German Journal of Exercise and Sport Research

, Volume 47, Issue 3, pp 194–204 | Cite as

Cross-sectional and longitudinal analyses of the relative age effect in German youth football

Impacts of talent selection procedures between competition levels and age categories
Main Articles

Abstract

Relative age effects (RAEs) describe an overrepresentation of youths born early within annual age cohorts. An understanding of how talent selection procedures cause RAE emergence in talent development programmes facilitates specific advice for their reduction. This cross-sectional and longitudinal study investigated the location of RAE differences between consecutive age categories and competition levels and RAE emergence through talent selection procedures. The sample comprised 35,390 male youth football players from the German talent development programme from three seasons (2010/2011–2012/2013). Cross-sectional analyses showed a consistent increase of RAEs over four ascending competition levels and slightly increasing RAEs from age categories U12 to U15, with a subsequent decrease until U19. The longitudinal analyses of talent selection procedures revealed an RAE increase for players newly selected for higher competition levels and no change in RAE extent for players retained across consecutive age categories at the same competition level. Findings were used to specify common suggestions to reduce RAEs in talent development programmes.

Keywords

Reduction interventions Selection processes Talent development Youth soccer 

Quer- und Längsschnittanalysen des relativen Alterseffekts im deutschen Jugendfußball

Auswirkungen der Talentauswahlprozesse zwischen Wettkampfniveaus und Altersklassen

Zusammenfassung

Ein relativer Alterseffekt (RAE) liegt bei einer auf einen Stichtag bezogenen Überrepräsentation relativ Älterer in Jahreskohorten vor. Für fundierte Vorschläge zu einer Reduktion des RAE ist es notwendig zu verstehen, wie Talentauswahlprozesse zur Entstehung des RAE in Talentförderprogrammen beitragen. Diese Studie untersucht querschnittlich und längsschnittlich, wo Unterschiede im RAE-Ausmaß zwischen aufeinanderfolgenden Wettkampfniveaus und Altersklassen auftreten und durch welche Talentauswahlprozesse eine Veränderung des RAE-Ausmaßes verursacht wird. Die Studienstichprobe enthält 35.390 Jugendfußballspieler des deutschen Talentförderprogrammes aus drei Spielzeiten (2010/11 bis 2012/13). Die querschnittlichen Analysen ergaben eine gleichmäßige Zunahme des RAE-Ausmaßes über vier aufsteigende Wettkampfniveaus und geringfügig ansteigende RAEs zwischen den Altersklassen U12 bis U15 mit einem anschließenden Rückgang bis zur U19. Die Längsschnittanalyse der Talentauswahlprozesse zeigte eine Zunahme des RAE-Ausmaßes bei der Auswahl neuer Spieler für höhere Wettkampfniveaus und keine RAE-Änderungen für Spieler, die auf demselben Wettkampfniveau in die nächsthöhere Altersklasse übernommen wurden. Aufbauend auf den Ergebnissen werden gängige Vorschläge für eine RAE-Reduktion spezifiziert.

Schlüsselwörter

Reduktionsmaßnahmen Auswahlprozesse Talentförderung Jugendfußball 

Introduction

Annual age-grouping with fixed cut-off dates in youth sports often leads to an overrepresentation of children born early in relation to the cut-off date. This issue has been discussed for the past three decades as relative age effects (RAEs) (Baker, Schorer, & Cobley, 2010; Barnsley, Thompson, & Barnsley, 1985). Particularly in male football, existing RAEs have been extensively reported in youth and adult players (Cobley, Baker, Wattie, & McKenna, 2009; Meylan, Cronin, Oliver, & Hughes, 2010; Musch & Grondin, 2001). The effect is widespread across European talent development programmes and well documented amongst currently successful youth football nations like France, Germany, Spain and Switzerland (Carling, le Gall, Reilly, & Williams, 2009; Grossmann & Lames, 2013; Jimenez & Pain, 2008; Romann & Fuchslocher, 2011). However, the causes of RAE development are still remarkably unclear (Roberts, 2014), and a noticeable reduction of RAEs in the last decade has not been achieved (Helsen et al., 2012). Therefore, research should focus on the factors that facilitate RAE emergence in talent development programmes to enable specific advice for practitioners about where and how to apply effective RAE reduction interventions in talent development programmes.

RAE emergence in talent development programmes is directly linked to talent selection procedures (i. e., the process of choosing some players from a larger group of youth players organised in annual age cohorts). These systematic selection procedures are meant to focus the limited promotion resources (e. g., high-level coaching) on the most promising players (Cobley, Schorer, & Baker, 2012; Delorme, Boiché, & Raspaud, 2010a; Vaeyens, Lenoir, Williams, & Philippaerts, 2008) and are to be distinguished from nonsystematic exchanges of players between amateur clubs.

