ZIP 49826 Property Distress & Foreclosure Data

Composite property distress in 49826 (Alger County, Michigan) lands at 8/100 — minimal on DLRadar's public-record scoring. The latent-versus-live split is 19/100 structural and 4/100 already moving. The sharpest non-environmental signals are construction/permit lag (53/100), structural risk (19/100), institutional ownership (16/100). By contrast, institutional ownership (16/100) and mortgage stress (14/100) register low.

The market reads expansion — home values rose 6.4% year on year (phase confidence 37/100). Appreciation rarely lifts every parcel — the laggards are the opportunity.

The typical home is worth about $335,700. 100% of housing is owner-occupied. Around 41% of adults hold a bachelor's degree or higher. The demographic-stress sub-score lands at 19/100. The ZIP holds roughly 51 housing units. The vacancy rate is 0.0%. About 103 people live here, median age 40. The poverty rate is 16.3% — high, a tax-stress and distress correlate.

Overall 49826 looks resilient on the surface, so the edge is isolating individual stressed parcels. Every signal above traces to a verifiable public dataset, refreshed continuously and scored the same way in every ZIP nationwide.

8/100
Composite stress
19/100
Structural risk
4/100
Distress activity

Distress signal breakdown — ZIP 49826

Foreclosure activity0
Mortgage stress14
Climate / FEMA risk8
+9 more distress dimensions scored for this ZIP

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 Alger County

Unlock the full ZIP 49826 acquisition report

Get every distressed property in 49826 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