player effects the development of self-regulatory skills.
The purpose of this study is to assess the level of development of self-
regulatory skills in ten to eleven year old football participants in grassroots
football teams in West Yorkshire, England; between early born and later born
participants. Self-regulatory skills, are the process of controlling one’s thoughts,
feelings and actions (Baumeister and Vohs, 2004), essential tools to develop
to succeed in football (Toering et al., 2011). Self-regulation consist of 6 aspects:
planning, self-monitoring, evaluation, reflection, effort and self-efficacy (Toering
et al., 2009). Research has continual revealed that in football, certain children
are overlooked or not given opportunities due to their age (Brewer, Van Raalte
and Linder, 1993; Cobley, Schorer and Baker, 2008; Delorme, Boiche and
Respaud, 2009), this has been termed the relative age effect (RAE). It has been
the norm to select athletes who were born early in the chronological year. The
RAE refers to the consequence of age differences between individuals within
the same cohort, either in school or sports teams (Musch and Grondin, 2001).
i.e. a player born in August will be 11 months younger that a player born in
September of the previous year yet still be in the same relative age grouping
(Barnsley, Thompson and Steblsky, 1991). With football being a competitive
and evolving industry (The FA, 2010), developing players that show excellence
in all areas is essential to achieve success. This has made the selection
process for talent development schemes vital. Understanding the impacts
relative age has on player’s psychological development is therefore key.
The reason for this study is that past research has highlighted that early borns
tend to be physically more developed (Baxter-Jones, Eisenmann and Sherar,

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2005), however at this stage there is limited research around the effects of
psychological traits in relation to the relative age affect (Esteve and Drobnic,
2008). Studies have indicated that there could be an effect on player’s levels of
psychological development as a result of the relative age effect (Helsen,
Starkes and Van Wincke, 2000), although to limited extent. Helsen, Starkes and
Van Wincke (2000) highlighted that height and weight do not reflect the
development of effective skill development, and have suggested positive skill
development may link to the psychological state of the player. The only current
research around self-regulatory skill development, looks at the development of
these traits in elite international youth footballers in the Netherlands aged 12-
17 years of age (Toering et al., 2011), a comparison between early and later
born players was not made. Additionally, alongside Toering et al.’s (2011)
paper, previous research in the subject area has predominantly been around
different countries. (Glamser & Vincent, 2006; Jimenez and Pain, 2008;
Delorme, Boiche and Respaud, 2009), and infrequently been specified around
the English game (Musch and Grondin, 2001). The lack of research in the
English game, and more specifically around the development of psychological
traits (Mujika et al., 2009; Cobley et al., 2009; Till et al., 2015), identified an
area for future research. The study therefore aims to inform and contribute to
provide an improvement of training programmes and practices by making
coaches aware of psychological differences in ten to eleven year old players.
Coaches will have the opportunity to reflect on personal practice and make the
appropriate modifications and adaptions to ensure continual holistic
development of the participants. Furthermore the results will provide
understanding around skills that are not seen in appearance, allowing for
appropriate adaptions to talent identification models that will lead to change in
how talent is spotted. The benefit of the potential to improve talent identification
is a huge benefit to the coach (Carling et al., 2009; Cobley et al., 2008).
To summarise, the introduction has informed the following:
 Previous studies have identified a tendency to select early born players,
over there late born peers

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 Research suggests that a players psychological development could be
affected by the quartile they are born in
 Limited research has been conducted around the effect of RAE on the
development of self-regulatory skills
 The only current study focusing on self-regulatory skills, looks at older
aged elite international players in the Netherlands

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Literature Review:
This section reviews previous research, in relation to the relative age effect,
showing specificity around topics linked to the aims of the study to understand
the outcome of the effect.
What is the Relative Age effect?
Children are categorised into selection periods, based on their age throughout
their life in lower level education, this is to provide a ‘level playing field’ for
individuals at different levels of development (Baker, Schorer and Cobley,
2010). In England, this ranges from Nursery to Year 11. The English school
year starts on September 1st and runs through to children born on August 31st
(Kent County Council, 2016). The by-product of this age grouping in Education,
is local, national and international sports organisations adopt this age grouping
for teams, clubs and events. Therefore participants born immediately after this
selection date (I.e., September 5th) are almost 12 months more developed than
a cohort member with a birthday on August 29th (Baker, Schorer and Cobley,
2010).
Although the purpose of the chronological age selection is for positive intentions
(Barnsley, Thompson & Barnsley, 1985); attempting to keep children that
should demonstrate similar development (E.g. cognitive and biological)
together; there is increasing research that demonstrates inequalities among
cohort members (Musch and Grondin, 2001; Schorer et al., 2008).See figure
1.0 where Grondlin, Deschaies and Nault (1984) first identified an unequal birth
distribution in all stages of Canadian ice-hockey and volleyball. Further
research has identified the distribution within exams, assessments and talent
identification systems (Baker, Schorer and Cobley, 2010).
Studies assessing the relative age effect usually consider how age differences
in annual age grouping (Barnsley, Thompson & Barnsley, 1985) affect

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developmental outcomes. i.e, talent identification and development. These are
often in terms of biological development in post-pubescent athletes.
Figure 1.0: Distribution of athletes (percentage) per quartile (n = 189,411).
What ages are affected by the Relative Age effect?
Previous research has been conducted around the relative age effect in
England (Simmons and Paull, 2001). The research identified inequalities in
English football academies. The under 15 and under 16 age groups showed
large differences in participant numbers between early and late born players.
The early born players within the cohorts consisted of 58.7%, while the later
born players only consisted of 12.7% of players in the academies (Simmons
and Paull, 2001). See table 1.2. A weakness of the study however is the setting
for the research. The study analyses under 15’s and under 16’s in academies.
This is a crucial age, as academies have to decide to either offer the player a
pro-contract or release the player at under 16’s (The Football League, 2014).
Cobley et al., (2009) found that coach’s decisions, were largely biased towards
the early born players in a cohort, due to showing greater performance levels.
This could be used to explain the findings of the large population of early born
players, as coaches may lean towards the older players, because in general
they show greater maturity and higher performance levels and at that time they

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may believe that they offer greater potential to receive a professional contract
(Helsen et al., 2000).
Jimenez and Pain’s (2008) research supports this current question of the study.
The research shows the effect advances through younger age groupings
through to an adult setting. The results of the study showed that within an
average cohort, players born in the first quartile of an annual age grouping
consisted of 45% of the population, whereas players born in the final quartile,
only consisted of 15% of the population. This demonstrates that throughout an
average cohort the difference between early and later born players is 30% in
favour of the older players. Research carried out by Williams and Reilly (2000);
Thompson (2012) support this suggestion that the effect continues throughout
all the age categories. Thompson (2012) claims that the number of participants
in under 9’s, 10’s and 11’s cohorts in academy teams decrease as progression
moves through each quartile. Thompson’s (2012) research identified that
players born in quartile one comprised of 47.8% of the sum of players, with this
decreasing to 7.9% for players born in quartile 4. See table 1.1 for further
details.
There are certain draw backs to these research studies however. The
environmental influences on the study needs to be considered. Jimenez and
Pain’s (2008) research is conducted in Spain, the environment and
surroundings of the study could have an impact on selection or participation,
due to talent identification being focused upon individuals technique, which
could foster biased results. Additionally all studies (Jimenez and Pain, 2008;

