Deer Lick, OK
How exposed is Deer Lick to wildfire?
USFS's Wildfire Risk to Communities model puts Deer Lick at the 90th national percentile for risk to structures, in USFS's highest wildfire-risk band nationally — a score built from 45 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Deer Lick's burn probability — fire likelihood with no building count factored in — sits at the 92nd percentile nationally.
Deer Lick's building exposure, zone by zone
USFS classifies 100% of Deer Lick's buildings as Direct exposure, higher than its 0% Indirect share and far above its 0% Minimal share — a profile where 45 structures sit close enough to vegetation that lot clearing matters most.
Where Deer Lick ranks
Deer Lick ranks lower within Oklahoma (47th 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, Deer Lick ranks 3,219 for wildfire risk (1 is highest) and 31,056 by building count (1 is largest). Within Oklahoma alone, it ranks 443 of 834 places by risk. See the full county-by-county picture for Oklahoma on its state page.
Deer Lick and the insurance market
Deer Lick's 90th-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 Deer Lick
Because Direct exposure dominates in Deer Lick (100%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Deer Lick's figures come from
Every one of the two percentiles behind Deer Lick's 3,219-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Deer Lick's dominant direct exposure actually means, with real examples from across the dataset.