Neelyville, MO
Neelyville, MO's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Neelyville at the 31st national percentile for risk to structures, close to the middle of USFS's national wildfire-risk range — a score built from 295 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Neelyville at the 31st percentile, close to its 31st-percentile risk score.
Neelyville's building exposure, zone by zone
Neelyville rates 59.3% Minimal exposure against just 40.7% Direct and 0% Indirect — of 295 buildings counted, few sit close enough to burnable vegetation for USFS to flag them individually.
Neelyville against the rest of the country
Inside Missouri, Neelyville sits at just the 10th percentile even though it scores 31st nationally — the state's overall wildfire exposure is high enough to make this a relatively quiet corner of it. Among the 31,521 US communities USFS scores, Neelyville ranks 21,805 for wildfire risk (1 is highest) and 21,761 by building count (1 is largest). Within Missouri alone, it ranks 961 of 1,062 places by risk. See the full county-by-county picture for Missouri on its state page.
Neelyville and the insurance market
Neelyville's moderate wildfire rating (31st 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.
What would actually reduce this score
With 59.3% of buildings rated Minimal exposure, Neelyville gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Neelyville's figures come from
Neelyville's 31st-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 Neelyville's dominant minimal exposure actually means, with real examples from across the dataset.