Seffner, FL
Seffner wildfire risk explained
Seffner sits at the 82nd percentile nationally for wildfire risk to structures — in USFS's highest wildfire-risk band nationally — per USFS's Wildfire Risk to Communities model, built from its 3,415 counted buildings, not vegetation cover alone. (Source: USFS's Wildfire Risk to Communities methodology.)
USFS's separate burn-probability score — fire likelihood alone, before counting what's built there — puts Seffner at the 84th percentile, close to its 82nd-percentile risk score.
Seffner's building exposure, zone by zone
USFS classifies 41.6% of Seffner's buildings as Direct exposure, higher than its 29.4% Indirect share and far above its 29.1% Minimal share — a profile where 1,419 structures sit close enough to vegetation that lot clearing matters most.
Seffner against the rest of the country
Seffner's 82nd national percentile looks worse in isolation than its 54th ranking inside Florida does — this place is on the milder end for its own state, by 28 points. Among the 31,521 US communities USFS scores, Seffner ranks 5,608 for wildfire risk (1 is highest) and 4,897 by building count (1 is largest). Within Florida alone, it ranks 437 of 955 places by risk. See the full county-by-county picture for Florida on its state page.
Shopping for coverage in Seffner
At the 82nd percentile nationally, Seffner carries the very high rating that has pushed some carriers to limit new business in similarly-scored places elsewhere in the country. Worth comparing quotes rather than assuming last year's renewal terms still apply.
What would actually reduce this score
Because Direct exposure dominates in Seffner (41.6%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.
Where Seffner's figures come from
The methodology guide shows exactly how USFS turned 3,415 counted buildings into the percentiles shown above for Seffner. The exposure-zones guide covers what Seffner's dominant direct exposure actually means, with real examples from across the dataset.