Abstract

The purpose of the study was to investigate the performance level at which birth date effects selection for performance pathways in English football, as well as examining whether coaches are currently implementing arrangements to limit the relative age effect. The study comprised of 2450 players from performance levels including community, grass root and academy. The birth dates of each player within every performance level were analysed through the use of statistical tools within Microsoft Excel, with interviews analysed through transcription and the highlighting of recurrent themes. The sub-groups were viewed by age group, month of birth and the total percentage of players born within each quartile of the selection year to analyse the birth bias within specific performance levels. The statistical data of each sub-group were then collated to view differences in progressing through each performance level.

The main results found an over-representation of players born in the first quartile throughout each performance level. The bias within the community and grass root subgroup was 4.1%, with a 39.9% bias towards the eldest players at academy standard. The evidence highlighted that birth date only has significant impact on selection once the academy standard of play is reached, with minimal difference in impact when progressing through inferior performance levels. Coaches in the study showed high awareness of the effect, with implementation of two strategies to reduce the relative age effect being implemented. The two strategies were found to be ineffective in the reduction of the relative age effect, through implementation occurring after selection.

To conclude the academy pathway highlighted the most significant bias, with birth date having minimal impact at inferior performance levels. Strategies to reduce the relative age effect are currently ineffective requiring further research into reducing the bias prior to selection.

Introduction

Aims

  • To investigate the performance level at which birth date may affect selection for performance pathways in English football.
  • To examine if football coaches are making arrangements to limit the Relative age effect in football

Research Question:

In English football is there a starting point to the relative age effect and if this is the case then how are football coaches currently taking this bias into consideration when working with children at all levels of football.  

Rationale

Relative age effect is the difference in ages between children in the same age group. An example being, a child born in the start of the selection period in football i.e. 1st September will be 11 months older than a player who falls in the same age group born on the 1st of August. (Barnsley et al, 1992) Throughout the study research has referred to the relative age effect as birth date and birth bias, all meaning the same.

The football world is competitive and making sure that your team are developing young athletes to progress into the first team and national team is very important. This has made the selection and development of children an important aspect in youth football.

Studies have progressively shown that in football there are children not given the opportunity, due to a simple aspect such as their age. (Brewer et al 1995; Cobley et al 2008; Delorme et al 2010) The research that has previously been carried out has rarely been specified around the English game with only a minority being carried out in this area. (Simmons & Paull, 2001; Musch & Grondin, 2001) The research has predominantly been aimed towards a number of different nations across the world. (Glamser & Vincent, 2004; Jimenez, 2008; Delorme et al 2010; Campo et al 2010) The limited amount of research on the English game highlighted an area in which further study could be carried out in order to fully understand the impact the relative age effect has within English football. Correspondingly the research into the affect performance level has on the impact of the relative age effect within English football has been under-represented by preceding research. The research specific to this area often views different nations or sports. (Mujika et al, 2007; Cobley et al, 2009; Till et al, 2010) The knowledge of how performance level could affect selection will allow understanding of where birth bias is present and predominant, furthermore highlighting the level at which change is needed to reduce the relative age effect. The results will be of great value to coaches within the performance level that the relative age effect is most predominant by raising awareness and creating knowledge for change.

Preceding research has also viewed how different organisations and football associations have tried to reduce the impact of the relative age effect in different countries. (Helson et al 2000; Vaeyens et al 2003) Although this research has shown how interventions have been made there has not been a study on how the coaches within the football clubs in these associations are practically trying to reduce the bias or in fact if they are. This is an area of research that is being analysed. This will help compare the current tools being put in place and to see if there is a working intervention to help reduce the birth bias. The context of the study will include raising awareness of the relative age effect to the coaches in which the relative age effect is most predominant within the standard at which they coach. Research has previously highlighted this to be an advantage in reducing the effect, increasing the value of the study. (Baker et al, 2010; Cobley et al, 2009)  

The study begins viewing previous research on the relative age effect reviewing specifically topics around the aims and secondary topics in which can affect the predominance of the effect. The second section views the method in which the study carried out the research with reasoning and description, progressing onto the results in which are presented with the discussion following. A conclusion in relation to the aims of the study is carried out in the penultimate section, ending with self reflection discussing the learning throughout the study.    

Literature Review

1. Relative Age Effect

Children are split into age groups throughout school and whilst they are in education. In England the children are split into age groups running from nursery, primary school with years 1-6, then into secondary schools with years of 7-11. In England the school year starts in early September and runs to August (Direct.gov, 2009). This means that two children within the same year participating in educational studies and sports could have a difference of more than eleven months between them.

In sport, the relative age effect was first noticed in Cana­dian ice-hockey and volleyball. Grondin et al, (1984) found unequal birth-date distributions for males and females at recreational, competitive and senior professional levels for both sports dur­ing the 1981/1982 season.

