WHOOP Data From the Tour de France with EF Pro Cycling

Image | WHOOP

 

WHOOP Data at the Tour de France

The Tour is over but the data analysis has only just begun.

WHOOP was the official fitness wearable of the EF Pro Cycling team and all riders collected 24×7 data from a WHOOP strap. Their data unsurprisingly showed massive training loads (strain) over the entire duration of the race – the blue line in the chart below. If you follow professional endurance sport, the high loads may not surprise you and you will know that in order to achieve those loads you also need awesome powers of recovery and that too was shown by the WHOOP recovery metrics – green and yellow data points on the chart below.

 

 

Interesting WHOOP Fact: The team members’ average resting heart rate was 42 beats at the start of the race.

Source :  whoop.com

 

Must Read: Check out the latest WHOOP Review

the Whoop 4 Review 2023 + Discount – Is It Accurate?

 

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4 thoughts on “WHOOP Data From the Tour de France with EF Pro Cycling

  1. Indeed, saw this as well. Setting aside for a second the accuracy issues, it’s a super cool data set, and would love to see more insights like this from teams.

    That said, I feel like the chart above sorta illustrates in one handy picture the entirety of the problem with having a mythical max of 21 strain score: It doesn’t work.

    Aside from Stage 1, they basically near capped out the strain score every day. Of course, we know that’s not the actual strain of riders in the TdF. We know there’s more strain in the mountains, and more strain towards the end of the tour. But it seems like the algorithm simply can’t cope with that. Or, I suppose there’s the possibility than the riders all simply put on these straps the day before, in which case Whoop was like ‘WTF?!?’

    1. in those scenarios, power-measured strain and hrv/hr-measured strain would be different, no?

      yes, if they donned the straps for the first time on Day 0 of the race then the whole shebang is probably meaningless.

      1. Power based strain would show the output load by the cyclist, but not necessarily how that cyclist is handling that load (since 300w or X hours means something different to each cyclist).

        I think a HR approach for that particular graph would work quite well, but just not with the cap of 21. That’s the core of the issue. It doesn’t really seem like the algorithm accounts for the load (or more accurately, strain), of a Grand Tour.

        But, I suspect the real answer is simply that aside from 1 or 2, almost all of them probably just put it on during the team presentation…

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