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Thompson, 2012; Williams, 2009) were carried out in intense talent
development environments. Clubs are experiencing pressure to identify and
develop talent early (Stratton et al., 2004), which could again impact the
reliability of the study, with selection being the prominent focus.
What is affected by the Relative Age effect?
Previous studies have identified various explanations for the bias towards older
players in an annual age grouping (Delorme and Raspaud, 2009: Musch and
Grondin, 2001; Sherar et al., 2007). Children born shortly before a cohort’s
cutoff date suffer from being promoted to higher age groups earlier than their
later born peers (Musch and Grondin, 2001). The older players have therefore
had a longer period to develop and have had opportunities for greater
experience. This correlates with Musch and Grondin’s (2001) research which
suggests that the most likely cause of the effect is early borns superior physical,
cognitive, emotional and motivational development; this is the main suggestion
for the negative cause of the relative age effect. Past research supports this by
highlighting that early borns tend to be physically more developed (Baxter-
Jones, Eisenmann and Sherar, 2005). Carling et al’s., (2009) research supports
this, by explaining that early borns experience advantages in body size and
weight, body fat percentage and skeletal age. See table 1.3. This means that
there are physical differences within characters in the same age grouping
(Malina, Bouchard and Bar-Or, 2004). A drawback to this research design is
data collection was conducted with age groups associated with puberty,
meaning rates of growth and maturation could be associated with this bias. This
indicates maturation as a significant factor in identification and development of
player, however this does not show effects in age groups 11 and under, which
Helsen, Starkes and Van Winckel (2000) found is influenced by the relative age
effect.
Schorer et al’s., (2008) research conflicts with initial suggestions that
physiological differences are the cause of the relative age effect. The study
examined later born players ability to endure in a system which favours early

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born participants in the same cohort. This was to understand if there was any
maturational, physical or technical advantages. The sample (n=140) were
selected from a German National handball team. Results showed that a relative
age effect was present in the sample, however no differences between early
and later born players were identified in terms of maturation (i.e, height/weight)
or technical skills (Table 1.4). This also referred to the clubs ‘All-star’ team, as
there was no difference between players selected and not selected. Schorer et
al’s., (2008) study demonstrates that differences between early and later born
players in the same cohort are not due to technical skills or physical
development. The difference could be due to the players’ psychological
differences. This is supported by other studies which indicated that there could
be an effect on player’s levels of psychological development as a result of the
relative age effect (Helsen, Starkes and Van Wincke, 2000), although to limited
extent. Yet at this stage there is limited research around the effects of
psychological traits in relation to the relative age affect (Esteve and Drobnic,
2008).
What psychological characteristics do development models explain
under 11’s possess?
Psychological processes can impact the progression to elite performance, this
is widely recognised across areas of expertise (Abbot et al., 2007). It is
becoming widely accepted that, for an individual to excel in performance
domain, they need to possess strong psychological characteristics, such as
commitment and goal setting (Ericsson, Krampe and Tesch-Romer, 1993). At
this stage it is unclear as to what specifically these characteristics are. Previous
research has attempted to identify certain psychological personality
characteristics young people possess, however this body of research was
inconclusive due to the effect environment and surroundings play in their
development (Abbot et al., 2007).
Merging The FA 4 Corner Model (2014), Harewood’s 5C Model (2008) and
MacNamara, Button and Collins (2010a & 2010b) ‘The Role of Psychological
Characteristics’ research, identifies a number of desired psychological

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attributes: creativity, commitment, resistances, confidence, communication,
concentration, control creativity and positive motivation. Harewood (2005)
discusses the need for developing confidence in youths, to generate a
readiness to be creative and controlled when errors are made (Harewood,
2008). This is supported by Deci et al., (1991) whose research demonstrates
the need to develop confidence in athletes, which ultimately leads to competent
players. Additionally MacNamara et al., (2010) and Harewood (2008) explain
that concentration and commitment need to be cherished at under 11’s, to
ensure long-term participation and positive-development take place. The
development of a growth-mindset in participants is especially needed, to allow
for personal growth and learning (Dweck, 2006). Dweck (2006, p. 57) states,
“In our study, only the students with fixed mindset showed decline. They
showed an immediate drop-off in grades, and slowly but surely did worse
and worse over the two years. The students with the growth mindset
showed an increase in their grades over the two years”
Kohlberg (1973) supports this by explaining that young players lie in the pre-
conventional stage of moral development. This can be utilised to understand
the motives of individuals. The pre-conventional stage is split into two groups:
punishment/obedience and rewards (Kohlberg, 1973). Dweck (2006) advises
the development of a growth mind-set to ensure continual personal
development, with the development of a growth-mindset being linked with to
continuation in sport (McMorris and Hale, 2006). The drawbacks to this study,
relate to the research on personality characteristics, which may have been
unsuccessful in considering the psychological issues that impact in the
adaptation of potential to achieve (Abbot et al., 2007). Although, studies that
have a focus on the usage of psychological behaviours, as opposed to
personality characteristics, have successfully identified a link between
psychological characteristics and performance (Smith, 1997; Thomas, Murphy
and Hardy, 1999). Therefore, measuring behavioural characteristics from a
sample, may provide understanding to the effects of the age grouping on
player’s psychological development.

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Orlick and Partington’s (1988) concept of “Psychological Characteristics for
Developing Excellence” (PCDE’s) can be used to explain the importance
psycho-behavioural skills play in a child’s development. The skills relate to
characteristics that will enhance an athlete’s performance in training and
education (Gould, Damarjian and Medbery, 1999), a range of psycho-
behavioural traits, such as imagery and performance evaluation, have been
linked to elite performance (MacNamara, Button and Collins, 2010a & 2010b;
McAffrey and Orlick, 1989). Giving young athletes the psychological tools to
deal with their performance, to reflect and improve is another useful ability for
development. Talbot-Honeck and Orlick (1998) and McDonald, Orlick and Letts’
(1995) research has highlighted goal-setting, performance evaluation and self-
reinforcement, self-awareness, imagery, planning, commitment, role clarity,
focus and evaluating/coping with pressure as the key psycho-behavioural
characteristics to nurture. See figure 1.1. An immediate critique of this research
however is the age of the study, performance domains are ever evolving with
the demands on athletes increasing (The FA, 2010), and data is likely to be
dated. Recent research by Abbot et al., (2007) has further supported this belief.
The study identifies psycho-behavioural strategies and processes that have
been successful by consistent world-class performers across a range of
achievement environments (Abbot, et al., 2007). The study found that the
psycho-behavioural skills shown in figure 1.1, can frequently produce success,
no matter what area of challenge is tested. As highlighted within figure 1.1,
Abbot et al’s., 2007 psycho-behavioural curriculum has highlighted that the
psycho-behavioural traits are developed across three levels:
 Level One: Realisation of Competence and Self-Reinforcement
 Level Two: Begin to Take Responsibility for Own Development
 Level Three: Aspiring to Excellence: Autonomous Development
Achieved

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Although the focus of the studies are around behavioural characteristics in
young athletes, the research fail to account for how these psycho-behavioural
skills are effectively employed. An additional constraint is the lack of correlation
between the psycho-behavioural skills identified and the psychological
demands of football. Therefore measuring performance levels of these
psychological characteristics, would not be beneficial in understanding how
annual age grouping impacts the performance domain.
What are self-regulatory skills?
Research has highlighted psycho-behavioural skills as a performance
enhancing tool for athletes in training and education (Ashworth and Heyndels,
2007; Zimmerman, 2006; Gould, Damarjian and Medbery, 1999). Preceding
studies have demonstrated a bias towards understanding the effects of psycho-
behavioural skills on the relative age effect (Martin et al., 2004). Toering et al.,
(2011) supports this by explaining that self-regulatory skills allow for affective
Figure 1.1: Abbot et al’s., (2007) Three levels of psycho-behavioural skill
development

