Relative Age Effects (RAEs) refer to the selection and performance differentials between children and youth who are categorized in annual-age groups. In the context of Swiss 60m athletic sprinting, ...7761 male athletes aged 8 - 15 years were analysed, with this study examining whether: (i) RAE prevalence changed across annual age groups and according to performance level (i.e., all athletes, Top 50%, 25% & 10%); (ii) whether the relationship between relative age and performance could be quantified, and corrective adjustments applied to test if RAEs could be removed. Part one identified that when all athletes were included, typical RAEs were evident, with smaller comparative effect sizes, and progressively reduced with older age groups. However, RAE effect sizes increased linearly according to performance level (i.e., all athletes - Top 10%) regardless of age group. In part two, all athletes born in each quartile, and within each annual age group, were entered into linear regression analyses. Results identified that an almost one year relative age difference resulted in mean expected performance differences of 10.1% at age 8, 8.4% at 9, 6.8% at 10, 6.4% at 11, 6.0% at 12, 6.3% at 13, 6.7% at 14, and 5.3% at 15. Correction adjustments were then calculated according to day, month, quarter, and year, and used to demonstrate that RAEs can be effectively removed from all performance levels, and from Swiss junior sprinting more broadly. Such procedures could hold significant implications for sport participation as well as for performance assessment, evaluation, and selection during athlete development.
Relative age effects (RAE) generate consistent participation inequalities and selection biases in sports. The study aimed to investigate RAE across all sports of the national Swiss talent development ...programme (STDP). In this study, 18 859 youth athletes (female N = 5353; mean age: 14.8 ± 2.5 y and male N = 13 506; mean age: 14.4 ± 2.4 y) in 70 sports who participated in the 2014 competitive season were evaluated. The sample was subdivided by sex and the national level selection (NLS, N = 2464). Odds ratios (ORs) of relative age quarters (Q1-Q4) and 95% confidence intervals (CI) were calculated. In STDP, small RAE were evident for females (OR 1.35 (95%-CI 1.24, 1.47)) and males (OR 1.84 (95%-CI 1.74, 1.95)). RAE were similar in female NLS athletes (OR 1.30 (95%-CI 1.08, 1.57)) and larger in male NLS athletes (OR 2.40 (95%-CI 1.42, 1.97)) compared to athletes in the lower selection level. In STDP, RAE are evident for both sexes in several sports with popular sports showing higher RAE. RAE were larger in males than females. A higher selection level showed higher RAE only for males. In Switzerland, talent identification and development should be considered as a long-term process.
An the recent article by Baker and Wattie (2018), they provided an update on the widely cited review of “Innate Talent” by Howe, Davidson and Sloboda (1998). The article summarizes that the defined ...criteria for “Innate Talent” are still valid, standing the test of time. However, new findings in epigenetics should be considered. The epigenome interacts with environmental factors, such as physical exercise, contributing to phenotypical and performance differences of the same gene. In this context, researchers in sport science face the task of defining ethical standards that are accepted by society. From an epigenetic perspective, one should refrain from thinking that genetics have a fixed performance outcome, since the epigenome is adaptable. Instead, research and practice should consider how created environments support athlete development.
Bio-banding (BB) has been introduced to account for varying maturity and to improve the talent development of junior soccer players. To date, research that investigated the physiological and ...technical effects of BB is sparse. Therefore, the aim of the study was to compare effects of BB with CA on selected technical and tactical parameters in U13 and U14 soccer players.
BB significantly increased the number of duels (p = 0.024) and set pieces (p = 0.025) compared to chronological age. The mean time of ball possession per action was reduced (p = 0.021) and the rate of successful passes was lower with BB (p = 0.001). Meanwhile, the total number of passes was unaffected (p = 0.796), and there was a trend towards a lower difference in ball possession between BB teams (p = 0.058). In addition, BB reduced the distances covered while jogging (p = 0.001), running (p = 0.038) and high-speed running (p = 0.035). With BB, an increased number of duels, unsuccessful passes and set pieces resulted in a quicker change of match play situations between teams. While physical demand was reduced, BB seems to result in a more technically and tactically challenging game. Benefits in long-term player development, however, require further investigation.
