| Literature DB >> 35998177 |
Claude Simon1, Fraser Carson1,2, Irene Renate Faber3,4, Thorben Hülsdünker1,2.
Abstract
The relative age effect (RAE) is a well-established phenomenon in football. However, while the majority of previous studies focussed on established football nations, it remains unclear if the constraint of a limited population of soccer players in smaller countries associated with less strict selection procedures may reduce the risk of RAE. This study aims to investigate the RAE in Luxembourg that follows an 'open-door' selection policy in youth football due to the limited pool of players. Birthdates from all licensed and actively playing Luxembourgish youth footballers including all players of the youth national teams (396 girls and 10981 boys) competing in the season 2018/2019 were analysed and categorised into birth quarters and semesters. To further investigate a performance dependence of the RAE in amateur leagues, success was determined based on the teams' rankings at the end of the season. Differences between observed and expected birthdate distributions were calculated across all licensed players and age groups, within the national teams, and for the top- and bottom-tier football teams using chi-square statistics. While a RAE was absent across all age groups (except U7), significant RAEs with high effect sizes were observed in the top-level and national teams. These findings contrast the substantial RAE effects in large football nations and suggest that open selection systems might reflect an environmental constraint that limit the prevalence of RAE in football. Further, this study indicates that a performance dependence of the RAE is not limited to high level football but already occurs on an amateur level.Entities:
Mesh:
Year: 2022 PMID: 35998177 PMCID: PMC9398004 DOI: 10.1371/journal.pone.0273019
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.752
Overview of the female and male football players and the age categories in Luxembourgish youth football.
| Age group | n | Age |
|---|---|---|
| (1) | ||
| U7 ♂ | 1224 | 5.9 ± 0.5 |
| U9 ♂ | 2264 | 7.8 ± 0.6 |
| U11 ♂ | 1839 | 9.8 ± 0.6 |
| U13 ♂ | 1825 | 11.7 ± 0.6 |
| U15 ♂ | 1520 | 13.8 ± 0.6 |
| U17 ♂ | 1257 | 15.7 ± 0.6 |
| U19 ♂ | 1052 | 17.8 ± 0.6 |
| Subtotal U7 to U19 ♂ | 10981 | |
| U15 ♀ | 299 | 12.9 ± 1.2 |
| U19 ♀ | 97 | 16.5 ± 1.1 |
| Subtotal U15 to U19 ♀ | 396 | |
| Total | 11377 | |
| (2) | ||
| U12 ♂ | 55 | 11.3 ± 0.3 |
| U13 ♂ | 39 | 12.2 ± 0.5 |
| U14 ♂ | 33 | 13.3 ± 0.3 |
| U15 ♂ | 25 | 14.3 ± 0.3 |
| U16 ♂ | 25 | 15.2 ± 0.6 |
| U17 ♂ | 14 | 16.3 ± 0.3 |
| U19 ♂ | 29 | 17.7 ± 0.6 |
| Total | 220 | |
| (3) | ||
| U13 ♂ | 90 / 98 | 12.0 ± 0.6 / 11.7 ± 0.6 |
| U15 ♂ | 87 / 96 | 13.9 ± 0.6 / 13.7 ± 0.6 |
| U17 ♂ | 98 / 109 | 16.0 ± 0.5 / 15.6 ± 0.6 |
| U19 ♂ | 115 / 105 | 17.8 ± 0.6 / 17.7 ± 0.6 |
| Subtotal U13 to U19 ♂ | 390 / 408 | |
| U15 ♀ | 86 / 90 | 13.2 ± 1.2 / 12.7 ± 1.3 |
| Total | 476 / 498 |
♀ = female, ♂ = male, Values present mean ± standard deviation
Relative age effect analyses across age groups in Luxembourgish youth football.
