Deadwood, SD
Deadwood, SD's wildfire risk, in USFS's own numbers
Out of every US place USFS scores, Deadwood lands at the 85th percentile for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — a figure built from its 959 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 Deadwood at the 84th percentile, close to its 85th-percentile risk score.
Where Deadwood's buildings actually sit
68.5% of Deadwood's 959 buildings fall in USFS's Indirect exposure zone — ember cast rather than direct flame — against 31.5% Direct and 0% Minimal. Vent screens and roofing material matter more here than lot clearing alone.
How Deadwood compares
There's little gap between Deadwood's 85th national percentile and its 85th percentile inside South Dakota, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Deadwood ranks 4,862 for wildfire risk (1 is highest) and 12,237 by building count (1 is largest). Within South Dakota alone, it ranks 65 of 439 places by risk. See the full county-by-county picture for South Dakota on its state page.
What this risk score means for insurance
Deadwood's very high rating (85th percentile) puts it among the places where the national carrier-pullback trend is most relevant — not a guarantee of a coverage problem, but a reason to shop rather than assume.
Hardening a home in Deadwood
Because 68.5% of Deadwood's buildings sit in the Indirect zone, sealing the ember pathway (vents, roofing, gutters) is the intervention this page's data actually supports — see the home-hardening guide.
Where Deadwood's figures come from
Every one of the two percentiles behind Deadwood's 4,862-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Deadwood's dominant indirect exposure actually means, with real examples from across the dataset.