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evaluation of youth football players psycho-behavioural skills, due to the
correlation with the demands of the sport.
Self-regulatory skills contrast this belief however, self-regulatory skills, are the
process of controlling one’s thoughts, feelings and actions (Baumeister and
Vohs, 2004; Clearly and Zimmerman, 2001). Zimmerman (2008) explains that
self-regulation of learning refers to self-initiated strategies that allow players to
convert their psychological attributes into performance enhancing skills. The
development of efficient self-regulation have been suggested to effectively
assist in the learning process (Zimmerman, 2006), and lead to the development
of potential. In a sporting context, expert athletes have shown greater self-
regulation than their amateur counter-parts, with poor application of self-
regulatory skills being found as a potential performance reducer (Anshel and
Porter, 1996; Jordet, 2009a, 2009b). Self-regulation is therefore an essential
tool for future athletes. This is supported by documents produced by the English
Football Association (2010 & 2014), describing the desirable psycho-
behavioural skills required for ‘The Future England Player’. The research
highlights the importance of developing efficient and prominent psycho-
behavioural skills that can be transferred to the game. The FA Future Game
(2010) document explains that a future England player needs to able to
mentally plan and constantly analyse and monitor their performance and the
oppositions. While showing commitment and a desire even in difficult situations,
as they have the belief they will be able to change the situation. The future
player will also demonstrate appropriate evaluation skills, allowing them to
critically analyse and reflect on their personal performance. The psycho-
behavioural skills discussed by the Future Game (2010) report relate directly to
self-regulatory skills (Toering et al., 2011). Examples of this are, The Future
Game document (2010) expects the future player to demonstrate reflective
practice, planning and analysis of performance. These are all skills self-
regulation measures.

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Is there an advantage in being younger?
Past studies have identified a favoritism to select the relatively older players
over their younger peers in an age grouping (Cobley, Schorer and Baker, 2008;
Till et al., 2010; Mujika et al., 2007). Although (Ashworth and Heyndels’, 2007)
argues against this belief, explaining that often if later born players are
successful in progressing to elite status they can often be advantaged. In
Ashworth and Heyndels’ (2007) study they explain that participants born in the
final quartile of a cohort, earned higher wages than earlier born players in the
age grouping. The study investigated football players during the German 97-98
and 98-99 leagues. The results showed that players born early in a selection
year earned 2 million, compared to their later born counter-parts who earned
close to 2.8 million. Ashworth and Heyndels (2007) suggested the cause of the
results were down to psycho-behavioural skills developed by the later born
players while training alongside or against their relatively older peers who were
often more physically and cognitively developed.
Are self-regulatory skills affected by the Relative age effect?
While past studies have highlighted a tendency to favour early borns compared
to later born participants in annual age groupings, when there is a focus around
physical and cognitive development (Cobley, Schorer and Baker, 2008; Till et
al., 2010; Mujika et al., 2007), very few studies have linked self-regulatory trait
development to the relative age effect (Esteve and Drobnic, 2008). Studies
have however indicated that there could be an effect on player’s levels of
psycho-behavioural skill development as a result of the relative age effect
(Helsen, Starkes and Van Wincke, 2000).
Research conducted by Toering et al., (2011) investigated the relationship
between self-regulated learning and the performance level of 256 elite youth
football players aged 12 to 17 years. Participants were selected from national
and international levels; n = 76 and n = 178 respectively. Player’s practice and
match time were equal. Analysis shown in table 1.5, that participants

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demonstrating high levels of self-regulation tended to be the players playing at
international level. These players were also calculated as being relatively
younger compared to the national level athletes. The study continued, by
identifying ‘reflection’ as the key predictor between international and national
level participants, suggesting that participants had a 1.69 times greater chance
of belonging to the international group for every point they scored on reflection
(Table 1.6).
The study demonstrates, that development of self-regulatory skills, is affected
by the relative age effect. The sample was selected from the top 1% of elite
players in Holland (Toering et al., 2009), consisting of 0.4% of the ‘best’ players
in their age category, these were players scouted by the Royal Netherlands
Football Association (KNVB) to represent their district or the country. While the
following 0.6% of players were playing in elite professional youth academies.
This sample fails to account for the 99.04% of other players within the selected
age bracket that participate in the game. Additionally the study was carried out
in an ‘intense’ talent development focused environment, which could again
impact the reliability of the study, with selection being the prominent focus.
However this could explain the findings. Self-regulatory skills have been
identified as being essential skills for aspiring elite football players (Toering et
al., 2011), this may suggest why international players tended to demonstrate
greater performance levels of the psycho-behavioural skills, as playing at a
higher standard may inspire, educate and require the players to demonstrate
self-regulatory skills.
An additional critique is the age of the study. The game is ever evolving and the
demands on athletes are increasing (The FA, 2010), players all at levels are
required to demonstrate greater performance levels in all areas, suggesting the
data could be dated. Furthermore the environmental influences on the study is
a consideration. Toering et al’s., (2011) research is conducted in Holland, the
environment and surroundings of the study could have an impact on selection
or participation, which could foster biased results.

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Schorer et al., (2008)
Components of test Selected for ‘All-star’
Not selected for ‘All-
star’
Throw Accuracy 3.10 3.35
Throw Speed 1.48 1.51
Test Duration 4.39 4.46
Table 1.4: Players across the birth quartiles were similar in terms of
technical skill

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Toering et al., (2011)
International
Level (n=76)
National Level
(n=178)
Effect Size
Planning
(Range 1-4)
2.63 2.58 0.09
Self-Monitoring
(Range 1-4)
2.76 2.69 0.14
Evaluation
(Range 1-5)
3.61 3.53 0.13
Reflection
(Range 1-5)
4.25 4.06 0.31
Effort
(Range 1-4)
3.07 3.00 0.14
Self-Efficacy
(Range 1-4)
2.90 2.87 0,,07
Toering et al., (2011)
β(SE) OR
95% CI of
OR
p
Reflection)
0.52(0.25) 1.69 1.04-2.75 0.04
Relative Age
0.78(0.34) 2.19 1.12-4.27 0.02
Chronological
Age
-0.38(0.16) 0.68 0.50-0.93 0.02
Practice hours
per week
0.22(0.15) 1.25 0.92-1.68 0.15
Literature review conclusion -
To summarise, the literature review has informed the following:
 The RAE is the effect age grouping has upon developmental outcomes
depending on the month in which a player is born.
 Thompson (2012) suggests that the effect is present in age groupings
as young as under 9’s.
Table 1.5: Self-regulation aspects of International Level and National level
Youth Soccer Players
Table 1.5: Toering and colleagues identified reflection as the key predictor

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 The effect has proven to cause a bias to relatively older players, the
cause being the player’s physical differences. Although at this stage
there is limited evidence that older players are psychologically superior
(Esteve and Drobnic, 2008).
 Studies have suggested that players need to develop psycho-
behavioural traits to access elite performance, with these skills being
linked to experts in achievement environments.
 Self-regulation are a collection of psycho-behavioural skills that allow for
performance increases. The skills allows individuals to control one’s
thoughts, feelings and actions (Baumeister and Vohs, 2004).
 The RAE, effects the development of self-regulatory skills (Toering et al.,
2011), however this study used a sample of elite international athletes
which fails to account for the larger population. Conclusive research on
10-11 year old English football players is therefore required to
understand how self-regulation is effected by the relative age effect.

