By 30th September 2022, I had clocked up a total of over 2000 km of running in 2022. This milestone was a good opportunity to look at how I got to this point. The code is shown below. First, we can make a histogram to look at the distance of runs. From this type of plot it’s clear that my runs this year consist of a lot of 4-5 km runs and then a chunk of 21 km plus.

Joe Friel reposted an article earlier this year on Efficiency Factor in running. Efficiency Factor (EF) can be viewed in Training Peaks software and he describes how it is calculated. This post describes how I went about calculating EF in R using a single gpx file. What is Efficiency Factor (EF)? Essentially, EF is the average distance that you are propelled forward per heart beat. The higher the number, the more efficient you are at running.

The Green Leek 10.5 km run is a mixed terrain race now in its third year. Today’s was a wet and muddy edition. The chip times were posted this afternoon and using my previous code, I took a look at the results. I was a bit disappointed with my time, which was about 24 s slower than last year. Considering that I’m running faster this year than last, I wondered whether the conditions affected my time.

I’d seen the small multiple artwork of running and cycling routes from Marcus Volz’s R package Strava all over the web. Ads for “posters of your GPS tracks” pop up on Reddit and I’d notice a few #Rstats people put up their posters on Twitter. I’ve had the package bookmarked for a while and this week I finally got round to generating a small multiple poster of some of my cycling routes.

I recently got a new GPS running watch, a Garmin Fēnix 5. As well as tracking runs, cycling and swimming, it does “activity tracking” – number of steps taken in a day, sleep, and so on. The step goals are set to move automatically and I wondered how it worked. With a quick number crunch, the algorithm revealed itself. Read on if you are interested how it works.

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.

The following is a guest blog post by David Schindel and colleagues and is a response to the paper by Antonio Marques et al. in Science doi:10.1126/science.341.6152.1341-a.Marques, Maronna and Collins (1) rightly call on the biodiversity research community to include latitude/longitude data in database and published records of natural history specimens.