One of the deep truths that every endurance athlete has to discover somewhere along their journey is that tomorrow matters as much as today. Maybe you can pick up the pace or add a few more miles to your workout; whether you should depends on whether doing so will compromise the next day’s training. The real gains come from stacking up weeks and months of work, but finding the edge of what’s sustainable is an art—for now, at least.
The latest attempt to turn athletic recovery into a science comes from researchers at the University of Auckland’s Sports Performance Research Institute New Zealand. A team led by Jeffrey Rothschild tracked 43 endurance athletes for up to 12 weeks, feeding reams of data into a series of machine learning models in an attempt to figure out what factors predict workout recovery. The results, which are published in the European Journal of Applied Physiology, offer some surprising insights on what matters and, just as importantly, what doesn’t.
The prerequisite for a study like this is athletes who are really into the idea of collecting data on themselves. The group ranged from…
