Rugby, ND
Rugby, ND's wildfire risk, in USFS's own numbers
USFS scores Rugby at the 48th national percentile for wildfire risk to structures (modestly above the national average for wildfire risk), a figure built from 1,790 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Rugby at the 45th national percentile — 3 points below its risk-to-structures score, a gap driven by how much is actually built there.
Rugby's building exposure, zone by zone
USFS classifies 89.6% of Rugby's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 10.4% Direct and 0% Indirect — a landscape-level risk rather than a building-by-building one.
Where Rugby ranks
Rugby scores 48th nationally and 46th within North Dakota — close enough that its state context doesn't change the picture the national number already gives. Among the 31,521 US communities USFS scores, Rugby ranks 16,492 for wildfire risk (1 is highest) and 8,098 by building count (1 is largest). Within North Dakota alone, it ranks 218 of 402 places by risk. See the full county-by-county picture for North Dakota on its state page.
Shopping for coverage in Rugby
Rugby's elevated wildfire rating (48th 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.
Hardening a home in Rugby
Even with 89.6% of Rugby outside USFS's Direct and Indirect zones, basic hardening — gutter maintenance, ember-resistant vents — is inexpensive relative to the regional burn-probability risk noted above. Details in the home-hardening guide.
Where Rugby's figures come from
Every one of the two percentiles behind Rugby's 16,492-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Rugby's dominant minimal exposure actually means, with real examples from across the dataset.