Old Stine, CA
Old Stine, CA's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Old Stine at the 55th national percentile for risk to structures, modestly above the national average for wildfire risk — a score built from 1,645 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Old Stine at the 56th percentile, close to its 55th-percentile risk score.
Where Old Stine's buildings actually sit
Old Stine rates 99.3% Minimal exposure against just 0.7% Direct and 0% Indirect — of 1,645 buildings counted, few sit close enough to burnable vegetation for USFS to flag them individually.
How Old Stine compares
Old Stine ranks lower within California (14th percentile statewide) than its 55th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Old Stine ranks 14,141 for wildfire risk (1 is highest) and 8,604 by building count (1 is largest). Within California alone, it ranks 1,347 of 1,570 places by risk. See the full county-by-county picture for California on its state page.
What this risk score means for insurance
Old Stine's 55th-percentile score lands in California, the only two states requiring a wildfire disclosure at sale. California's surplus-lines homeowners market passed 300,000 policies for the first time in 2025, driven by carriers pulling back from wildfire-exposed areas statewide. The disclosure-law guide covers what it requires.
What would actually reduce this score
Old Stine's 99.3% Minimal-exposure share means structure-level hardening matters less here than it would elsewhere — still worth the low-cost basics, per the home-hardening guide.
Where Old Stine's figures come from
The methodology guide shows exactly how USFS turned 1,645 counted buildings into the percentiles shown above for Old Stine. The exposure-zones guide covers what Old Stine's dominant minimal exposure actually means, with real examples from across the dataset.