Sunray, OK
Sunray wildfire risk explained
Out of every US place USFS scores, Sunray lands at the 90th percentile for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — a figure built from its 651 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 Sunray at the 91st percentile, close to its 90th-percentile risk score.
Where Sunray's buildings actually sit
80% of Sunray's 651 buildings sit in USFS's Direct exposure zone, roughly 521 structures close enough to burnable vegetation for flame contact, not just embers — 20% fall in the Indirect, ember-only zone and 0% are Minimal.
How Sunray compares
Sunray ranks lower within Oklahoma (49th percentile statewide) than its 90th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Sunray ranks 3,096 for wildfire risk (1 is highest) and 15,197 by building count (1 is largest). Within Oklahoma alone, it ranks 430 of 834 places by risk. See the full county-by-county picture for Oklahoma on its state page.
Shopping for coverage in Sunray
At the 90th percentile nationally, Sunray carries the very high rating that has pushed some carriers to limit new business in similarly-scored places elsewhere in the country. Worth comparing quotes rather than assuming last year's renewal terms still apply.
What would actually reduce this score
With 80% of Sunray in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Sunray's figures come from
The methodology guide shows exactly how USFS turned 651 counted buildings into the percentiles shown above for Sunray. The exposure-zones guide covers what Sunray's dominant direct exposure actually means, with real examples from across the dataset.