It’s really not too complicated to try to model yourself and estimate individualized parameters. I always like to share this paper and spreadsheet.
Clarke and Skiba provide a rational DIY method for doing so…and for FREE.
You can use this spreadsheet, from Clarke and Skiba…tableS1
You can also use Golden Cheetah for Banister modeling.
The workflow is like this:
-Establish CP (FTP) from 2+ time trials. Verify CP (FTP) with RPE. No goofy approximations.
-Perform regular time trials during training to compare modeled performance to actual.
-Collect enough time trials (6+) to tighten model parameters and get SEE of the model
-Once the model parameters are optimized, you can then forecast future performance by your planned TSS, XSS, scoring units, etc.
I’ve been running more this year, and the model has been surprisingly useful.
Is this method going to be able to estimate to the watt or three? No! but it gives an idea of how the future training could impact future performance.