(1) Generate accurate estimates of the relationship between decimal age (i.e., chronological and relative) with swimming performance based on longitudinal data. (2) Determine whether corrective ...adjustment procedures can remove Relative Age Effects (RAEs) from junior/youth swimming.
Longitudinal and repeated years of cross-sectional performance data were examined.
(1) Participants were 553 male 100m Freestyle swimmers (10–18 years) who participated in ≥five annual events between 1999–2017. Growth curve modelling quantified the relationship between age and swimming performance, permitting corrective adjustment calculations. (2) Participants were N=2141 male 100m Freestyle swimmers (13–16 years) who swam at state/national events in 2015–2017. Relative age distributions for ‘All’, ‘Top 50%’, ‘25%’ and ‘10%’ of swimming times were examined based on raw and correctively adjusted swim times. Chi-square, Cramer’s V and Odds Ratios (OR) determined whether relative age (quartile) inequalities existed according to age-groups, selection level and correctively adjusted swim times.
Based on raw swim times, for ‘All’ swimmers RAEs was evident at 13 and 14 years-old and dissipated thereafter. But, RAE effect sizes substantially increased with selection level, with large-medium effects between 13–15 years-old (e.g., 15 years — Top 50% Q1v Q4 OR=2.28; Top 10%=6.02). However, when correctively adjusted swim times were examined, RAEs were predominantly absent across age-group and selection levels.
With accurate longitudinal reference data, corrective adjustment procedures effectively removed RAEs from 100m Freestyle swimming performance, suggesting the potential to improve swimming participation experience and performance evaluation.
Inter-individual differences in maturation-associated development can lead to variations in physical performance, resulting in performance (dis)advantages and maturation selection bias within youth ...sport systems. To address such bias and account for maturational differences, Maturation-based Corrective Adjustment Procedures (Mat-CAPs) could be beneficial. The present study aimed to: (1) determine maturity timing distributions in youth female swimming; (2) quantify the relationship between maturation status and 100-m front-crawl (FC) performance; (3) implement Mat-CAPs to remove maturational influences upon swimming performance. For Aim 1 and 2, participants were 663 female (10–15 years) swimmers who participated in 100-m FC events at Australian regional, state, and national-level competitions between 2016–2020 and underwent anthropometric assessment (mass, height and sitting height) to estimate maturity timing and offset. For Aim 3, participants aged 10–13 years were categorised into maturity timing categories. Maturity timing distributions for Raw (‘All’, ‘Top 50%’ and ‘Top 25%’) and Correctively Adjusted swim times were examined. Chi-square, Cramer’s
V
and Odds Ratios determined the presence of maturation biases, while Mat-CAPs identified whether such biases were removed in targeted age and selection-groups. Results identified that between 10–13 years, a significantly higher frequency of ‘early’ maturers was apparent, although tapered toward higher frequencies of ‘Late-normative’ maturers by 14–15 years. A curvilinear relationship between maturity-offset and swim performance was identified (
R
2
=
0.51, p<0.001) and utilised for Mat-CAPs. Following Mat-CAPs application, maturity timing biases evident in affected age-groups (10–13 years), and which were magnified at higher selection levels (‘Top 50%’ & ‘25%’ of swim performances) were predominantly removed. Findings highlight how maturation advantages in females occurred until approximately 13 years old, warranting restricted Mat-CAPs application. Mat-CAPS has the potential to improve female swimmer participation experiences and evaluation.
To determine the prevalence, magnitude and transient patterning of Relative Age Effects (RAEs) according to sex and stroke event across all age-groups at the Australian National age swimming ...Championships.
Repeated years of cross-sectional participation data were examined.
Participants were 6014 unique male (3185) and female (2829) swimmers (aged 12–18 years) who participated in Freestyle (50, 400m) and/or Breaststroke (100, 200m) at the National age swimming Championships between 2000–2014 (inclusive). RAE prevalence, magnitude and transience were determined using Chi-square tests and Cramer’s V estimates for effect size. Odds Ratios (OR) and 95% Confidence Intervals (CI) examined relative age quartile discrepancies. These steps were applied across age-groups and according to sex and each stroke event.
