Mabscott, WV
Mabscott, WV's wildfire risk, in USFS's own numbers
USFS scores Mabscott at the 57th national percentile for wildfire risk to structures (modestly above the national average for wildfire risk), a figure built from 760 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Mabscott at the 59th national percentile — 2 points above its risk-to-structures score, a gap driven by how much is actually built there.
Mabscott's building exposure, zone by zone
79.1% of Mabscott's 760 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 20.9% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
Mabscott against the rest of the country
There's little gap between Mabscott's 57th national percentile and its 46th percentile inside West Virginia, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Mabscott ranks 13,538 for wildfire risk (1 is highest) and 14,025 by building count (1 is largest). Within West Virginia alone, it ranks 232 of 429 places by risk. See the full county-by-county picture for West Virginia on its state page.
What this risk score means for insurance
At the 57th national percentile, Mabscott rates elevated for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
What would actually reduce this score
With ember exposure the dominant pattern in Mabscott (79.1% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Mabscott's figures come from
Mabscott's 57th-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 Mabscott's dominant indirect exposure actually means, with real examples from across the dataset.