An optimal pacing approach for track distance events

Track athletes aiming to compete at the highest level often must meet specific qualifying standards for middle and high school state championships, national collegiate championships, and ultimately, the Olympic Games. In this project, we aimed to address the best approach for achieving personal best times in track distance events. We used an existing mathematical model based on physiological attributes of world-record-setting elite runners to yield an optimal pacing approach. We then confirmed the validation of this energy depletion model using elite men’s and women’s gold medal performances at the Tokyo 2020 Olympic Games. We hypothesized that the average pace of a field of high school athletes competing in 800 m, 1600 m, and 3200 m distance events at a championship track meet does not follow the optimal pacing profile. Instead, we believed many runners begin with a fast pace to stay within close range of the race leaders, while others start conservatively to save energy for the final stage of the race. We used official timing data to test our hypothesis against computational simulations. We found that the average pace could deviate from the theoretical optimal pace by as much as 4%, translating to a difference of 1-2 seconds every 200 meters. Our analysis helps middle and high school athletes understand how pacing can improve their personal best times and what training can be performed to improve their physiological capabilities.