The effects of predictive trials on critical stroke rate and critical swimming speed

Raimundo, João Antônio Gesser; Ribeiro, Guilherme Aramizo; Lisbôa, Felipe Domingos; Pereira, Gustavo Soares; Loch, Thiago; Aguiar, Rafael Alves de; Martins, Eduardo Campos; Caputo, Fabrízio

doi:10.23736/s0022-4707.20.10846-6

Cited by 4 publications

(2 citation statements)

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“…running and cycling). While the best practices to determine CS and D′ were used ( Muniz-Pumares et al, 2019 ; Raimundo et al, 2020 ), we acknowledge that a high standard error of the estimate for D′ can decrease D' BAL model accuracy in swimming. In addition, the swimmers were asked to swim at a constant pre-determined speed, in which there could be some little variation.…”

Section: Discussionmentioning

confidence: 99%

“…Swimmers were instructed to swim distances of 200, 400, 600, and 800 m as quickly as possible and each performance was recorded at the nearest 0.01 s by a manual stopwatch ( Raimundo et al, 2020 ). These performances were used to calculate the CS (slope) and the D' ( y -intercept) by applying the distance-time linear regression model ( Dekerle et al, 2002 ).…”

Section: Methodsmentioning

confidence: 99%

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Modeling the expenditure and reconstitution of distance above critical speed during two swimming interval training sessions

et al. 2022

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In swimming, the speed-time relationship provides the critical speed (CS) and the maximum distance that can be performed above CS (D′). During intermittent severe intensity exercise, a complete D′ depletion coincides with task failure, while a sub-CS intensity is required for D′ reconstitution. Therefore, determining the balance D′ remaining at any time during intermittent exercise (D'BAL) could improve training prescription. This study aimed to 1) test the D'BAL model for swimming; 2) determine an equation to estimate the time constant of the reconstitution of D' (τD′); and 3) verify if τD′ is constant during two interval training sessions with the same work intensity and duration and recovery intensity, but different recovery duration. Thirteen swimmers determined CS and D′ and performed two high-intensity interval sessions at a constant speed, with repetitions fixed at 50 m. The duration of passive recovery was based on the work/relief ratio of 2:1 (T2:1) and 4:1 (T4:1). There was a high variability between sessions for τD' (coefficient of variation of 306%). When τD′ determined for T2:1 was applied in T4:1 and vice versa, the D'BAL model was inconsistent to predict the time to exhaustion (coefficient of variation of 29 and 28%). No linear or nonlinear relationships were found between τD′ and CS, possibly due to the high within-subject variability of τD'. These findings suggest that τD′ is not constant during two high-intensity interval sessions with the same recovery intensity. Therefore, the current D'BAL model was inconsistent to track D′ responses for swimming sessions tested herein.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%