The Perception Deception

We know from the Stress, Recovery, Adaptation Cycle that stress must be increased over time in order to continually disrupt homeostasis, recover from that disruption, and adapt to the stress (and thus need a bigger stress to disrupt homeostasis the next time). But since stress can’t be measured in units, we need some form of metrics to measure progress, so that we know that the amount of stress and recovery is appropriate to bring about a strength increase.

Types of: Quantitative and Qualitative

Quantitative data is objective. It’s real. It’s true. Our primary piece of quantitative data is the PR, or the personal record. We believe so much in it’s power that we focus a vast majority of our work around the personal record and celebrate it no matter how big or how small.

Then there are secondary forms of quantitative data:

  • Total work volume (sets and reps)
  • Intensity (with regards to both % of 1RM and ACTUAL load on the bar)
  • Tonnage (or the weight times reps times sets to get a number). Example: If I did 315x5x5, then my tonnage for that lift on that day is 7875lb
  • Calculated 1RM, which uses an equation based on reps at a given weight to give an approximation about the strength of the lifter. In general, if the calculated 1rm is going up, then strength should be as well.

Remember that quantitative data is objective, and it allows us to organize and program for training based on our previous training.

Qualitative data is subjective, based on perception, and is most-often self-reported.
Qualitative data gives us perceived information about qualities; how hard something was perceived to be, how many reps the lifter perceived they had left in the tank, how close the form was perceived to be compared to the model, perceived fatigue, etc.

The problem with Rating of Perceived Exertion (RPE) and RPE based programming is that it is, by it’s very nature subjective (perceived), self-reported, and therefore qualitative. This doesn’t mean it’s completely worthless, but that it must not be held in the same regard as quantitative data.

Qualitative data is an appropriate communication tool as a descriptor, but is often inaccurate and ineffective as a prescriptor, and is unreliable to draw conclusions about the effectiveness of programming. The existence of RPE percentage tables shows that in practice, RPE is often just a proxy for percentage based programming.

So if you really want to know whether your programming is working, simply ask yourself, “Am I setting PRs on a routine and generally consistent basis?” If the answer is yes, then you’re getting stronger. If the answer is no, but your perception is that you are getting stronger…maybe it’s time you used a better metric…just to be sure.


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