5 Deals the DealIntel Kill List Would Reject (Illustrative Composites)
Every spreadsheet has a story. The story it tells is almost always optimistic — that is its job. The job of an institutional kill list is to layer the questions the spreadsheet does not ask, and surface the deals where the story breaks down.
Below are five illustrative composite deals generated from the DealIntel underwriting model. Each one is built on realistic market-rate inputs (purchases, comps, budgets, financing) drawn from typical 2025–2026 metro conditions. They are not a record of specific historical transactions. They are scenarios designed to show exactly how a kill list catches what a spreadsheet misses. Once we have a public live-prediction ledger running on real listings, we will publish that separately and with outcomes tracked forward in time.
Composite 1 — The $61k spreadsheet profit that wasn't
Phoenix, AZ submarket. Purchase $355k, rehab $52k, ARV $510k. Spreadsheet shows $61k projected profit on a 5-month flip. The operator scenario: a confident intermediate flipper, three deals under their belt, ready to wire EMD.
Kill list flag: comp set too thin. Only 2 renovated comps inside 0.5 miles and 90 days. Both are 14% larger than subject by square footage. The "ARV" is being pulled from a $/sqft assumption on out-of-range comps. The kill list re-underwrites at 92% of base ARV ($469k instead of $510k) and the deal collapses to ($-12k) projected profit.
Verdict: Pass. The kill list does not argue with the spreadsheet — it shows the spreadsheet a comp confidence the spreadsheet did not check.
Composite 2 — The "fully renovated" property that wasn't
Atlanta, GA. Marketed as a completed flip — buy turnkey, hold for cash flow. Listing claims new roof, new HVAC, full kitchen and bath remodel. Asking $295k. Operator scenario: a BRRRR investor looking to buy at $260k.
Kill list flag: open permits. The composite applies the permit-history check that DealIntel runs on every property — and surfaces what such a check would reveal on a property with this profile: an open electrical permit from the most recent renovation, plus an open addition permit from years prior that was never closed.
Closing the open permits would require exposing the electrical, scheduling re-inspections, and — for the addition — potentially de-permitting or rebuilding to code. Realistic exposure: $14–28k of unbudgeted scope plus weeks of timeline.
Verdict: Pass. See why permits matter.
Composite 3 — The flip that pencils at 10.5% but not at 15.2%
Houston, TX. Purchase $268k, rehab $44k, ARV $385k. Hard money loan quoted at 10.5%. Spreadsheet profit: $34k on a 6-month hold.
Kill list flag: carry cost > 30% of projected profit. The all-in cost of the hard money — 10.5% rate, 2.5 points origination, $2,800 in typical junk fees, 6-month minimum interest — produces a true annualized cost of capital around 15.2%. Total financing cost over the hold: ~$26k. Add taxes, insurance, utilities — another ~$5.8k. Total carry: ~$31.8k against a $34k margin. Carry is 93% of projected profit.
Verdict: Pass. The deal cannot survive even a 30-day overrun. See the true cost of hard money.
Composite 4 — The submarket with rising days-on-market
Tampa, FL. Purchase $410k, rehab $68k, ARV $585k. Spreadsheet shows $58k profit on a 90-day list-time assumption. Operator scenario: a flipper with two successful local projects in 2024.
Kill list flag: days-on-market trend rising. Across the typical 2026 Tampa submarket profile, DOM has drifted from sub-three-week regimes (2024) into the 40–50 day range. Inventory is up materially year over year. A 90-day list-time assumption no longer matches the regime.
Re-running at a 150-day list time (today's typical median), extra carry runs roughly $9,200 in interest and $1,800 in other holding costs. Profit drops from $58k to ~$47k — survivable. Stress test at 180 days: drops to ~$41k. At the 75th-percentile DOM in the new regime: ~$35k — but the operator only modeled 90 days.
Verdict: Negotiate. Not an automatic Pass, but the deal needs to be repriced 4–6% lower to survive current market conditions.
Composite 5 — The pretty house with foundation movement
Charlotte, NC. Purchase $325k, rehab budget $38k (mostly cosmetic — kitchen, bath, paint, floors). ARV $475k. Spreadsheet profit: $54k.
Kill list flag: structural — sloped floors. A walkthrough captures a measurable dip across the dining room. The operator characterizes it as "old house settling." The kill list requires an engineering quote before underwriting can complete.
On this composite, the engineering quote returns active foundation movement attributable to grading and lateral pressure: $32k for pier-and-beam stabilization, exterior drainage, re-leveling. Rehab budget nearly doubles, work shifts from cosmetic to structural — permit, inspection, timeline extension all triggered. Spreadsheet profit collapses to ~$20k before any overrun.
Verdict: Pass. See foundation problems that kill profit.
The pattern across all five composites
None of these scenarios has bad spreadsheet numbers. Every one is a green light to an operator running a quick model. The Pass verdict comes from a layer the spreadsheet does not contain — comp confidence, permit history, true cost of capital, market-regime change, structural diligence.
That is what an institutional kill list is for. It is not a replacement for the spreadsheet. It is the layer that catches what the spreadsheet cannot see.
What about real outcomes?
Composites are useful for showing how the methodology works. They do not substitute for a track record of real verdicts. The next stage of DealIntel is a public live prediction ledger — verdicts published on real, public listings, tracked forward in time, with outcomes recorded when they resolve. Once that ledger has enough resolved outcomes to be meaningful, we will publish it as a separate evidence base. The composites you just read are the methodology view; the ledger will be the outcomes view.
Related reading
- 10 deal killers every fix and flip investor should walk away from
- Fix and flip red flags checklist
- 10 reasons flips lose money
- How to analyze a fix and flip deal
Keep reading
- How to Analyze a Fix and Flip Deal (The Institutional Workflow)A step-by-step workflow for underwriting a fix and flip deal the way an institutional capital allocator would — ARV from a confidence-weighted comp set, MAO from the 70% rule, stress-tested rehab budget, full carry math, and a pre-mortem before the offer goes in.
- Fix & Flip Red Flags Checklist (25 Things to Inspect Before You Sign)A pre-offer red flags checklist for fix and flip operators — structural, mechanical, legal, market, and financing red flags that should trigger a renegotiation or a walk. Built from the 25-point Kill List DealIntel runs on every property.
- 10 Reasons Fix and Flips Lose Money (Ranked by How Often We See Them)Most failed flips do not fail for exotic reasons. They fail for the same ten reasons, in roughly the same order, every cycle. Here is the ranked list — and the institutional discipline that prevents each one.
Matt Abadi is the founder of DealIntel. He leads the development of the platform's six-strategy underwriting engine, 25-point Kill List, and Monte-Carlo financial model — the institutional analysis stack DealIntel applies to every fix and flip deal. DealIntel was founded in 2025 with the central thesis that knowing when not to invest is the most valuable number on the page.