Environmental factors, like promotion resources, have been assigned a decisive role in talent models for the development of natural giftedness into systematic talent (Gagné, 2009; Ward, Hodges, Starkes, & Williams, 2007). Consequently, a more frequent selection of relatively older players is considered unfair and inefficient (Dixon, Horton, & Weir, 2011; Edgar & O’Donoghue, 2005). Furthermore, promoted players have a higher probability of being continuously selected at higher competition levels of talent development programmes, resulting in a “vicious circle” (Helsen, van Winckel, & Williams, 2005, p. 630). This feedback loop explains the persistence of RAEs throughout talent development programmes and into adulthood (Lames, Augste, Dreckmann, Görsdorf, & Schimanski, 2008). For this reason, studies should examine the role of selection procedures in promoting RAE emergence within talent development programmes.

The multitiered selection procedures in talent development programmes take place over several consecutive competition levels and age categories. This assumption applies to all football associations that conduct a systematically organised multilayered talent development programme. The selection procedures in these programmes basically are of two different types: players selected for the first time from lower to higher competition levels (hereinafter called “newly selected”) and players remaining at a certain competition level across consecutive age categories (“retained”) if coaches decide that they are worthy of further promotion (Huijgen, Elferink-Gemser, Lemmink, & Visscher, 2014).

A means to locate selection procedures that lead to greater RAEs in talent development programmes is to find differences in the RAE extent between groups from consecutive competition levels and age categories. Previous studies’ data with respect to this issue lack consistency (irrespective of the studies’ original research purpose), thus underlining the need for further research. For example, the data from a comprehensive review by Cobley et al. (2009), which aimed to find moderators of RAE extent, showed larger RAEs in older compared to younger age categories. On the other hand, subsequent studies found no RAE differences between age categories (Diaz Del Campo, Vicedo, Villora, & Jordan, 2010; Votteler & Höner, 2014). In addition to the study-specific explanations for the results, a methodological aspect may be responsible. Most of these studies compared groups that simultaneously differed in their respective competition levels and age categories (Jimenez & Pain, 2008; Romann & Fuchslocher, 2011). For example, in a complex analysis of several influencing factors, Schorer, Cobley, Büsch, Bräutigam, and Baker (2009) examined a subsample of 13- to 16-year-old regional representative players and a subsample of 16- to 19-year-old youth national players in team handball. Since the variables competition level and age category were confounded, their effect on RAE differences cannot be considered in isolation. Hence, for a definite location of RAE differences, a study’s design should ensure that the respective groups only differ in either their age category or their competition level.

The foremost cross-sectional studies on RAE differences have located where in talent development programmes changes in the extent of RAE occur, but they do not reveal exactly which selection procedures cause RAEs. In this respect, one exceptional longitudinal study by Till et al. (2010) in UK Rugby examined the RAE extent of players reselected into representative teams in consecutive age categories. It showed that the retention of players through consecutive age categories was a structural feature of the Rugby talent development programme that facilitated RAE persistence across the age categories U13 to U15.

Noticeably, the longitudinal design made it possible to consider that youth players in talent development programmes are often chosen from previously selected groups (“selection within the selection”, Jimenez & Pain, 2008, p. 999). This aspect is important because even a random selection of players from a preselected group with an existing RAE bias results in the maintenance of the RAE. So far, it is unclear whether the findings from Till et al. (2010) are applicable to youth football because the talent development system in UK Rugby, with each player starting again at the lowest level of competition in the next age category, differs from the structure of talent development programmes in European football (Huijgen et al., 2014; Jimenez & Pain, 2008; Romann & Fuchslocher, 2011). Thus, a similar longitudinal study investigating the effect of different selection procedures on the emergence of RAEs in football is warranted.

The present study focuses on the talent development programme of the German Football Association (DFB), (arguably) the largest talent development programme in football worldwide (Schott, 2010). The programme includes four ascending competition levels (competence centre, youth academy, regional association and youth national team) and extends across the age categories U12 to U19. The study investigates the emergence of the RAE across these competition levels and age categories with two methodological approaches. First, cross-sectional RAE differences between consecutive competition levels and age categories are separately analysed to locate where exactly in the talent development programme changes in RAE extent occur (objective I). Secondly, longitudinal analyses investigate how selection procedures influence the emergence of RAEs by choosing newly selected players for higher competition levels and retaining players across consecutive age categories (objective II).

Methods

Sample and design

In the German talent development programme, basic talent promotion at the lowest competition level, the competence centre, includes four age categories from U12 to U15, roughly covering early adolescence. Starting with U12, the (more) elite promotion of players at youth academies continues during middle adolescence until the age category U19. At the next competition level, regional associations play official nationwide tournaments in the four age categories U15 to U18. At the highest competition level, the youth national teams are assembled in the age categories U15 to U19. Therefore, the study design included 21 groups, each with a different competition level × age category combination, to strictly differentiate competition levels and age categories (Fig. 1).
Fig. 1

Structure of the German talent development programme with number of selected players per season (based on the sample used in this study) and selection pathways examined in this study

With respect to the analyses of the two types of selection procedures (objective II), Fig. 1 schematically models the most important selection pathways for newly selected players (from lower to higher competition levels) and for retained players (across consecutive age categories) in the DFB talent development programme.