2. What age does the relative age effect occur?

Simmons & Paull (2001) are a set of researches who have previously viewed the relative age effect in England. They found that there was a bias within centre of excellences in England. In 1997 in the age groups of U-15 - U16 there was seen to be a large difference within the birth dates of players participating, players oldest within the year consisted of 58.7% with just 12.7% of younger children being within these centres. Glamser, Vincent, (2004); Musch & Grondin (2001) found specifically that ‘players in the United Kingdom, Sweden, and Belgium approximately 70% of elite youth players had birthdays in the first half of the soccer year.' This shows that there is a bias within English football and shows that the age effect occurs highly in these ages.

The relative age effect does not just occur within England. Del Campo et al (2010) viewed the relative age effect within Spain. The research that was carried out found that the relative age effect occurred through age groups including under 11's to 18's. The players within the teams included within the research consisted of a minimum of 45% of players born within the first trimester, with only a maximum of 15% of the players coming from the fourth trimester. This shows that throughout each age group the difference between the players born early in the year and the ones later in the year was 30% in favour to the players born in the early stages of the selection period.

Williams, (2009) study on the U-17 World Cup also suggests that the relative age effect is continued into not just the older age groups but also into senior international teams. Williams (2009) looked at all the players participating within the tournament and found a large difference in the months of when the players were born. The study found that,

‘Nearly 40% of the players are born in the first three months of the year while only 16% are born in the last quarter'.

Dudink (1994) research supports the research carried out by Williams (2009) into evidence that the relative age effect progresses through all age groups. Dudink (1994) claimed that both Dutch and English players born early in the competition year are more likely to participate in national soccer leagues. This research not only suggests that the relative age effect occurs through childhood and adolescence but also occurs through to adulthood.

3. Why does the relative age effect occur?

Research has shown many reasons behind why there are biases towards players who are older than their peers. (Delorme & Raspaud, 2009: Musch and Grondin, 2001). Musch and Grondin, (2001) suggests that ‘as children are separated into age groups there are regularly cognitive, physical and emotional differences between the youngest and oldest'. Research backing up this is seen from Malina et al,(2004) who states there are ‘advantages in body size, fat free mass and several components of physical fitness including aerobic power, muscular strength, power, endurance, and speed'. This means that there is a difference within all aspects of a character within players in the same year. It has been sug­gested that the size of the relative age effect may be affect­ed by additional maturational variation at ages associated with the onset of puber­ty, generally applicable at the ages of 13-15 in boys and 12-14 in girls (Musch & Grondin, 2001). This meaning that puberty is a large section of a player's selection/development process in which could affect the number of players who are chosen. Helsen et al (2000) found that relative age effect was present within children aged as young as 8.

As players develop differently at different stages this would suggest the younger players would have a larger disadvantage at the stage of puberty. Research from Gil et al, (2007b) found when looking at the selection of young soccer players in terms of anthropometric and physiological factors found that during puberty the players selected were taller, heavier, leaner and faster than the non-selected players and that a high percentage of those chosen were found to be born within the first 6 months of the year.

Helsen et al, (2000) looked at the possible difference between two players within the same selection year:

‘A 10-year-old child in the 5th percentile is likely to be 1.26 m tall with a body mass of 22 kg, whereas a child in the 95th percentile who is almost 11 years of age is likely to be 1.54 m tall and 49 kg in mass.'

This shows that one player could be as much as 0.3m taller and 27kg heavier than a player placed in the same selection year showing a clear advantage physically towards the older player.

Along with maturation levels studies have shown that the playing position of a player also has an effect. Ashworth and Heyndels (2007) noted the relative age effect var­ied according to playing position in elite German soccer. The strongest effect sizes were found for goalkeepers and defend­ers, with relative age effects not evident for forwards. Research carried out by Gil et al, (2007a) found that goalkeepers and defenders are on average are the tallest players being five centre meters taller than both the midfielders and attackers. This with the research found from Malina et al., (2004) shows that it could be very difficult for the younger players to achieve selection within these positions. Research by Gil et al, (2007a) also progresses on to further back up research from Malina et al, (2004) as when viewing players who were in the selection process, players who had better endurance, were faster and in some instances taller were primarily selected. Although there were statistical information found within research from Gil et al, (2007a) looking further into the study there were also instances in which the research challenged the statement by Malina et al,(2004) in which they stated players who were faster and taller for example had an advantage. Gil et al (2007a) found that when viewing players who were selected and those not, it turned out that the non selected players were taller faster and had superior endurance.

Examples being that the goalkeepers non-selected were four centre meters taller, 0.3 seconds faster than the selected players. The research found that in midfield where players are seen to run the most which in turn means they need to have greater endurance levels the non selected players were found to have lower heart rates after an endurance test. (Gil et al, 2007a) This research highlights evidence contesting the advantages older children are perceived to possess.

4. The effect on participation levels

Researchers have also viewed that the relative age effect can make players drop out of sport. Delorme et al (2010), suggests that the players born later within the year ‘experience inferiority and failure within their practice and may be reduced to less playing time.' Vaeyens et al (2005) also had similar thoughts and stated that the reason why the relative age effect relates to the players dropping out is due to the older players receiving more playing time than the younger players. This leading to the younger players feeling less competent and increasing the possibility of them dropping out of the sport.  Cobley et al (2009) noted that the size of the relative age effect increased with age un­til late adolescence, but then decreased in adult sporting contexts meaning that if the players who are born in the younger part of the year, who carry on in sport have a good chance of being selected to play at a high standard, contesting research carried out by Williams (2009) and Dudink (1994).

While Musch and Grondin (2001), stated that;

‘The relative age effect is not only thought to generate discrimination in the selection process, but also to lead to dropout among less advantaged players'  (i.e. those born at the end of the year)

Delorme et al, (2010) found that the rates of drop outs in French football were highest within players in the last two quarters of the year. This means that although Cobley et al, (2009) found that the relative age effect decreases into adulthood the number of the late born players progressing through to that stage is low. Research by Delorme et al, (2010) supports research by Cobley et al (2009) as they found the number of players dropping out in French adult football was higher within the players born early within the year with a number of 1,612 players dropping out more than the late born players. 

Although this can be seen from the research, Delorme et al (2010) also show that the number of players born late in the years that are dropping out is higher throughout the ages of 9 - 15. This means that a high number of players born within the last part of the year have already dropped out implying that as the years progress the number of players that can drop out have reduced significantly.

5. Does the level of play affect the relative age effect?

Research from Mujika et al, (2007) views similar areas to the one carried out in this study with the difference of them viewing this within Spanish football. They viewed the difference between the relative age effect at different levels of football within Spain. The levels they viewed were players from La Liga (Spain's highest division) club AC Bilbao, Elite youth from AC Bilbao, Regional Youth and School Youth. The research found that players born in the first quarter of the selection period decreased as did the level of football, after the La Liga players group who had 43.9%. Elite youth players consisted of 46.6% of players in the first quarter, the regional youth group consisted of 28.6% whilst the school youth group had the lowest percentage at 27.1%. These statistics show that throughout youth football the relative age effect increases, slightly decreasing when reaching the highest level of football although only by 2.1%. They also found that players in the last quarter were found mostly in the School Youth subgroup consisting 22.9%, decreasing to 21.2% in the regional youth group, then significantly decreasing to just 10% of players within the Elite youth subgroup, finishing with a very slight increase in the number of players within the La Liga group of 2.2% to a total of 12.2% of players being within the last quarter. This again shows that there is a bias throughout the progression in performance level within Spanish football. 

Cobley et al (2009) viewed performance level in relation to the size of the relative age effect among similar levels to the current study. Cobley et al (2009) found that the largest bias towards the oldest players was found within players that participate within the representative stage. This stage related to the level below the elite stage which was viewed to be the highest level in the study. Cobley et al (2009) progressed to suggest that the level that players partake within has an effect on the size of the relative age effect. The relative age effect was found to increase within each progression in performance level until the optimal performance level is reached comparable to the findings by Mujika et al (2007)

Till et al (2010) viewed the relative age effect within rugby league players, similar to Mujika et al (2007) they found that as the performance level increases as does the impact of the relative age effect.  In the study throughout each increase in performance level there was an increase in the size of the relative age effect. The highest bias towards the eldest players found was 61.34%, this statistic was found within the under 13's age group. The research highlights that the birth bias is affected by skill/performance level not just within football but also other sporting environments.  

6. Is being young an advantage?

While previous research has shown a bias towards the players born early within a selection period, there is research suggesting that if the later born players successfully progress through and become professional players they can be at an advantage. Ashworth and Heyndels (2007) found that players who were seen as being born in the later period of selection had higher wages than the players born in the early period. When looking at German football players during the 97-98 and 98-99 seasons, players born in the cut off month of August 1st earned 2 million deutschemarks where players born later in the selection period earn up to 2.8 million deutschemarks. Ashworth and Heyndels (2007) stated that this occurred when the later born players played in a high standard soccer education programme. The later born players benefited playing with the early born players or perceived better players, enhancing their development as young players benefit from playing alongside or against superior players. They further progress to imply that for the later born players to succeed throughout the selection process, when younger they must have above average talent.

7. Can the relative age effect be decreased?

Research has viewed the possibilities of whether a change in selection dates will correct the bias that occurs within football.

The Royal Belgian Football Association changed their cut off date in 1997 to reduce the impact of the relative age effect, but the shift from August the 1st to the 1st January just meant a shift in the Bias. (Vaeyens et al, 2005) Similarly research has viewed Japan's competition year which begins on 1st April and the bias is observed in May and July, Germany and Brazil produce similar distributions with a start date of 1 August. In each case, the season-of-birth bias aligns with whichever quarter is earliest in the competition year.