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Methodology:
The Sample –
The research project involved human participants to gather primary data to
identify whether earlier born participants develop a higher level of self-
regulatory psychological skills compared to their later born counter-parts in a
relative age grouping. The research included a sum of 32 youth football players,
aged between ten and eleven years of age playing at grassroots level in
England. The players were selected from FA Skill Centre’s that are run by FA
Youth qualified coaches, in the West Riding region. The reason for this
suggested participant sample is that there is limited research into participants
at football development Centre’s and grassroots clubs in England at this age
and stage of development, especially when concentrating on the development
of psychological traits. Furthermore utilising a well-structured and safe
environment, such as FA Skill Centre sessions, provides both participant and
coaches with a safe environment to conduct the research project. There was
no form of selection method used to identify the players for the study, with all
attendee’s aged ten to eleven elected to participate, with recruitment being
conducted through word of mouth.
Data Collection –
The project adopts a mixed method design to collect the data. The two forms
of data collection used are qualitative and quantitative.
Qualitative research:
Qualitative research involves research that is based on individual’s views and
opinions, without using a measure but describes characteristics (Thomas,
2003).
Quantitative research:
Whereas quantitative studies comprises of reflecting on data to understand the
volumes of characteristics portrayed (Thomas, 2003). Quantitative research
was gathered through primary research, using qualitative methods. The FA

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Skills team in the West Riding and club team managers were contacted through
a letter regarding participation in the study. Included in the letter was details of
what the research involved and the ethical considerations. The information was
directed to the projects intended gate keeper, who were the West Riding FA
Skills team leader, and grassroots team managers. (Appendix 4)
The benefit of this data collection is that this methodological approach
encourages the sample to 'reflect' what suits the participants 'normal'
environmental requirements (Gratton and Jones, 2010). The sample group are
all participants who participated (at the time of data collection) in FA Skill
Centre’s in West Yorkshire and in local grassroot teams. The researcher has
been working with the sample groups for the past 12 months, providing the
researcher with the ability to create a safe and normal environment for the
participants to operate in comfortably and confidently. The chosen players,
were selected as a result of their accessibility. Participants that were selected
were based on accessibility and availability. This was a result of time,
convenience and cost preventing research further afield. Before the data-
collection process, participants and their guardians were asked review and
complete the necessary information required for the project. (Appendix 2, 3)
Procedure -
The participants were assigned to a category, based upon their month of birth.
Sub group one consisted of 15 participants born in either quartile one
(September, October or November) or quartile two (December, January or
February) of a relative age grouping. The second sub group consisted of 17
participants born in either quartile three (March, April or May) or quartile four
(June, July or August) of a relative age grouping.
To collect the data from the participants, structured face to face questionnaires
were used. Questionnaires are simple tools to collect data from large sample
groups, with minimal bias (Gratton and Jones, 2010). The questionnaire was
an adopted version of Toering et al.'s (2011) questionnaire, used in a recent
study on elite youth football players in the Netherlands (Toering et al., 2011).

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Adopting a previously used, validated, and ethical questionnaire from a
previous study removes any bias from the data-collection and increases
trustworthiness (Gratton and Jones, 2010). The questions were adapted to
communicate in the participants own language and to add greater reliability to
the study (Johnson and Christensen, 2011). This was to engage the
participants in effective self-reflection (McCusker and Gunaydin, 2015), by
asking players to rate themselves against personal qualities. Additionally
Toering's et al., (2011) questionnaire removes any psychological harm, by
querying opinions and personal beliefs, this removes any potential for 3rd party
views to influence participants. (Appendix 1)
The questionnaires were conducted in the players ‘normal environment’, this
was achieved by the researcher asking the players to complete the
questionnaire one by one during the session. Although the presence of the
researcher can affect the honesty of responses (Thomas, 2003) the researcher
was able to create a safe and normal environment for the participants to operate
in comfortably and confidently, because of their past experience coaching the
participants, this can only engender reliability.
Structured scale questionnaires increase the reliability of the study (McCusker
and Gunaydin, 2015). The purpose of this study is to identify if early borns
possess stronger self-regulatory traits than their later born counter parts, the
participants could therefore be distracted into different areas if open question
were included (Gratton and Jones, 2010). Additionally a scale questionnaire
was used to answer the question around ‘what’ of a phenomenon (McCusker
and Gunaydin, 2015), by aiming to understand how the individuals perceive
their capabilities around self-regulatory skills (McCusker and Gunaydin, 2015).
An interview was not adopted because of lack of anonymity and ill effects
surrounding ethical considerations on the study (Johnson and Christensen,
2011). Questionnaires counter this as they are totally confidential and only seek
the month in which the participants is born, with no further data required.
Therefore there are no additional risks to participants which emerge from the
study other than what they are used to experiencing in their day to day lives.

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Data Analysis –
Analysing the strength of traits within the participants, was conducted by
splitting data into the categories of early borns and late borns, and based upon
month participants were born. The sub-groups were; September - November,
December - February, March - May and June - August; the groupings had been
adapted a past study’s (Cote et al., 2006), which supports reliability. Answers
were then coded to produce quantitative data, for analysis. The reason for
adopting a quantitative data method for data analysis, is the increased
efficiency in analysis and comparison of data in testing the hypothesis
(McCusker and Gunaydin, 2015). The statistics will then show in which category
participants possess the most prominent level of self-regulatory skills.
Percentages of each categories mean score were calculated, to provide a
statistic which would allow for comparison. IBM SPSS Statistics Viewer, was
the statistical analysis tool used to generate the results in the study.
The data collected through questionnaire had a subscale of planning, self-
monitoring, effort and self-efficacy, which were scored on a 4 point Likert rating
scale: (1) Almost never to (4) Almost always, as within Toering et al's (2011)
study. While the subscales of evaluation and reflection were scored on a 5-
point average Likert. Evaluation will range from (1) never to (5) always and
reflection will range from (1) strongly agree to (5) strongly disagree. Prior to
conducting data analysis, reflection scores were inverted to ensure
correspondence with the scores on the other five subscales. Once this was
conducted results were collected for analysis. Utilising the questionnaire in this
way, allowed for the assessment of each aspect of self-regulation to be
considered as individual variables for each participant.
Logistic regression analysis –
A logistic regression analysis was completed to establish the self-regulation
aspects that were associated with performance levels (Toering et al., 2011).
With the study aiming to understand the effects of the relative age effect on self-
regulation, a logistic binary regression was conducted to attempt to estimate

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whether a participant was born in the first or second half of an academic year,
based upon their self-regulation score
Ethical Considerations –
Club coaches, parents and participants (assent forms) completed the
appropriate consent forms to agree to participation. Data-collection did not start
until parent/guardian and participants had agreed to their involvement
(Appendix 2, 3, 4). The procedures were in accordance with requirements of
the Research Ethics Committee at Leeds Beckett University.

