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Predicting middle-distance track and cross-country performances of national and international level adolescent runners

Alex Bliss Orcid Logo, Mark Waldron Orcid Logo, Neil Maxwell Orcid Logo

European Journal of Sport Science, Volume: 22, Issue: 3, Pages: 305 - 313

Swansea University Author: Mark Waldron Orcid Logo

Abstract

This study evaluated the contribution of physiological data collected during laboratory testing in predicting race performances of trained junior middle-distance track (TK) and cross-country (XC) athletes. Participants performed a submaximal incremental ramp test, followed by an incremental test to...

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Published in: European Journal of Sport Science
ISSN: 1746-1391 1536-7290
Published: Informa UK Limited 2022
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa55892
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Abstract: This study evaluated the contribution of physiological data collected during laboratory testing in predicting race performances of trained junior middle-distance track (TK) and cross-country (XC) athletes. Participants performed a submaximal incremental ramp test, followed by an incremental test to exhaustion in a laboratory, with the results used to predict either 800 m TK, 1500 m TK or 4000–6000 m XC race performance. Twenty-eight participants (male (M), 15; female (F), 13) were analysed (age = 17 ± 2 years, height = 1.72 ± 0.08 m, body mass = 58.9 ± 8.9 kg). Performance times (min:s) for 800 m were: M, 1:56.55 ± 0:05.55 and F, 2:14.21 ± 0:03.89; 1500 m: M, 3:51.98 ± 0:07.35 and F 4:36.71 ± 0:16.58; XC: M (4900 ± 741 m), 16:00 ± 01:53; F (4628 ± 670 m), 17:41 ± 02:09. Stepwise regression analysis indicated significant contributions of speed at V̇O2max (V̇O2max), and heart rate maximum (HRmax) to the prediction of 800 m TK (F(2,15) = 22.51, p < 0.001, adjusted R 2= 0.72), V̇O2max for 1500 m TK (F(1,13) = 36.65, p < 0.001, adjusted R 2= 0.72) and V̇O2max, allometrically scaled to body mass and speed at lactate threshold (sLT) for XC (F(2,17) = 25.1, p < 0.001, adjusted R 2= 0.72). Laboratory-based physiological measures can explain 72% of the variance in junior TK and XC events, although factors that explain performance alter depending on the race distance and tactics. The factors determining performance in TK and XC events are not interchangeable.
Keywords: Endurance; running; physiology; junior; regression; performance modelling
College: Faculty of Science and Engineering
Issue: 3
Start Page: 305
End Page: 313