(Simmons and Paull, 2001) Fifa and Uefa have also been seen to prolong the selection period for players in order to make it fairer. Research found that the number of players within teams that were looked at had more players in a wider range of months but there was still a bias to the younger players in the selection process. (Helson et al, 2005)

Although footballs attempt to shift the selection dates has seen little or slight improvements in producing equality into the selection process, varying the cut off dates for selection in sports has before been seen as a way of being successful in reducing if not preventing relative age effect. For example in swimming they have no cut off date. Ryan (1989) stated this would be successful if key competitions were avoided within certain months. Although this may work for individual sports such as swimming has been seen to not be applicable in team sports. (Musch & Grondin, 2001) This shows that there is a possibility of reducing the relative age effect.

The results and interventions found and used in other nations will help when aiming to reduce the impact which may be found within the English game and to see if there are any differences between England and the other Nations. Although these have been used to try and reduce the relative age effect in the sport few research have gone into what the coaches can do. Cobley et al (2009) suggested that just raising awareness of those responsible for the infrastructure and coordination of youth sport may be effective. Baker et al (2010) also suggested that increasing awareness and under­standing of the relative age effect, as part of coach training and education programs, may help centre coaches attention to the potential selection bi­as.

Methodology

Sample

The study comprised of a total of 2540 football players, ranging from the under 9 to under 15 age category within England. The players were allocated to one of three sub groups relating to their standard of play within the sport. The Academy group perceived as the highest level within the study consisted of a total number of 416players who played for an academy football team at the time of the study. The Grass root group consisted of 354players who played for a FA Chartered team. The third subgroup contained players who played recreational football within a community scheme that related to the lowest standard of play within the study. The total number of players in the recreational sub group was 1770. 

Area 1

The study required the birth dates of football players within age groups from U-9 to U-15. The players were chosen from community football, grass root football to academy football. The players were then sub-divided into secondary groups of grass root team players, community players and academy players. The details of the players were collected through contacting teams from the respective leagues through the use of letters. These letters detailed the information required from the clubs and how the results of the information would be used.

Area 2

There were a number of coaches selected to undertake an interview. The coaches were chosen from the category in which the largest relative age effect was found from area one which was within the academy standard. The number of coaches chosen was four and this was due to limited time. The coaches selected were based on accessibility. Prior to interview the coaches were provided information regarding to the research in which is to be carried out. (Appendix 1.1) 

Data Collection

There are two types of research, these are qualitative and quantitative. Qualitative research involves ‘researches describing kinds of characteristics of people and events without the use of measurements or amounts.' (Thomas, 2003). Quantitative research involves ‘measurements and amounts of the characteristics displayed by people and events.' (Thomas, 2003).   

The data that will be collected will be both qualitative and quantitative. The quantitative data will be collected through primary research. Individual clubs from each area and age group were contacted through a letter which included the details of what the study will involve, the information needed and ethical considerations. The letter was sent to the coaches of the grass root teams, the academy managers and the chief executive of the community scheme. This data collection method was chosen to save time which is limited and through previous research having successfully acquired similar data. (Diaz Del Campo, 2010)  Grass root team players are players from teams who were found to be FA chartered and within division A of their respected leagues. The recreational players came from a local community scheme located in South Yorkshire. The academy players were selected from a number of professional academy teams. The players and teams that were selected were based on accessibility and convenience. The teams that were chosen were local teams based within South Yorkshire, as money and time limitations would not enable collecting data from teams located in different regions.  The teams were presented with a sample research response sheet in which they entered the necessary information required for the study. (Appendix 1.2, 1.3, 1.4)

To collect the data from the coaches structured interviews were carried out involving a number of open and probing questions. (Appendix 1.5) Open ended questions were used to allow the interviewee to provide more detail, rather than a one word answer from a closed question. The open ended questions allowed the interviewee to communicate using their own language and this takes you into their own world to view the area from their perspective. (Johnson & Christensen, 2011). This would add value to the study information being reliable. (Johnson & Christensen, 2011). The interviews were recorded through the use of a Dictaphone to reduce the risk of missing information and this enabled re analysis to ensure all important data was processed. Although a Dictaphone can help in recording the interviews, they can also have changed the behaviour of the interviewee and the answers they gave. (Silk et al, 2005) The interviewer made sure the coach was comfortable before progressing with the interview to enable reliable results could be collected and the coach's responses weren't systematic and fictitious. 

