WildfireRiskFinder

Stoy, IL

Stoy, IL's wildfire risk, in USFS's own numbers

Low
5thpercentile nationally

Out of every US place USFS scores, Stoy lands at the 5th percentile for wildfire risk to structures — among the lower wildfire-risk places nationally — a figure built from its 119 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)

Fire likelihood alone (USFS's burn-probability figure) ranks Stoy at the 5th national percentile — 0 points above its risk-to-structures score, a gap driven by how much is actually built there.

Where Stoy's buildings actually sit

119Total buildings
97.5%Direct exposure
0%Indirect exposure
2.5%Minimal exposure

Direct exposure dominates in Stoy: 97.5% of its 119 buildings, versus 0% Indirect and 2.5% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.

Stoy against the rest of the country

Within Illinois, Stoy ranks higher (29th percentile) than it does nationally (5th) — one of the more fire-exposed places in a state that, overall, scores lower than that. Among the 31,521 US communities USFS scores, Stoy ranks 29,938 for wildfire risk (1 is highest) and 28,186 by building count (1 is largest). Within Illinois alone, it ranks 1,031 of 1,445 places by risk. See the full county-by-county picture for Illinois on its state page.

Shopping for coverage in Stoy

Stoy's low wildfire rating (5th 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.

Hardening a home in Stoy

Because Direct exposure dominates in Stoy (97.5%), the highest-leverage fix is defensible space, not roofing or vents alone — covered in the home-hardening guide.

Where Stoy's figures come from

The methodology guide shows exactly how USFS turned 119 counted buildings into the percentiles shown above for Stoy. The exposure-zones guide covers what Stoy's dominant direct exposure actually means, with real examples from across the dataset.