The comprehensive study sample consisted of 35,390 different male players in the age categories U12 to U19 who had been selected at least once during three seasons (2010/11, 2011/12 and 2012/13) for one of the 366 competence centres, 45 youth academies, 21 regional associations teams or the youth national team. The corresponding squad lists, including players’ names, birthdays, age categories and club names, were provided by the German Football Association. The ethics department of the Faculty of Economics and Social Sciences at the University of Tübingen and the scientific board of the DFB approved the implementation of this study.

Procedure and statistical analysis

Based on players’ date of birth, the independent variable relative age was defined as the chronological age of a player within his age category with January 1st as the cut-off date. Temporal resolutions of relative age in birth months, birth quarters (Q1: January–March, Q2: April–June, Q3: July–September, Q4: October–December) and birth half-years (H1: January–June; H2: July–December) were used. The temporal resolution of birth months was applied to show the relationship between relative age and observed birth frequencies while maintaining as much information about the actual distribution of players’ relative age as possible (Loffing, 2016).

For both objectives, players from all three seasons were included to gain reliable results. This procedure is consistent with similar studies that analysed the RAE at high competition levels with typically small sample sizes (Romann & Fuchslocher, 2011; Till et al., 2010). Thus, the sample sizes of the U15 to U19 youth national team, for example, correspond to the number of players selected at least once for the corresponding team during the three examined seasons. Since the analyses focused on the structural influence of selection procedures on RAE development, we thereby accepted that, for instance, a player considered for the age category U15 in the season 2010/11 was repeatedly included in the analysis of the age category U16 in the following season.

Furthermore, some players are promoted at different selection levels within one season (e. g., youth academy players can play regional association tournaments and youth national team matches in the same season). We accepted that these players were simultaneously included in the subsamples of different selection levels within one age category to evaluate the practice in the status quo. The resulting number of cases per group and the corresponding birth distribution is shown in Table 1.
Table 1

Number of cases, relationship of birth month and birth frequency, birth distribution in birth quarters and extent of relative age effects for each group

Competition level

Age category

N

Birth distribution

RAE extent

Relationship birth month × birth frequency

(rs)

Percentage in birth quarters (%)

χ2

OR(half-years 1 vs. 2)

[95% CI]

1

(Jan–Mar)

2

(Apr–Jun)

3

(Jul–Sep)

4

(Oct–Dec)

Competence centre

U12

14,191

−0.99**

34.2

26.4

23.9

15.5

869.70**

1.53 [1.48; 1.59]

U13

11,928

−0.98**

34.2

26.1

24.1

15.6

734.47**

1.53 [1.47; 1.59]

U14

7686

−0.98**

34.5

26.6

24.0

14.9

516.08**

1.57 [1.49; 1.64]

U15

5004

−0.97**

35.3

26.4

23.5

14.8

416.24**

1.65 [1.56; 1.75]

Youth academy

U12

2004

−0.99**

41.4

27.2

19.9

11.4

367.95**

2.19 [1.99; 2.40]

U13

2187

−0.99**

40.8

27.7

19.2

12.3

381.11**

2.19 [2.00; 2.39]

U14

2503

−0.99**

43.3

26.5

18.7

11.4

541.64**

2.31 [2.12; 2.52]

U15

2586

−0.99**

43.9

26.8

18.7

10.6

615.10**

2.47 [2.27; 2.69]

U16

2577

−0.99**

44.5

26.2

18.9

10.5

650.35**

2.50 [2.30; 2.72]

U17

2243

−0.99**

43.6

25.9

19.1

11.4

524.77**

2.38 [2.18; 2.61]

U18

1702

−0.98**

42.2

26.5

20.1

11.2

359.36**

2.24 [2.02; 2.48]

U19

1296

−0.97**

40.0

24.6

21.1

14.3

184.43**

1.83 [1.63; 2.05]

Regional association

U15

1060

−0.97**

47.5

26.4

16.5

9.5

342.02**

2.91 [2.54; 3.34]

U16

1013

−0.98**

48.9

23.8

19.1

8.3

352.00**

2.76 [2.40; 3.17]

U17

1015

−0.99**

46.8

26.1

17.8

9.3

316.84**

2.81 [2.45; 3.23]

U18

1071

−0.97**

42.6

26.9

19.2

11.3

233.59**

2.32 [2.03; 2.64]

Youth national team

U15

390

−0.95**

53.1

24.4

15.6

6.9

183.99**

3.52 [2.78; 4.47]

U16

291

−0.91**

52.2

23.7

17.2

6.9

129.34**

3.28 [2.50; 4.29]

U17

167

−0.92**

47.9

26.9

18.6

6.6

59.85**

3.11 [2.19; 4.42]

U18

213

−0.94**

47.4

28.2

16.4

8.0

75.24**

3.15 [2.31; 4.31]

U19

177

−0.90**

45.2

26.0

17.5

11.3

47.23**

2.47 [1.79; 3.42]

