Ball Pond, CT
How exposed is Ball Pond to wildfire?
Out of every US place USFS scores, Ball Pond lands at the 39th percentile for wildfire risk to structures — close to the middle of USFS's national wildfire-risk range — a figure built from its 1,506 buildings, not the land around them. (Source: USFS's Wildfire Risk to Communities methodology.)
Separately from the risk score above, Ball Pond's burn probability — fire likelihood with no building count factored in — sits at the 37th percentile nationally.
Where Ball Pond's buildings actually sit
USFS classifies 58.4% of Ball Pond's buildings as Direct exposure, higher than its 40.4% Indirect share and far above its 1.2% Minimal share — a profile where 880 structures sit close enough to vegetation that lot clearing matters most.
Where Ball Pond ranks
Ball Pond's 75th-percentile standing inside Connecticut outpaces its 39th 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, Ball Pond ranks 19,245 for wildfire risk (1 is highest) and 9,139 by building count (1 is largest). Within Connecticut alone, it ranks 54 of 214 places by risk. See the full county-by-county picture for Connecticut on its state page.
Shopping for coverage in Ball Pond
At the 39th national percentile, Ball Pond rates moderate for wildfire risk — well short of the threshold where insurers have been withdrawing coverage, though comparing a quote costs nothing either way.
What would actually reduce this score
Ball Pond's 58.4% Direct-exposure share means lot clearing around the structure typically outweighs any single material upgrade here. The home-hardening guide ranks the options for a place shaped like this.
Where Ball Pond's figures come from
Every one of the two percentiles behind Ball Pond's 19,245-place national rank traces to USFS's Wildfire Risk to Communities dataset — see the methodology guide. The exposure-zones guide covers what Ball Pond's dominant direct exposure actually means, with real examples from across the dataset.