WildfireRiskFinder

Pocasset, OK

Pocasset wildfire risk explained

Very High
94thpercentile nationally

Pocasset's 243 buildings earn a 94th-percentile wildfire-risk score nationally under USFS's model — in USFS's highest wildfire-risk band nationally. (Source: USFS's Wildfire Risk to Communities methodology.)

Separately from the risk score above, Pocasset's burn probability — fire likelihood with no building count factored in — sits at the 94th percentile nationally.

What "at risk" means for the buildings here

243Total buildings
46.9%Direct exposure
53.1%Indirect exposure
0%Minimal exposure

USFS puts 53.1% of Pocasset's 243 buildings in the Indirect exposure zone, versus 46.9% Direct and 0% Minimal — a place where the fire doesn't need to reach the structure directly for embers to.

Pocasset against the rest of the country

Pocasset ranks lower within Oklahoma (68th percentile statewide) than its 94th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Pocasset ranks 2,054 for wildfire risk (1 is highest) and 23,374 by building count (1 is largest). Within Oklahoma alone, it ranks 265 of 834 places by risk. See the full county-by-county picture for Oklahoma on its state page.

What this risk score means for insurance

Pocasset's very high rating (94th 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.

What would actually reduce this score

With ember exposure the dominant pattern in Pocasset (53.1% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.

Where Pocasset's figures come from

Pocasset's 94th-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 Pocasset's dominant indirect exposure actually means, with real examples from across the dataset.