Int J Sports Med 2014; 35(03): 217-222
DOI: 10.1055/s-0033-1349139
Training & Testing
© Georg Thieme Verlag KG Stuttgart · New York

Allometric Scaling and Predicting Cycling Performance in (Well-) Trained Female Cyclists

R. P. Lamberts
1  Exercise Science and Sports Medicine, University of Cape Town, Sport Science Institute of South Africa, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Newlands, South Africa
2  Division of Orthopaedic Surgery, Department of Surgical Sciences, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, South Africa
,
K. J. Davidowitz
1  Exercise Science and Sports Medicine, University of Cape Town, Sport Science Institute of South Africa, Department of Human Biology, Faculty of Health Sciences, University of Cape Town, Newlands, South Africa
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Further Information

Publication History



accepted after revision 31 May 2013

Publication Date:
30 July 2013 (eFirst)

Abstract

As female cycling attains greater professionalism, a larger emphasis is placed on the ability to predict and monitor changes in their cycling performance. The main aim of this study was to determine if peak power output (PPO) adjusted for body mass (W · kg−0.32) accurately predicts flat 40-km time trial performance (40 km TT) in female cyclists as found in men. 20 (well-) trained female cyclists completed a PPO test including maximal oxygen consumption (VO2max) and a flat 40 km TT test. Relationships between cycling performance parameters were also compared to the cycling performance of 45 male cyclists. Allometrically scaled PPW (W · kg−0.32) most accurately predicted 40 km TT performance in the female cyclists (r=−0.87, p<0.0001) compared to any other method, however different slopes between the parameters were found in the female and male cyclists (p=0.000115). In addition gender differences were also found between the relationship between relative PPO (W · kg−1) and relative VO2max (ml · min−1 · kg−1)(p<0.0001), while no gender differences were found between actual and predicted cycling performance based on the Lamberts and Lambert Submaximal Cycle Test (LSCT), which was used a standardized warm-up. In conclusion, relationships between relative cycling parameters seem to differ between genders, while relationships between absolute cycling parameters seem to be similar. Therefore gender specific regression equations should be used when predicting relative cycling performance parameters.