Oracle, AZ
Oracle wildfire risk explained
USFS scores Oracle at the 97th national percentile for wildfire risk to structures (in USFS's highest wildfire-risk band nationally), a figure built from 2,503 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Oracle at the 97th national percentile — 0 points above its risk-to-structures score, a gap driven by how much is actually built there.
What "at risk" means for the buildings here
88.8% of Oracle's 2,503 buildings sit in USFS's Direct exposure zone, roughly 2,222 structures close enough to burnable vegetation for flame contact, not just embers — 11.2% fall in the Indirect, ember-only zone and 0% are Minimal.
Where Oracle ranks
Oracle's 97th national percentile looks worse in isolation than its 81st ranking inside Arizona does — this place is on the milder end for its own state, by 16 points. Among the 31,521 US communities USFS scores, Oracle ranks 1,060 for wildfire risk (1 is highest) and 6,289 by building count (1 is largest). Within Arizona alone, it ranks 88 of 441 places by risk. See the full county-by-county picture for Arizona on its state page.
Oracle and the insurance market
At the 97th percentile nationally, Oracle 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.
Lowering exposure, not just insuring around it
Oracle's 88.8% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.
Where Oracle's figures come from
Every one of the two percentiles behind Oracle's 1,060-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Oracle's dominant direct exposure actually means, with real examples from across the dataset.