**p < 0.01

RAE relative age effects, OR odds ratio, 95% CI 95% confidence interval

Statistical analyses were conducted with SPSS 21 (IBM) and Excel 2007 (Microsoft). The level of significance was fixed at α = 0.05 for all significance tests. As a preliminary analysis to show the relationship between relative age and observed birth frequencies, a Spearman rank correlation coefficient between month of birth and the respective birth frequency was calculated. A χ2 test (goodness-of-fit) examined the existence of a RAE. To prevent an increased type I risk in the goodness-of-fit test, the test compared the birth distributions in birth quarters of all examined groups with the expected birth distributions of all eligible German youth players from the corresponding birth years (Delorme & Champely, 2015). Thus, a possibly skewed birth distribution of all eligible youth players is considered (Delorme, Boiché, & Raspaud, 2010b). A χ2 test against a hypothetical equal distribution would result in considerable deviation in the χ2 values (difference of 0.4 to 136.9 points), without changing the main results of the significance tests however. The expected birth distributions were extracted from extended member statistics provided by the DFB (internal data request from 13 March 2011, data available as supplementary online material).

For the analyses of cross-sectional RAE differences between consecutive competition levels and age categories (objective I), odds-ratios (ORs) with 95% confidence intervals were calculated as effect sizes for the RAE extent in all groups (Cobley et al., 2009). The applied OR (H1:H2) displays the relative changes of being selected for players born in the first half of the year as compared to players born in the second half of the year. Therefore, the odds of players from the first half of the year (e. g., number of U12 competence centre players born in the first half year divided by the number of all eligible German U12 youth players born in the first half year) were divided by the odds of players from the second half of the year. ORs of 1.44, 2.48, and 4.27 were interpreted as small, medium and large effects, respectively, applying a transformation of commonly used limits for Cohen’s d (Borenstein, Hedges, Higgins, & Rothstein, 2011; Cohen, 1988). Significant RAE differences between consecutive competition levels or age categories were indicated by an OR outside the confidence interval limits of the lower competition level or previous age category, respectively.

For the longitudinal analyses of newly selected and retained players (objective II), the players’ selection pathways during the three examined seasons were tracked by re-identifying their name, birth date and club name on all examined squad lists. For the horizontal and diagonal selection pathways between two consecutive seasons, the data of two selection cycles between 2010/11 and 2011/12 as well as between 2011/12 and 2012/13 were combined. For the vertical selection pathways within one season, the two selection cycles within the season 2011/12 and within the season 2012/13 were summarized.

Fig. 2 shows that one group of retained players from the former age category (e. g., players retained from U12 youth academy to U13 youth academy) and one group of newly selected players from a lower competition level (e. g., newly selected from U12 competence centre to U13 youth academy) are combined into one resulting group (e. g., U13 youth academy). Retained youth academy players and players newly selected from the competence centres were examined over two selection cycles. The resulting group additionally includes a residual number of players from alternative (not examined) selection procedures.
Fig. 2

Exemplary design and results for the longitudinal analysis in objective II: players selected into the U13 youth academy. Proportions of selection procedures within the resulting group and change in relative age effects (RAE) extent of selected players compared with their previous competition level or their former age category. H1 percentage of births in first half-year

First, we analysed the proportion of retained and selected players within the resulting group to determine to which degree RAE emergence in the resulting group was affected by a change in RAE extent of retained players and by a change in RAE extent of newly selected players compared to their previous competition level. Together with an additional proportion of players from alternative selections, the proportions of retained and newly selected players sum up to 1.0.

Subsequently, to investigate a change in RAE through both selection procedures, we compared the RAE extent of the retained players with the RAE extent in their previous age category and the RAE extent of newly selected players with that of their previous competition level. As a descriptive single value for the RAE extent we used the percentage of births in the first half-year (H1). As a value for the change in RAE extent for selected players, we calculated the difference ∆H1 between the RAE extent of the selected players and the RAE extent in the players’ previous group.

For additional significance testing, χ2 (goodness-of-fit) tests revealed whether the birth distribution of the selected players (in half-years) differed significantly from the birth distribution of the players’ former groups. Small effects between these subsamples were to be expected because the former groups consisted of talent development programme players with an already existing RAE. In order to test these small effects with an appropriate test power of 1‑β = 0.90, large samples sizes of N = 1000 would be necessary (Faul, Erdfelder, Lang, & Buchner, 2007). The examined subgroups of selected players, however, were particularly small at high competition levels. Therefore, irrespective of the significance tests’ results, a difference of at least 5% in the percentage of births in the first half of the year (e. g., 55% in the former total group vs. 60% in the players selected from the former group) was considered a relevant change in RAE extent. Such a difference corresponds to a small effect of w = 0.10 in the χ2 test (Cohen, 1988).

