Data and code repository for the manuscript: JC Selinger, JL Hicks, RW Jackson, CM Wall-Scheffler, D Chang, and SL Delp. Running in the Wild: Using large-scale wearable data to understand ecological running speed preferences. Current Biology (2022).

Human runners have long been thought to have the ability to consume a near constant amount of energy per distance traveled regardless of speed, allowing speed to be adapted to particular task demands with minimal energetic consequence. However, recent and more precise laboratory measures indicate that humans may in fact have an energy-optimal running speed. Here we characterize runners’ speeds in a free-living environment and determine if preferred speed is consistent with task or energy dependent objectives.

We analyzed data from anonymized runners using the Lumo Run wearable device (Lumo Bodytech Inc.), in combination with pooled laboratory data of running energetics, to answer two questions. First, do runners adapt their preferred speed for different distance tasks? If minimizing cost of transport is not a dominant objective, and runners instead tailor their preferred speed to the task (for example minimizing time across run distance), we might expect faster paces for shorter distances and slower paces for longer distances. Second, are runners’ preferred speeds energy optimal? If minimizing cost of transport is a dominant objective, we expect preferred running speeds to be unaffected by the task (run distance) and also consistent with speeds that minimize cost of transport.

We found that individual runners preferred a particular speed that did not change across commonly run distances. We compared data from lab experiments that measured participants’ energy-optimal running speeds to the free-living preferred speeds of age- and gender-matched runners in our dataset and found the speeds to be indistinguishable. Human runners prefer a particular running speed that is independent of task distance, and consistent with the objective of minimizing energy expenditure.