Turn Performance Variation in European Elite Short-Course Swimmers

. 2022 Apr 21 ; 19 (9) : . [epub] 20220421

Jazyk angličtina Země Švýcarsko Médium electronic

Typ dokumentu časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/pmid35564428

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.

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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. PubMed DOI

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. PubMed DOI

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. PubMed DOI PMC

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. PubMed DOI

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. PubMed DOI

Cuenca-Fernandez F., Ruiz-Navarro J.J., Gonzalez-Ponce A., Lopez-Belmonte O., Gay A., Arellano R. Progression and variation of competitive 100 and 200m performance at the 2021 European Swimming Championships. Sports Biomech. 2021:1–15. doi: 10.1080/14763141.2021.1998591. PubMed DOI

López-Belmonte Ó., Gay A., Ruiz-Navarro J.J., Cuenca-Fernández F., González-Ponce Á., Arellano R. Pacing profiles, variability and progression in 400, 800 and 1500-m freestyle swimming events at the 2021 European Championship. Int. J. Perform. Anal. Sport. 2022;22:90–101. doi: 10.1080/24748668.2021.2010318. DOI

Skorski S., Faude O., Abbiss C.R., Caviezel S., Wengert N., Meyer T. Influence of pacing manipulation on performance of juniors in simulated 400-m swim competition. Int. J. Sports Physiol. Perform. 2014;9:817–824. doi: 10.1123/ijspp.2013-0469. PubMed DOI

Skorski S., Faude O., Rausch K., Meyer T. Reproducibility of pacing profiles in competitive swimmers. Int. J. Sports Med. 2013;34:152–157. doi: 10.1055/s-0032-1316357. PubMed DOI

Gonjo T., Olstad B.H. Race Analysis in Competitive Swimming: A Narrative Review. Int. J. Environ. Res. Public Health. 2020;18:69. doi: 10.3390/ijerph18010069. PubMed DOI PMC

Barbosa T.M., Barbosa A.C., Simbana Escobar D., Mullen G.J., Cossor J.M., Hodierne R., Arellano R., Mason B.R. The role of the biomechanics analyst in swimming training and competition analysis. Sports Biomech. 2021:1–18. doi: 10.1080/14763141.2021.1960417. PubMed DOI

Thompson K.G., MacLaren D.P., Lees A., Atkinson G. The effects of changing pace on metabolism and stroke characteristics during high-speed breaststroke swimming. J. Sports Sci. 2004;22:149–157. doi: 10.1080/02640410310001641467. PubMed DOI

Morais J.E., Barbosa T.M., Forte P., Pinto J.N., Marinho D.A. Assessment of the inter-lap stability and relationship between the race time and start, clean swim, turn and finish variables in elite male junior swimmers’ 200 m freestyle. Sports Biomech. 2021:1–14. doi: 10.1080/14763141.2021.1952298. PubMed DOI

Morais J.E., Barbosa T.M., Neiva H.P., Marinho D.A. Stability of pace and turn parameters of elite long-distance swimmers. Hum. Mov. Sci. 2019;63:108–119. doi: 10.1016/j.humov.2018.11.013. PubMed DOI

McGibbon K.E., Pyne D.B., Shephard M.E., Thompson K.G. Pacing in Swimming: A Systematic Review. Sports Med. 2018;48:1621–1633. doi: 10.1007/s40279-018-0901-9. PubMed DOI

Born D.P., Kuger J., Polach M., Romann M. Start and turn performances of elite male swimmers: Benchmarks and underlying mechanims. Sports Biomech. 2021:1–21. doi: 10.1080/14763141.2021.1872693. PubMed DOI

Olstad B.H., Wathne H., Gonjo T. Key Factors Related to Short Course 100 m Breaststroke Performance. Int. J. Environ. Res. Public Health. 2020;17:6257. doi: 10.3390/ijerph17176257. PubMed DOI PMC

Wolfrum M., Knechtle B., Rust C.A., Rosemann T., Lepers R. The effects of course length on freestyle swimming speed in elite female and male swimmers-A comparison of swimmers at national and international level. SpringerPlus. 2013;2:643. doi: 10.1186/2193-1801-2-643. PubMed DOI PMC

Polach M., Thiel D., Krenik J., Born D.P. Swimming turn performance: The distinguishing factor in 1500 m world championship freestyle races. BMC Res. Notes. 2021;14:248. doi: 10.1186/s13104-021-05665-x. PubMed DOI PMC

