Normative data and percentile curves for long-term athlete development in swimming

Race analysis in swimming: understanding the evolution of publications, citations and networks through a bibliometric review

The aim of this study was to conduct a scoping and bibliometric review of swimming articles related to race analysis. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used to identify relevant studies. Articles on race analysis in swimming published between 1984 and December 31, 2023 were retrieved from the Web of Science database. 366 records were screened and a total of 74 articles were retained for analysis. Until 2012, there were some time intervals with no or few publications. From 2012, there was a clear upward trend in publications and citations. This theme was led by the United States of America, Australia, and Spain. Australia and Spain maintain their status as the countries with the most publications. The analysis of author collaborations revealed two clusters with Spanish authors, and the remaining clusters are composed of Portuguese, Swiss, and Australian authors. With this bibliometric review, it has been possible to understand the evolution of the articles published on race analysis in swimming, the countries and the authors that have contributed most to this topic over the years. The prediction model shows that the number of articles and citations on this topic will continue to increase over the next 10 years (until 2034).

Evaluation of a non-auditory neurocognitive test battery in hearing-impaired according to age

PURPOSE

Due to the demographic shift, the number of older people suffering from hearing loss and from cognitive impairment increases. Both are closely related and hard to differentiate as most standard cognitive test batteries are auditory-based and hearing-impaired individuals perform worse also in non-auditory test batteries. Therefore, reference data for hearing-impaired are mandatory.

METHODS

The computer-based battery ALAcog assesses multiple cognitive domains, such as attention, (delayed) memory, working memory, inhibition, processing speed, mental flexibility and verbal fluency. A data set of 201 bilaterally hearing-impaired subjects aged ≥ 50 (mean 66.6 (SD 9.07)) was analysed. The LMS method, estimated curves for the 10th, 25th, 50th, 75th and 90th percentile were calculated, and classified according to age, starting from the age of 50.

RESULTS

Cognitive function shows a decline in all subtests as people age, except for verbal fluency, which remains almost stable over age. The greatest declines were seen in recall and delayed recall and in mental flexibility. Age and hearing ability did not correlate (p = 0.68). However, as people age, inter-subject variability of cognitive test results increases. This was especially the case for inhibition. Cognitive function was not correlated with hearing ability (each p ≥ 0.13).

CONCLUSION

The present results make an approach to establish reference data for a comprehensive non-auditory test battery in a large sample of elderly hearing-impaired people which can be used as a simple tool to better contextualise cognitive performance beyond mean and median scores.

Advancing athlete development: How Percentile Comparison Methods (PCMs) can identify youth developmental profiles

OBJECTIVES

Inter-individual developmental differences confound the capability to accurately evaluate youth athletic performance, highlighting the need for considerate methodology and analytical approaches. The present study demonstrated how Percentile Comparison Methods (PCMs) were developed, tested, and applied to identify athlete developmental profiles in Australian youth swimming.

DESIGN

Cross-sectional.

METHODS

Participants were N = 866 female 100-metre (m) Front-Crawl swimmers, aged 9-15 years, competing at 36 Australian regional-national level long course events. At respective events, swim performance time was collated alongside, age, date of birth, and anthropometric measures to identify age group, relative age, and maturity status. Quadratic relative age and maturity status with 100-m performance regression trendlines were generated. Then, individual swim performances at a given relative age or maturity status were converted into percentile rank distributions and compared with raw (unadjusted) annual age-group performance percentile ranks.

RESULTS

At a cohort level, initial testing confirmed relative age and maturity-adjusted percentile rankings were associated with general rank improvements for relatively younger and later maturing swimmers compared to raw ranks (and vice versa). When assessing individual swimmer plots, where three percentile rank scores were compared and rank change threshold criteria applied, five Percentile Comparison Method profile types were identified, namely: 'Early Developing' (19 %); 'Later Developing' (18 %); 'Consistent' (15 %); 'Mixed' (38 %) and 'Counteracting' (10 %). Percentile Comparison Method plots helped identify developmentally (dis-)advantaged swimmers; specific factors leading to (dis-)advantage, and likely onward development trajectories.

CONCLUSIONS

Overall and with practical considerations, Percentile Comparison Methods can improve the validity of youth athletic performance evaluation as well as inform athlete development programming.

Variation vs. specialization: the dose-time-effect of technical and physiological variety in the development of elite swimmers

OBJECTIVE

It is heavily discussed whether larger variety or specialization benefit elite performance at peak age. Therefore, this study aimed to determine technical (number of different swimming strokes) and physiological (number of different race distances) variety required to become an international-class swimmer (> 750 swimming points) based on 1'522'803 race results.

RESULTS

Correlation analyses showed lower technical variety in higher ranked swimmers (P < 0.001), yet with small effects (0.11-0.30). However, Poisson distribution revealed dose-time-effects and specified number of swimming strokes required during each age group. Specifically, freestyle swimmers showed highest chances when starting to compete in three to four swimming strokes but reduced their variety to three swimming strokes at the ages of 12/13yrs with another transition to two swimming strokes at the ages of 19/21yrs (female/male swimmers, respectively). Although both sexes showed similar specialization pattern throughout their career, earlier specialization was generally evident in female compared to male swimmers. At peak performance age, freestyle was most frequently combined with butterfly. Swimmers who either kept competing in all five swimming strokes or focused on only one at the beginning of their careers showed lowest probability of becoming an international-class swimmer. Physiological variety increased during junior age but declined again to three race distances towards elite age.