| Birthdate distribution (%) | Odds Ratio (95% CI) | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Age group | N | Q1 | Q2 | Q3 | Q4 | χ2 | p | V | Q1 vs. Q4 | S1 vs. S2 |
|
| ||||||||||
| U7 ♂ | 1224 | 352 (28.76) | 330 (26.96) | 317 (25.90) | 225 (18.38) | 32.05 |
| 0.09 | 1.58 (1.25–1.99) | 1.28 (1.09–1.50) |
| U9 ♂ | 2264 | 630 (27.83) | 585 (25.84) | 565 (24.96) | 484 (21.38) | 17.88 |
| 0.05 | 1.26 (1.07–1.49) | 1.18 (1.05–1.33) |
| U11 ♂ | 1839 | 490 (26.64) | 438 (23.82) | 472 (25.67) | 439 (23.87) | 2.35 | 0.503 | 0.02 | 1.05 (0.88–1.26) | 1.04 (0.91–1.18) |
| U13 ♂ | 1825 | 445 (24.38) | 461 (25.26) | 493 (27.01) | 426 (23.34) | 4.85 | 0.183 | 0.03 | 1.09 (0.90–1.31) | 1.03 (0.91–1.17) |
| U15 ♂ | 1520 | 433 (28.49) | 362 (23.82) | 398 (26.18) | 327 (21.51) | 11.30 |
| 0.05 | 1.25 (1.02–1.53) | 1.08 (0.93–1.24) |
| U17 ♂ | 1257 | 334 (26.57) | 331 (26.33) | 305 (24.26) | 287 (22.83) | 5.14 | 0.162 | 0.04 | 1.15 (0.92–1.44) | 1.13 (0.97–1.32) |
| U19 ♂ | 1052 | 290 (27.57) | 269 (25.57) | 256 (24.33) | 237 (22.53) | 6.57 | 0.087 | 0.05 | 1.18 (0.92–1.51) | 1.11 (0.94–1.32) |
| U15 ♀ | 299 | 81 (27.09) | 77 (25.75) | 66 (22.07) | 75 (25.08) | 3.07 | 0.382 | 0.06 | 1.10 (0.70–1.72) | 1.15 (0.83–1.59) |
| U19 ♀ | 97 | 20 (20.62) | 24 (24.74) | 27 (27.84) | 26 (26.80) | 1.25 | 1.248 | 0.07 | 0.77 (0.34–1.73) | 0.81 (0.46–1.43) |
| Total | 11377 | 3075 (26.44) | 2877 (25.34) | 2899 (25.36) | 2526 (22.86) | 45.43 |
| 0.04 | 1.20 (1.11–1.29) | 1.11 (1.05–1.16) |
♀ = female; ♂ = male; Q1-4, quarter; S1-2, semester; χ2, Chi-squared; df, degrees of freedom; p, significance
V, Cramer’s V; RP, reference population; Bold = Significant at an alpha of p < 0.05
* Significant OR
Relative age effect analyses across Luxembourgish national teams.
| ♂ | Birthdate distribution (%) | Odds Ratio (95% CI) | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Age group | N | Q1 | Q2 | Q3 | Q4 | χ2 | p | V | Q1 vs. Q4 | S1 vs. S2 |
| (df = 3) | ||||||||||
| U12 | 55 | 17 (30.91) | 16 (29.09) | 16 (29.09) | 6 (10.91) | 6.64 | 0.084 | 0.20 | 3.05 (0.92–10.11) | 1.62 (0.76–3.45) |
| U13 | 39 | 16 (41.03) | 10 (25.64) | 6 (15.38) | 7 (17.95) | 6.21 | 0.102 | 0.23 | 2.29 (0.66–7.96) | 2.11 (0.84–5.26) |
| U14 | 33 | 13 (39.39) | 9 (27.27) | 6 (18.18) | 5 (15.15) | 3.48 | 0.324 | 0.19 | 2.31 (0.57–9.41) | 1.78 (0.66–4.78) |
| U15 | 25 | 8 (32.00) | 9 (36.00) | 4 (16.00) | 4 (16.00) | 4.12 | 0.249 | 0.23 | 2.00 (0.38–10.41) | 2.30 (0.73–7.27) |
| U16 | 25 | 9 (36.00) | 10 (40.00) | 5 (20.00) | 1 (4.00) | 7.12 | 0.068 | 0.31 | 9.00 (0.85–94.9) | 2.92 (0.87–9.78) |
| U17 | 14 | 5 (35.71) | 3 (21.43) | 5 (35.71) | 1 (7.14) | 2.64 | 0.451 | 0.25 | 5.00 (0.34–72.77) | 1.56 (0.34–7.11) |
| U19 | 29 | 14 (48.28) | 5 (17.24) | 5 (17.24) | 5 (17.24) | 10.13 |
| 0.34 | 2.80 (0.65–12.09) | 1.90 (0.67–5.42) |
| Total | 220 | 82 (37.62) | 62 (28.10) | 47 (21.66) | 29 (12.63) | 27.90 |
| 0.21 | 2.78 (1.57–4.90) | 1.91 (1.30–2.81) |
♂ = male; Q1-4, quarter; S1-2, semester; χ2, Chi-squared; df, degrees of freedom; p, significance
V, Cramer’s V; Bold = Significant at an alpha of p < 0.05
* Significant OR
Fig 1Male and female player distribution across age groups.
(A) Distribution of male (black) and female (red) players in the whole population of Luxembourgish football players. (B) Player distribution across birth quarters in the Luxembourgish national teams. Data points reflect average values across age groups.
