PeerJ (Aug 2015)

Field-measured drag area is a key correlate of level cycling time trial performance

  • James E. Peterman,
  • Allen C. Lim,
  • Ryan I. Ignatz,
  • Andrew G. Edwards,
  • William C. Byrnes

DOI
https://doi.org/10.7717/peerj.1144
Journal volume & issue
Vol. 3
p. e1144

Abstract

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Drag area (Ad) is a primary factor determining aerodynamic resistance during level cycling and is therefore a key determinant of level time trial performance. However, Ad has traditionally been difficult to measure. Our purpose was to determine the value of adding field-measured Ad as a correlate of level cycling time trial performance. In the field, 19 male cyclists performed a level (22.1 km) time trial. Separately, field-determined Ad and rolling resistance were calculated for subjects along with projected frontal area assessed directly (AP) and indirectly (Est AP). Also, a graded exercise test was performed to determine $\dot {V}{O}_{2}$V̇O2 peak, lactate threshold (LT), and economy. $\dot {V}{O}_{2}$V̇O2 peak ($\mathrm{l}~\min ^{-1}$lmin−1) and power at LT were significantly correlated to power measured during the time trial (r = 0.83 and 0.69, respectively) but were not significantly correlated to performance time (r = − 0.42 and −0.45). The correlation with performance time improved significantly (p < 0.05) when these variables were normalized to Ad. Of note, Ad alone was better correlated to performance time (r = 0.85, p < 0.001) than any combination of non-normalized physiological measure. The best correlate with performance time was field-measured power output during the time trial normalized to Ad (r = − 0.92). AP only accounted for 54% of the variability in Ad. Accordingly, the correlation to performance time was significantly lower using power normalized to AP (r = − 0.75) or Est AP (r = − 0.71). In conclusion, unless normalized to Ad, level time trial performance in the field was not highly correlated to common laboratory measures. Furthermore, our field-measured Ad is easy to determine and was the single best predictor of level time trial performance.

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