Analysis of the 72-h ultramarathon using a predictive XG Boost model - Knechtle, B.; Villiger, E.; Weiss, K.; Valero, D.; Gajda, R.; Scheer, V.; Barbosa de Lira, C. A.; Braschler, L.; Nikolaidis, P. T.; Vancini, R. L.; Cuk, I.; Rosemann, T.; et al. (Sport Sciences for Health, 2024)
Background Ultramarathon running enjoys unwavering popularity. This includes the 72-h run, the longest time-limited ultramarathon based on hours and not days, yet this specific race format remains understudied. In particular, we are still determining where the fastest 72-h ultra-marathoners originate or where the fastest races are held. The aim of the present study was to investigate the origins of the best performers and the locations of the fastest races.