CSS is a great measure of Cardiac Stress and, quite naturally, it relies on the athlete wearing a heart rate monitor (HRM) during exercise. However, sometimes we exercise without a HRM and sometimes we want this to “count” towards our overall accrued CSS. This is recognised in the Fit-Fat tab, which makes an estimate of CSS even for activities in which a HRM is not used.

This same estimation methodology has been extended to give an estimate of CSS its components; this is shown on a new All-in tab. Here, you can see four charts:

First, an estimate of CSS that takes into account all activities recorded on Strava, even those where an HRM was not used:


Here, the purple mass (technically, a density plot) shows the distribution of estimates amongst all Crickles athletes over the chosen period. We can see in this example that the most common value is at about 2,500, there are quite a few athletes (around 1/5th of the number at 2,500) at 5,000 and even a blip indicating one athlete over 20,000.

The vertical black line picks out the value for the chosen athlete (me in this example), and you can see that in this case the athlete (me) is bang on the most common value.

If an athlete wears an HRM all the time the estimate of CSS will be as good as we can get. Conversely, to the extent that an HRM is not used the quality of the estimate will decline. The second chart shows this quality for the given athlete over the chosen period:


Again, the purple mass is a density plot showing where Crickles athletes overall lie on the quality chart. Happily, the most common value is at over 90%. About 1/6th of the number at this high value are at zero, indicating that they didn’t use an HRM at all over this period. Again, the vertical black line represents the chosen athlete and again it’s me. I’m at about 87.5% usage. To verify consistency, you can multiply this percentage (87.5%) by the CSS estimate (2,500) we just saw and that will show the CSS that you see on the Relative CSS tab (about 2,188).

Very thoughtful readers may correctly spot that when you’re on a bike with a power meter Crickles is able to give a high quality estimate of CSS even in the absence of a HRM. This is indeed true but this is not reflected on this quality chart.

The third and fourth charts show the components of the full CSS estimate. These are Intensity:


and average weekly exercise hours:


The Intensity estimate is subject to the same estimate quality as the full CSS estimate (more HRM usage -> a better estimate) whereas the weekly exercise hours are a simple sum of “moving times” and are unaffected by HRM (non-)usage.

These charts work the same way as the others: for example, the most common weekly exercise time amongst Crickles users over this period is shown by the last chart to be five hours (the peak of the purple mass) and I did fractionally more than that (the vertical black line).

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