Most flips that go sideways in south Monroe County do not go sideways because of the house. They go sideways because the after repair value was borrowed from a number nobody checked. A dashboard said one thing, a wholesaler's spreadsheet said another, and the offer went out anyway.

This post walks through the sequence I use before an offer goes out on a Henrietta, West Henrietta, Rush, Mendon or Honeoye Falls property. You will get: how to spot a comp data set that is internally broken, how to verify comps one at a time, how to adjust for the things aggregators cannot see, and how to stress test the exit so a soft resale does not eat the whole spread.

One note up front. You will not find market statistics in this post. I could not verify current figures for these towns to a standard I would put my name on, so I am not going to quote any. Everything below is method. When I have period-stamped numbers from the local MLS reports, I publish them with the month attached.

Why comp data breaks down in these specific towns

Rochester flip underwriting is not hard because data is scarce. It is hard because the data that exists is thin at the town level and mixed in character.

• Small monthly sales counts. Towns like Rush, Mendon and Honeoye Falls close a modest number of homes in any given month. A single unusual sale moves the median. Any town-level median you use should be a rolling three or twelve month figure, and it should be labelled as such.
• Mixed housing stock inside one ZIP. Henrietta runs from postwar ranches and split levels in tight subdivisions to newer builds on larger parcels. Rush and West Henrietta mix older farmhouses on acreage with tract homes. A comp two streets away can be a different product entirely.
• Utility differences that never show in a price feed. Some parcels are on town water and sewer. Others run well and septic. That difference affects buyer pool, inspection outcomes and appraisal adjustments, and no aggregator will flag it for you.
• Geography labels get sloppy. "Rochester" in a data feed can mean the city, the metro, or the county. Those are three different markets. Mixing them is the single most common source of a bad after repair value in Henrietta.

Step one: fix the geography before you look at a single number

Before you evaluate any figure, write down what area it covers and what month it covers. If you cannot answer both, the number is not usable yet. This sounds pedantic. It is the cheapest thing you will do all week.

Then confirm the subject property's own labels: town, school district, sewer or septic, water source, lot size and road frontage from the county parcel record. Name the school district factually in your notes, because it defines the comp pool. Do not rate it.

Step two: sanity check the aggregate numbers with arithmetic

You do not need a data subscription to catch a broken dashboard. You need division.

• Months of supply is active listings divided by monthly closed sales. If a site shows a very low months of supply, back out the implied sales pace and ask whether that pace is plausible for the geography named. If it is not, the listing count and the sales count are probably drawn from different areas, or the listing count is lagged.
• A sale-to-list ratio above 100 percent sitting next to a long days on market is a tell. Those two do not normally coexist. Usually one of them is defined differently than you assume.
• Days on market has at least two definitions. Some sources count list to contract, which is true market exposure. Others count list to close, which folds in the financing and closing period. Same house, very different number. Pull the source's own methodology page before you build anything on it.
• A dramatic year over year percentage may be a base effect from an odd prior-year month rather than a trend. Check the prior year raw count, not just the percentage.

None of this tells you what a house is worth. It tells you whether the market context you are underwriting into is real.

Step three: verify comps one at a time

This is where ARV comps verification actually happens. Three comps you can defend beat twelve you pulled from a map view. For each candidate comp, I want:

• The full listing history, including prior expired or withdrawn attempts and every price change.
• Interior photos from the sold listing, so I can see finish level rather than guess it. A renovated kitchen and a 1972 kitchen sell at different numbers on the same floor plan.
• Whether the sale was financed or cash. A cash purchase by an investor often reflects condition, not retail value.
• Seller concessions. If a concession was rolled into the contract price, the recorded number overstates what the buyer paid for the house.
• Utilities, lot size and outbuildings. A comp on public sewer is not a clean match for a septic parcel.
• Any addition or finished basement space, and whether the square footage in the listing matches the assessment record. When they disagree, find out why.

If a comp survives all six checks, it goes in the file. If it does not, it goes in a second list labelled "context only."

Which source to trust for what

Step four: build the after repair value from the bottom up

Start from your verified comps and adjust to the subject property, not the other way around. Write each adjustment down with a reason. If you cannot explain an adjustment out loud in one sentence, drop it.

Then pick your exit finish level and hold it consistent. An after repair value in Henrietta based on a full renovation is not the ARV for a paint-and-carpet turn. Investors lose money by underwriting the top comp and budgeting the middle scope.

Finally, check that your ARV would survive an appraisal built from the same comp set. Whatever financing your eventual buyer uses, an appraiser will work inside a tighter box than you did.

Step five: the things I look for inside these houses

Investor due diligence in Rochester NY is mostly about repair cost accuracy, because that is the number you control least. In older stock across these towns I check for knob and tube or mixed wiring, aluminum branch wiring in certain 1960s and 1970s builds, buried oil tanks, septic age and location, well flow and water quality, sump and drainage history, and additions that never appear in the permit record. Any one of them can move a budget by five figures.

Bring a trade partner on the second walk. Not for a favour. For a number.

Step six: stress test the exit before you commit

• Underwrite a resale price below your ARV and see if the deal still clears. If it only works at your best case, it is not a deal, it is a bet.
• Extend your hold period assumption and recalculate carrying costs, taxes and insurance.
• Plan for one price reduction in your timeline, not zero.
• Confirm the resale price band actually has buyer depth in that town, based on verified sold activity rather than active list prices.

If you are wholesaling Monroe County contracts

Wholesaling Monroe County property does not exempt you from any of this. It raises the stakes, because your assignment fee depends on an end buyer reaching the same conclusions you did. Verify before you market, disclose your position in writing, and share your comp file rather than a headline ARV. Assignments that fall apart at diligence cost you the next three deals with that buyer.

When there are genuinely no comps

It happens, especially with acreage parcels in Rush and Mendon or unusual older homes. Widen the radius deliberately and document why each distant comp is comparable. Look at pending sales for direction. Use price per square foot only within genuinely similar stock. And be willing to walk. A property you cannot value is a property you cannot price risk on.

If you want a second read on a specific address before you send the offer, send me the parcel and your numbers. I will pull the sold history, tell you which of your comps I would throw out and why, and give you a straight answer on whether the spread is real. Book a time with me here: schedule a meeting with Khem Kadariya.

About this data

The figures in this post were compiled from publicly available sources including Houzeo, Zillow, RochesterFirst, Movoto and Redfin, along with other public market data. Real estate numbers change quickly, and these were accurate as of August 2026. For current figures on a specific home, street, or town, ask me directly rather than relying on a published average.