Improvement and Variability of Adolescent Backstroke Swimming Performance by Age

Sprinting to the top: comparing quality of distance variety and specialization between swimmers and runners

Objectives

To compare performance progression and variety in race distances of comparable lengths (timewise) between pool swimming and track running. Quality of within-sport variety was determined as the performance differences between individual athletes' main and secondary race distances across (top-) elite and (highly-) trained swimmers and runners.

Methods

A total of 3,827,947 race times were used to calculate performance points (race times relative to the world record) for freestyle swimmers (n = 12,588 males and n = 7,561 females) and track runners (n = 9,230 males and n = 5,841 females). Athletes were ranked based on their personal best at peak performance age, then annual best times were retrospectively traced throughout adolescence.

Results

Performance of world-class swimmers differentiates at an earlier age from their lower ranked peers (15-16 vs. 17-20 year age categories, P < 0.05), but also plateaus earlier towards senior age compared to runners (19-20 vs. 23 + year age category, P < 0.05), respectively. Performance development of swimmers shows a logarithmic pattern, while runners develop linearly. While swimmers compete in more secondary race distances (larger within-sport variety), runners specialize in either sprint, middle- or long-distance early in their career and compete in only 2, 4 or 3 other race distances, respectively. In both sports, sprinters specialize the most (P < 0.05). Distance-variety of middle-distance swimmers covers more longer rather than sprint race distances. Therefore, at peak performance age, (top-) elite female 200 m swimmers show significantly slower sprint performances, i.e., 50 m (P < 0.001) and 100 m (P < 0.001), but not long-distance performances, i.e., 800 m (P = 0.99) and 1,500 m (P = 0.99). In contrast, (top-) elite female 800 m middle-distance runners show significantly slower performances in all their secondary race distances (P < 0.001). (Top-) elite female athletes specialize more than (highly-) trained athletes in both sports (P < 0.05).

Conclusions

The comparison to track running and lower ranked swimmers, the early performance plateau towards senior age, and the maintenance of a large within-sport distance variety indicates that (top-) elite sprint swimmers benefit from greater within-sport specialization.

Analysis of the fastest backstroke age group swimmers competing in the World Masters Championships 1986-2024

Backstroke has been thoroughly investigated in the context of sports science. However, we have no knowledge about the nationalities of the fastest age group backstroke swimmers. Therefore, the present study intended to investigate the nationalities of the fastest backstroke swimmers. For all World Masters Championships held between 1986 and 2024, the year of competition, the first and last name, the age, and the age group, and both the stroke and the distance were recorded for each swimmer. Descriptive data were presented using mean, standard deviation, maximum and minimum values, and confidence intervals. The top ten race times for each swimming distance and sex were identified for descriptive purposes. Nationalities were then grouped into six categories: the top five nationalities with the most appearances in the backstroke swimming top ten times by distance each year and one group consisting of all other nationalities. The Kruskal-Wallis test compared nationality differences, followed by Bonferroni-adjusted pairwise comparisons to identify specific distinctions. Between 1986 and 2024, most age group backstroke swimmers (39.6%) competed in the 50 m event (11,964, 6206 women, and 5,758 men), followed by the 100 m event (32.3%, n = 9764, 5157 women, and 4607 men), and the 200 m event (28.1%, n = 8483, 4511 women, and 3,972 men). Germany had the highest number of top ten female swimmers in the 50 m backstroke distance. Brazil had the highest number of top ten male swimmers in the same distance. The USA had the highest number of female and male swimmers among the top ten in the 100 m and 200 m backstroke distances. Germany and Great Britain were the only countries with swimmers in the top ten for all female backstroke distances. Brazil, the USA, Italy, and Germany were the countries that had swimmers in the top ten for all male backstroke distances. In summary, the fastest backstroke age group swimmers originated from Germany, Brazil, USA, Great Britain, and Italy, where differences between the sexes and race distances exist.

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.