Structured interviews will be used as the reliability of the interviews will be increased. (Hersen et al 2007) When looking at the purpose of the study which is to see if the coaches are aware of the relative age effect and what they are doing about it, the coaches could diverse into different areas if a structured path is not in place similar to a semi structured interview. (Hersen et al 2007) Although when designing this interview considerations such as making sure all areas needed are covered were considered to ensure the responses did not divulge into unnecessary areas. (Hersen et al 2007). The questions started with short and easy questions in which they could comfortably answer in order not to scare them and make them feel comfortable. (Johnson & Christensen, 2011) The interview then progressed onto more sensitive questions in which were placed once the interviewee felt comfortable and had given alot of their time to the interview reducing the possibility of fictitious responses being given. (Johnson & Christensen, 2011). Questionnaires were not used as a tool to collect this data as questionnaires could be returned incomplete and also could be found as being ambiguous. This would lead to incomplete data and unreliable sources. (Gratton & Jones, 2005)

Data Analysis

Analysing data from the birth dates of players, each teams data that was collected were placed into the categories assigned for them (Community, grass root and academy). The different age groups were separately analysed to highlight which age group had the largest relative age effect. The birth dates were organised into sub categories, these were the birth months of the players. These sub categories are; September to November, December to February, March to May and June to August. These categories have been used in previous studies, (Simmons & Paull, 2001) and using these will give an area of comparison. The statistics will then show in which area the birth bias is evident and the different impact of the bias within different levels of the sport. Percentages of which players are born within each month will be produced giving a statistic which can be easily be compared. The statistical analysis tools within Microsoft Excel were used to create the data throughout the study.    

The data collected through the structured interviews were analysed by transcription of the interviews, in which throughout this key themes could be formed to help seek whether there are current similarities in how coaches are selecting players and strategies minimizing the impact of the relative age effect. (Appendix 1.6) Any interventions being inputted by coaches were highlighted and used to compare what coaches are doing to overcome the relative age effect in their teams currently. Direct quotes seen as aiding research and results of the research are highlighted within the main body to provide evidence.

Ethical Considerations

Throughout the research of the study ethical issues will be considered throughout. When collecting data for the birth dates of players, the managers of the grass roots teams, chief executive of the community scheme and academy managers were told specifically what they will be partaking within and what information is needed from them. (Appendix 1.7)To keep the players details confidential all that was required were the birth dates of the child, as this will keep personal details which are not required safe and ensured the research could not be related back to any specific person. Consent forms were included to evidence their cooperation within the study. (Appendix 1.2, 1.3, 1.4) When giving information the use of a data template in which the teams filled out to make sure only the necessary information is given was used.

The collection of data for the interviews will include specifically explaining verbally and documenting what the coaches will be partaking within, and where the results of the research will be used with consent forms highlighting their cooperation within the study. (Appendix 1.9)The necessary resources needed to carry out the interviews were accessed prior to the interviews, such as Dictaphones and interview rooms. (Appendix 2.0). The information collected from the coaches was specific to the research needs and the only information needed personally from the coach was of what club they are involved with. The information gathered through the interview was only viewed by the researcher and the MIS Supervisor. Questions were designed prior to the interviews to enable ethical approval on them. (Appendix 1.5)

It was made aware to all parties involved within the research project that there was ethical approval approved by an appropriate representative of the Faculty Research Ethics Committee at Leeds Metropolitan University and that if any issues arise they will be informed to ensure confidence in the divulgence of research. This was done through the completion of necessary forms, such as risk assessment (Appendix 2.1) local level approval .

The results of the research that has been carried out in context to themselves or their team has been made available for them to view at the end of the research, to ensure the participants have evidence that the ethical considerations they agreed to have been kept and to view areas in which may help their development.

Results

Birth Month Statistics

The research project aimed at the start to view the different levels of football and how the influence of the relative age effect impacts each of the levels (Academy, Gras root and Community).

Figure one below shows the total number of Academy players within the study. The results in figure one show that throughout the age groups excluding one (U12) the majority of players are made up by the oldest players from the selection period with the younger players being underrepresented. 

Table 1: Percentage of Academy players

Age Group

Sep - Nov

Dec - Feb

Mar - May

June - Aug

U9

55.6

28.9

11.1

4.4

U10

42.9

23.2

16.1

17.9

U11

47.3

32.7

16.4

3.6

U12

38.2

40.0

16.4

5.5

U13

46.6

26.0

19.2

8.2

U14

53.7

26.9

16.4

3.0

U15

50.8

23.1

13.8

12.3

The table above relates to figure one. The table highlights the difference in the number of academy players born within each month.

When viewing the grass root football players the effect that the birth bias had on this level of football was found to be significantly different to the one found within the academy results. Figure 2 shows the number of the grass root players categorised into age and birth month groups.

Table 2: Percentage of Grass root players

Age Group

Sep - Nov

Dec - Feb

Mar - May

June - Aug

U9

28.3

23.9

26.1

21.7

U10

26.1

26.1

19.6

28.3

U11

30.0

22.0

26.0

22.0

U12

33.3

27.5

19.6

19.6

U13

28.8

25.0

21.2

25.0

U14

29.6

20.4

27.8

22.2

U15

23.6

27.3

23.6

25.5

Table two below presents the percentage of players born, categorized into age groups and the month in which the players were born. The table highlights the divergence throughout the age groups in relation to the relative age effect.

