Born, Dennis; Rüeger, Eva; Beaven, C Martyn; Romann, Michael (2022). Comparing cross-sectional and longitudinal tracking to establish percentile data and assess performance progression in swimmers. Scientific Reports, 12(1), p. 10292. Springer 10.1038/s41598-022-13837-3
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Born_2022_Comparing cross-sectional and longitudinal tracking to establish percentile data and assess performance progression in swimmers.pdf - Published Version Available under License Creative Commons: Attribution (CC-BY). Download (1MB) | Preview |
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.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
Swiss Federal Institute of Sports Magglingen SFISM > EHSM - Leistungssport > Trainingswissenschaft |
Name: |
Born, Dennis 0000-0002-1058-4367; Rüeger, Eva; Beaven, C Martyn and Romann, Michael 0000-0003-4139-2955 |
ISSN: |
2045-2322 |
Publisher: |
Springer |
Language: |
English |
Submitter: |
Sabina Wolfensberger |
Date Deposited: |
05 Jul 2023 08:42 |
Last Modified: |
05 Jul 2023 08:42 |
Publisher DOI: |
10.1038/s41598-022-13837-3 |
Related URLs: |
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PubMed ID: |
35717501 |
Uncontrolled Keywords: |
Sport Trainingswissenschaft |
ARBOR DOI: |
10.24451/arbor.19392 |
URI: |
https://arbor.bfh.ch/id/eprint/19392 |
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