nickobec wrote:I have a decent 5 min, my 5 to 10 min power is well above my critical power curve, sub 5 minute drops away dramatically from the curve and after 10 minutes, my power goes into a steady decline below the curve.
So knowing those guidelines, using the critical power curve, I know I need to work on my sprinting and endurance / FTP and I need to start using my strength to my advantage.
The idea of understanding your individual characteristics to help guide your training is a good one, however there is no such thing as a "CP curve" since there is only
one critical power.
CP is the slope of the line plotting maximal energy output versus duration.
The Critical Power (CP) paradigm describes the work-time relationship, where the work (joules) performed during a maximal bout of exercise is dependent on the duration of effort and the individual’s current aerobic and anaerobic capabilities. i.e. a higher work rate (power) is possible over shorter durations and vice versa.
The work-time relationship is readily (and quite accurately*) expressed as a linear equation:
Workmax = AWC + (CP x t)
Workmax is the total work performed (in joules)
AWC is the anaerobic work capacity (y axis intercept – joules)
CP is the Critical Power (slope of the line – watts)
t is time (x axis – seconds)
In this sense CP is the maximal Power output sustainable over a long time without fatiguing. In practical terms CP corresponds closely to FTP.
It is possible (indeed useful) to use this relationship to establish both a rider’s CP and AWC and can be readily done via measuring the average Power of two or more maximal exercise bouts over different durations between 3 and 30 minutes.
The CP paradigm can also be used to pre-determine/estimate a rider’s maximal Power output over various untested durations, as well as establish changes in both AWC and CP resulting from training.
* There are of course some caveats in using the CP model as described, particularly about not using it in a predictive sense for predicting Power for very short or very long durations, and importantly the quality of the inputs used in the model. Feed the model rubbish data and you'll get crap output (GIGO).