![]() ![]() Measuring the physiological response to physical activity can provide important insights for a variety of populations ranging from elite athletes to recreational exercisers to patients in rehabilitation 7, 8. In principle, these data provide an exciting opportunity to monitor human physiology noninvasively under real-world conditions outside the laboratory. For example, endurance athletes like runners and cyclists currently upload from GPS enabled sensors more than a billion activities per year worldwide 6. Recent decades have witnessed an ever growing exercising population which uses wearable sensors to bring together astonishing volumes of data for speed, distance, heart rate, accelerations, and more 3, 4, 5. Over the years, endurance running has undergone substantially change. ![]() It probably originated as a hunting skill but has later developed to competition, dating back to ancient Olympic Games ~720 BC 2 and exercise form for mass population. Skeletal evidence suggests that endurance running may have evolved 2 million years ago 1. Our findings hint at new ways to quantify and predict athletic performance under real-world conditions. Correlations between performance indices and training volume and intensity are quantified, pointing to an optimal training. Inclusion of endurance, which describes the decline in sustainable power over duration, offers novel insights into performance: a highly accurate race time prediction and the identification of key parameters such as the lactate threshold, commonly used in exercise physiology. Our model depends on two performance parameters: an aerobic power index and an endurance index. Here we demonstrate feasibility of this idea by applying a previously validated mathematical model to real-world running activities of ≈ 14,000 individuals with ≈ 1.6 million exercise sessions containing duration and distance, with a total distance of ≈ 20 million km. These data hold great potential for enhancing our understanding of the complex interplay between training and performance. Wearable exercise trackers provide data that encode information on individual running performance. ![]()
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