If you follow StravaвЂ™s suggestion of using FTP, subsequent calculations will underestimate your Training Load, which, in turn, impacts your Fitness & Freshness curves. This is important because this figure is used to calculate Intensity and Training Load. The problem is that if StravaвЂ™s Weighted Average Power is based on SkibaвЂ™s xPower, it would be more consistent to use Critical Power, as I did in the table above. Strava allows you to set your Functional Threshold Power under your personal performance settings.

The emphasis of FTP is on the maximum power sustainable for one hour, whereas CP is the power theoretically sustainable indefinitely. Functional Threshold Power and Critical Power measure slightly different things. It is important for a serious cyclist to have a good idea of the power that he or she can sustain for a prolonged period. For a well-paced time trial, the variability index should be close to 1.00. These are very high figures, due to the hilly nature of the session. The variability index compares each adjusted power against average power, resulting in variabilityВ indices of 1.57 and 1.41 respectively. Both the Normalised Power of 282W and xPower of 252W were significantly higher than the straight average power of 179W. The hill reps ride included multiple bouts of high power, causing repeated accumulation of lactate and other stress related factors. This suggests that taking the average of smoothed watts raised to the power 4 gives an indication of the average level of lactate in circulation during the ride. PlottingВ the actual data from a recent test on a log-log scale, I obtained a coefficient of between 3.5 and 4.7, for the relation between lactate level and watts. The following chart is a good example, showing the rapid accumulation of blood lactate concentration at high levels of effort. Why do both metrics take the watts and raise them to the fourth power? Coggan states that many of the bodyвЂ™s responses are вЂњcurvilinearвЂќ. Secondly, the smoothing used for xPower is less volatile, therefore xPower will always be lower than Normalized Power (because the fourth-power scaling is dominated by the highest observations).

Firstly, xPowerвЂ™s exponential smoothing is more highly correlated with heart rate, so it could be argued that it does indeed correspond more closely with the underlying physiological processes.

The following chart zooms into part of the hill reps session, showing the raw power output (in blue), moving average smoothing for Normalised Power (in green), exponential smoothing for xPower (in red), with heart rate shown in the background (in grey). According to Skiba, exponential decay is better than CogganвЂ™s linear decay in representing the way the body reacts to changes in effort. Normalized Power uses a 30 second moving average, whereasВ xPower uses a вЂњ25 second exponential averageвЂќ. The only difference between the calculations is the way that smoothing accounts forВ the bodyвЂ™s physiological delay in reacting to rapid changes in pedalling power.

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