Predicting future stars: Probability and performance corridors for elite swimmers

OBJECTIVES

To evaluate the new age groups of the World Junior Championships in swimming from a scientific perspective, establish benchmarks and performance corridors that predict success at peak performance age and compare performance corridors between men and women and short-, middle-, and long-distance freestyle races.

DESIGN

Longitudinal big data analysis.

METHODS

In total, 347,186 annual best times of male (n = 3360, 561 ± 177 Swimming Points) and female freestyle swimmers (n = 2570, 553 ± 183 Swimming Points) were collected across all race distances at peak performance age and retrospectively analyzed throughout adolescence. Cumulative Poisson distribution was used to calculate probabilities of becoming world-class finalist, international-class, or national-class swimmer for each age group. Performance corridors were expressed relative to the World Record and compared between performance levels, sex, race distances, and age groups with a 2-way analysis of variance.

RESULTS

Females are required to swim faster relative to the World Record at a younger age and show earlier performance plateaus than males at national and international levels. Additionally, world-class long-distance finalists show higher Swimming Points earlier in their career compared to short-distance swimmers. This effect is more distinctive in females than males.

CONCLUSIONS

Based on the sex-specific performance corridors and developments, the newly aligned age groups for the World Junior Championships are questionable regarding long-term athlete development. Based on race times from 131 nations, the present benchmarks provide valid international normative values to predict success chances at peak performance age and guide young swimmers along their talent pathway.

Tracking performance and its underlying characteristics in talented swimmers: a longitudinal study during the junior-to-senior transition

The present study strived to gain a more profound understanding of the distinctions in development between swimmers who are considered to be on track to the senior elite level compared to those who are not. Longitudinal data of 29 talented sprint and middle-distance swimmers (12 males; 17 females) on season best performances (season best times) and underlying performance characteristics (anthropometrics, starts, turns, maximal swimming velocity, stroke index [SI, an indirect measure of swimming efficiency] and lower body power) were collected over four swimming seasons (median of n = 3 seasons per swimmer). Based on their season best performance at early senior age (males aged 18-19; females aged 17-18), some swimmers were considered to be on track to reach the elite level (referred to as high-performing seniors; 6 males and 10 females), whereas others were not (referred to as lower-performing seniors; 6 males and 7 females). Retrospectively studying these swimmers (males and females separately), we found that all high-performing seniors were already on track to the elite level at late junior age (males aged 17; females aged 16), evidenced with faster season best performances throughout their transition compared to their lower-performing peers (p < 0.05). Independent sample t-tests revealed that high-performing seniors significantly outscored their lower-performing peers on maximal swimming velocity (males and females), starts and turns (males), SI (females) and lower body power (females) at late junior age (p < 0.05). Additionally, multilevel models showed faster rates of development for high-performing seniors on turns and maximal swimming velocity (males), and SI (females) compared to lower-performing peers during the junior-to-senior transition (p < 0.05). Particularly, the higher initial levels of swim performance and underlying characteristics at late junior age as well as the ability to keep progressing on season best performances (males and females), turns and maximal swimming velocity (males), and SI (females) during the junior-to-senior transition, may be crucial factors in the attainment of swimming expertise.

Performance Development of European Swimmers Across the Olympic Cycle

The aims of the study were to (1) quantify the performance development of race times and key performance indicators of European swimmers across the last Olympic cycle (from 2016 to 2021) and (2) provide reference values for long-course swimming pool events for both sexes from 50 m to 1,500 m including butterfly, backstroke, breaststroke, freestyle, and individual medley. Individual events from the 2016 and 2021 European swimming championships were included. Specifically, 246 men (age: 24.2 ± 3.4 years, FINA points: 890 ± 40) and 256 women races (age: 24.2 ± 4, FINA points: 879 ± 38) of the finalists were recorded and key performance indicators and split times analyzed. Performance differences in finalists of the 2016 and 2021 European championships were determined by an independent t-test and Cohen's d effect size. Reference values were retrieved from 2021 European championship finalists and are provided for all key performance indicators. Race times improved significantly (P < 0.05) or showed moderate (d = 0.5–1) to large effect sizes (d > 1) in 14 (men) and 6 (women) out of 16 events. Improvements were primarily evident in 100 m and 200 m events for males, as well as BR and sprint events for female swimmers. While start times improved in 15 (men) and 14 (women) events, turn times remained inconclusive in both sexes. Generally, breakout distances increased. Clean swimming velocities were faster in 12 (men) and 5 (women) events. In particular, for alternating swimming strokes, i.e., backstroke and freestyle, effect sizes indicated improved swimming efficiency with an inverse relationship between reduced stroke rate and increased distance per stroke. Coaches and performance analysts may use the present reference values as comparative data for race analyses and to specifically prepare swimmers for the various race sections. Data on the performance development should be used to analyze swimmers' potential and set goals for the various events and the next Olympic cycle.

Comparing cross-sectional and longitudinal tracking to establish percentile data and assess performance progression in swimmers

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.