Ak Chin, AZ
How exposed is Ak Chin to wildfire?
Ak Chin's 34 buildings earn a 68th-percentile wildfire-risk score nationally under USFS's model — well above the national norm for wildfire risk. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Ak Chin at the 64th percentile, close to its 68th-percentile risk score.
What "at risk" means for the buildings here
34 buildings are counted in Ak Chin, and 100% of them sit in USFS's Direct exposure zone — flame contact, not just ember cast, is the live possibility for most of them, against 0% rated Minimal.
Ak Chin against the rest of the country
Inside Arizona, Ak Chin sits at just the 31st percentile even though it scores 68th 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, Ak Chin ranks 10,105 for wildfire risk (1 is highest) and 31,287 by building count (1 is largest). Within Arizona alone, it ranks 304 of 441 places by risk. See the full county-by-county picture for Arizona on its state page.
Shopping for coverage in Ak Chin
Ak Chin's 68th-percentile, high rating is the kind of score behind a broader national pattern: insurers pulling back from the highest wildfire-risk markets, non-renewing or declining new policies outright, most visibly in California. Shopping around, not assuming automatic renewal, tends to matter here.
Lowering exposure, not just insuring around it
Ak Chin's 100% 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 Ak Chin's figures come from
Every one of the two percentiles behind Ak Chin's 10,105-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Ak Chin's dominant direct exposure actually means, with real examples from across the dataset.