Watt Matters is a blog about training and racing with power and other related musings.

Aside from writing items here on occasions, I also provide cycling performance improvement services via coaching, aerodynamics testing and host a cycling tour.

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VAM & W/kg estimates

VAM & W/kg estimates

Just wanted to post a few charts for reference.

First chart compares W/kg estimates based on the same vertical ascent rate (VAM) for each of two methods:

Dr Ferrari's formula and the mathematical model described in the paper by Martin et al:

The plot compares the W/kg estimates for each of three gradients: 6%, 8% and 10% for a range of VAMs between ~800 m/h and ~2000 m/h. A red unity line is included for reference.

To make the variances between each method a little easier to see, the following chart plots the difference between the two W/kg estimates, again a line for each of the three gradients: 6%, 8% and 10%.

I don't have a lot to add to the charts other than to say the Dr Ferrari formula is a bit of a quick and dirty way to estimate W/kg from ascent rates but it does not consider a range of variables included in the Martin et al formula.

In particular we can see the estimates can vary quite a bit depending on both gradient and on VAM.

Same plot as above but this time with the variance expressed as a percentage of the Martin et al method estimate:

I would certainly place more faith in the Martin et al method, and that was also the conclusion of this paper by @ammattipyoraily and @veloclinic (Dr. Mike Puchowicz) which examined the different methods of calculation compared with actual power meter data from a large number of data files.

Estimating climbing performances of professional cyclists: a larger dataset

For consistency with the analysis in the paper above I chose rider mass and CdA in the middle of the range from that paper. I do not know what Crr assumption were used though. I settled on 0.005.

A Crr value in the range 0.004 to 0.005 would be typical and the impact on calculations of a difference between 0.004 and 0.005 is equivalent to adding 0.1% to gradient (and an associated bias error in W/kg estimates of about the same order).

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