Fannett, TX
Fannett, TX's wildfire risk, in USFS's own numbers
Out of every US place USFS scores, Fannett lands at the 86th percentile for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — a figure built from its 1,575 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Fannett at the 90th national percentile — 4 points above its risk-to-structures score, a gap driven by how much is actually built there.
Fannett's building exposure, zone by zone
Indirect exposure is dominant in Fannett (55.2% of 1,575 buildings): far enough from burnable vegetation to avoid flame contact, close enough for wind-blown embers. Only 44.8% sit in the Direct zone.
Where Fannett ranks
There's little gap between Fannett's 86th national percentile and its 75th percentile inside Texas, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Fannett ranks 4,424 for wildfire risk (1 is highest) and 8,861 by building count (1 is largest). Within Texas alone, it ranks 441 of 1,795 places by risk. See the full county-by-county picture for Texas on its state page.
What this risk score means for insurance
At the 86th percentile nationally, Fannett carries the very 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.
What would actually reduce this score
Fannett's 55.2% Indirect-exposure share points at embers, not flame contact, as the main pathway — ember-resistant vents and non-combustible roofing rank ahead of defensible space here. Detail in the home-hardening guide.
Where Fannett's figures come from
The methodology guide shows exactly how USFS turned 1,575 counted buildings into the percentiles shown above for Fannett. The exposure-zones guide covers what Fannett's dominant indirect exposure actually means, with real examples from across the dataset.