Results

Table 1 shows the birth distribution for all examined groups. The preliminary analysis demonstrated existing RAEs in all examined groups. The Spearman rank correlation coefficient showed a clear, negative relationship between the month of birth and the birth frequency in each month (−0.99 ≤ rs ≤ −0.90, p < 0.01 each). Accordingly, the relative birth frequency per birth quarter steadily decreased from birth quarter one to birth quarter four (with values ranging from Q1: 34.2–53.1%, Q2: 23.7–28.2%, Q3: 15.6–24.1% to Q4: 6.6–15.6%) and significantly differed from the expected birth distribution of all eligible German youth players (47.23 ≤ χ2 ≤ 869.70, p < 0.05 each). The examined groups consisted of 60–77% relatively older players with birth dates between January and June, translating into RAEs with effect sizes ranging from small to medium-large (1.53 ≤ OR(H1:H2) ≤ 3.52) in all groups.

Cross-sectional RAE differences (objective I)

Overall, the differences in RAE extent between consecutive competition levels in Fig. 3 revealed a stepwise increase of RAE effect sizes in the corresponding order of competition levels with similar increase rates for all three steps. The RAE at the (higher) competition level youth academy (2.19 ≤ OR(H1:H2) ≤ 2.47) was distinctly larger than at the competence centre level (1.53 ≤ OR(H1:H2) ≤ 1.65) in each of the age categories U12 to U15. Similarly, in each age category U15 to U19, the RAEs increased from the youth academies (1.83 ≤ OR(H1:H2) ≤ 2.50) to the regional associations (2.32 ≤ OR(H1:H2) ≤ 2.91) and again to the youth national teams (2.47 ≤ OR(H1:H2) ≤ 3.52). These differences in the extent of RAE between consecutive competition levels were significant with few exceptions. Only the ORs of the U18 regional association and the U17 youth national team lay within and not above the confidence interval limits of the ORs at the previous competition level.
Fig. 3

Cross-sectional differences in relative age effects (RAE) extent (odds ratio with 95% confidence intervals) between consecutive age categories and competition levels. *p < 0.05

Altogether, the differences in RAE extent between consecutive age categories were considerably smaller and mostly nonsignificant. Nevertheless, a visible trend of a slight increase between consecutive age categories from U12 to U15 at the competence centres and youth academies and a decrease from U15 to U19 at the youth academies (from U16 to U19), regional associations and youth national teams was observed. The clearest RAE decreases were found between the second-oldest and oldest age categories at each competition level above the competence centres, reaching significance in two of three cases (decreasing RAE from U18 to U19 youth academies and from U17 to U18 regional associations).

Longitudinal analyses of newly selected and retained players (objective II)

To explain the complex pattern of results for objective II, Fig. 2 gives an illustrative example for the age category U13 at the youth academy competition level. The U13 youth academy group was assembled from 69% (proportion of 0.69) of players retained from the previous age category (U12 youth academy) and 19% newly selected players from the lower competition level (U12 competence centre), respectively. In all, 12% of the players in the resulting group came from alternative, not examined selection pathways (e. g., from amateur clubs to youth academies).

Players retained across the age categories U12 to U13 at the youth academy level hardly changed their RAE extent compared to their previous age category (∆H1 = −0.2% of births in the first half of the year). However, newly selected players for the U13 youth academies from the U12 competence centre level showed a relevant RAE increase of ∆H1 = +5% in players born in the first half-year, thereby contributing to the RAE increase between the competence centre level and the youth academies.

Table 2 shows the proportions of all newly selected and retained player groups. A major proportion of at least 56 to 82% of players in the resulting groups was retained from the former age category with only one exception (proportion of 0.47 in U18 youth national team). As a consequence, newly selected players from lower competition levels mostly represented smaller proportions (from 11 to 38%) of the resulting groups. Exceptions with higher proportions included the newly selected players for the age category U18 at the youth national team level (0.53) and the newly selected players for the U12 competence centres, U15 regional associations and U15 youth national teams (1.00, 0.65 and 1.00, respectively), in which no additional players from previous age categories were retained, per design.
Table 2

Proportion and change in relative age effects (RAE) extent for newly selected players from lower competition levels and players retained across age categories

Resulting group

(Seasons 2011/12 and 2012/13 combined)

Proportions of selected players

within resulting group

Change in RAE extent for selected players (RAE extent H1 in %)

Competition level

Age category

N

RAE extent

(H1 in %)

Retained

Newly selected

Alternative selections

Retained

Newly

selected

Alternative

selections

Competence centre

U12

9444

61.2

1.00

(61.2)

U13

8039

60.9

0.80

0.20

+0.6 (60.8)

(61.1)

U14

5180

61.3

0.82

0.18

+1.2 (60.7)

(64.1)

U15

3382

61.5

0.80

0.20

+0.1 (61.1)

(63.2)

Youth academy

U12

1322

68.8

1.00

(68.8)

U13

1450

68.5

0.69

0.19

0.12

−0.2 (69.6)

+5.0 (65.2)

(66.1)

U14

1671

68.5

0.63

0.21

0.16

+0.5 (68.6)

+6.0 (65.5)

