ZIP 54511 Property Distress & Foreclosure Data
Forest County, Wisconsin's ZIP 54511 registers 15/100 composite distress, which DLRadar reads as low. The most distinctive pressure shows up in construction/permit lag (83/100), structural risk (35/100), mortgage stress (13/100). On the quiet end sit mortgage stress (13/100) and institutional ownership (5/100). Structural risk reads 35/100 against active distress of 4/100.
The expansion-phase market in 54511 posted values that rose 6.7% over the year, and 16% higher over three years, at 35/100 phase confidence. Rising prices can mask pockets of distress, where per-parcel scoring earns its keep.
Population is roughly 1,375 with a median age of 53. Vacancy runs 59.7%, above the national norm and a classic distress-and-opportunity signal. 92% of housing is owner-occupied. Rent burden reaches 60% of tenant households. The typical home is worth about $172,700 (2.4× income, relatively affordable). The poverty rate is 4.2% — low. At $64,405, median income runs below typical U.S. levels. The demographic-stress sub-score lands at 33/100. There are about 1,511 housing units across 54511. Around 13% of adults hold a bachelor's degree or higher.
On the whole, 54511 leans distressed, with opportunity clustered in specific stressed parcels. Every signal above traces to a verifiable public dataset, refreshed continuously and scored the same way in every ZIP nationwide.
Distress signal breakdown — ZIP 54511
Tax delinquency, institutional ownership, insurance pressure, NFIP/flood, construction lag, price dislocation and auction velocity — plus the 0 individual distressed properties (owner, address, APN, per-property score and exit read) are in the full DLRadar report.
Nearby ZIPs in Forest County
Unlock the full ZIP 54511 acquisition report
Get every distressed property in 54511 with owner, address, APN, per-property distress score, bank exposure, exit-velocity read and a one-click funding + closing path. Nationwide, refreshed continuously.
Deterministic. Every signal traces to a public dataset · methodology