Information generated from a 13.1-mile footrace often known as the Golden Leaf Half Marathon usually consists of ending instances for every participant, typically categorized by age group and gender. These datasets may function extra data, corresponding to participant names, bib numbers, and general placement. An instance could be a desk itemizing every runner’s title alongside their ending time and general rank throughout the race.
Entry to this aggressive data gives runners precious insights into their efficiency. It permits for self-assessment, comparability with different members, and monitoring of non-public progress over time. Moreover, race outcomes contribute to the historic document of the occasion, documenting particular person achievements and the general evolution of participant efficiency. This data may be helpful for race organizers, sponsors, and researchers finding out athletic developments.
