One of the best features of Strava is the battle to be King (or Queen) of the Mountain. Originally, in cycling, segments were typically climbs or difficult sections of road, and the simple idea, is who can complete the segment in the quickest time. Hence they would be KOM/QOM, King or Queen of the Mountain. Segments quickly expanded to pretty much any section of a course and to include running segments, to separate them from cycling.

There are lots of ways for runners and cyclists to analyse training data. A key question most fitness enthusiasts want to know is “how am I doing?”. “How you are doing” is referred to as form . Unsurprisingly, form can be estimated in many ways. One method is using training stress scores (acute training load and chronic training load) to assess form as training stress balance.

A short follow-up post. Previously, I looked at how to reproduce a Strava feature that compares performance over similar courses. With a few modifications to the code, I was able to analyse a much larger dataset of cycling performance on similar courses. Two courses with the highest number of tracks are shown below. I cycle these courses all the time. Well, I did until the pandemic struck.

As a geek, the added bonus of exercise is the fun that you can have with the data you’ve generated. A recent conversation on Twitter about the accuracy of wrist-based HRMs got me thinking… how does a wrist-based HRM compare with a traditional chest-strap HRM? Conventional wisdom says that the chest-strap is more accurate, but my own experience of chest-strap HRMs is that they are a bit unreliable. Time to put it to the test.

I use a Garmin 800 GPS device to log my cycling activity. including my commutes. Since I have now built up nearly 4 years of cycling the same route, I had a good dataset to look at how accurate the device is. I wrote some code to import all of the rides tagged with commute in rubiTrack 4 Pro (technical details are below). These tracks needed categorising so that they could be compared.

This year #paperOTD (or paper of the day for any readers not on Twitter) did not go well for me. I’ve been busy with lots of things and I’m now reviewing more grants than last year because I am doing more committee work. This means I am finding less time to read one paper per day. Nonetheless I will round up the stats for this year.