Does Pool Performance of Elite Triathletes Predict Open-Water Performance?
J Funct Morphol Kinesiol
; 8(4)2023 Dec 06.
Article
em En
| MEDLINE
| ID: mdl-38132720
ABSTRACT
The capacity of laboratory tests to predict competition performance has been broadly researched across several endurance sports. The aim of the present study was to analyse how pool swimming performance can predict the result of the swimming segment in triathlon competitions and compare predictability differences based on competition level and distance. Eighteen male triathletes participated in the study. Three were ranked world-class, ten elite/international level, and five highly trained/national level. A total of sixty-one graded multi-stage swimming tests were conducted. Blood lactate was measured to calculate the following hypothetical predictor variables speed at lactate threshold 1 (LT1), speed at lactate threshold 2 (LT2), and speed in the last repetition of the test (SL200). The following data were collected for a total of 75 races time in the swimming leg (TSL); position after the swimming leg (PSL); time difference with the first triathlete after the swimming leg (DFT); and final race position. The race levels were divided according to participant levels as follows world series (WS) (n = 22); World Cup (WC) (n = 22); Continental Cup (CC) (n = 19); national championship (N) (n = 5); and local race (L) (n = 5). Based on distance, they were divided into Olympic distance (OD) (n = 37) and sprint distance (SD) (n = 38). A moderate to strong positive association was found between LT1, LT2, SL200 and PSL and TSl at all race levels except for the SD CC, SD WC, and OD CC races, where no or weak-to-moderate correlations were found. The present study demonstrated that performance measured in a graded multi-stage pool lactate test can predict performance in a triathlon swimming segment. This finding is highly useful for coaches as it can help them to obtain a reliable measure of the triathlete's specific capabilities in the swimming leg.
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01-internacional
Base de dados:
MEDLINE
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article