Submitted:
12 December 2024
Posted:
16 December 2024
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Abstract
The aim of this study was to investigate the relative age effect (RAE) in junior padel players participating in the 2024 European Junior Championships by Teams. The sample comprised 285 junior athletes (165 boys from 16 boys’ teams, and 120 girls from 12 girls’ teams). Dates of birth were categorized into quartiles. Data analysis included Chi2 goodness-of-fit tests, Fisher’s exact goodness-of-fit tests, Chi2 tests, Fisher’s exact tests with Monte Carlo correction (95% CI), and Spearman correlations. Results indicated no consistent RAE overall. However, in boys, a higher proportion of players were born in Q1 (CSR = 2.2), and in the last year of eligibility (CSR = 2.0), in the highest-ranked teams. Additionally, position correlated directly with both quartile (boys: p = 0.015; girls: p = 0.001) and category year (boys: p = 0.032; girls: p = 0.038). These findings provide new insights into how RAE and multi-year age categories influence talent identification in junior padel, highlighting the need for equitable selection strategies such as adjusted age classifications.
Keywords:
1. Introduction
2. Materials and Methods
2.1. Sample
2.2. Study Variables
- o
- Sex: The sex of the players, classified into two categories: boys and girls.
- o
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Year category: This variable specifies the player's birth year relative to the eligibility range within each age category. It distinguishes between players born in:
- Last possible year for the age category (e.g., 2013 for U14, 2011 for U16, and 2009 for U18).
- Second last possible year (e.g., 2012 for U14, 2010 for U16, and 2008 for U18).
- Third last possible year (e.g., 2011 for U14, 2009 for U16, and 2007 for U18).
- Fourth last possible year (e.g., 2010 for U14, 2008 for U16, and 2006 for U18).
- o
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Quartile: Players' birthdates were divided into quartiles based on their birth month within a calendar year:
- Q1: January to March.
- Q2: April to June.
- Q3: July to September.
- Q4: October to December.
- o
- Position: The final ranking of the team at the conclusion of the championship. This variable was used to investigate the relationship between team performance and player selection based on relative age. Teams were categorized by their final standing, with special focus on the top teams and the bottom teams.
2.3. Procedure
2.4. Statistical Analysis
3. Results
4. Discussion
- Strengths, limitations and future studies
- Practical Applications
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Conflicts of Interest
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| Number and (%) of young athletes per quartile | χ2 | p | ||||||
|---|---|---|---|---|---|---|---|---|
| Q1 | Q2 | Q3 | Q4 | Total | ||||
| All athletes | 70 (24.6) | 79 (27.7) | 78 (27.4) | 58 (20.4) | 285 | 3.968 | 0.265 | |
| By sex | ||||||||
| Male | 35 (21.2) | 44 (26.7) | 48 (29.1) | 38 (23.0) | 165 | 2.491 | 0.477 | |
| Female | 35 (29.2) | 35 (29.2) | 30 (25.0) | 20 (16.7) | 120 | 5.000 | 0.172 | |
| Boys | ||||||||
| Position | Country | |||||||
| 1 | Spain | 5 (41.7) | 2 (16.7) | 0 (0.0) | 5 (41.7) | 12 | 1.500 | 0.622 |
| 2 | France | 3 (30.0) | 5 (50.0) | 1 (10.0) | 1 (10.0) | 10 | 4.400 | 0.261 |
| 3 | Sweden | 1 (8.3) | 4 (33.3) | 7 (58.3) | 0 (0.0) | 12 | 4.500 | 0.115 |
| 4 | Belgium | 3 (30.0) | 4 (40.0) | 2 (20.0) | 1 (10.0) | 10 | 2.000 | 0.720 |
| 5 | Italy | 3 (25.0) | 3 (25.0) | 2 (16.7) | 4 (33.3) | 12 | 0.667 | 0.978 |
| 6 | Portugal | 5 (41.7) | 0 (0.0) | 3 (25.0) | 4 (33.3) | 12 | 0.500 | 0.935 |
| 7 | Netherlands | 4 (33.3) | 3 (25.0) | 4 (33.3) | 1 (8.3) | 12 | 2.000 | 0.705 |
| 8 | Estonia | 0 (0.0) | 2 (33.3) | 2 (33.3) | 2 (33.3) | 6 | 0.000 | 1.000 |
