Why don’t we measure stress in energy expended instead of a derived (contrived?) metric like TSS? Right off the bat you introduce a lot of fudge factor with the dependence on measuring based off your FTP, which will fluctuate, and might not be “accurate”, ever.
If you used something like KJs, sure they’re not respective or your FTP, but you would know what 5000, or 10000, or whatever, felt like in a week, or in a day, and you could calculate 6 week rolling averages, to a view of chronic load.
You’d still test, to get a measure of improvement, and to gauge what intensities to shoot for.
Yep, intensity would definitely be a challenge. You’d do your fitness testing, so you could eyeball it and see all the efforts over say, your 5 minute MMP, but it wouldn’t be as effective as IF for that.
I find both useful, but I find tss better to frame a training plan. Ultimately, you want to ramp by training stress and tss is a better way to measure than kj’s.
Higher ftp, more KJ expended at the same relative training stress (IF).
Relative metrics, like TSS, are much more informative. That is, unless you think more absolute power is harder regardless of body size and strength to weight ratios of the athlete
I agree. If you want to rely on a metric then TSS is much better suited then kJ.
Or you could start paying attention to your heart rate, power, sleep quality, mood and general feeling. I think this would always be more benefitial. 1. You learn to know your own body. 2. We are not created equal, and other life stressors is not constant unless you are very lucky. 700 TSS one week could feel completely different the next. My relationship to TSS and ramp rates are as a curiosity in post analysis, not something that control my training at all. More often than not I see no correlation to how I actually feel and perform.
Fatigue is felt to have a nonlinear relationship with intensity. Using kJ assumes a linear relationship between intensity and fatigue because it uses average power.
Ex: workout A is 1h @ 60% (200w: ie: basically a recovery ride). This is 720kJ. (200w x 3600s) / 1000.
Workout B is 1h where you alternate 10min @ 20% and 10min @ 100% (ie 3 x 10min @ FTP). Average power is still 200w, still 720kJ.
TSS works by assuming that fatigue is not linear with intensity. It is based off of normalized power, not average power. Normalized power can be thought of as a type of weighted average that puts more weight towards higher intensity efforts.
As a result, the NP for workout A and B will be different, leading to a higher TSS for workout B than workout A.
TL:DR: kJ assumes fatigue is linear with intensity, which probably isn’t true. TSS does not make this assumption.
Kj doesn’t really assume anything other than the accuracy of your power meter. It’s just Kj’s… But yeah, everything you outline about TSS is dead on and the reason it’s a better measure to inform your training stress.
Maybe? I don’t know if I completely get your point, or if we’re just arguing semantics.
The point is that kJ will underestimate fatigue because the relationship between fatigue and intensity is nonlinear, and the formula for kJ just uses a simple average (average power), rather than a type of weighted average (NP).
The use of a simple average means you are weighing all intensities equally, rather than putting more weight on high intensity work.
Ie it assumes a linear relationship between intensity and fatigue.
Yeah, maybe semantics. Total agreement on what you are saying about TSS, but KJs doesn’t have a “calculation” with some complex formula or algorithm. TSS is an estimate of training stress and KJs is just a unit of measure (like inches or pounds). KJs isn’t an average or estimate of anything, it’s a measure of the work being pushed through the pedals. It’s often used to help calculate the calories (kcal) you are burning while performing that work.
Here’s an experiment for anyone who has the data to hand and can be bothered:
Have a look at a) Hours Ridden, b) TSS and c) kJ and see how tightly they correlate.
My guess is that in most cases you can just look at hours ridden and use it as a serviceable proxy for the other two, because IF converges on a figure somewhere btwn, say, 70% and 80% as rides are aggregated over time.