The final level of football that the study researched into was the football players who participated in football within a community scheme. Figure three shows the number of players within each age group divided into the quarter months. The graph clearly presents that the relative age effect is still prevalent within this level of football, which is the lowest standard within the study.

Table three highlights the percentage of players participating within the community scheme. The table presents the findings of the players through the use of percentages in relation to the number of players each birth month consists of.

Table 3: Percentage of Community Players

Age Group

Sep - Nov

Dec - Feb

Mar - May

June - Aug

U9

34.7

23.1

19.9

22.4

U10

21.6

25.4

23.8

29.2

U11

25.0

23.4

23.4

28.1

U12

31.7

26.7

23.3

18.3

U13

28.8

19.6

28.4

23.2

U14

32.7

24.9

21.0

21.5

U15

24.8

20.4

29.9

24.8

Table 4: Difference between the Oldest and Youngest Players

Age Group

Community

Grass root

Academy

U9

12.3

6.5

51.1

U10

-7.5

-2.2

25.0

U11

-3.1

8.0

43.6

U12

13.4

13.7

32.7

U13

5.6

3.8

38.4

U14

11.2

7.4

50.7

U15

0

-1.8

38.5

Table four above presents the difference between the oldest players and youngest players (%) within the different age groups, categorized into standard of play. The table presents both positive differences and negative differences (-). Negative differences equal a bias towards the youngest players within the year groups.

Interview Analysis

Figure four above presents the results of question four within the interview in relation to the awareness of the relative age effect. The results highlight optimal level of awareness of the relative age effect.

Table 5: Impact of the Relative Age Effect

Response

Can the relative age effect Impact your Coaching?

Have you tried Anything to help Reduce the affect in your team?

Yes

2

4

No

1

0

Unsure

1

0

Table five above highlights the number of coaches that feel the relative age effect impacts their coaching process along with whether they have implemented anything into their coaching to reduce the effect.

Discussion

This study examined the influence of performance level on the prevalence of the relative age effect in youth football within England.  The research presented highlights that this criterion influences the distribution of football players within England. The current study consists of corresponding findings to preceding research into English football. (Simmons & Paull, 2001; Glamser & Vincent, 2004; Musch & Grondin, 2001).

Relative age effect was most prevalent within the highest level of youth football within England, i.e. the academy level. The number of players that participate for academy teams decreases as the months of the selection period progresses through the year. Players born earliest in the selection period were compromised of 47.8% of the total number of players. This number decreased to 28.4% for players born between December and February, 15.9% between March and May and 7.9% between June and August. (Figure 1). Simmons & Paull (2001) comply with the studies current results in relation to youth football players at the highest level. Similarities arise through the comparison of the two studies with Simmons & Paull (2001) who accumulated results showing 61% of centre of excellence players were represented by the oldest players in the teams, with the younger players being underrepresented occupying 11% of the total number of players. The two studies highlight a large bias towards the oldest players by 39.9% and 50% respectively.

Furthermore in relation to the birth bias towards players born early within the selection period participating at the highest level Musch & Grondin, (2001) found that in the United Kingdom, Sweden, and Belgium 70% of elite youth players were born within the first half of the year. The current study presents comparable results supporting the research in which statistical analysis found 76.2% of the academy players were born within the first half of the year.

The study aimed to view if the level of football being played impacted the relative age effect. The current study found that the birth bias towards the oldest players although present at each level did not always increase. The players participating at the lowest level (community) consisted of 24.2% of the total amount of players in which emerge from the youngest age group. This was only 4.1% less than the total amount for the oldest players, highlighting the lowest bias between players within the study along with the grass root players. In relation to the impact of the performance level of a participant on the relative age effect, the study's results provide evidence that the significance of raising the performance level does not affect the selection of younger players when moving from the community scheme to a grass root team. The results contest previous research conducted by Mujika et al (2007). The Difference in the youngest and oldest players within the two subgroups of community and grass root does not alter with the adjustment in standard of play; Mujika et al (2007) found within their study that as the performance level increased so did the relative age effect. In numerous age groups the impact of the relative age effect can be seen to decrease as the performance level increases (Table 2 & 3). Although the study opposes this area of research by Mujika et al, (2007) the study corresponds when viewing academy players. In relation to corresponding with Mujika et al, (2007) the current study found similar results in the impact of the birth bias when reaching the academy level. Mujika et al, (2007) found that the difference between players who participate within the highest level of youth football and the ones who participate within the lowest level was of significance, finding that this difference was 23.7% in favour for the older players with the current study presenting a difference of 23.6%.