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Results
The research project aimed to start to educate practitioners of the effects
relative age grouping has upon the development of self-regulation in 10-11 year
old football players.
Table 2.0 below displays the self-regulation scores for each sub-category for
participants born in quartile one. The results demonstrate that on average,
participants born in quartile one possess more prominent evaluation skills than
other self-regulatory skills, yet effort is seen to be the lowest scoring category
(Table 2.1).

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Participants from quartile two showed varying scores between the sub-
categories of self-regulation seen on Table 2.2. Different to participants in
quartile one the results highlight reflection as the highest scoring self-regulatory
skill and self-monitoring to have the lowest score. (Table 2.3).

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The following table 2.4 represents the average score for participants born in
quartile one and two, representing the first half of the academic year. Reflection
and evaluation were found to be the most prominent skills and effort as the
lowest scoring skill.

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Table 2.5 illustrates the self-regulation scores again dependent on the sub-
category for quartile three individuals. Findings in table 2.6 demonstrate that
similar to quartile one and two, reflection and evaluation are higher scoring
skills. However, for this group of participants, self-efficacy outlines the skill
scoring the lowest points.

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In tables 2.7 and 2.8, quartile four participants are represented with regards to
the sub-categories of skill. Again, reflection is shown to be the highest scoring
category (3.92) while self-monitoring, similar to quartile 2, has the lowest score
(2.9). Though it is evident that overall, quartile 4 participants develop superior
skills in every aspect of self-regulation compared to their quartile 1 peers.

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Reflection and evaluation were again found to be the most prominent skills for
participant in quartile’s 3 and 4 combined, with scores of (3.84) and (3.67)
respectively. Self-monitoring was once more recognised as the least prominent
aspect of self-regulation in later born participants skill set. This is represented
in table 2.9 below, which represents the average score for participants born in
quartile three and four.

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The results shown in Table 3.0 draw on the two halves of the academic year,
providing a comparison of the skills that contribute to self-regulation. Looking
at these results, both the first and second half participants score the highest for
reflection (3.4 and 3.84 respectively), yet the first half scores the lowest in effort
(2.81) and the second half score the lowest in self-monitoring (3.09).

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Logistic binary regression –
A logistic regression analysis was completed to establish the self-regulation
aspects that were associated with performance levels (Toering et al., 2011).
With the study aiming to understand the effects of the relative age effect on self-
regulation, a logistic binary regression was conducted to attempt to estimate
whether a participant was born in the first or second half of an academic year,
based upon their self-regulation score. The procedure involved 5 steps: a)
identifying the most appropriate model to analyse: indicating self-monitoring
and effort as the key model (Table 3.1) b) rerunning of the data, c) reviewing
results for residuals to understand influential cases, outliers, Cook’s distance
leverage values and DFBeta values, d) checking the variables against linearity
of the logits: revealing that the expectation of linearity was met, e) testing for
multicollinearity: tolerance and VIF statistics determined no multicollinearity
issues. Quartile of birth were included as the categorical variable, with first and
second halves of the year as reference categories, with the six aspects of self-

41 | P a g e
regulation included as the independent variables. The logistic regression
analysis indicated that the self-regulation aspects of ‘self-monitoring’ and ‘effort’
as the best predictors for performance. The odds ratio specified that players
had a 2.7 time’s greater chance to belong to the second half of the year group,
for each point they scored on self-monitoring and effort (Table 3.2).
Output 3.1 shows the overall summary statistics for the model. ‘Self-monitoring’
and ‘effort’ were classified as the best predictors for performance. These
aspects of self-regulation were selected as a cause of the change in chi-square
statistics between the previous models. The chi-square informs the researcher
on the significant improvement in the model (Field, 2013). The model yields a
chi square of 6.190, which is highly significant (p<0.05), p = 0.013 (Table 3.1).
This is supported by table 3.3, which shows the Wald statistic as 4.257, with
the significance of the factor being 0.039. This is significantly different to zero,
the assumption is that ‘effort’ is making a significant contribution to the
prediction of the outcome.
The beta values establish the probability that a case falls into a certain category
(Field, 2013). The β values for other aspects of self-regulation did not change
significantly, consequently they were not measured, as these factors did not
affect the affiliation between the self-regulation scores and month of birth.
Participants born in the latter half of the sample year, were more likely to
possess greater self-regulation skills (Figure 1.0). Conducting a Hosmer and
Lemeshow Goodness-of-Fit assessment exposed that the model fitted the data,
χ2 (n = 32) = 6.19, P = .0.013. The Nagelkerke R2 showed that the variance
that the model explained was 12.1%
Though the highest scoring sub-categories were rather consistent across the
four quartiles, being either evaluation or reflection, after completing the logistic
binary regression analysis it was found that the key determinants for whether
the participant belonged to the second half of the year group were down to self-
monitoring and effort. Coincidentally, these sub-skills were highlighted as the
lowest scoring skills for quartiles one, two and four (effort was

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Table 3.3: Wald statistic demonstrates that effort is a significant factor to
determine the month of birth of a participant in the sample.

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Figure 1.2: Histogram shows, that participants who scored higher in terms of
self-regulation tended to belong to the second half of a relative age grouping

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Discussion
Principle findings -
The study aimed to examine the influence relative age grouping has upon ten
to eleven year olds development of self-regulatory skills. The current study is
unique in nature with a focus around amateur league players. The research has
offered original findings that have the potential to contribute to data already in
the field of research and assist in the reduction of the relative age effect.
Self-regulation of learning, refers to an integrated process that makes it
possible to transfer cognitive skills into performance enhancing skills
(Zimmerman, 2008). In regards to sport, self-regulation has been shown to
enhance performance and is readily associated with elite performers. It was
therefore the hypothesis of this study that early born athletes would possess
greater self-regulation due to experiencing more opportunities to regulate their
learning. The research presented highlights that the relative age effect, is
influential in ten to eleven year old participants, in regards to their development
of self-regulation. While the current study consists of comparable findings from
previous studies, on the effects of relative age on self-regulation in football (e.g.
Toering et al., 2009; Toering et al., 2011).
The purpose of this study was to assess the level of self-regulation
development in ten to eleven year old football participants in English football,
between early born and later born participants. The research presented,
highlights that the month a player is born in has significant effects upon their
ability to develop more efficient and prominent self-regulatory skills (Table 3.0;
Figure 1.1). Results highlighted that on average relatively younger participants
tended to score higher in each component of the self-regulation questionnaire
than their early born peers (Figure 3.0). The logistic regression analysis went
on to show that higher self-monitoring and effort scores, tended to link with a
greater chance of the player belonging to the second half of an academic year
(Table 3.2).

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Limitation of the study -
The study is not without its limitations. Due to the aim of study being to
investigate the self-regulatory skills of ten to eleven year old football players in
England, a previously used self-reported instrument was adopted. Self-reported
questionnaires are widely used in sport psychology, yet the results should not
be considered to be definite. Self-reported questionnaires, tend to cause bias
to the socially desirable responses (Young and Starkes, 2006), i.e, the less
mature participants may answer the ‘most desirable’ response. Additionally the
validity of results, requires participants to precisely report their levels of
cognition (Nisbett and Wilson, 1977).
The present study emphasises differences between relatively younger and
older participants, with results indicating significant differences in all aspects of
self-regulation. A limitation, nonetheless of the study relates to the environment
the study was conducted in, and the studies inability to control participants
environment. The study was executed in ‘upper-class’ regions of West
Yorkshire. Stereotypically, children brought up within more affluent areas, tend
to have more experiences and opportunities in which self-regulation can be
matured and refined (Gov., 2016). The results of this study, support the concept
that relatively younger participants demonstrate greater self-regulation in more
affluent regions, although it is not yet clear to whether this finding continues into
less affluent areas. Furthermore, the study fails to understand the effects of
player’s immediate socio-cultural influences, such as family. Nakata and
Sakamoto (2013) indicated that socio-cultural factors had a significant influence
upon player’s development. It could therefore be suggested that differences
between groups could be a resultant of their immediate environment.
A final short-coming of the study, is small sample size. The sample fails to
represent the population of ten to eleven year olds that regularly participant in
football in the West Yorkshire region. This study should be repeated to include
more participants, this would improve the reliability of the information collected.

