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Weekly Weigh-In

Weight: 85.4kg (no change - again!)
Weekly Distance: 200km (+77km)
Peak 5 Min Power: 295
Peak 20 Min Power: 247
Peak 60 Min Power: 225 (NP 245)
Highlight of this week: Um. Not a good week.
Goal for next week: No refined carbs.

On plan this week, the sessions are focusing on cadence rather than power so the intensity isn't there and working on leg speed is a bit 'boring' :-)

Weight loss stalled, not due to lack of exercise, but too much eating. I'm being good and eating 3 good meals a day, but also polishing off chocolate bicuits, bars etc isn't a pro-athlete regimen.

Must try harder.

Here are some charts...


Oh, speaking of charts, Damien Grauser has coded the Heartrate based TRIMP metric for Golden Cheetah. It isn't published yet but I was playing with it over the weekend and updated the performance manager and other charts to plot it. I thought it would be interesting to plot a HR (TRIMP) based PMC against an Power (SKIBA) based PMC to see how they aligned.

Lets just say, I'll be wearing my HR strap on every ride from now on... I think the results bear close examination and potentially provide some new insight between power/hr for tracking performance and fatigue...


And as requested in the comments, here is a comparison of TRIMP vs Coggan metrics, rather than Skiba metrics:

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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…