Lake Mills, WI
Lake Mills wildfire risk explained
USFS scores Lake Mills at the 35th national percentile for wildfire risk to structures (close to the middle of USFS's national wildfire-risk range), a figure built from 2,733 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 Lake Mills at the 36th percentile, close to its 35th-percentile risk score.
What "at risk" means for the buildings here
71.7% of Lake Mills's 2,733 buildings sit in USFS's Minimal exposure zone, with only 21.8% rated Direct — risk here comes from regional burn probability more than proximity to burnable vegetation at the structure itself.
Lake Mills against the rest of the country
Lake Mills's 82nd-percentile standing inside Wisconsin outpaces its 35th national percentile — this is a hotter spot than most of its own state, even though the state as a whole runs cooler nationally. Among the 31,521 US communities USFS scores, Lake Mills ranks 20,535 for wildfire risk (1 is highest) and 5,878 by building count (1 is largest). Within Wisconsin alone, it ranks 147 of 808 places by risk. See the full county-by-county picture for Wisconsin on its state page.
What this risk score means for insurance
Lake Mills's moderate wildfire rating (35th 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
With 71.7% of buildings rated Minimal exposure, Lake Mills gets less benefit from structure hardening than a Direct- or Indirect-dominant place would — the home-hardening guide explains why the zone matters.
Where Lake Mills's figures come from
The methodology guide shows exactly how USFS turned 2,733 counted buildings into the percentiles shown above for Lake Mills. The exposure-zones guide covers what Lake Mills's dominant minimal exposure actually means, with real examples from across the dataset.