How does XERT estimate fatigue (and therefore recovery time)?

I’ve read a few posts on this topic already but thought I’d ask for clarification. I’m 62 years old and I know for sure that I don’t recover like I did 40 years ago. Nowadays, if I do a hard workout, I’d better wait for at least a couple of days before I try to do that again. However, I recall Armando (maybe?) said that there’s no age model for the athlete in XERT which would partially take this into account. And of course, there are other factors besides age that will affect recovery rate. So, how does XERT estimate my freshness?? The only thing I can see is that it’s based on my historical load, which then assumes that during that period I wasn’t over- or under-training. Of course, part of the goal of XERT is to provide a reasonable estimate of progression that will optimize and maintain the athlete in this ‘sweet-spot’, so this seems rather circular. I’m starting to conclude that I need to self-calibrate or get a coach who has more experience to ‘guess’ my freshness for me.

Hi David. HOLD THIS THOUGHT! We are working on a new feature specifically to address this question. It’s in testing now so hopefully won’t be long before we release it. it will allow you to provide feedback so that the algorithm can better represent how you’re able to recover. Stay tuned…

That sounds interesting! Better estimation of fatigue would certainly be welcome. On the other hand, this would still be a best-guess. It would seem like the best way would be to get a real measure of fatigue. I can see a couple potential ways. Would lab monitoring be a way, perhaps? Something like oxygen saturation or something? Another (and maybe fitting in better with XERT) would be to insert a short fatigue measurement section at the end of a workout. If it’s short enough then it wouldn’t be too draining to the athlete so as to mess up, say, a rest day. Then, by measuring a decreased MPA by going to failure (basically, I’m tired today and I can’t put out the power that my nominal MPA says I should) wouldn’t that give a gauge of tiredness that is dynamic?

We’re measuring tiredness across three systems and use this in prescribing training. It makes it harder to use other methods which are often uni-dimensional. Your thought about adding a test at the end of a ride is a very good one. We have in fact tested this approach and we have been able to pick up on the fatigue that occurs. We’ve called this “slow-recovery fatigue” (We even make reference to this in one of our first blogs: Physiologically, this is likely the result of decreased glycogen stores and the recovery needed is the time needed to replenish these stores. We are looking to add this modeling to the sofware in the future both by showing what happens between activities as well as intra-ride itself.

Very cool stuff! One last (?) question on this topic: Almost none of the workouts show a prediction of MPA dropping to achieve a breakthrough (with the exception of the RAMPS FOR BREAKTHROUGH and SHORT INDOOR FITNESS TEST). I guess some of the harder workouts might not be completed if I’m tired but so far XERT hasn’t suggested any of those. So, if I am able to complete all suggested workouts, it would seem that XERT should assume I’m still fresh (unless it guesses that I’m tired based on a model). So, when you say you measure tiredness across three systems, does that mean model-based using my XPMC settings? And, this goes back to my point that unless I show weakness in some way then there’s no way to distinguish between having JUST BARELY finished a workout and EASILY finishing a workout. Is this accurate?

It is model-based on the three impulse response models (3 xpmcs). The workouts get scored based on their difficulty scores and there is an expectation that with more training, you can handle workouts with greater difficulty. We don’t yet look at how well a workout was completed to establish a secondary measure of tiredness/readiness to train at this time. WIth the new feedback tool we are working on, it will be the responsibility of the user to tune the setting whereby it will better reflect their feelings of readiness. This will be post workout completion but should remain static over a given time period and apply to new workouts moving forward.