Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Apr 21;19(9):5033.
doi: 10.3390/ijerph19095033.

Turn Performance Variation in European Elite Short-Course Swimmers

Affiliations

Turn Performance Variation in European Elite Short-Course Swimmers

Francisco Cuenca-Fernández et al. Int J Environ Res Public Health. .

Abstract

Turn performances are important success factors for short-course races, and more consistent turn times may distinguish between higher and lower-ranked swimmers. Therefore, this study aimed to determine coefficients of variation (CV) and performance progressions (∆%) of turn performances. The eight finalists and eight fastest swimmers from the heats that did not qualify for the semi-finals, i.e., from 17th to 24th place, of the 100, 200, 400, and 800 (females only)/1500 m (males only) freestyle events at the 2019 European Short Course Championships were included, resulting in a total of 64 male (finalists: age: 22.3 ± 2.6, FINA points: 914 ± 31 vs. heats: age: 21.5 ± 3.1, FINA points: 838 ± 74.9) and 64 female swimmers (finalists: age: 22.9 ± 4.8, FINA points: 904 ± 24.5 vs. heats: age: 20.1 ± 3.6, FINA points: 800 ± 48). A linear mixed model was used to compare inter- and intra-individual performance variation. Interactions between CVs, ∆%, and mean values were analyzed using a two-way analysis of variance (ANOVA). The results showed impaired turn performances as the races progressed. Finalists showed faster turn section times than the eight fastest non-qualified swimmers from the heats (p < 0.001). Additionally, turn section times were faster for short-, i.e., 100 and 200 m, than middle- and long-distance races, i.e., 400 to 1500 m races (p < 0.001). Regarding variation in turn performance, finalists showed lower CVs and ∆% for all turn section times (0.74% and 1.49%) compared to non-qualified swimmers (0.91% and 1.90%, respectively). Similarly, long-distance events, i.e., 800/1500 m, showed lower mean CVs and higher mean ∆% (0.69% and 1.93%) than short-distance, i.e., 100 m events (0.93% and 1.39%, respectively). Regarding turn sections, the largest CV and ∆% were found 5 m before wall contact (0.70% and 1.45%) with lower CV and more consistent turn section times 5 m after wall contact (0.42% and 0.54%). Non-qualified swimmers should aim to match the superior turn performances and faster times of finalists in all turn sections. Both finalists and non-qualified swimmers should pay particular attention to maintaining high velocities when approaching the wall as the race progresses.

Keywords: competition analysis; freestyle; performance; race analysis; swimming.

PubMed Disclaimer

Conflict of interest statement

The authors have no conflict of interest to declare. The funder had no role in the development of the study design, data interpretation, or decision to publish the results.

Figures

Figure 1
Figure 1
Coefficients of variation and relative changes in performance with ANOVA main effects corre-sponding to performance level and race distance for men and women. A significant main effect for: ¥ performance levels in men; # race distances in men; † performance levels in women; § race distances in women. Significant post-hoc effect in men: (a) between 100 and 1500 m races; (b) between 100 and 400 m races; (c) between 100 and 200 m races; (d) between 200 and 1500 m races; (e) between 200 and 400 m races; the significant difference in women: (f) between 100 and 800 m races; (g) between 100 and 400 m races; (h) between 100 and 200 m races; (i) between 200 and 800 m races.

Similar articles

Cited by

References

    1. Kjendlie P.L., Ingjer F., Stallman R.K., Stray-Gundersen J. Factors affecting swimming economy in children and adults. Eur. J. Appl. Physiol. 2004;93:65–74. doi: 10.1007/s00421-004-1164-8. - DOI - PubMed
    1. Menting S.G.P., Elferink-Gemser M.T., Huijgen B.C., Hettinga F.J. Pacing in lane-based head-to-head competitions: A systematic review on swimming. J. Sports Sci. 2019;37:2287–2299. doi: 10.1080/02640414.2019.1627989. - DOI - PubMed
    1. Stoggl T., Pellegrini B., Holmberg H.C. Pacing and predictors of performance during cross-country skiing races: A systematic review. J. Sport Health Sci. 2018;7:381–393. doi: 10.1016/j.jshs.2018.09.005. - DOI - PMC - PubMed
    1. Neuloh J.E., Skorski S., Mauger L., Hecksteden A., Meyer T. Analysis of end-spurt behaviour in elite 800-m and 1500-m freestyle swimming. Eur. J. Sport Sci. 2020;21:1628–1636. doi: 10.1080/17461391.2020.1851772. - DOI - PubMed
    1. Stewart A.M., Hopkins W.G. Consistency of swimming performance within and between competitions. Med. Sci. Sports Exerc. 2000;32:997–1001. doi: 10.1097/00005768-200005000-00018. - DOI - PubMed

Publication types

LinkOut - more resources