Sawgrass, FL
Sawgrass wildfire risk explained
Out of every US place USFS scores, Sawgrass lands at the 66th percentile for wildfire risk to structures — well above the national norm for wildfire risk — a figure built from its 2,235 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Sawgrass's burn probability — fire likelihood with no building count factored in — sits at the 65th percentile nationally.
Where Sawgrass's buildings actually sit
Most of Sawgrass's buildings (77.6% of 2,235) 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.
Sawgrass against the rest of the country
Sawgrass's 66th national percentile looks worse in isolation than its 22nd ranking inside Florida does — this place is on the milder end for its own state, by 44 points. Among the 31,521 US communities USFS scores, Sawgrass ranks 10,610 for wildfire risk (1 is highest) and 6,852 by building count (1 is largest). Within Florida alone, it ranks 746 of 955 places by risk. See the full county-by-county picture for Florida on its state page.
Shopping for coverage in Sawgrass
Sawgrass's 66th-percentile, 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 Sawgrass
Even with 77.6% of Sawgrass outside USFS's Direct and Indirect zones, basic hardening — gutter maintenance, ember-resistant vents — is inexpensive relative to the regional burn-probability risk noted above. Details in the home-hardening guide.
Where Sawgrass's figures come from
The methodology guide shows exactly how USFS turned 2,235 counted buildings into the percentiles shown above for Sawgrass. The exposure-zones guide covers what Sawgrass's dominant minimal exposure actually means, with real examples from across the dataset.