Polach M., Born D.P. Data Analysis: How Enhanced Turn Performance Led Florian Wellbrock to WR in 1500 Freestyle (Visual Charts). Swimming World Magazine, 15 January 2022. [(accessed on 1 March 2022)]. Available online: https://www.swimmingworldmagazine.com/news/data-analysis-how-enhanced-turn-performance-led-florian-wellbrock-to-world-record-in-1500-freestyle-visual-charts/

Morais J.E., Barbosa T.M., Forte P., Bragada J.A., Castro F.A.S., Marinho D.A. Stability analysis and prediction of pacing in elite 1500 m freestyle male swimmers. Sports Biomech. 2020:1–18. doi: 10.1080/14763141.2020.1810749. PubMed DOI

Ruiz-Navarro J.J., Lopez-Belmonte O., Gay A., Cuenca-Fernandez F., Arellano R. A new model of performance classification to standardize the research results in swimming. Eur. J. Sport Sci. 2022:1–23. doi: 10.1080/17461391.2022.2046174. PubMed DOI

IOC Swimming Events Tokyo. 2021. [(accessed on 16 February 2022)]. Available online: https://olympics.com/tokyo-2020/olympic-games/en/results/swimming/olympic-schedule-and-results.htm.

Born D.P., Kuger J., Polach M., Romann M. Turn Fast and Win: The Importance of Acyclic Phases in Top-Elite Female Swimmers. Sports. 2021;9:122. doi: 10.3390/sports9090122. PubMed DOI PMC

Morais J.E., Marinho D.A., Arellano R., Barbosa T.M. Start and turn performances of elite sprinters at the 2016 European Championships in swimming. Sports Biomech. 2019;18:100–114. doi: 10.1080/14763141.2018.1435713. PubMed DOI

Shapiro J.R., Klein S.L., Morgan R. Stop ‘controlling’ for sex and gender in global health research. BMJ Glob. Health. 2021;6:e005714. doi: 10.1136/bmjgh-2021-005714. PubMed DOI PMC

Pyne D., Trewin C., Hopkins W. Progression and variability of competitive performance of Olympic swimmers. J. Sports Sci. 2004;22:613–620. doi: 10.1080/02640410310001655822. PubMed DOI

Ferguson C.J. An effect size primer: A guide for clinicians and researchers. Prof. Psychol. Res. Pract. 2016;40:532–538. doi: 10.1037/a0015808. DOI

Arellano R., Ruíz-Teba A., Morales-Ortíz E., Gay A., Cuenca-Fernandez F., Llorente-Ferrón F., López-Contreras G. Short course 50m male freestyle performance comparison between national and regional Spanish swimmers. ISBS Proc. Arch. 2018;36:139.

Sánchez L., Arellano R., Cuenca-Fernández F. Analysis and influence of the underwater phase of breaststroke on short-course 50 and 100m performance. Int. J. Perform. Anal. Sport. 2021;21:307–323. doi: 10.1080/24748668.2021.1885838. DOI

Veiga S., Roig A. Effect of the starting and turning performances on the subsequent swimming parameters of elite swimmers. Sports Biomech. 2017;16:34–44. doi: 10.1080/14763141.2016.1179782. PubMed DOI

Veiga S., Cala A., Frutos P.G., Navarro E. Comparison of starts and turns of national and regional level swimmers by individualized-distance measurements. Sports Biomech. 2014;13:285–295. doi: 10.1080/14763141.2014.910265. PubMed DOI

Marinho D.A., Barbosa T.M., Neiva H.P., Silva A.J., Morais J.E. Comparison of the Start, Turn and Finish Performance of Elite Swimmers in 100 m and 200 m Races. J. Sports Sci. Med. 2020;19:397–407. PubMed PMC

Nicol E., Ball K., Tor E. The biomechanics of freestyle and butterfly turn technique in elite swimmers. Sports Biomech. 2021;20:444–457. doi: 10.1080/14763141.2018.1561930. PubMed DOI

Veiga S., Cala A., Mallo J., Navarro E. A new procedure for race analysis in swimming based on individual distance measurements. J. Sports Sci. 2013;31:159–165. doi: 10.1080/02640414.2012.723130. PubMed DOI

Gonjo T., Olstad B.H. Start and Turn Performances of Competitive Swimmers in Sprint Butterfly Swimming. J. Sports Sci. Med. 2020;19:727–734. PubMed PMC

Papic C., Andersen J., Naemi R., Hodierne R., Sanders R.H. Augmented feedback can change body shape to improve glide efficiency in swimming. Sports Biomech. 2021:1–20. doi: 10.1080/14763141.2021.1900355. PubMed DOI