| 9 | Denmark | 3 (50.0) | 2 (33.3) | 0 (0.0) | 1 (16.7) | 6 | 1.000 | 0.877 |
| 10 | Lithuania | 0 (0.0) | 5 (62.5) | 2 (25.0) | 1 (12.5) | 8 | 3.250 | 0.296 |
| 11 | Finland | 2 (16.7) | 2 (16.7) | 7 (58.3) | 1 (8.3) | 12 | 7.333 | 0.065 |
| 12 | Switzerland | 1 (11.1) | 1 (11.1) | 3 (33.3) | 4 (44.4) | 9 | 3.000 | 0.481 |
| 13 | Austria | 1 (9.1) | 1 (9.1) | 7 (63.6) | 2 (18.2) | 11 | 9.000 | 0.032* |
| 14 | Norway | 2 (22.2) | 3 (33.3) | 2 (22.2) | 2 (22.2) | 9 | 0.333 | 1.000 |
| 15 | Germany | 0 (0.0) | 2 (16.7) | 4 (33.3) | 6 (50.0) | 12 | 2.000 | 0.424 |
| 16 | Hungary | 2 (16.7) | 5 (41.7) | 2 (16.7) | 3 (25.0) | 12 | 2.000 | 0.705 |
| Girls by country | ||||||||
| Position | Country | |||||||
| 1 | Spain | 7 (58.3) | 4 (33.3) | 1 (8.3) | 0 (0.0) | 12 | 4.500 | 0.115 |
| 2 | Italy | 6 (50.0) | 4 (33.3) | 1 (8.3) | 1 (8.3) | 12 | 6.000 | 0.130 |
| 3 | Portugal | 4 (33.3) | 2 (16.7) | 2 (16.7) | 4 (33.3) | 12 | 1.333 | 0.780 |
| 4 | France | 2 (20.0) | 5 (50.0) | 2 (20.0) | 1 (10.0) | 10 | 3.600 | 0.431 |
| 5 | Belgium | 1 (16.7) | 3 (50.0) | 2 (33.3) | 0 (0.0) | 6 | 1.000 | 0.877 |
| 6 | Sweden | 2 (16.7) | 2 (16.7) | 7 (58.3) | 1 (8.3) | 12 | 7.333 | 0.065 |
| 7 | Netherlands | 4 (40.0) | 3 (30.0) | 0 (0.0) | 3 (30.0) | 10 | 0.200 | 1.000 |
| 8 | Estonia | 3 (42.9) | 2 (28.6) | 1 (14.3) | 1 (14.3) | 7 | 1.571 | 0.846 |
| 9 | Finland | 2 (25.0) | 3 (37.5) | 2 (25.0) | 1 (12.5) | 8 | 1.000 | 0.962 |
| 10 | Hungary | 0 (0.0) | 2 (20.0) | 6 (60.0) | 2 (20.0) | 10 | 3.200 | 0.242 |
| 11 | Germany | 2 (16.7) | 3 (25.0) | 5 (41.7) | 2 (16.7) | 12 | 2.000 | 0.705 |
| 12 | Czech Republic | 2 (22.2) | 2 (22.2) | 1 (11.1) | 4 (44.4) | 9 | 2.111 | 0.654 |
| Note. *p < 0.05 | ||||||||
| Boys | |||||||||
|---|---|---|---|---|---|---|---|---|---|
| Rank 1-8 | Rank 9-16 | ||||||||
| n | % | CSR | n | % | CSR | ||||
| Q1 | 24 | 27.9a | 2.2 | 11 | 13.9b | -2.2 | |||
| Q2 | 23 | 26.7 | 0.0 | 21 | 26.6 | 0.0 | |||
| Q3 | 21 | 24.4 | -1.4 | 27 | 34.2 | 1.4 | |||
| Q4 | 18 | 20.9 | -0.7 | 20 | 25.3 | 0.7 | |||
| Girls | |||||||||
| Rank 1-6 | Rank 7-12 | ||||||||
| n | % | CSR | n | % | CSR | ||||
| Q1 | 25 | 35.2 | 1.8 | 10 | 20.4 | -1.8 | |||
| Q2 | 22 | 31.0 | 0.5 | 13 | 26.5 | -0.5 | |||
| Q3 | 16 | 22.5 | -0.8 | 14 | 28.6 | 0.8 | |||
| Q4 | 8 | 11.3 | -1.9 | 12 | 24.5 | 1.9 | |||
| Note. n: number; % percentage; CSR: corrected standard residuals; CSR > 1.96: Bold; a, b = indicate significant differences in the Z tests for comparison of column proportions from p < 0.05 adjusted according to Bonferroni. | |||||||||
| Boys | ||||||
|---|---|---|---|---|---|---|
| Rank 1-8 | Rank 9-16 | |||||
| n | % | CSR | n | % | CSR | |
| Last year | 62 | 72.1a | 2.0 | 45 | 57.0b | -2.0 |
| Second last year | 23 | 26.7 | -1.0 | 27 | 34.2 | 1.0 |
| Third last year | 1 | 1.2 | -1.8 | 5 | 6.3 | 1.8 |
| Fourth last year | 0 | 0.0 | -1.5 | 2 | 2.5 | 1.5 |
| Girls | ||||||
| Rank 1-6 | Rank 7-12 | |||||
| n | % | CSR | n | % | CSR | |
| Last year | 43 | 60.6 | 1.3 | 24 | 49.0 | -1.3 |
| Second last year | 27 | 38.0 | -0.5 | 21 | 42.9 | 0.5 |
| Third last year | 0 | 0.0a | -2.1 | 3 | 6.1b | 2.1 |
| Fourth last year | 1 | 1.4 | -0.3 | 1 | 2.0 | 0.3 |
| Note. n: number; % percentage; CSR: corrected standard residuals; CSR > 1.96: Bold; a, b = indicate significant differences in the Z tests for comparison of column proportions from p < 0.05 adjusted according to Bonferroni. | ||||||
| Boys | |||
|---|---|---|---|
| Variable | Position | Quartile | Category year |
| Position | 1 | 0.188* | 0.167* |
| Quartile | 1 | -0.071 | |
| Category year | 1 | ||
| Girls | |||
| Variable | Position | Quartile | Category year |
| Position | 1 | 0.304** | 0.190* |
| Quartile | 1 | 0.043 | |
| Category year | 1 | ||
| Note. *p < 0.05; **p < 0.01 | |||
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