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dc.contributor.authorNevill, Alan M.
dc.contributor.authorJobson, Simon A.
dc.contributor.authorDavison, R.C.R.
dc.contributor.authorJeukendrup, A.E.
dc.date.accessioned2007-01-25T16:12:51Z
dc.date.available2007-01-25T16:12:51Z
dc.date.issued2006
dc.date.submitted2007-01-25
dc.identifier.citationEuropean Journal of Applied Physiology, 97(4): 424-431
dc.identifier.issn1439-6319
dc.identifier.pmid16685550
dc.identifier.doi10.1007/s00421-006-0189-6
dc.identifier.urihttp://hdl.handle.net/2436/7756
dc.description.abstractThe purpose of this article was to establish whether previously reported oxygen-to-mass ratios, used to predict flat and hill-climbing cycling performance, extend to similar power-to-mass ratios incorporating other, often quick and convenient measures of power output recorded in the laboratory [maximum aerobic power (W(MAP)), power output at ventilatory threshold (W(VT)) and average power output (W(AVG)) maintained during a 1 h performance test]. A proportional allometric model was used to predict the optimal power-to-mass ratios associated with cycling speeds during flat and hill-climbing cycling. The optimal models predicting flat time-trial cycling speeds were found to be (W(MAP)m(-0.48))(0.54), (W(VT)m(-0.48))(0.46) and (W(AVG)m(-0.34))(0.58) that explained 69.3, 59.1 and 96.3% of the variance in cycling speeds, respectively. Cross-validation results suggest that, in conjunction with body mass, W(MAP) can provide an accurate and independent prediction of time-trial cycling, explaining 94.6% of the variance in cycling speeds with the standard deviation about the regression line, s=0.686 km h(-1). Based on these models, there is evidence to support that previously reported VO2-to-mass ratios associated with flat cycling speed extend to other laboratory-recorded measures of power output (i.e. Wm(-0.32)). However, the power-function exponents (0.54, 0.46 and 0.58) would appear to conflict with the assumption that the cyclists' speeds should be proportional to the cube root (0.33) of power demand/expended, a finding that could be explained by other confounding variables such as bicycle geometry, tractional resistance and/or the presence of a tailwind. The models predicting 6 and 12% hill-climbing cycling speeds were found to be proportional to (W(MAP)m(-0.91))(0.66), revealing a mass exponent, 0.91, that also supports previous research.
dc.format.extent303402 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherSpringer Berlin / Heidelberg
dc.relation.urlhttp://www.springerlink.com/content/l140p0304285u540/
dc.subjectPerformance measurement
dc.subjectTime-trial cycling
dc.subjectPower output
dc.subjectHill-climbing
dc.subjectSports Medicine
dc.subjectSpeed measurement
dc.titleOptimal power-to-mass ratios when predicting flat and hill-climbing time-trial cycling.
dc.title.alternativeCycling
dc.typeJournal article
dc.identifier.journalEuropean Journal of Applied Physiology
dc.format.digYES
refterms.dateFOA2018-08-21T15:54:51Z
html.description.abstractThe purpose of this article was to establish whether previously reported oxygen-to-mass ratios, used to predict flat and hill-climbing cycling performance, extend to similar power-to-mass ratios incorporating other, often quick and convenient measures of power output recorded in the laboratory [maximum aerobic power (W(MAP)), power output at ventilatory threshold (W(VT)) and average power output (W(AVG)) maintained during a 1 h performance test]. A proportional allometric model was used to predict the optimal power-to-mass ratios associated with cycling speeds during flat and hill-climbing cycling. The optimal models predicting flat time-trial cycling speeds were found to be (W(MAP)m(-0.48))(0.54), (W(VT)m(-0.48))(0.46) and (W(AVG)m(-0.34))(0.58) that explained 69.3, 59.1 and 96.3% of the variance in cycling speeds, respectively. Cross-validation results suggest that, in conjunction with body mass, W(MAP) can provide an accurate and independent prediction of time-trial cycling, explaining 94.6% of the variance in cycling speeds with the standard deviation about the regression line, s=0.686 km h(-1). Based on these models, there is evidence to support that previously reported VO2-to-mass ratios associated with flat cycling speed extend to other laboratory-recorded measures of power output (i.e. Wm(-0.32)). However, the power-function exponents (0.54, 0.46 and 0.58) would appear to conflict with the assumption that the cyclists' speeds should be proportional to the cube root (0.33) of power demand/expended, a finding that could be explained by other confounding variables such as bicycle geometry, tractional resistance and/or the presence of a tailwind. The models predicting 6 and 12% hill-climbing cycling speeds were found to be proportional to (W(MAP)m(-0.91))(0.66), revealing a mass exponent, 0.91, that also supports previous research.


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