Formosa D.P., Sayers M.G., Burkett B. Backstroke swimming: Exploring gender differences in passive drag and instantaneous net drag force. J. Appl. Biomech. 2013;29:662–669. doi: 10.1123/jab.29.6.662. PubMed DOI

Ruiz-Navarro J.J., Cano-Adamuz M., Andersen J.T., Cuenca-Fernandez F., Lopez-Contreras G., Vanrenterghem J., Arellano R. Understanding the effects of training on underwater undulatory swimming performance and kinematics. Sports Biomech. 2021:1–16. doi: 10.1080/14763141.2021.1891276. PubMed DOI

Houel N., Elipot M., Andre F., Hellard P. Influence of angles of attack, frequency and kick amplitude on swimmer’s horizontal velocity during underwater phase of a grab start. J. Appl. Biomech. 2013;29:49–54. doi: 10.1123/jab.29.1.49. PubMed DOI

Papic C., McCabe C., Gonjo T., Sanders R. Effect of torso morphology on maximum hydrodynamic resistance in front crawl swimming. Sports Biomech. 2020:1–15. doi: 10.1080/14763141.2020.1773915. PubMed DOI

Naemi R., Easson W.J., Sanders R.H. Hydrodynamic glide efficiency in swimming. J. Sci. Med. Sport. 2010;13:444–451. doi: 10.1016/j.jsams.2009.04.009. PubMed DOI

Cortesi M., Gatta G., Michielon G., Di Michele R., Bartolomei S., Scurati R. Passive Drag in Young Swimmers: Effects of Body Composition, Morphology and Gliding Position. Int. J. Environ. Res. Public Health. 2020;17:2002. doi: 10.3390/ijerph17062002. PubMed DOI PMC

Vilas-Boas J.P., Costa L., Fernandes R.J., Ribeiro J., Figueiredo P., Marinho D., Silva A.J., Rouboa A., Machado L. Determination of the drag coefficient during the first and second gliding positions of the breaststroke underwater stroke. J. Appl. Biomech. 2010;26:324–331. doi: 10.1123/jab.26.3.324. PubMed DOI

Marinho D.A., Barbosa T.M., Rouboa A.I., Silva A.J. The Hydrodynamic Study of the Swimming Gliding: A Two-Dimensional Computational Fluid Dynamics (CFD) Analysis. J. Hum. Kinet. 2011;29:49–57. doi: 10.2478/v10078-011-0039-4. PubMed DOI PMC

Veiga S., Roig A. Underwater and surface strategies of 200 m world level swimmers. J. Sports Sci. 2016;34:766–771. doi: 10.1080/02640414.2015.1069382. PubMed DOI

Veiga S., Pla R., Qiu X., Boudet D., Guimard A. Effects of Extended Underwater Sections on the Physiological and Biomechanical Parameters of Competitive Swimmers. Front. Physiol. 2022;13:815766. doi: 10.3389/fphys.2022.815766. PubMed DOI PMC

Tor E., Pease D.L., Ball K.A. How does drag affect the underwater phase of a swimming start. J. Appl Biomech. 2015;31:8–12. doi: 10.1123/JAB.2014-0081. PubMed DOI

Novais M.L., Silva A.J., Mantha V.R., Ramos R.J., Rouboa A.I., Vilas-Boas J.P., Luis S.R., Marinho D.A. The Effect of Depth on Drag During the Streamlined Glide: A Three-Dimensional CFD Analysis. J. Hum. Kinet. 2012;33:55–62. doi: 10.2478/v10078-012-0044-2. PubMed DOI PMC

Pla R., Poszalczyk G., Souaissia C., Joulia F., Guimard A. Underwater and Surface Swimming Parameters Reflect Performance Level in Elite Swimmers. Front. Physiol. 2021;12:712652. doi: 10.3389/fphys.2021.712652. PubMed DOI PMC

Ikeda Y., Ichikawa H., Shimojo H., Nara R., Baba Y., Shimoyama Y. Relationship between dolphin kick movement in humans and velocity during undulatory underwater swimming. J. Sports Sci. 2021;39:1497–1503. doi: 10.1080/02640414.2021.1881313. PubMed DOI

Hochstein S., Blickhan R. Body movement distribution with respect to swimmer’s glide position in human underwater undulatory swimming. Hum. Mov. Sci. 2014;38:305–318. doi: 10.1016/j.humov.2014.08.017. PubMed DOI

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