Consistent RAEs with large-medium effect sizes were evident for males at 12–15 years of age respectively, and with large-medium effects for females at 12–14 respectively across all four swimming strokes. RAE magnitude then consistently reduced with age across strokes (e.g., Q1 vs. Q4 OR range 16year old males=0.94–1.20; females=0.68–1.41). With few exceptions, by 15–16 years RAEs had typically dissipated; and by 17–18 years, descriptive and significant inverse RAEs emerged, reflecting overrepresentation of relatively younger swimmers.
Performance advantages associated with relative age (and thereby likely growth and maturation) are transient. Greater consideration of transient performance and participation in athlete development systems is necessary. This may include revising the emphasis of sport programmes according to developmental stages and delaying forms of athlete selection to improve validity.
As young football players develop important technical and tactical skills during competitive matches, this study investigated quantity and quality of technical and tactical actions in real game ...conditions in a 4v4 compared to the traditional 7v7 match format. In total, three matches of each format were played by 103 young football players (10.3±0.6 years) and video monitored for subsequent manual tagging of technical and tactical events. Based on the number of technical and tactical actions in the 7v7 matches, players were classified as dominant or non-dominant and changes in these subgroups were assessed during the 4v4 match format. The 4v4 match format significantly (P<0.001) increased total number of actions per player per minute compared to the 7v7 matches (5.59±1.44 and 2.78±0.73, respectively) and the number of successful (2.88±0.92 and 1.15±0.49, respectively) and unsuccessful (1.05±0.42 and 0.67±0.23, respectively) actions. Both dominant and non-dominant players increased their number of actions during the 4v4 compared to 7v7 match format. Despite a missing significant interaction effect, there was a larger percentage increase in number of actions for the non-dominant players (143%) compared to dominant players (72%) in 4v4. The 4v4 match format shows twice as many technical and tactical actions in real game conditions and, therefore, may improve players' skill development.
While talent development and the contributing factors to success are hardly discussed among the experts in the field, the aim of the study was to investigate annual variation in competition ...performance (AVCP), number of races per year, and age, as potential success factors for international swimming competitions. Data from 40'277 long-course races, performed by all individual female starters (n = 253) at the 2018 European Swimming Championships (2018EC) for all 10 years prior to these championships, were analyzed. Relationships between 2018EC ranking and potential success factors, i.e., AVCP, number of races per year, and age, were determined using Pearson's correlation coefficient and multiple linear regression analysis. While AVCP was not related to ranking, higher ranked swimmers at the 2018EC swam more races during each of the ten years prior to the championships (P < 0.001). Additionally, older athletes were more successful (r = -0.42, P < 0.001). The regression model explained highly significant proportions (P < 0.001) and 43%, 34%, 35%, 49% of total variance in the 2018EC ranking for 50m, 100m, 200m, and 400m races, respectively. As number of races per year (β = -0.29 --0.40) had a significant effect on ranking of 50-400m races, and age (β = -0.40 --0.61) showed a significant effect on ranking over all race distances, number of races per year and age may serve as success factors for international swimming competitions. The larger number of races swum by higher ranked female swimmers may have aided long-term athlete development regarding technical, physiological, and mental skill acquisitions. As older athletes were more successful, female swimmers under the age of peak performance, who did not reach semi-finals or finals, may increase their chances of success in following championships with increased experience.
Abstract
To provide percentile curves for short-course swimming events, including 5 swimming strokes, 6 race distances, and both sexes, as well as to compare differences in race times between ...cross-sectional analysis and longitudinal tracking, a total of 31,645,621 race times of male and female swimmers were analyzed. Two percentile datasets were established from individual swimmers’ annual best times and a two-way analysis of variance (ANOVA) was used to determine differences between cross-sectional analysis and longitudinal tracking. A software-based percentile calculator was provided to extract the exact percentile for a given race time. Longitudinal tracking reduced the number of annual best times that were included in the percentiles by 98.35% to 262,071 and showed faster mean race times (
P
< 0.05) compared to the cross-sectional analysis. This difference was found in the lower percentiles (1st to 20th) across all age categories (
P
< 0.05); however, in the upper percentiles (80th to 99th), longitudinal tracking showed faster race times during early and late junior age only (
P
< 0.05), after which race times approximated cross-sectional tracking. The percentile calculator provides quick and easy data access to facilitate practical application of percentiles in training or competition. Longitudinal tracking that accounts for drop-out may predict performance progression towards elite age, particularly for high-performance swimmers.
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