Wagoner, OK
Wagoner, OK's wildfire risk, in USFS's own numbers
Wagoner's 4,066 buildings earn a 85th-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.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Wagoner at the 87th percentile, close to its 85th-percentile risk score.
Wagoner's building exposure, zone by zone
Most of Wagoner's buildings (41.8%) sit in the Indirect zone, where wind-blown embers rather than flame front are the mechanism USFS is scoring — ember-resistant vents and non-combustible roofing are the interventions this pattern favors, more than defensible space alone.
Wagoner against the rest of the country
Inside Oklahoma, Wagoner sits at just the 32nd percentile even though it scores 85th 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, Wagoner ranks 4,733 for wildfire risk (1 is highest) and 4,175 by building count (1 is largest). Within Oklahoma alone, it ranks 570 of 834 places by risk. See the full county-by-county picture for Oklahoma on its state page.
Shopping for coverage in Wagoner
Wagoner'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.
What would actually reduce this score
With ember exposure the dominant pattern in Wagoner (41.8% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Wagoner's figures come from
Every one of the two percentiles behind Wagoner's 4,733-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Wagoner's dominant indirect exposure actually means, with real examples from across the dataset.