Cumulative scores: inputs, outputs, and more
Cumulative scores: inputs, outputs, and more
A better way to look at your response.
In HRV4Training Pro, you can build your own cumulative score, based on physiological and subjective data.
Here we don't build scores that are driven by your behavior (input), but we look at outputs instead. We also don't convert it to any % or made-up scale (e.g. 0-100), but show it changes with respect to your own normal range for the same set of parameters. Outputs are:
how your physiology responded (heart rate, HRV)
how you feel in the morning
This is a key difference from what you get in terms of readiness or recovery scores in most wearables. Why is that?
The whole point of assessing your state, either objectively via heart rate variability (HRV) or subjectively by feel, is to determine how you responded to your given circumstances. You already know the input (behavior) and are assessing the output (physiology or feel).
In other words, if I train hard or more for a few days, I want to assess how I responded (output). Including activity (input) in my assessment would mean penalizing me regardless of my body's response. For athletes (of any level), this method, used in readiness and recovery scores in wearables, is particularly ineffective: it hides information.
If you train, there is no point looking at readiness or recovery scores to assess how you are responding to a given training stimulus as these scores confound your response with your behavior. Is the score low because I responded poorly, or just because I did more?
Many of these scores trick you into thinking that “they work” exactly for this reason: they include your behavior in the equation. If you sleep less, the score will always be lower, but that has nothing to do with the actual state of your body. It is absolute nonsense for an athlete to rely on readiness or recovery scores that include behavior (and yes, they all do).
Including subjective feel is of course different: this is the output, i.e. how you feel after the fact, in the morning, which will be conditioned on what you did before (i.e. your behavior) but won’t be deterministic.
When combining your subjective feel with your physiological response (heart rate, HRV), you can get a more comprehensive picture of your response, and make meaningful adjustments to your plans.
The data is then used in HRV4Training Pro to build your own normal range for this cumulative score, and a baseline, so that you can determine if there are meaningful changes (e.g. a baseline below normal range) or not.
I am of course not claiming this is perfect, but it provides a more meaningful overview of your response (physiological and subjective) and how it is changing over time, in my opinion, with respect to made-up scores that combine your behavior and physiology, but include how you feel or key aspects of athletic performance that cannot possibly be measured by common wearables (such as muscle soreness).
Other variables (inputs like sleep time, activity levels, traveling, sickness, etc.) remain key as context, but should not drive the score (again, in my opinion).
See an example below:
if you use the HRV4Training app, you can try Pro at this link. You can also use referral code SCIENCE for 20% off any plan.
Thank you for your support.
Marco holds a PhD cum laude in applied machine learning, a M.Sc. cum laude in computer science engineering, and a M.Sc. cum laude in human movement sciences and high-performance coaching.
He has published more than 50 papers and patents at the intersection between physiology, health, technology, and human performance.
He is co-founder of HRV4Training, advisor at Oura, guest lecturer at VU Amsterdam, and editor for IEEE Pervasive Computing Magazine. He loves running.
Social:
Twitter: @altini_marco.
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