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Comparisons and differences with past studies –
The current research aimed to provide contribution to the growing research into
the impact and consequences of the RAE. The study identifies that participants
psycho-behavioural development is affected by their month of birth. This
corresponds with previous studies which suggest the RAE has the potential to
effect a player’s psychological development, with bias towards the relatively
older player (e.g. Helsen, Starkes and Van Wincke, 2000; Esteve and Drobnic,
2008). The results, contest this hypothesis however, concluding that relatively
younger participants on average possessed more efficient self-regulation of
learning.
Previous research has highlighted the RAE as being present as young as under
9’s level, with physique being labeled the main cause (Thompson, 2012; Cobley
et al., 2009). This study therefore aimed to understand if player’s self-regulation
was affected by age grouping. The present research demonstrates that as the
quartiles of birth progress through a relative age, the participant’s self-
regulation scores increase (Table 3.0; Figure 1.2). Players born earliest within
a selection period achieved scores of 2.78 planning, 2.8 self-monitoring, 2.59
effort, 2.84 self-efficacy, 3.15 evaluation and 3.1 reflection (Table 2.1). This
progressed to scores of 3.04 planning, 2.9 self-monitoring, 3.15 effort, 3.16 self-
efficacy, 3.34 evaluation and 3.92 reflection from players born in quartile 4
(Table 2.8). This demonstrates an increase in scores as the age of participants
decrease. This current research, supports previous research findings (e.g.
Toering et al., 2011), in that results show that relatively younger participants
tend to possess superior self-regulation to their early born peers (Table 3.0).
Toering et al.,’s (2011) investigation into the relationship between self-
regulation in learning and performance between international and national level
players, again proves that this is the case. The international level group were
relatively younger, but results still indicated greater development of self-
regulation compared to the athletes at national level, demonstrating that the
relatively younger international athletes posed more efficient reflection skills
than their older national level peers (Toering et al., 2011). This provides support

48 | P a g e
to the evidence the current study displays, by identifying that relatively younger
players developed superior self-regulator skills (Table 3.0).
Possible reasoning for the association between self-regulated learning and the
RAE is that later born participants scored higher in self-regulation due to the
need to compensate for their lower technical and physical capabilities. It is
widely accepted that children, adolescents and adults develop at different rates;
with this fluctuating from one domain to another (Lloyd and Oliver, 2012; The
FA Future Game, 2010). In performance domains that are physically and
technically demanding, early borns tend to have an advantage over their
younger peers due to showing superiority in physical and technical
development (Musch and Grodin, 2001; Baxter-Jones, Eisenmann and Sherar,
2005). Relatively younger participants therefore struggle to achieve success
when competing against their older peers, requiring them to compensate in
other domains (Abbott et al., 2007). This is supported by the research findings
which indicate effort and self-monitoring as key determinants, suggesting
compensation is occurring so the individuals can achieve success with lower
physical attributes in this sample group. Ericsson, Krampe and Tesch-Romer’s
(1993) research further complements this. Their holistic development of
children research, showed that early born participants tended to demonstrate
greater physical and technical development, however results also indicated
limited potential in the players psycho-social and pyscho-behavioural skill
development when compared to the older participants. Supporting the research
philosophy that a child is unconsciously improving in other aspects of
development, as a result of the otherwise limited success. Self-regulation skills
being one. Therefore the findings in this research, that prove self-monitoring
and effort to be traits relating to younger participants, suggest that their success
could be enhanced and stimulated more often if the environment initiates the
psycho-social consideration alongside a performance related task.
The study aimed to understand which aspects of self-regulation could predict
the half of the year a participant was born in based on their score in that
component of the self-regulation questionnaire. The study found ‘self-
monitoring’ and ‘effort’ as being the significant aspects to predict a child’s month

49 | P a g e
of birth. Analysis revealed significant differences (p<0.05, p=0.013) between
early and later born scores in self-monitoring and effort (Table 3.1). Showing
that players had 2.7 times greater chance to belong to the second half of an
age grouping for each point they scored on self-monitoring and effort.
Additionally the relatively younger athletes on average developed self-
monitoring and effort to greater significance than their relatively older peers
(Table 3.0). Hong and O’Neil (2000) describe self-monitoring as the ability to
be aware of one’s actions during task execution and explain effort as an
individual’s readiness to achieve an objective. The impact on performance
outcomes could be used to explain these findings. Early borns tend to
experience success; with limited effort and understanding required; against
their later maturing peers due to their development of greater physical and
cognitive capacities. This is in contrast to the relatively younger participants
who require focus on a task, demonstrating understanding and awareness of
body movements to achieve the same levels of success. These findings
challenge Toering et al.,’s (2011) past research studies as reflection was
highlighted as the key indicator. This contradiction could be argued by the
sample groups investigated. Toering et al.,’s (2011) sample was of elite
athletes, playing at international or national level, allowing for the comparison
of homogenous groups meant micro differences would be considered. There is
a potential that minor dissimilarities in reflection could lead to potentially pivotal
benefits between an international and national level player (Abbott et al., 2007).
Whereas the present study evaluates amateur performers, meaning that the
personal characteristics have a wide variation between subjects causing larger
discriminations but also has a wider range between existing literature causing
differing results. This justifies the need for younger participants to exert more
effort and monitor their own performance to reach their potential.
Moreover, the utilisation of a sample of amateur participants justified the
ecological validity (Field, 2013). The analysis of amateur groups, allows for
transferability from one domain to another. Though the research ultimately
outlines the differentiation and rationalisation of skills between age groups, the
whole cohort demonstrates higher abilities with reflection and evaluation which
are important to transfer to other areas at this developing age group. The

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research has the potential to be conveyed to other walks of life which cannot
be said for Toering et al.,’s (2011) research which limits the ability for
practitioners in other domains to transfer the findings. Elite athletes represent
less than 1% of the World’s population (Levett, 2015). This fails to account and
provides limited representation for the ‘average’ person.
A draw-back to this research, nevertheless, is the lack of understanding of how
the results impact upon different performance levels. This is significant in
understanding how raising the performance levels affect the demands on a
player’s self-regulation. Toering et al.,’s (2009, 2011) papers consider the
performance level, and practice hours per week of the participants. This
increases the reliability of the study, as the current study fails to understand
how environment and opportunities affect self-regulatory performance.
Reflection was identified as the main predictor. The standard of competition
could be used to explain the difference between studies. Elite football is ever
evolving, requiring players to make faster and more accurate decisions
(Kannekens, Elferink-Gemser and Visscher, 2009). Reflection has the
capability to help athletes understand situations and past actions (Abernethy,
Thomas and Thomas, 1993). This can be used as another explanation between
the differences between key predictors of self-regulation.
Implications of research findings -
This current research shows that on average relatively younger participants
tended to develop superior self-regulation to their early born peers (Figure 3.0).
Tying this into Simmons and Paull’s (2001) research, which found that the RAE
was present in English football academies, showing that 61% of players in
English football centers’ of excellence were relatively older players, compared
to their younger peers who were underrepresented at 11% of the sum of
players. The study’s findings suggest that football talent identification systems
in England, select players primarily based on experience, growth and
maturation (Helsen, Van Winckel and Williams, 2005). Research conducted by
Musch and Grodin (2001) found that players born in the first half of a relative
age grouping consisted of 70% of elite youth players, though it is stated by

