Earlier shift in race pacing can predict future performance during a single-effort ultramarathon under sleep deprivation In this study, Ultramarathon’s research camp was built over 50 and 100 miles to examine human endurance capabilities under extreme sleep loss and stress. It takes average> 24 hours to run 100 miles with minimal sleep, so we can create 24-hour performance profiles.We collected performance data that has been recorded over time (racing spots) and distance, self-reported sleeping and training patterns and endpoint data for cardiovascular fitness / adaptation to total sleep deprivation and extreme workout. In general, we realized that the self-reported nap in 100 mile runners was higher than 50-mile runners, and that ultra races may be previously selected for early risers. We have also compared performance profiles between the first 50 miles covered by all runners to investigate amplitude and acrophase differences in performance using a cosine form model. We have shown that runners, who completed a 100-mile ultramarathon, had a former acrophase shift compared to non-finishers, although all runners slowed over time.
We were able to identify time-dependent predictions about the overall performance with minimal sleep, which justifies the ultramarathone athlete as a unique demographic structure for future investigations of sleep and chronobiological relations in the real world. The whole work can be found under https://www.ncbi.nlm.nih.gov/pmc/articles/pmc7347363/