Hi TrainerRoad team - do you incorporate HRV as a recovery / readiness signal into your algorithms at all? If not, what are your thoughts on it’s effectiveness and do you plan to incorporate this in the future?
Thanks!
Have a look at the massive RLGL thread, its not based on HRV though.
HRV is affected by tons of factors, and is almost useless in determining if you should or shouldn’t train, much less determining how fresh or fatigued you are. Many many times I wake up with very high hrv despite being deep into a training block and feeling all sorts of fatigue, or having lower HRV despite a rest week and feeling really fresh. Or walking up with low HRV, doing my workout as planned, and then having normal hrv the next day without and recovery issues. Pretty pointless IMO. I’ve used Whoop and/or Garmin since 2021.
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Sian Allen has written a lot about the HRV and how to use it as an athlete. She has also compared different devices; if I am correct the Whoop was not one of her recommended devices for following HRV.
Rlgl doesn’t take into account any data outside of workouts. Sure, most of the time your outside of workout stress is pretty similar day to day but not always.
I’m not saying blindly follow hrv results, but have it as an input can be useful. I’m sure the machine learning can figure out how to use the data
It doesn’t do any specific analysis that I am aware of, but RLGL does take account of TSS due to outside workouts (it might consider more but I am not privy to behind the scenes at TR) and adapts your indoor workouts down if it considers that you outside workouts (TSS) are too much with the aim of keeping you to your plan target. Have a look at the link and video embedded, it probably explains it better than me.