(72.3)

U15

1734

71.6

0.68

0.15

0.17

+2.0 (72.7)

+15.5** (76.5)

(64.8)

U16

1736

70.5

0.71

0.11

0.18

+0.9 (71.0)

+7.2 (68.7)

(69.4)

U17

1497

68.8

0.75

0.25

+0.4 (70.0)

(65.3)

U18

1118

68.9

0.79

0.21

+0.5 (70.6)

(62.3)

U19

935

65.1

0.76

0.24

−1.3 (67.3)

(58.3)

Regional association

U15

703

76.5

0.65

0.35

+6.1* (77.7)

(74.3)

U16

650

74.3

0.63

0.21

0.16

+2.8 (75.7)

+4.8 (75.3)

(67.8)

U17

657

73.2

0.66

0.23

0.11

+1.4 (72.2)

+7.4 (76.2)

(72.5)

U18

711

67.9

0.56

0.25

0.19

+0.6 (73.0)

−8.6 (60.3)

(62.7)

Youth

national team

U15

251

81.0

1.00

+4.5 (81.0)

U16

197

76.7

0.62

0.38

+4.8 (82.5)

−7.2 (67.1)

U17

124

75.7

0.77

0.23

+0.2 (72.1)

+14.4 (87.6)

U18

147

75.6

0.47

0.53

+1.8 (78.3)

+5.3 (73.2)

U19

113

71.7

0.79

0.18a

0.03

−2.8 (72.0)

+5.9 (71.0)

(69.7)

*p < 0.05, **p < 0.01 for the χ2 (goodness-of-fit) test comparing the birth distribution of the selected players (in half-years) with the expected birth distribution in the previous group. H1 percentages of birth in the first half-year

In boldface: Change in RAE extent (H1) of at least 5%, whereby a 5% difference corresponds to a small effect in the χ2 test (Cohen, 1988)

aSelection pathway from U19 youth academy to U19 youth national team because U19 regional association does not exist

Considering the longitudinal changes in RAE extent of newly selected and retained players, overall, choosing newly selected players led to a relevant increase in RAE, whereas the RAE extent of retained players showed only minor changes. Among the retained players, the RAE extent did not change significantly compared to the previous age categories (χ2 ≤ 1.26, 0.22 ≤ p ≤ 0.97).

The analysis of newly selected players to higher competition levels resulted in an increase in RAE extent in 11 of 13 cases. In nine of these cases, the increase in percentages of players born in the first half-year was relevant (i. e., more than 5%). The underlying differences in the birth distribution compared with the former competition level were significant for the players newly selected for the age category U15 at the competition levels youth academy (χ2 = 13.20, p < 0.001) and regional association (χ2 = 4.20, p = 0.040).

Discussion

Given the pervasiveness of RAEs in youth football and the need to understand the causes of RAE development to derive specific and feasible reduction interventions, the current study focused on RAE development driven by selection procedures between consecutive competition levels and age categories within the German football talent development programme. Moving the state of current knowledge forward, the study presented results for the exact location of relevant changes in RAE extent. It revealed a significant stepwise increase in RAE extent between ascending competition levels. Overall, minor changes in RAE extent between consecutive age categories still revealed a systematic trend, with the exception of a decrease in the oldest age categories (objective I). Longitudinal analyses of the underlying selection procedures showed that newly selected players from lower to higher competition levels yielded an increase in the RAE extent of selected players, whereas the retention of players did not result in a change in RAE extent (objective II).

Cross-sectional RAE differences (objective I)

Considering the cross-sectional RAE differences between competition levels (in objective I), samples from other highly regarded football talent development programmes in England, Spain, France and Switzerland (Carling et al., 2009; Diaz Del Campo et al., 2010; Jimenez & Pain, 2008; Lovell et al., 2015; Romann & Fuchslocher, 2011) revealed similar RAE differences between youth national teams and youth academies. In addition to these findings, the current study’s strict separation of several competition levels and age categories showed that relevant changes in RAE extent take place between each of the consecutive competition levels in a similar amount and irrespective of age category.

With respect to the smaller and mostly nonsignificant cross-sectional RAE differences between age categories, other youth football studies showed similarly small differences for the age categories U11 to U18 (Diaz Del Campo et al., 2010; Helsen, Starkes, & Van Winckel, 1998). Despite the small differences, a trend of increasing RAEs from U12 to U15 and decreasing RAEs in the higher age categories was still visible at each competition level. Furthermore, the study design allowed for an unambiguous assignment of differences in RAE extent. Thus, the resulting trend across age categories is more reliable than in studies where, due to other research purposes, some confounding occurred (Cobley et al., 2009).

The most noticeable decrease in RAEs in this study between U18 and U19 was even more pronounced in another study examining the youth national teams participating in the UEFA championships in the year 2000 (U16: birth percentages in first half-year H1 = 73.2%, U18: 60.4%, U21: 49.7%) (Helsen et al., 2005). The study of Helsen et al. (2005), however, did not discuss whether the change in cut-off dates for some participating nations three years before the UEFA tournament, with a subsequent overlap of two different RAEs (Helsen, Starkes, & Van Winckel, 2000; Ostapczuk & Musch, 2013), contributed to the more pronounced RAE decrease between the U16 and U21 national teams.

