Skip to main content
Weight and FTP Targets

My 20 minute max power comes in regularly at about 280w during my 2x20 sessions making my estimated FTP about 266w (although I'm testing this specifically later this week with the powertap and turbo). Since my weight is currently 76.1kg this means that today, with no wind, I would average 7.9mph whilst climbing the 8.6 miles up the 21 switchbacks of the Alpe D'Huez - taking me 65 minutes.
I'm currently out by almost 10%.

There is under 3 months to go. I need to either improve my FTP to 292w or I need to drop to 68kg. Neither is a realistic option so a happy compromise of both increased FTP and reduced Weight is required - but what should the goals be?

Doing the maths shows that every kilo that I lose will save me 3w on my FTP. Whilst the most optimistic sources suggest that the best I can expect from a 3 month dose of L4 training is a 10% increase in FTP and that is for an untrained individual - and that is not me.

The chart below helps to illustrate the dramatic impact of weight on FTP for 8.6mph up the Alpe D'Huez.

Looking at my power and weightloss data I believe my targets could realistically be to get to 72kg and an FTP of 280w, minimum. With no wind I would make it up in just under 60 minutes, a stretch target of of 290w and weight of 70kg would be fantastic, giving me a few valuable seconds.

So with all the pondering it looks like the targets set over two months ago are right; 292w FTP and 70kg.

Enough waffle, I'm off for a L4 workout.

Popular posts from this blog

W'bal its implementation and optimisation

So, the implementation of W'bal in GoldenCheetah has been a bit of a challenge.

The Science I wanted to explain what we've done and how it works in this blog post, but realised that first I need to explain the science behind W'bal, W' and CP.

W' and CP How hard can you go, in watts, for half an hour is going to be very different to how hard you can go for say, 20 seconds. And then thinking about how hard you can go for a very long time will be different again. But when it comes to reviewing and tracking changes in your performance and planning future workouts you quickly realise how useful it is to have a good understanding of your own limits.

In 1965 two scientists Monod and Scherrer presented a ‘Critical Power Model’ where the Critical Power of a muscle is defined as ‘the maximum rate of work that it can keep up for a very long time without fatigue’. They also proposed an ‘energy store’ (later to be termed W’, pronounced double-ewe-prime) that represented a finit…

Polarized Training a Dialectic

Below, in the spirit of the great continental philosophers, is a dialectic that attempts to synthesize the typical arguments that arise when debating a polarized training approach.

It is not intended to serve as an introduction to Polarized training, there are many of those in-print and online. I think that Joe Friel's blog post is a good intro for us amateurs.

For Synthesis Against A Elite athletes have been shown in a number of studies to train in a polarized manner [1][2][3] There is more than one way to skin a cat. Elite athletes adopt plans that include high-volumes of low intensity and low-volumes of high-intensity. Elite athletes have also been shown to train in a pyramidical manner
[13] B Polarized Zones are between LT1/VT1 and LT2/VT2 [1]
LT1/VT1 and LT2/VT2 can be identified using a number of field based approaches [4][5][6][7]

You can follow guidelines on mapping LT1/LT2 to cycling power to make it useful for amateur cyclists. Polarized zones are har…

W'bal optimisation by a mathematician !

So the integral computation for W'bal was expensive.

I tried to optimise from a domain and  programming perspective, where Dave Waterworth, a mathematician found a much more elegant and fast reformulation.

This means W'bal can EASILY be computed as you ride.

To explain the math here are his words;

I posted a comment on you Blog post on optimising the Wbal model. I've done some more thinking and I defn think it can be done without visiting the previous samples as the Skiba formula can be decomposed further, i.e. From your blog I believe the integral part of the equation is:

Basically this takes a weighted sum of preceding W'exp samples where the weight decays at a rate determined by tau, older samples are weighted less than newer ones. We can approximate as a sum provided tau is large compared to Ts (the sample rate):

Basic properties of exponential functions allow the for…