Analytics on apples and oranges: Comparing sports

I was an exercise logger long before I had heard the word “analytics.” I became a semi-serious recreational runner in 1996, and after a few months of paper logs, I’ve kept track of my running digitally. Early on, I used one of the first log apps, The Athlete’s Diary (which still appears to exist!), then for many years a modified Excel template created by a couple of people from the Dead Runners Society. Since switching to GPS watches, I’ve used a bunch. Currently I use and like Garmin Connect and Strava, as I wrote last week.

The analytics these new tools provide are impressive. But running is, in lots of ways, easy to be analytical on: There’s time and distance, and therefore speed. There’s effort, for which a heart rate is a pretty great proxy. Add terrain (from GPS or your own logging), cadence (from your watch’s accelerometer), and you can analyze and compare almost everything you do.

But what if you do different sports? Or, worse yet, sports that are very complex. When “constantly varied” is in the definition of a sport, as it is for CrossFit, my preferred version of “functional fitness,” you know it’s not going to be easy to figure out how one workout relates to another. What’s a boy to do? Continue reading