Relative age effect analyses of the top-6 and bottom-6 teams.
| Birthdate distribution (%) | Odds Ratio (95% CI) | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Age group | N | Q1 | Q2 | Q3 | Q4 | χ2 | p | V | Q1 vs. Q4 | S1 vs. S2 |
| (df = 3) | ||||||||||
| Top– 6 teams | ||||||||||
| U13 ♂ | 90 | 32 (35.56) | 26 (28.89) | 18 (20.00) | 14 (15.56) | 9.88 |
| 0.19 | 2.39 (1.01–5.64) | 1.89 (1.04–3.44) |
| U15 ♂ | 87 | 39 (44.83) | 19 (21.84) | 11 (12.64) | 18 (20.69) | 19.47 |
| 0.27 | 2.07 (0.91–4.69) | 1.95 (1.06–3.61) |
| U17 ♂ | 98 | 29 (29.59) | 34 (34.69) | 21 (21.43) | 14 (14.29) | 9.09 |
| 0.18 | 2.07 (0.88–4.86) | 1.80 (1.02–3.19) |
| U19 ♂ | 115 | 38 (33.04) | 32 (27.83) | 18 (15.65) | 27 (23.48) | 8.51 |
| 0.16 | 1.36 (0.66–2.80) | 1.53 (0.91–2.58) |
| Subtotal ♂ | 390 | 138 (35.38) | 111 (28.46) | 68 (17.44) | 73 (18.72) | 35.16 |
| 0.17 | 1.91 (1.28–2.85) | 1.77 (1.33–2.35) |
| U15 ♀ | 86 | 29 (33.72) | 20 (23.26) | 17 (19.77) | 20 (23.26) | 4.41 | 0.220 | 0.13 | 1.45 (0.63–3.33) | 1.32 (0.73–2.41) |
| Total | 476 | 167 (35.08) | 131 (27.52) | 85 (17.86) | 93 (19.54) | 37.98 |
| 0.16 | 1.78 (1.24–2.55) | 1.67 (1.29–2.17) |
| Bottom– 6 teams | ||||||||||
| U13 ♂ | 98 | 25 (25.51) | 29 (29.59) | 18 (18.37) | 26 (26.53) | 3.08 | 0.379 | 0.10 | 1.00 (0.46–2.19) | 1.28 (0.73–2.24) |
| U15 ♂ | 96 | 21 (21.88) | 22 (22.92) | 28 (29.17) | 25 (26.04) | 1.08 | 0.783 | 0.06 | 0.81 (0.36–1.82) | 0.81 (0.46–1.43) |
| U17 ♂ | 109 | 33 (30.28) | 21 (19.27) | 32 (29.36) | 23 (21.10) | 4.00 | 0.261 | 0.11 | 1.38 (0.65–2.95) | 0.96 (0.57–1.64) |
| U19 ♂ | 105 | 23 (21.90) | 26 (24.76) | 34 (32.38) | 22 (20.95) | 2.34 | 0.505 | 0.09 | 1.05 (0.47–2.34) | 0.88 (0.51–1.50) |
| Subtotal ♂ | 408 | 102 (25.00) | 98 (24.02) | 112 (27.45) | 96 (23.53) | 0.60 | 0.897 | 0.02 | 1.04 (0.70–1.54) | 0.96 (0.73–1.27) |
| U15 ♀ | 90 | 28 (31.11) | 27 (30.00) | 14 (15.56) | 21 (23.33) | 6.61 | 0.086 | 0.16 | 1.33 (0.59–3.02) | 1.57 (0.87–2.84) |
| Total | 498 | 130 (26.10) | 125 (25.10) | 126 (25.30) | 117 (23.49) | 0.60 | 0.896 | 0.02 | 1.09 (0.77–1.56) | 1.06 (0.83–1.36) |
♀ = female; ♂ = male; Q1-4, quarter; S1-2, semester; χ2, Chi-squared; df, degrees of freedom; p, significance
V, Cramer’s V; Bold = Significant at an alpha of p < 0.05; * Significant OR
Fig 2Male and female player distribution for top and bottom teams.
Distribution of football male (black) and female (red) players across birth quarters in the top (A) and bottom (B) teams of the Luxemburgish football leagues. Data points reflect average values across age groups.
Comparison of birthdate distribution between top-6 and bottom-6 teams.
| Performance* Quarter Crosstabulation | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|
| ♂ | Quarter | Total | ||||||||
| Q1 | Q2 | Q3 | Q4 | |||||||
| Performance | Top | Count | 138 | 111 | 68 | 73 | 390 | |||
| % within Performance | 35.40% | 28.50% | 17.40% | 18.70% | 100.00% | |||||
| Adjusted Residual | 3.198 | 1.427 | -3.384 | -1.663 | ||||||
| Bottom | Count | 102 | 98 | 112 | 96 | 408 | ||||
| % within Performance | 25.00% | 24.00% | 27.50% | 23.50% | 100.00% | |||||
| Adjusted Residual | -3.198 | -1.427 | 3.384 | 1.663 | ||||||
| Total | Count | 240 | 209 | 180 | 169 | 798 | ||||
| % within Performance | 30.10% | 26.20% | 22.60% | 21.20% | 100.00% | |||||
| Statistics | z-score | 3.198 | 1.427 | -3.384 | -1.663 | |||||
| χ2 | 10.23 | 2.04 | 11.45 | 2.77 | ||||||
| p |
| 0.614 |
| 0.385 | ||||||
| V | 0.065 | 0.029 | 0.069 | 0.034 | ||||||
♂ = male; Q1-4, quarter; χ2, Chi-squared; p, significance; V, Cramer’s V
Bold = Significant at an alpha of p < 0.05