Insufficient data on adolescent athletes is contributing to the challenges facing youth athletic development and accurate talent identification. The purpose of this study was to model the progression of male sub-elite swimmers’ performances during adolescence. The performances of 446 males (12–19 year olds) competing in seven individual events (50, 100, 200 m freestyle, 100 m backstroke, breaststroke, butterfly, 200 m individual medley) over an eight-year period at an annual international schools swimming championship, run under FINA regulations were collected. Quadratic functions for each event were determined using mixed linear models. Thresholds of peak performance were achieved between the ages of 18.5 ± 0.1 (50 m freestyle and 200 m individual medley) and 19.8 ± 0.1 (100 m butterfly) years. The slowest rate of improvement was observed in the 200 m individual medley (20.7%) and the highest in the 100 m butterfly (26.2%). Butterfly does however appear to be one of the last strokes in which males specialise. The models may be useful as talent identification tools, as they predict the age at which an average sub-elite swimmer could potentially peak. The expected rate of improvement could serve as a tool in which to monitor and evaluate benchmarks.

The aims of this study were to determine the effect of age, sex and race distance on velocity (v), stroke rate (SR), stroke length (SL) and stroke index (SI) of subelite adolescent swimmers in competition, and to investigate their pacing strategies during the 100-m and 200-m events. Video footage of 112 adolescent swimmers (56 female; 56 male), competing in the 100-m and 200-m freestyle events, in two age groups (12-14; 15-18 years) was recorded and subsequently analyzed. A MANOVA showed that all stroke parameters significantly differed between sexes and between race distances. The older adolescents had a higher v, a longer SL and a greater SI (p < .01) than the younger adolescents. There were significant interaction effects between age and sex for v, SL and SI. Most adolescents had a SL that was within 7% of that reported for 1992 Olympians, but had up to 16% lower SRs. Separate Friedman's ANOVAs showed that SL differed between successive race quarters for both age groups, both sexes and both race distances. It is likely that physical immaturity, inexperience in competition pacing and within-race fatigue strongly influence the performances of subelite adolescent front crawl swimmers.

The purpose of this research was to determine the expected progression of adolescent female swimming performances using a longitudinal approach. The performances of 514 female swimmers (12–19 year olds) who participated in one or more FINA-regulated annual international schools’ swimming championships over an eight-year period were analysed. Quadratic functions for each of the seven individual events (50, 100, 200 m freestyle, 100 m backstroke, breaststroke, butterfly, 200 m individual medley) were determined using mixed linear models. The predicted threshold of peak performance ranged from 16.8 ± 0.2 (200 m individual medley) to 20.6 ± 0.1 (100 m butterfly) years of age, preceded by gradual rates of improvement (mean rate of 1.6% per year). However, following cross validation, only three events (100 m backstroke, 200 m individual medley and 200 m freestyle) produced reliable models. Identifying the factors that contribute to the progression of female performance in this transitory period of life remains challenging, not least since the onset of puberty is likely to have occurred prior to reaching 12 years of age, the minimum competition age for this championship.

Purpose: To evaluate the efficacy of existing performance models to assess the progression of male and female adolescent swimmers through a quantitative and qualitative mixed-methods approach. Methods: Fourteen published models were tested using retrospective data from an independent sample of Dutch junior national-level swimmers from when they were between 12 and 18 years of age (n=13). The degree of association by Pearson's correlations were compared between the calculated differences from the models and quadratic functions derived from the Dutch junior national qualifying times. Swimmers were grouped based on their differences from the models and compared with their swimming histories that were extracted from questionnaires and follow-up interviews. Results: Correlations of the deviations from both the models and quadratic functions derived from the Dutch qualifying times were all significant except for the 100 m breaststroke and butterfly and the 200 m freestyle female events (p<0.05). Additionally, the 100 m freestyle and backstroke for males and 200 m freestyle male and female events were almost directly proportional. In general deviations from the models were accounted for by the swimmers' training histories. Higher levels of retrospective motivation appeared to be synonymous with higher-level career performance. Conclusion:This mixed-methods approach helped to confirm the validity of the models that were found to be applicable to adolescent swimmers at all levels, allowing coaches to track performance and set goals. The value of the models in being able to account for the expected performance gains during adolescence allows for peripheral factors that could affect performance to be quantified.