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Making the best recovery test even better

Scott Semple

When I woke up this morning, I knew that I needed to change my training plan. My Training Peaks metrics are positive, but my reality is far different.

My TSB is near zero, but I’m tired. I should be feeling recovered and ready to start another training block. But I don’t, and I’m not.

HRV apps are not the answer

A year ago, I co-wrote an article on the latest crop of HRV apps. Our conclusion, at best, was that HRV apps are not helpful. At worst, they’re dangerous.

The make-or-break question for a recovery test is, “How often does it show a false positive?” How often does the test recommend training when rest is really what’s needed?

The HRV apps that we tested all showed several false positives, some dangerously frequent. Luckily, the orthostatic heart rate test (OSHR) is a simple, low-tech option. I’ve never had a false positive with it. Even better, it flashes warning signs when there may be a problem on the horizon.

Improving the orthostatic recovery test

To make the OSHR even more robust, I ask myself seven questions before I look at the test results. Even on their own, these questions are often enough to paint a clear picture of my recovery status.

  • Do I have any leg fatigue walking up a flight of stairs?
  • Do I feel any general fatigue?
  • Did I have a bad sleep?
  • Do I feel any delayed onset muscle soreness (DOMS)?
  • Am I exposed to any sick people?
  • Do I have any cold or flu symptoms?
  • Was yesterday stressful?

And then I track my answers in a spreadsheet. If I answer “yes” to any of the questions, the summary cell turns red. If “meh”, the cell turns yellow. If “no”, green. It gives me graphic feedback on where I’m at.

Image of recovery questions in a spreadsheet
What a recovery log looks like for a clinically type-A tweaker

The power of negative thinking

It’s very important that the questions are framed in the negative. I want to look for disconfirming evidence. If the questions were framed in the positive:

“Did you have a good sleep?” instead of “Did you have a bad sleep?”

…then I’d be looking for evidence to support my preferred outcome. It would bias me toward short-term training and away from what’s more important: long-term training.