Associations Between Selected Biological Features and Absolute and Relative Swimming Performance of Prepubescent Boys Over a 3-Year Swimming Training Program: A Longitudinal Study

The study aimed to investigate the effect of 3-year swimming training on selected biological variables in prepubescent male swimmers and to determine the best predictors of absolute (VS_a) and relative (VS_r) swimming velocity for 50 m and 400 m front crawl. Twenty-one 10-year old boys subjected to endurance swimming training (4 x 70 min per week) and 18 boys consisting a control group were assessed semi-annually for basic anthropometric and respiratory characteristics, breath-hold time (BHT), VO_2max, leg explosiveness (HJ), and abdominal strength endurance (ASE). After three years of training, BHT (p < 0.001), VO_2max (p < 0.01), HJ (p < 0.01) and ASE (p < 0.01) were greater in the swimmers than in the controls. VS_a and VS_r expressed as a percentage of baseline velocity increased more for the 50 m than for the 400 m distance (p < 0.001 and p < 0.01, respectively). The 50 m VS_a and VS_r positively correlated with those obtained for the distance of 400 m (in both cases p < 0.001). Baseline VS_a was negatively correlated with the increase in absolute swimming velocity for both distances (50 m: r = -0.684, p < 0.001 and 400 m: r = -0.673, p < 0.001). The best predictors of VS_a for 50 m and 400 m front crawl were HJ (r₂ = 0.388; p < 0.001) and VO_2max (r₂ = 0.333; p < 0.001), respectively. The key predictors of VS_r for both distances were age (50 m: r² = 0.340, p < 0.001 and 400 m: r² = 0.207, p < 0.001) and, after excluding it from analysis, HJ (50 m: r² = 0.176, p < 0.001 and 400 m: r² = 0.104, p < 0.001). These results suggest that regardless of prepubescent boys’ initial abilities and exercise capacity, improvement in their swimming performance mainly depends on increases in power and neuromuscular coordination.

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.

Competition age: does it matter for swimmers?

OBJECTIVE

To establish reference data on required competition age regarding performance levels for both sexes, all swimming strokes, and race distances and to determine the effect of competition age on swimming performance in the context of other common age metrics. In total, 36,687,573 race times of 588,938 swimmers (age 14.2 ± 6.3 years) were analyzed. FINA (Fédération Internationale de Natation) points were calculated to compare race times between swimming strokes and race distances. The sum of all years of race participation determined competition age.

RESULTS

Across all events, swimmers reach top-elite level, i.e. > 900 FINA points, after approximately 8 years of competition participation. Multiple-linear regression analysis explained up to 40% of variance in the performance level and competition age showed a stable effect on all race distances for both sexes (β = 0.19 to 0.33). Increased race distance from 50 to 1500 m, decreased effects of chronological age (β = 0.48 to - 0.13) and increased relative age effects (β = 0.02 to 0.11). Reference data from the present study should be used to establish guidelines and set realistic goals for years of competition participation required to reach certain performance levels. Future studies need to analyze effects of transitions between various swimming strokes and race distances on peak performance.

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

OBJECTIVES

To provide normative data and establish percentile curves for long-course (50 m pool length) swimming events and to compare progression of race times longitudinally for the various swimming strokes and race distances.

DESIGN

Descriptive approach with longitudinal tracking of performance data.

METHODS

A total of 2,884,783 race results were collected from which 169,194 annual best times from early junior to elite age were extracted. To account for drop-outs during adolescence, only swimmers still competing at age of peak performance (21-26 years) were included and analyzed retrospectively. Percentiles were established with z-scores around the median and the Lambda-Mu-Sigma (LMS) method applied to account for potential skewness. A two-way analysis of variance (ANOVA) with repeated measure and between-subject factor was applied to compare race times across the various events and age groups.

RESULTS

Percentile curves were established based on longitudinal tracking of race times specific to sex, swimming stroke, and race distance. Comparing performance progression, race times of freestyle sprint events showed an early plateau with no further significant improvement (p > 0.05) after late junior age (15-17 years). However, the longer the race distance, the later the race times plateaued (p < 0.05). Female swimmers generally showed an earlier performance plateau than males. Backstroke and freestyle showed an earlier performance plateau compared to the other swimming strokes (p < 0.05).

CONCLUSIONS

Performance progression varied between sex, swimming strokes, and race distances. Percentile curves based on longitudinal tracking may allow an objective assessment of swimming performance, help discover individual potentials, and facilitate realistic goal setting for talent development.