I really like the variety of approaches the thread is touching on in regard to quantifying effort/stimulus. Whether lactate, heart rate, pace, or power. It’s interesting to see how the various metrics align with training and race performance too.
With regard to power, something that might be of interest to the group. The power model that Stryd uses, from what I can tell, is based on the sum of three power components. The primary values that contribute to the power level, specifically if power for air resistance and elevation are not a factor, are weight (kg), speed (m/s), and ECOR. ECOR stands for energy cost of running. Based on the data Stryd provides, they use a standard ECOR value of 1.04. So the simplified power equation looks like:
Power = Speed*Weight*ECOR
However, if you look at their data, it shows the better a runner you are, the lower your ECOR value. They list an elite runner as having an ECOR of 0.93, an average runner as 1.01, and an untrained runner as 1.06.
If you change your ECOR value from 1.04 to 1.01 in the power formula, that leads to a 2.88% REDUCTION in power, assuming speed and weight hold constant. So for those of us looking to target power for workouts and races, who are “better” hobbyists, keep that in mind.
Sirpoc has a good approach to go on feel and compare it to other metrics he uses. If you’re really into data, you can “fine tune” your ECOR value by observing it over the course of your sessions and calculating it yourself from the data.
ECOR = Power / (Speed*Weight)
If you want to use that data to get a more accurate race time prediction (assuming similar conditions as your workouts of course), based on a targeted power level:
Time = (ECOR*Distance*Weight) / Power
where Distance is in meters and Time in seconds
Hope that’s insightful for the nerds on the thread.
P.S. sirpoc, I like your idea of using the thread to crowd source data for more accurate training metrics over a span of devices/inputs. Lets make it happen LOL