The competitive outcome of this challenging Arizona ultramarathon provides valuable data for runners, coaches, and race organizers. A typical dataset includes finishing times, placements, and potentially additional information like DNF (Did Not Finish) statistics and split times at various aid stations. This data often allows analysis of runner performance across different age groups, genders, and experience levels.
Access to this information offers crucial insights into the race’s difficulty and the participants’ preparedness. It allows runners to benchmark their performance against others and identify areas for improvement. Coaches can utilize the data to refine training strategies, and race organizers can gain valuable feedback for future event planning. The historical context of these outcomes, tracked year over year, reveals trends in participation, performance improvements, and the evolving nature of the ultra-running community.