MIDDLEMIST PROPERTIES LLC

Flipper active in St. Louis, MO-IL. 20 acquisitions, $1.63M tracked volume, $81,575 average price, latest observed Mar 2026.

St. Louis, MO-ILflipperorganization
5% cash2 observed lenders$81,575 avgLatest Mar 2026

Investor profile snapshot

MIDDLEMIST PROPERTIES LLC is a flipper real estate investor active in St. Louis, MO-IL with 20 recorded acquisitions totaling approximately $1,631,500. Recorded purchases appear concentrated in a tighter local market footprint. The most recent recorded purchase was in March 2026, so the visible activity window still looks fairly recent from a deed-record standpoint.

Recorded purchases skew toward Single Family Residential. Average observed purchase price sits near $81,575, which reads as entry-level to lower-middle price points. Behavioral signals point to flip-oriented behavior and frequent private-lender financing within the recorded deed activity.

Observed window
January 2022 to March 2026

About 4 years of observed acquisition activity

Latest recorded purchase
March 2026

Recent enough to suggest the profile is still active

Market footprint
1 state / 1 metro

Activity appears concentrated in a narrower local market footprint

Strategy read
Flip-oriented

Derived from observed cash, financing, and flip-like transaction patterns

About this profile

SFR Analytics builds investor profiles from observed deed, mortgage, and assessor records. Use these metrics to compare acquisition patterns, market footprint, and financing signals across investors. Public-record coverage and entity resolution vary by county, so counts represent observed activity in our dataset rather than a complete legal ownership record.

Transaction Summary

20
Transactions
20
Properties
$1.63M
Total Volume
$81,575
Average Price

Property Types

Single Family ResidentialObserved type
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Financing Signal

Recorded mortgage data links this profile to 2 observed lenders. The public page shows a sample; Private Lender Radar is where lender teams can review the full lender history, borrower activity, lender share, and contact workflow.

Sample observed lenders

Showing 2 of 2 observed lender relationships.

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Mercantile Capital INCWin Win Funding Solutions LLC

Who else does Mercantile Capital INC fund?

This investor uses 2 observed lenders. See borrower activity, lender market share, and verified contacts in St. Louis, MO-IL.

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Frequently asked questions

What type of real estate does MIDDLEMIST PROPERTIES LLC focus on?

Public records associated with MIDDLEMIST PROPERTIES LLC show activity in Single Family Residential across St. Louis, MO-IL.

How many properties are associated with MIDDLEMIST PROPERTIES LLC?

Public records show approximately 20 properties and 20 recorded transactions associated with MIDDLEMIST PROPERTIES LLC in this dataset.

Which lenders has MIDDLEMIST PROPERTIES LLC worked with?

Recent recorded mortgage activity references Mercantile Capital INC, Win Win Funding Solutions LLC. Full lender history is available in SFR Analytics.

How recent is MIDDLEMIST PROPERTIES LLC's activity?

Records show activity from 2022 through 2026, with the most recent observed purchase recorded in March 2026.

Where is MIDDLEMIST PROPERTIES LLC active?

Recorded activity is concentrated in St. Louis, MO-IL, with footprint across 1 state and 1 metro in this dataset.

How is associated activity determined?

SFR Analytics matches recorded deeds, mortgages, and assessor records across counties to assemble investor-level activity profiles. Matches use name normalization, address co-occurrence, and entity signals from public records. Profiles are directional - they reflect what is observable in deed-backed data and may not capture every off-record transaction or affiliated entity.

Data sources & methodology

SFR Analytics builds these profiles from recorded deeds, mortgages, assessor records, and entity matching. They are designed for market research: comparing acquisition activity, property focus, market footprint, and financing signals across investors. Coverage varies by county and record type, so counts reflect observed activity in our dataset.