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Eur J Appl Physiol. 2010 Jan;108(1):183-90. doi: 10.1007/s00421-009-1291-3. Epub 2009 Nov 18.

Measuring submaximal performance parameters to monitor fatigue and predict cycling performance: a case study of a world-class cyclo-cross cyclist.

Author information

1
Department of Human Biology, Faculty of Health Sciences, Sport Science Institute of South Africa, University of Cape Town, Newlands, South Africa. robert.lamberts@uct.ac.za

Abstract

Recently a novel submaximal test, known as the Lamberts and Lambert submaximal cycle test (LSCT), has been developed with the purpose of monitoring and predicting changes in cycling performance. Although this test has been shown to be reliable and able to predict cycling performance, it is not known whether it can measure changes in training status. Therefore, the aim of this study was to determine whether the LSCT is able to track changes in performance parameters, and objective and subjective markers of well-being. A world class cyclo-cross athlete (31 years) volunteered to participate in a 10-week observational study. Before and after the study, a peak power output (PPO) test with respiratory gas analysis (VO(2max)) and a 40-km time trial (40-km TT) test were performed. Training data were recorded in a training logbook with a daily assessment of well-being, while a weekly LSCT was performed. After the training period all performance parameters had improved by a meaningful amount (PPO +5.2%; 40-km TT time -2.5%; VO(2max) +1.4%). Increased training loads during weeks 2 and 6 and the subsequent training-induced fatigue was reflected in the increased well-being scores. Changes during the LSCT were most clearly notable in (1) increased power during the first minute of third stage, (2) increased rating of perceived exertion during second and third stages, and (3) a faster heart rate recovery after the third stage. In conclusion, these data suggest that the LSCT is able to track changes in training status and detect the consequences of sharp increases in training loads which seem to be associated with accumulating fatigue.

PMID:
19921241
DOI:
10.1007/s00421-009-1291-3
[Indexed for MEDLINE]
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