The impact on performance levels of players participating within each of the subgroups differed throughout different age groups.  Table 4 presents evidence highlighting that during the participation within the under 10's age group at every standard of play the bias towards the older players is at the lowest level, evidently in the community and grass root subgroup the bias can be seen  to be in favour of the younger players. There is a higher representation of younger players over older players in the under 10's age group by 7.5% and 2.2% respectively contesting research by Helsen et al (2000) who found the relative age effect to impact each age group including players as young as 8 year old. Table 4 progresses to highlight the most affected age group in total throughout the different standards of play is within the under 9's age group. The difference between the oldest and youngest players are 12.1% in the community group, 6.5% in the grass root subgroup with the highest difference being 51.1% in favour of the older players. The most significant finding found that there was no relative age effect within the community scheme at under 15's, this age group was also the lowest within grass root players with a difference of 1.8%. The findings into the age in which the relative age effect is present resonates with research from Helsen et al (2000). In which both studies found that the relative age effect is present within the youngest age groups, with the older players being labelled as talented.

Overall the statistical research found that in relation to performance level, the relative age effect is most predominant when reaching the academy standard with low performance levels providing little evidence of a significant bias. The age of a player in relation to the impact of the relative age effect at academy level provides evidence suggesting that the impact of the relative age effect is prominent throughout all ages with the older age groups presenting higher numbers of older players.

The study's secondary aim was to view if football coaches where the relative age effect has most impact are currently arranging strategies to limit the bias. The research found that out of the four coaches interviewed on the matter every coach had been made aware of the relative age effect. Highlighting this result along with the impact the relative age effect has at this performance level contests preceding research by Cobley et al (2009). Cobley et al (2009) stated that raising awareness in coaches would be effective in reducing the effect. The current results highlight that coaches have been made aware and results from Figure 1 and Table 2 present results against research that states raising awareness is an effective strategy to reduce the relative age effect as it is still predominant. Whilst coaches in the study conveyed that they had been made aware, results from the interviews highlight uncertainty in the definition and understanding of the issue. Responses consisted of phrases presenting this uncertainty, for example ‘if I'm Right; I think'. This finding should be considered when analysing research by Cobley et al (2009) because although the coaches have been made aware, the issue has not been fully understood limiting knowledge and in turn limiting the impact this could have on them.

The coaches interviewed in the study stated that they were made aware of the relative age effect through ‘development days and coaching courses'. The relative age effect has most impact in relation to the standard of play that the coaches questioned work at. Baker et al (2010) suggested that increasing awareness and under­standing of the relative age effect as part of coach training and education programs, may help centre coaches attention to the potential selection bi­as. Results in the study deviate from Baker et al (2010) research as the coaching courses have not centred coaches to the selection bias, coaches felt that the relative age effect did not affect them as they mainly view ‘technical ability' and argued that ‘You don't know how old that player is when you select him'. This provides evidence suggesting the coaching courses are raising awareness but the issue of the relative age effect is not being made specific to the coaches to allow understanding.

The preceding research into limiting the relative age effect in football referred to raising awareness and the implementation of new selection periods. (Baker et al 2010; Cobley et al 2009; Vaeyens et al, 2005; Simmons and Paull, 2001) The initial strategy has been contested throughout this study in which found new ways the coaches are aiming to reduce the bias. The coaches at academy level suggested the strategy of ‘playing players up or down one year' can help develop players. The results present new findings in the research to limiting the relative age effect within football. However  whilst the academy coaches can be seen to be implementing this, Figure one and Table one highlight results questioning the effectiveness of this strategy as the relative age effect is predominant at that performance level. Relating to prolonging the playing career of players that the relative age effect detriments coach D provided strategies to facilitate this. Coach D when viewing coaching strategies suggests ‘social' development is imperative. Actions such as allowing players ‘to set up sessions, do demonstrations and be captains', all with the aim of improving confidence and allowing the younger players to progress. The strategy aims to prolong and develop players when already within the academy team; however this would not change the birth bias in the most important area which is the selection process. If the younger players are not progressing through to the team then the strategy would become redundant.

Interviews including the academy coach's emphasised that when selecting players the main attribute the coach's look for is technical ability, with impact the player has in the game being the secondary attribute. Malina et al,(2004) stated there were ‘advantages in body size, fat free, mass and several components of physical fitness, including aerobic power, muscular strength, power, endurance, and speed'. The physical attributes portrayed by Malina et al (2004) can contribute to players utilising them in different positions to produce this ‘impact' within games. (Bloomfield et al 2007). The preponderance of evidence implied the impact of the player during a game was one of the attributes coaches viewed as necessary in performing at the academy standard. However in interviewing coaches, acceptance of selecting the older players came to the fore in one instance. Coach B conveyed that they would look to the players the birth bias effects; ‘if i needed a centre half i do look at the taller age ranges'. The preceding research along with the current studies qualitative results suggests the selection process used by coaches, seek to identify the attributes that the players oldest in the selection period are perceived to possess. This implicit acknowledgement provides evidence of why the relative age effect is so predominant at this performance level.