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Ashworth and Heyndels’ (2007) that once later born athletes reach elite level
they tend to earn greater salaries and produce better performances. Adopting
an identification system that only views the ‘shell’ of players, provides limited
information on a player’s holistic adaptability and potential to achieve (Morris,
2000). This is further reinforced by Abbott et al., (2005) that argue talent
identification systems ignore aspects of a player’s development that relate to
potential. This forces the questions to why use talent identification systems that
tend to focus on the physical and technical capabilities of a player.
Psychological processes can impact the progression to elite performance, this
is widely recognised across areas of expertise (Abbot et al., 2007). Toering et
al.,’s (2011) research demonstrates that international level participants tend to
develop superior self-regulatory skills than their national levels peers. The study
also suggests that the international level athletes were relatively younger than
the national level players. Self-regulation in learning, has been suggested to
assist in an individual’s learning and is therefore thought to be associated with
potential (Zimmerman, 1989). This suggests that psycho-behavioural skills
could be an assessment method of potential talent, to understand and measure
a player’s ability to cope during difficult periods of their development (Abbott et
al., 2005). The data has indicated that self-monitoring and effort, are not
affected by the relative age effect, while at the same time assist in the
development of potential and performance. It could therefore be argued for
these reasons that self-monitoring and effort should be the psycho-behavioural
skills used to measure talent. The research consequently proposes that
although physical and technical capabilities are an essential component of an
athlete’s performance, there should be a change in how talent identification
systems classify talent and potential for the future by assessing player’s
psycho-behavioural capabilities.
A concluding implication for coaches working with aspiring football players, is
to ensure their athletes are conscious of the benefits of self-regulation of
learning, in particular effort and self-monitoring. Vygotsky (1973) suggests that
players show vast development, from coaches who inspire them to consider
their attributes and weaknesses, before acting to deal with challenges.

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Recommendations –
Effort and self-monitoring are both psycho-behavioural skills that have the
potential to identify talent. A proposal for future studies is to examine the
connection between effort and self-monitoring at different performance levels.
This has the potential to lead to exploration in relation to the effects effort and
self-monitoring have upon progress in football specific attributes. Aspiring
footballers who demonstrate commitment in practice and games and show self-
monitoring on personal performance may possibly be the players who advance
over time.

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Conclusion:
The primary aim of this study was to investigate differences between ten to
eleven year old grassroot football players in the West Yorkshire region, born in
the first half of a relative age grouping against their peers in the final half of a
relative age grouping, in relation to the development of self-regulatory skills.
The current study’s findings present classification to preceding research that
suggests psycho-behavioural skill development is affected by the relative age
effect (Helsen, Starkes and Van Wincke, 2000; Esteve and Drobnic, 2008). The
results demonstrate significant differences between early and late born athletes
in relation to their development of self-regulation. Athletes possessed a 2.7
times greater chance of belonging to the second half a relative age grouping
for every point they scored on self-monitoring and effort. The study provides
support to suggestions that players born in the later months of a selection
period score higher in terms of self-regulation due to the need to compensate
for their lower capabilities to compete with their relatively older peers. Although
the research contradicts previous research, which shows reflection as the key
predictor, the sample group used in the study is a potential reason for this.
The findings presents informative data that has great value for talent
identification systems and coaches in the field. The current research
demonstrates the need for a change in the way in which potential is recognised,
to account for a player’s long-term development. Assessing a players self-
monitoring and effort attributes is the suggested method. Additionally the
results suggest to coaches, to educate their players on the need to develop
self-regulation of learning in life and in their sporting context.
The project was restricted to the West Yorkshire region, when producing data,
resulting in restricted sample size. This was a result of time, convenience and
cost. Forthcoming research should explore a broader boundary and sample
size, in order to provide a more holistic understanding of the impacts on
grassroots English football,

54 | P a g e
To conclude, the present study identified that on average relatively younger
participants developed more prominent self-regulatory skills than their older
peers.

55 | P a g e
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64 | P a g e
Appendix 1 – Self-regulatory questionnaire
Is there a difference between football players born early in an academic
year compared to players born at the end of an academic year when it
comes to a players mental skills?
Introduction – As part of a piece of work in university, I am looking at what
your opinions and beliefs are around the thinking skills you own. The following
questionnaire will ask you a number of questions. I would like you to tick the
box that best fits your opinion of your own thinking skills. You have to right to
withdraw your questionnaire at any point up until the 14.03.16
Month of birth:………………………………………………………………………
Almost Never Not really Sometimes Almost
Always
‘I determine
how to solve a
problem before
I begin’
‘I think through
in my mind the
steps of a plan I
have to follow’
‘I ask myself
questions about
what a problem
requires me to
do to solve it,
before I do it’
‘I imagine the
parts of a
problem I still
have to
complete’
‘I carefully plan
my course of
action to solve
a problem’
‘I figure out my
goals and what
I need to do to
accomplish
them’
‘I clearly plan
my course of
action to solve
a problem’
‘I develop a
plan for the

65 | P a g e
solution of a
problem’
Always
‘I check how
well I am doing
when I solve a
task’
‘I check my
work while
doing it’
‘While doing a
task, I ask
myself, how
well I am doing’
‘I correct my
errors’
‘I check my
accuracy as I
progress
through a task’
‘I judge the
correctness of
my work’
Always
‘I keep working
even on
difficult tasks’
‘I put forth my
best effort
when
performing
tasks’
‘I concentrate
fully when
doing a task’
‘I don’t give up
even if the task
is hard’
‘I work hard on
a task even if it
is not
important’
‘I work as hard
as possible on
all tasks’
‘I work hard to
do well even if I

66 | P a g e
don’t like a
task’
‘If I’m not really
good at a task I
can make up for
it by working
hard’
‘If I keep
working on a
task, I’ll
eventually
succeed’
‘I am willing to
do extra work
on tasks in
order to learn
more’
Always
‘If I keep
working on a
task, I’ll
eventually
succeed’
‘I know how to
handle
situations I
have not been
in before
because I can
well think of
ways to cope
with things that
are new to me’
‘It is easier for
me to
concentrate on
my goals and to
achieve them’
‘I am confident
that I could deal
quickly and
correctly with
unexpected
events’
‘I remain calm
when facing
difficulties
because I know
many ways to

67 | P a g e
cope with
difficulties’
‘I always
manage to
solve difficult
problems if I try
hard enough’
‘I can solve
most problems
if I invest the
necessary
effort’
‘When I am
confronted with
a problem, I
usually find
several
solutions’
‘No matter
what comes my
way, I’m usually
able to handle
it’
Never Almost
Never
Sometimes Almost
Always
Always
‘I look back
and check if
what I did was
right’
‘I double-
check to make
sure I did it
right’
‘I check to see
if my
calculations
are correct’
‘I look back to
see if I did the
correct
procedures’
‘I check my
work all the
way through
the problem’
‘I look back at
the problem
to see if my
answer makes
sense’

