IXL, OK
IXL, OK's wildfire risk, in USFS's own numbers
Out of every US place USFS scores, IXL lands at the 97th percentile for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — a figure built from its 72 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 IXL at the 98th percentile, close to its 97th-percentile risk score.
Where IXL's buildings actually sit
100% of IXL's 72 buildings sit in USFS's Direct exposure zone, roughly 72 structures close enough to burnable vegetation for flame contact, not just embers — 0% fall in the Indirect, ember-only zone and 0% are Minimal.
Where IXL ranks
IXL's risk sits at a similar level relative to Oklahoma (91st percentile statewide) as it does nationally (97th) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, IXL ranks 1,077 for wildfire risk (1 is highest) and 30,221 by building count (1 is largest). Within Oklahoma alone, it ranks 78 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
IXL's 97th-percentile, very 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.
Hardening a home in IXL
With 100% of IXL 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 IXL's figures come from
The methodology guide shows exactly how USFS turned 72 counted buildings into the percentiles shown above for IXL. The exposure-zones guide covers what IXL's dominant direct exposure actually means, with real examples from across the dataset.