Conclusion

The primary aim of the study was to investigate the performance level at which birth date may affect selection for performance pathways in English football. The current study's findings present divergent results in comparison to preceding research that highlighted as the performance level of a player increased, so did the relative age effect. (Till et al 2010; Mujika et al 2007) The current study's results presents that the performance level of a player only illustrates an impact on the birth date of a performer once the highest level of youth football is achieved. The results establish that the football pathway towards elite football demonstrates a bias towards the oldest players within the selection period, this bias dissimilar to any other standard in English football. The results compiled within the study provides evidence that once players reached the highest level of youth football the players who were born earliest within selection periods possessed the necessary attributes to continue. Whereas the evidence implies that players born latest within the selection period have not at this stage of selection acquired those attributes. The study's results differentiate from previous in which throughout each standard of play the impact of the relative age effect progressively increases. The data is of important value to members of the academy structure, highlighting an area in which improvement is acquired.

The secondary aim of the study was to explore the football coaches understanding of the relative age effect in addition to establishing whether strategies are currently in place to minimize the effect. The present findings highlight that the coaches within the academy structure are aware of the relative age effect, however unlike previous research suggested this awareness is not substantial enough to minimize the relative age effect at this level. (Cobley et al 2009; Baker et al 2010).  The coaches informed that the awareness was arisen through coaching courses and development days. Preceding research by Barker et al (2010) suggested that awareness through these sources would ignite a response in minimizing the bias. The current study provides sufficient evidence contesting this research as although the coaches are aware of the level of impact the relative age effect has; it is still predominant at this level.

In relation to strategies currently in place the study presented new findings into actively reducing the relative age effect. These strategies were to play players up or down one year dependant on a players development stage and to increase confidence of younger players within the teams, both of which were proven to be ineffective through statistical data gathered throughout the study. The area of weakness within the strategies in attempting to reduce the impact that birth date has on selection, is that they are currently aimed to limit the bias once players have been selected. The study was unsuccessful in presenting an effective strategy in reducing the relative age effect within English football, comparable to preceding research. The study provides guidance into the application of future research in which should concentrate on strategies in placement prior to selection, rather than once players have been selected.

The study's results presents informative data with great value for academy coaches and scouts. The study highlights that the academy's approach to minimizing the effect currently is ineffective, providing evidence that action is needed in order to reduce the relative age effect at this standard.

The current study was limited to the Yorkshire region when compiling results for the study due to time and convenience, future research should explore a wider circumference in order to analyse the overall impact on English football. In relation to the sample size of the study, the number of players viewed was imperative to acquiring informative results; however it is recommended that future research contributes increased time in the collection of a larger broad sample size in order to comprehensively view the impact of the relative age effect in English football.

To conclude, the study found that the performance level of a player only has an impact on the birth date in relation to selection once the highest level of youth football is viewed. The coaches are currently aware of the relative age effect but as yet there are no successful strategies in order to reduce this effect in the English game.

Self Reflection

The process of the major independent study has involved invaluable personal, professional and academic advantages throughout.  In the production of the MIS there were regular meetings completed with the researcher and the tutor that involved discussions around the completion of areas within the study, in which turned out to be informative in compiling the study. (Appendix 2.3)These discussions highlighted the inconsistency of the writing skills throughout the study. This enabled learning into self critique of the work, improving these skills that immediately enabled a more concise piece of work being complete; furthermore the skills will enable the researcher academically in future studies in order to ensure the content and style of writing is concise and relevant throughout. 

In the completion of the study one of the key learning outcomes that arose was the time management in relation to the acquisition of research data. The study highlighted a skill gap in time management, the main area that this will impact is within future academic studies and throughout future career aspirations. It is important that in future research the study is better time managed with a systematic approach in place in which contingency plans are created. This will allow time for the study to be completed efficiently with sufficient data included.

The researcher found the experience of investigating the topic area to be of real interest both personally and professionally. In the future the career aspirations are to progress into working within the academy structure, the results found within the study will impact on the approach in the selection of players within the career choice. The results highlight the importance of the selection process in the aim of recruiting potential football players, it is important to understand the development stage at which each player is at and to view future potential rather than current attributes. The study provides personal and academic opportunities to further the study within English football in relation to the relative age effect. The results highlighted a gap in research in which has ignited a passion to investigate further.

A strength highlighted throughout the process has been the ability to research relevant and up to date research in order to understand the topic area competently and provide relevant research compile a professional investigation into the subject area. This strength will aid in future studies as having the skills to research a subject area and having the knowledge to source the information efficiently enables relevant research to be established. In relation to future career aspirations the strength will allow areas relevant to the post to be researched and understood sufficiently in order to carry out the post competently.