68 | P a g e
‘I stop and
rethink a step
I have already
done’
‘I make sure I
complete
each step’
Strongly
Agree
Agree Unsure Disagree Strongly
Disagree
‘I reappraise
my experience
so I can learn
from them’
‘I try to think
about my
strengths and
weaknesses’
‘I think about
my actions to
see whether I
can improve
them’
‘I think about
my past
experiences to
understand
new ideas’
‘I try to think
about how I
can do things
better next
time’

69 | P a g e
Appendix 2 – Parental information sheet and consent form
Parent/ Guardian Information Sheet - Is there a difference between 10-11
year old participants in grassroots football in the West Yorkshire region, born
in the 1st and 2nd quartile compared participants born in the 3rd and 4th quartile
of a relative age grouping when it comes to the development of self-regulatory
skills?
Principal Investigators James Dunn
Project Start Date November 2015
Email j.dunn9726@student.leedsbeckett.ac.uk
Supervisor Name and
Contact details
Chris Low
Cavendish, 119
C.Low@LeedsBeckett.ac.uk
0113 812 3570
We are writing to you as we would like to offer your child the opportunity to
participate in a project which will compare children’s self-regulatory (psychological
skills) from early and later born participants aged 10-11 years old. To allow the
researchers to compare and consider any differences between early and late born
players.
If you do decide to take part you will be asked to sign a consent form which tells us
that you are happy with what you have read and that you would like to take part.
What are the data collection methods? And what does child have to do?
All testing will be carried out by fully trained members of our research team.
Your child will be asked to complete a short questionnaire around self-regulatory
skills. Self-regulatory skills are skills that allow your child to monitor and control their
own behaviour, emotions or thoughts, and allows for change in your child to
correspond with the demands of the environment. The researcher will ask the
participants to complete the 2-3 minute questionnaire at a convenient point in the
session. The researcher will do this at a time in which your child will not miss any
learning opportunities from the session; and the data-collection process will not take
any more time than you would usually be involved in the session.
The questionnaires will measure your child’s self-regulatory skills through an adopted
version of a previously used and ethical questionnaire. The questionnaire will be
confidential and only seek the month in which your child was born, with no further
data required.
Are there any side effects?
There will be no side effects of the data collection method as your child will be asked
for their opinions and beliefs only, in the questionnaire. Your child will also be
completing their regular exercise schedule as normal.

70 | P a g e
What are the benefits for your child taking part?
If findings suggest a difference between earlier and later born children, the
researcher will discuss the findings from the study with yourself, your child and their
coaches in a feedback session. The researcher will then have the opportunity to
discuss recommendations with coaches, about how to develop the group as a whole.
This will provide coaches with the opportunity to reflect on their coaching and make
any needed chances or adaptions to ensure your child continues to improve as a
player in the long-term.
An additional benefit is that your child will be contributing to the understanding of the
difference between earlier and later born players when it comes to the development
of self-regulatory skills. This means your child will be contributing to findings that
could lead to an improvement of training programmes and practices by making
coaching aware, which could benefit the whole of sport in England.
What if something goes wrong?
Due to the data collection tools used there is unlikely to be anything that will go
wrong. If, however, you would like to speak to someone about the project please
contact James Dunn, the lead researcher.
Will my child’s taking part in this study be kept confidential?
Yes. We would like to share the findings of the project at meetings or in articles.
Before we do this though we will remove any information (such as names) that will
mean your child will not be identified.
What will happen to the results?
Leeds Beckett University like to allow undergraduate students to use the information
for our dissertations. You and your child will be asked for your permission below to
agree to the researcher using your child’s questionnaire results in their dissertation.
if this is the case however.
We also hope to publish the results through conference presentations and scientific
journal articles, if appropriate.
Can my child withdraw from the project?
You can withdraw your child’s data from the project at any time up until the 14.03.16
during the project and you are not expected to provide a reason or explanation.
You can do this by: emailing the researcher, speaking with the researcher or
speaking with the coach of the session.
Who do I contact for further information?
If you have any questions at any time, please feel free to contact me, James Dunn at
j.dunn9726@student.leedsbeckett.ac.uk.
Jamie Poolton at J.Poolton@Leedsbeckett.ac.uk, Cavendish Hall 111, 0113 81235

71 | P a g e
PARENTAL CONSENT FORM
Is there a difference between 10-11 year old participants in grassroots football
in the West Yorkshire region, born in the 1st and 2nd quartile compared
participants born in the 3rd and 4th quartile of a relative age grouping when it
comes to the development of self-regulatory skills?
Name of Investigator: James Dunn
Please circle YES or NO for each question:
I confirm that I have read and understand the attached information
sheet for the above study and have had the opportunity to ask
questions.
Yes No
I understand that all the data collected throughout the study will be
kept safely and securely, and my child will not be named to any
results.
Yes No
I understand that participation is voluntary and that I am free to
withdraw my child’s at any time up until the 14.03.16 without
giving any reason
Yes No
I consent that my child’s (unnamed) personal data can be retained
in a protected storage device by the research team for the
purpose of research project
Yes No
I consent that personal data collected from the research can be
published in academic/professional journals and can also be
presented at conferences.
Yes No
I consent that my child’s data can be used as part of an
undergraduate Dissertation.
Yes No
Mine and my child’s anonymity will be protected at all times and I will not be
identified in any published or presented work, under any circumstances
Name of Parent/ Guardian (print
name)
Date Signature
Lead Researcher Date Signature

72 | P a g e
Appendix 3 – Participant information sheet and assent form
Participant Information Sheet - Is there a difference between 10-11 year old
participants in grassroots football in the West Yorkshire region, born in the 1st
and 2nd quartile compared participants born in the 3rd and 4th quartile of a
relative age grouping when it comes to the development of self-regulatory
skills?
Principal Investigators James Dunn
Project Start Date November 2015
Email j.dunn9726@student.leedsbeckett.ac.uk
Supervisor Name and
Contact details
Chris Low
Cavendish, 119
C.Low@LeedsBeckett.ac.uk
0113 812 3570
I am writing to you as I would like to offer you the opportunity to take part in a project
which will compare yours and others thinking skills. I will look to see if there are any
differences or similarities in thinking skills between early and later born players that
are the same age as you.
If you do decide to take part you will be asked to sign a form which tells us that you
are happy with what you have read and that you would like to take part.
What are the data collection methods? And what will you have to do?
All testing will be carried out by fully trained members of our team.
If you agree to take part, you will be asked to complete a short questionnaire around
self-regulatory skills. Self-regulatory skills are skills that allow you to reflect and
control your own behaviour, emotions, or thoughts. I will ask you to complete the 2-3
minute questionnaire at a good point in the session. I will do this at a time in which
you will not miss anything from the session; and the process will not take any more
time than you would usually be involved in the session.
The questionnaires will measure your self-regulatory skills (thinking skills) through a
version of a previously used questionnaire. The questionnaire will be private (no
names attached) and will only need the month you are born as information. With no
more information required.
Are there any side effects?
There will be no side effects, as you will be asked for your opinions and beliefs only,
in the questionnaire. Also you will be completing your normal exercise routine.
What are the benefits of taking part?

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