Wauconda, IL
Wauconda wildfire risk explained
Wauconda's 5,119 buildings earn a 33rd-percentile wildfire-risk score nationally under USFS's model — close to the middle of USFS's national wildfire-risk range. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Wauconda's burn probability — fire likelihood with no building count factored in — sits at the 34th percentile nationally.
Where Wauconda's buildings actually sit
USFS classifies 93.7% of Wauconda's buildings as Minimal exposure, the largest of the three zones here by a wide margin over 6.3% Direct and 0% Indirect — a landscape-level risk rather than a building-by-building one. At 5,119 buildings, this is a substantial built environment, so the shares below describe a real population of structures, not a handful of edge cases.
How Wauconda compares
Within Illinois, Wauconda ranks higher (84th percentile) than it does nationally (33rd) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Wauconda ranks 21,078 for wildfire risk (1 is highest) and 3,370 by building count (1 is largest). Within Illinois alone, it ranks 232 of 1,445 places by risk. See the full county-by-county picture for Illinois on its state page.
Wauconda and the insurance market
Wauconda's moderate rating (33rd percentile nationally) sits outside the range where wildfire risk alone reshapes an insurance market — still, a homeowner here loses nothing by comparing rates.
Lowering exposure, not just insuring around it
With 93.7% of buildings rated Minimal exposure, Wauconda gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Wauconda's figures come from
The methodology guide shows exactly how USFS turned 5,119 counted buildings into the percentiles shown above for Wauconda. The exposure-zones guide covers what Wauconda's dominant minimal exposure actually means, with real examples from across the dataset.