For my workout yesterday, I played around on the ‘Advanced MPA’ screen to try and understand how TP and HIE affect the MPA.
By tuning TP and HIE in concert, I can get to very similar levels of MPA and ‘best effort’. See attached screenshots with two extreme values of TP=240 and TP=280
In those two, how would I understand which one is correct? How would one choose between a higher TP, but lower HIE and a lower TP and higher HIE?
Which one represents reality, or … does it matter?
TP280 TP240
Xert’s extraction (optimization) technique looks for an overall pattern of fatigue. Maximal efforts have the greatest affect on the parameters but other data near MPA also have an impact. The extraction works best when the fitness signature the extraction starts with is representative of your previous fitness. What Xert does is base changes in your fitness signature relative to your current one. Over a period of breakthroughs, Xert narrows in on your numbers and then adjusts them up and down. The fine-tuning also uses your work (strain) you have accumulated. This is one reason that properly seeding your progression recalculation with a starting signature that is close to where you were at your first activity, generates best results.
So, which one would be correct? TP=240 or TP=280? How do I do the proper seeding so the starting signature is correct?
Rodrigo, I would suggest you try the Signature Calculator if you need more assistance. Based on 3 best efforts, you should be able to establish a good seed signature that you can use. 40W is a very large discrepancy in TP and a further MMP datapoint, together with something near PP as the first value, should provide a reasonable good estimate to start from.
Another interesting technique to try that I have used often, particularly on activities with a good number of maximal efforts at varying levels, is to do repeating extractions (click the extraction button, wait for results, click again, wait for results, etc.) This can work well to converge on a set of values that make the most sense. If your activity doesn’t have many maximal efforts, the process may diverge so you’d need to be careful. Nonetheless, it is an interesting approach.