University of Limerick
Browse

What is the optimal strength training load to improve swimming performance? a randomized trial of male competitive swimmers

Download (731.99 kB)
journal contribution
posted on 2021-11-17, 11:25 authored by Sofiene Amara, Emmet Crowley, Senda Sammoud, Yassine Negra, Raouf Hammami, Oussema Gaied Chortane, Riadh Khalifa, Sabri Gaied Chortane, Roland van den Tillaar
This study aimed to compare the effectiveness of high, moderate, and low resistance training volume-load of maximum strength training on muscle strength and swimming performance in competitive swimmers. Thirty-three male swimmers were randomly allocated to high (age = 16.5 ± 0.30 years), moderate (age = 16.1 ± 0.32 years) and a low resistance training volume-load group (age = 15.9 ± 0.31). This study was carried out in mid-season (January to March). Pre and post strength (e.g., repetition maximum [1RM] leg extension and bench press tests), swimming (25, 50 m front-crawl), start (speed, time, distance) and turn (time of turn) performance tests were conducted. Our findings revealed a large main effect of time for 1RM bench press: d = 1.38; 1RM leg extension: d = 1.55, and for 25 (d = 1.12), and 50 m (d = 1.97) front-crawl, similarly for start and turn performance (d = 1.28–1.46). However, no significant Group × Time interactions were shown in all strength swimming performances, start and turn tests (p > 0.05). In conclusion, low training loads have been shown to elicit the same results as moderate, and high training loads protocol. Therefore, this study shows evidence that the addition of low training volume-loads as a regular part of a maximal strength training regime will elicit improvements in strength and swimming performance.

History

Publication

International Journal of Environmental Research and Public Health;18, 11770

Publisher

MDPI

Note

peer-reviewed

Language

English

Usage metrics

    University of Limerick

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC