You can open Zillow, Redfin and Realtor.com in three tabs, look at the same town in south Monroe County, and come away with three different stories. One page says homes are flying. Another says they are sitting. A third says inventory is collapsing while buyers supposedly have more choice than last year.

Most of the time, nobody is lying. The numbers are measuring different things, over different areas, for different months, and the definitions live in a footnote or on a methodology page that almost nobody opens.

This post walks you through the check I run before I repeat any figure to a buyer or a seller. It takes about ten minutes. By the end you will know how to find the geography label, the reporting period, the days on market definition, and the one piece of arithmetic that catches a bad stat faster than anything else.

Why two honest sources disagree

Every housing data product is built on choices. Which listings count as active. Whether pending sales are still inventory. Whether new construction is included. Whether off market and private sales are captured at all. Whether "Rochester" means the city, the county, or the whole metro area.

Change any one of those choices and the headline number moves. That is why a real estate data sources comparison is not about finding the one true site. It is about knowing what each site actually counted.

Step 1: Find the geography label, then find it again

This is the single biggest source of confusion I see, and it takes twenty seconds to check.

"Rochester" on a national aggregator can mean the City of Rochester, Monroe County, or the Rochester metro statistical area, which is much larger. Those are three very different housing markets. A listing count pulled from the city and a sales count pulled from the county will produce a ratio that means nothing.

What to do:

• Look for the exact label above the chart, not the page title. Page titles are written for search engines. Chart labels are written by the data team.
• Check whether the page is a city page, a county page, a metro page or a ZIP code page. Then confirm every number on that page uses the same one. They sometimes do not.
• Remember that Henrietta, West Henrietta, Pittsford, Brighton, Mendon, Rush and Honeoye Falls are towns and villages inside Monroe County, not neighborhoods of Rochester. County level numbers will not describe them well.

Step 2: Check the reporting period and the lag

Monthly market reports are built from closed sales, and closings get recorded after the fact. Most MLS based monthly reports publish roughly one to two weeks after the month ends. So in the middle of any month, the most recent complete month of local data is the previous one, and sometimes the one before that.

If a page shows you the current month as though it were finished, it is either projecting or showing a partial count. Partial counts skew low on volume and can distort anything calculated from volume.

Two questions worth asking on every chart:

• What month or date range does this cover, and is that range closed?
• Is this a single month, a rolling three month figure, or a trailing twelve month figure? Rolling figures are smoother and slower to turn. Single months are twitchy.

Step 3: Read the days on market definition

This is where I catch the most damage, and it is the definition worth learning by name.

Some sources measure days on market as list to contract: the number of days a home was exposed to the market before a buyer went under contract. That is the number that tells you how fast buyers are moving.

Other sources measure list to close, which bundles in the entire financing and closing period after the contract is signed. In this market that period commonly runs several weeks or more on a mortgaged purchase. Same house, same sale, and a number that can look dramatically slower.

Here is the practical tell. If a page shows a fairly long days on market figure sitting next to a sale price above list price, those two facts are in tension. Homes that genuinely sit rarely sell over asking. Before you conclude the data is broken, check whether the days on market number is list to close. If it is, the actual market exposure was much shorter, and the two figures reconcile.

The fix is boring and reliable: find the site's own definitions page. Redfin data definitions and Zillow methodology pages both spell out what their fields measure. Realtor.com publishes notes on its inventory and listing metrics. Read the one paragraph that defines days on market, then decide what you are looking at.

Step 4: Ask what counted as inventory and what counted as a sale

Inventory sounds like a simple headcount. It is not.

• Are pending and under contract listings still counted as active? Different sources answer differently, and the answer changes the total substantially.
• Is new construction included? Some builder inventory never appears in an MLS feed.
• Is the count a snapshot on one day, a month end figure, or an average of daily snapshots? Snapshots on a slow listing week look thin.
• Does the feed cover the local MLS completely? National aggregators sometimes lag or undercount in specific areas, and an undercounted listing pool makes a market look tighter than it is.

Step 5: Run one piece of arithmetic

Months of supply is active listings divided by monthly closed sales. Because it is a ratio, you can reverse it and test whether the inputs make sense.

Say a page shows 200 active listings and claims 0.4 months of supply. That is a made up example, but do the division: 200 divided by 0.4 implies about 500 closed sales in a single month, or roughly 6,000 a year, in whatever area that page is describing. If that pace looks too high for the area, then one of the two inputs is wrong or they came from different geographies.

You can run the same test in reverse. If a source tells you five to six months of supply is a balanced market, multiply the implied monthly sales pace by five or six. That tells you how many listings the area would need to be balanced. When the gap between the actual count and that figure is enormous, you are usually looking at a definitional problem rather than a real market signal.

Step 6: Ask how small the sample is

Rochester housing statistics get less reliable as the area gets smaller, and south and southeast Monroe County has plenty of small areas.

Towns like Mendon, Rush and Honeoye Falls close a modest number of homes in any given month. A single month's median sale price there can swing on a handful of transactions, and one unusual property moves it. Pittsford and Brighton are larger but still thin enough that monthly medians bounce.

Two things follow. First, prefer rolling three month or twelve month figures at the town level, and say which one you are using. Second, some metrics simply should not be published at that scale. Months of supply and sale to list ratio for a small town are often built on sample sizes too small to mean anything. Substituting Monroe County numbers to fill the gap is worse than saying the data is not available.

Where the primary numbers live

My working rule is simple. Lead with the MLS based local sources for anything specific to Monroe County or its towns. Use the national portals to cross check direction and to read definitions. When they disagree with the local reports, say so out loud instead of picking the number you like.

What this looks like in practice

I do not quote a figure unless I can attach three things to it: the geography, the reporting period, and the source. If I cannot attach all three, I describe the market qualitatively and tell you what I do not know. That is less satisfying than a decimal point. It is also the only version that holds up when you are pricing a house or writing an offer.

The same discipline applies to automated valuations. Both Zillow and Redfin publish accuracy information for their estimate tools, including how error is measured and how it differs between homes currently listed and homes that are not. Go read that page before you treat an estimate as a price. It will change how you use it.

Ten minutes of footnote reading will not tell you what your house is worth. It will stop you from making a decision on a number that was never describing your market in the first place.

If you have a stat you cannot square with what you are seeing on the ground, send it to me and I will tell you what it is actually measuring and where the better number lives. Schedule a time with me here and bring the screenshots.

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.