Fredericktown, OH
Fredericktown wildfire risk explained
USFS's Wildfire Risk to Communities model puts Fredericktown at the 19th national percentile for risk to structures, among the lower wildfire-risk places nationally — a score built from 1,418 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Fredericktown at the 20th national percentile — 1 points above its risk-to-structures score, a gap driven by how much is actually built there.
Fredericktown's building exposure, zone by zone
Only 19.6% of Fredericktown's 1,418 buildings carry Direct exposure and 0.3% carry Indirect; the remaining 80.1% are Minimal, which shifts the risk driving this page's score toward the surrounding landscape rather than any one structure.
How Fredericktown compares
Compare Fredericktown's two percentiles: 49th within Ohio, only 19th nationally — a gap of 30 points that marks it as unusually exposed for its own state. Among the 31,521 US communities USFS scores, Fredericktown ranks 25,568 for wildfire risk (1 is highest) and 9,550 by building count (1 is largest). Within Ohio alone, it ranks 642 of 1,264 places by risk. See the full county-by-county picture for Ohio on its state page.
What this risk score means for insurance
Fredericktown's low wildfire rating (19th percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.
Lowering exposure, not just insuring around it
With 80.1% of buildings rated Minimal exposure, Fredericktown gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Fredericktown's figures come from
The methodology guide shows exactly how USFS turned 1,418 counted buildings into the percentiles shown above for Fredericktown. The exposure-zones guide covers what Fredericktown's dominant minimal exposure actually means, with real examples from across the dataset.