Irrespective of differences in the degree of the RAE decrease, the attenuation of RAEs in older age categories found in youth football studies is in line with smaller but still existing RAEs (H1 = 57%) in all European professional football leagues in adulthood (Besson, Poli, & Ravenel, 2013). An attenuation of RAEs in older age categories and a higher probability of already selected relatively younger players of becoming professionals in adulthood has already been observed in other studies (Carling et al., 2009; Schorer et al., 2009). The results of these studies indicate that after reaching high competition levels in talent development programmes, relatively younger players have better long-term career chances than relatively older players. Competing against superior, relatively older opponents may provide relatively younger players with a beneficial training environment (Baker et al., 2010), resulting, for example, in the development of superior technical skills (Votteler & Höner, 2014). An additional benefit for relatively younger players may be the development of an advantageous psychological disposition (McCarthy, Collins, & Court, 2016). Nevertheless, these assumptions are rather speculative and should be more closely addressed in future research.

Longitudinal analyses of newly selected and retained players (objective II)

Research designs that longitudinally track players’ selection pathways to detect changes in RAE extent were not applied in previous RAE studies in youth football. The longitudinal analyses showed that newly selected players increased the extent of RAE compared to the lower competition level. In combination with the cross-sectional RAE differences between competition levels (objective I), the current study showed that RAE emergence in talent development programmes is an additive effect of tiered selection procedures irrespective of the examined age category.

Although the RAE increase between competition levels was of comparable extent, different mechanisms within each selection procedure may be responsible. The initial preference for relatively older players during selection from amateur levels has been frequently attributed to maturity-related performance advantages of relatively older players (Baker et al., 2010; Furley & Memmert, 2016; Meylan et al., 2010). These performance differences, however, become considerably smaller within the increasingly homogeneous group of already selected players in talent development programmes (Carling et al., 2009; Skorski, Skorski, Faude, Hammes, & Meyer, 2016; Votteler & Höner, 2014). Therefore, an additional increase of RAEs during consecutive selections should have further underlying mechanisms, such as an increased focus on contemporary performance differences caused by greater pressure to succeed in team competition at higher competition levels (Hill & Sotiriadou, 2016; Jimenez & Pain, 2008). Consistent with this assumption, relatively older teams playing in the highest German youth league are more successful compared with relatively younger teams (Augste & Lames, 2011; Grossmann & Lames, 2013).

The longitudinal analyses of retained players revealed major proportions of retained players with minor changes in the RAE extent. This result can easily be connected to the small RAE differences across age categories at each competition level found for objective I and is nearly identical to the results from Till et al. (2010) in UK rugby. Therefore, the rugby study’s conclusion that retention is a main mechanism of the persistence of RAE (Till et al., 2010) can be extended to youth football in the examined age categories U12 to U19 and at all competition levels. The persistent RAEs of retained players may reflect coaches’ increased awareness of already selected players or their self-confident opinion, having already selected the most talented players (Sherar, Baxter-Jones, Faulkner, & Russell, 2007).

A different theoretical explanation can be derived from Gagné’s theoretical model of talent development (Gagné, 2009), in which developmental support (e. g., top-level coaching) is an important aspect of systematically developing natural (football) giftedness into talent. In Gagné’s terms, additional talent promotion for groups with an existing RAE transforms a former uniform distribution of giftedness into a skewed distribution of talent (with more talented relatively older players). Thus, the retention of more relatively older players in consecutive age categories for all competition levels may simply reflect the actual distribution of talent at the corresponding competition level.

Consequences for RAE reduction interventions

Because of some unfairness (better chances for relatively older players to become professionals) and inefficiency (talent promotion for relatively older players with limited talent) in talent development programmes with an existing RAE (Dixon et al., 2011; Edgar & O’Donoghue, 2005), interventions to prevent or reduce RAEs are desirable. According to the preceding theoretical explanation, reduction interventions should aim at an early prevention of RAE emergence. Furthermore, the findings of this study point out that reduction measures should focus on newly selected players from lower competition levels in all age categories.

A common reduction proposition is to implement quotas for the birth distribution of selected players (Barnsley & Thompson, 1988). However, the results of the current study stress that a player quota aiming at a uniform distribution of selected players’ birth months is too simplistic and may have unintended negative consequences (Wattie, 2013).

With respect to the assumption of an already skewed distribution of talent (with more talented relatively older players) at higher competition levels, player quotas should consider the extent of RAE bias already present at the previous competition level. For example, at the competence centre level the existing RAE of about 60% of births in the first half-year should be regarded as the actual distribution of talent. Thus, quotas for the selection of new players from competence centres to youth academies should consider this RAE extent of 60% as a baseline. A deterministic baseline, however, does not fit well with the rather probabilistic disadvantage (i. e., some relatively younger players are promoted at higher competition levels) of relatively younger players (Wattie, 2013). Therefore, feasible quotas for practice should include enough freedom to consider that the birth distribution of gifted players in small groups does not necessarily follow the theoretical uniform distribution of giftedness.

