Oldsmar, FL
Oldsmar, FL's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Oldsmar at the 85th national percentile for risk to structures, in USFS's highest wildfire-risk band nationally — a score built from 5,156 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 Oldsmar at the 85th percentile, close to its 85th-percentile risk score.
What "at risk" means for the buildings here
5,156 buildings are counted in Oldsmar, and 90.2% of them are Indirect exposure — ember-driven risk rather than the 9.5% in Direct exposure or the 0.3% rated Minimal. At 5,156 buildings, this is a substantial built environment, so the shares below describe a real population of structures, not a handful of edge cases.
Where Oldsmar ranks
Oldsmar ranks lower within Florida (65th percentile statewide) than its 85th national percentile suggests alone — a calmer spot in a state where wildfire risk generally runs high. Among the 31,521 US communities USFS scores, Oldsmar ranks 4,698 for wildfire risk (1 is highest) and 3,342 by building count (1 is largest). Within Florida alone, it ranks 340 of 955 places by risk. See the full county-by-county picture for Florida on its state page.
What this risk score means for insurance
Oldsmar's very high rating (85th percentile) puts it among the places where the national carrier-pullback trend is most relevant — not a guarantee of a coverage problem, but a reason to shop rather than assume.
What would actually reduce this score
With ember exposure the dominant pattern in Oldsmar (90.2% Indirect), vent screens and roofing material tend to matter more than lot clearing alone. The home-hardening guide covers both.
Where Oldsmar's figures come from
Oldsmar's 85th-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Oldsmar's dominant indirect exposure actually means, with real examples from across the dataset.