Victor, CA
Victor wildfire risk explained
USFS scores Victor at the 50th national percentile for wildfire risk to structures (modestly above the national average for wildfire risk), a figure built from 243 real buildings rather than raw vegetation cover. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Victor at the 52nd percentile, close to its 50th-percentile risk score.
What "at risk" means for the buildings here
Most of Victor's buildings (72.8% of 243) fall outside USFS's Direct and Indirect zones entirely — that doesn't zero out the score above, it means the risk is regional, not structure-by-structure.
Where Victor ranks
Victor ranks lower within California (11th percentile statewide) than its 50th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Victor ranks 15,686 for wildfire risk (1 is highest) and 23,353 by building count (1 is largest). Within California alone, it ranks 1,405 of 1,570 places by risk. See the full county-by-county picture for California on its state page.
Shopping for coverage in Victor
Victor's 50th-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.
Lowering exposure, not just insuring around it
Victor's 72.8% 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 Victor's figures come from
Every one of the two percentiles behind Victor's 15,686-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Victor's dominant minimal exposure actually means, with real examples from across the dataset.