Mascot, TN
How exposed is Mascot to wildfire?
Mascot sits at the 74th percentile nationally for wildfire risk to structures — well above the national norm for wildfire risk — per USFS's Wildfire Risk to Communities model, built from its 1,732 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Mascot at the 79th percentile, close to its 74th-percentile risk score.
Where Mascot's buildings actually sit
Of Mascot's 1,732 counted buildings, 69.4% carry Direct exposure and only 0% carry Minimal — a lopsided split that puts defensible-space clearing ahead of vents or roofing as the intervention worth doing first.
Where Mascot ranks
Mascot scores 74th nationally and 75th within Tennessee — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Mascot ranks 8,140 for wildfire risk (1 is highest) and 8,298 by building count (1 is largest). Within Tennessee alone, it ranks 127 of 502 places by risk. See the full county-by-county picture for Tennessee on its state page.
Mascot and the insurance market
At the 74th percentile nationally, Mascot 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
With 69.4% of Mascot in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Mascot's figures come from
Mascot's 74th-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Mascot's dominant direct exposure actually means, with real examples from across the dataset.