Loyall, KY
Loyall, KY's wildfire risk, in USFS's own numbers
Out of every US place USFS scores, Loyall lands at the 89th percentile for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — a figure built from its 385 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Loyall at the 91st percentile, close to its 89th-percentile risk score.
Where Loyall's buildings actually sit
85.5% of Loyall's 385 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 14.6% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
How Loyall compares
Loyall scores 89th nationally and 88th within Kentucky — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Loyall ranks 3,589 for wildfire risk (1 is highest) and 19,523 by building count (1 is largest). Within Kentucky alone, it ranks 66 of 552 places by risk. See the full county-by-county picture for Kentucky on its state page.
What this risk score means for insurance
Loyall's 89th-percentile, very high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
What would actually reduce this score
Loyall's 85.5% 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 Loyall's figures come from
The methodology guide shows exactly how USFS turned 385 counted buildings into the percentiles shown above for Loyall. The exposure-zones guide covers what Loyall's dominant indirect exposure actually means, with real examples from across the dataset.