Marvel, CO
Marvel wildfire risk explained
Out of every US place USFS scores, Marvel lands at the 79th percentile for wildfire risk to structures — well above the national norm for wildfire risk — a figure built from its 81 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Marvel at the 77th national percentile — 2 points below its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
86.4% of Marvel's 81 buildings sit in USFS's Direct exposure zone, roughly 70 structures close enough to burnable vegetation for flame contact, not just embers — 13.6% fall in the Indirect, ember-only zone and 0% are Minimal.
Where Marvel ranks
Inside Colorado, Marvel sits at just the 51st percentile even though it scores 79th nationally — the state's overall wildfire exposure is high enough to make this a relatively quiet corner of it. Among the 31,521 US communities USFS scores, Marvel ranks 6,736 for wildfire risk (1 is highest) and 29,839 by building count (1 is largest). Within Colorado alone, it ranks 232 of 472 places by risk. See the full county-by-county picture for Colorado on its state page.
Shopping for coverage in Marvel
At the 79th percentile nationally, Marvel carries the high rating that has pushed some carriers to limit new business in similarly-scored places elsewhere in the country. Worth comparing quotes rather than assuming last year's renewal terms still apply.
Lowering exposure, not just insuring around it
Marvel's 86.4% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.
Where Marvel's figures come from
The methodology guide shows exactly how USFS turned 81 counted buildings into the percentiles shown above for Marvel. The exposure-zones guide covers what Marvel's dominant direct exposure actually means, with real examples from across the dataset.