Fanwood, NJ
Fanwood, NJ's wildfire risk, in USFS's own numbers
USFS scores Fanwood at the 29th national percentile for wildfire risk to structures (close to the middle of USFS's national wildfire-risk range), a figure built from 2,809 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 Fanwood at the 28th percentile, close to its 29th-percentile risk score.
What "at risk" means for the buildings here
Most of Fanwood's buildings (60.3% of 2,809) 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 Fanwood ranks
There's little gap between Fanwood's 29th national percentile and its 24th percentile inside New Jersey, which means the state comparison mostly confirms what the national score already shows. Among the 31,521 US communities USFS scores, Fanwood ranks 22,472 for wildfire risk (1 is highest) and 5,744 by building count (1 is largest). Within New Jersey alone, it ranks 535 of 700 places by risk. See the full county-by-county picture for New Jersey on its state page.
What this risk score means for insurance
Fanwood's moderate wildfire rating (29th percentile) isn't the kind of score driving the carrier pullback making news in the highest-risk Western markets — but a standard homeowners quote is still worth comparing on its own terms.
What would actually reduce this score
Even with 60.3% of Fanwood 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 Fanwood's figures come from
Fanwood's 29th-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 Fanwood's dominant minimal exposure actually means, with real examples from across the dataset.