As a young runner in the 1990s, I spent a ton of effort collecting and interpreting data. I would check my pulse every morning as soon as I woke up, then again ten seconds after getting out of bed. The difference between those two numbers, I had read, was a sensitive early warning sign of overtraining. I plotted my weekly mileage in a Lotus 1-2-3 spreadsheet, and scrutinized the peaks and troughs and trailing averages. I faithfully memorized and recorded every split of every interval workout.
These days, of course, we’ve shifted from scarce and laboriously collected data to an abundance that I could hardly have imagined—which, for an obsessive enthusiast like me, is a mixed blessing. There’s a seemingly endless array of devices that offer you real-time feedback to optimize your training and performance. Over the years, I’ve written lots about heart-rate variability and continuous glucose monitors and muscle oxygen sensors and so on. I’ve also pondered the relative merits of subjective versus objective metrics, and descriptive versus prescriptive use of data. Overall, I’m still conflicted about it. Data,…
