Can critical power be estimated for mean maximal power output values - Spragg, J. (Journal of Science and Cycling, 2021)
The Critical Power (CP) represents an important threshold in exercise physiology (Poole, Burnley, Vanhatalo, Rossiter, & Jones, 2016) CP defines the border between the heavy and severe exercise domains (Burnley & Jones, 2018)and thus separates power outputs for which a physiological steady state can, and cannot, be achieved. It has been shown to have applicability to both stochastic and non-stochastic efforts within the severe exercise domain (Jones & Vanhatalo, 2017). CP is mathematically defined as the asymptote of the power-duration curve (Jones & Vanhatalo, 2017) . Traditionally, CP was estimated from 3-5 performance trials conducted on successive days (Moritani, Ata, Devries, & Muro, 1981) but it has recently been shown that CP can be estimated from a single exercise session (Simpson & Kordi, 2017). However, even this condensed approach may not always be feasible in-season in a professional cycling population due to the required volume of training (Metcalfe et al., 2017). Previous research (Pinot & Grappe, 2011) has shown that record power outputs (MMP) from training and racing can be used to derive a hyperbolic power-duration curve. The Critical Power (CP) represents an important threshold in exercise physiology (Poole, Burnley, Vanhatalo, Rossiter, & Jones, 2016) CP defines the border between the heavy and severe exercise domains (Burnley & Jones, 2018) and thus separates power outputsfor which a physiological steady state can, and cannot, be achieved. It has been shown to have applicability to both stochastic and non-stochastic efforts within the severe exercise domain (Jones & Vanhatalo, 2017). CP is mathematically defined as the asymptote of the power-duration curve (Jones & Vanhatalo, 2017) . Traditionally, CP was estimated from 3-5 performance trials conducted on successive days (Moritani, Ata, Devries, & Muro, 1981) but it has recently been shown that CP can be estimated from a single exercise session(Simpson & Kordi, 2017). However, even this condensed approach may not always be feasible in-season in a professional cycling population due to the required volume of training (Metcalfe et al., 2017). Previous research (Pinot & Grappe, 2011) has shown that record power outputs (MMP) from training and racing can be used to derive a hyperbolic power-duration curve.