Additionally, the group of selectable players gets even smaller when coaches have to select players, like goalkeepers, according to their playing position. Since coaches’ willingness to apply player quotas can be outweighed by various pressures to select certain players (Hill & Sotiriadou, 2016), quotas should consider the underlying conditions for the selecting coach (in clubs or associations).

Overall, the implementation of player quotas only provides a feasible and effective solution for reducing the extent of RAEs when the probabilistic nature and positional constraints for player selection as well as other factors influencing coaches’ selection strategy are considered. If the conditions for player quotas are not satisfactory (e. g., small number of selectable players), “human solutions” (Wattie, 2013, p. 13) to increase coaches’ awareness of players’ relative age, for example age-ordered numbering of players’ shirts (Mann & van Ginneken, 2017), should be preferred.

Furthermore, from a sports association’s perspective, some unfairness and inefficient distribution of talent promotion resources due to an existing RAE does not automatically translate into a less effective talent development programme. Indeed, recent international youth and adult successes demonstrated the talent development programmes of France, Germany, Spain and Switzerland to be effective in producing highly qualified youth players for the professional level despite an existing RAE (Carling et al., 2009; Jimenez & Pain, 2008; Romann & Fuchslocher, 2011).

In Germany, the enormous breadth of the programme guarantees developmental support for a high number of relatively younger players (e. g., approximately 2000 players from the fourth birth quarter in the U12 to U15 competence centres) and thereby reduces the risk of overlooking highly talented relatively younger players at that level (Votteler & Höner, 2014). Nevertheless, a reduction of RAEs should be considered with regard to further optimization of the distribution of financial and personal resources in talent development programmes. For example, a reduction of RAEs would mean that less time for training and the instruction of well-educated coaches is wasted on relatively older players with limited talent at lower competition levels.

Strengths and limitations

Overall strengths of the present study lie in its comprehensive, representative data set, and its examination of the whole German soccer developmental system. The results of the study were highly consistent and can be regarded as reliable and representative because the sample of 35,390 players is close to a total survey of all German talent development programme players from three seasons.

Limitations of this study derive from deviations between the examined structure of selection procedures and actual selection pathways in practice. The study examined only the most important and nationally representative selection pathways of systematic selections in the German talent development programme. Therefore, some pathways within the programme as well as nonsystematic selections between amateur clubs could not be considered. Most important may be the fact that the study design did not include the selection procedures between amateur clubs and the competence centres. However, these selection procedures covering the initial entrance into the talent development programme comprise several regional peculiarities (e. g., preceding selections for local district teams) and are therefore difficult to include in a consistent research design. Future research should more closely address the selection procedures between amateur clubs and the first stages of talent development programmes to understand how RAEs initially emerge.

Conclusion

This study is part of the ongoing process to extend RAE research beyond the initial proof of its existence to an explanation of its underlying causes. Despite three decades of RAE research, RAEs remain as persistent as ever (Helsen et al., 2012). Therefore, further knowledge about the causes of RAE development is necessary to provide specific and feasible scientific advice for a reduction of RAEs in practice. In this light, the current study assumed that selection processes between consecutive age categories and competition levels have an important role in the development of relative age effects in talent development programmes in youth football. Under this assumption, the study identified where relevant changes in RAE extent occur between consecutive competition levels and age categories within the German talent development programme. Furthermore, it showed how talent selection processes cause longitudinal changes in RAE extent.

Key findings of the study’s cross-sectional part were a stepwise increase in the extent of RAE across consecutive competition levels irrespective of the examined age category and minor changes between consecutive age categories at all competition levels. The study’s longitudinal analyses revealed that the choice of newly selected players for higher competition levels caused an increase in RAE extent whereas the retention of players from former age categories did not change the RAE extent. Overall, the study showed that the occurrence of RAEs in the German football talent development programme spans all age categories and competition levels and is caused by multiple tiered selection processes over time. These results were used to specify the suggestion of player quotas as a possible intervention to reduce RAEs in talent development programmes.

Notes

Acknowledgements

We would like to thank the staff of the DFB’s Department for Talent Development for general cooperation, support with additional data and productive discussions in several meetings.

Compliance with ethical guidelines

Conflict of interest

A. Votteler and O. Höner declare that they have no competing interests.

This article does not contain any studies with human participants or animals performed by any of the authors.

Supplementary material

12662_2017_457_MOESM1_ESM.docx (15 kb)
Expected Birth Distribution for the χ2 Test (Goodness-of-fit)

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Copyright information

© Springer-Verlag Berlin Heidelberg 2017

Authors and Affiliations

  1. 1.Institute of Sports ScienceEberhard Karls University of TübingenTübingenGermany

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