How the numbers are made

Every figure on this site comes from one test, repeated three times, that anyone with the same public data could rerun. This page describes it plainly, including what the numbers cannot claim.

The test

We rebuild the world as it looked on the 1st of January in each test year, using only information available on that day: Land Registry transactions, the property's own sale history, and Energy Performance Certificate records. The model then names its top 100 properties in each sector. Twelve months later, we count how many of those 100 actually came to market, and compare that with the sector's background rate — the share of all tracked homes that listed. The ratio is the advantage figure you see on every sector page.

The model never sees the future when it is tested. Anything lodged or registered after the snapshot date is invisible to it, the same way the future is invisible to you today. Properties already on the market at the snapshot are removed from the list before counting, because predicting a listing that already exists is not a prediction.

What counts as a hit

A hit is a marketed-sale Energy Performance Certificate lodged for the property in the twelve months after the snapshot — the certificate a seller obtains when a home is put up for sale. This record is incomplete: some genuine listings never produce one we can match. That cuts both ways, and we resolve it conservatively — the hit rates shown are floors. Sectors where the record is too thin to trust are not sold at all.

What the sector page shows

Every year of the test, separately: how many tracked homes the sector had, how many of the named 100 listed, the background rate, and the advantage. We show the worst year as prominently as the average. A sector is only listed for sale if it cleared a minimum advantage in every tested year, had enough tracked homes, and had a listing record complete enough to measure against.

What we will not claim

We do not claim to predict most of what comes to market: naming enough of a town captures most listings, and figures built that way say nothing about how sharp a list is. We do not publish return-on-spend multiples built on loose attribution. We publish the number an agent can check: of 100 named addresses, how many listed. If a competitor quotes you a bigger number, ask them for this one, for your sector, verified.

The data

HM Land Registry Price Paid Data and the Energy Performance of Buildings Register, refreshed monthly, plus probate notices from The Gazette for the flags marked urgent. All are public records. Scores are recomputed monthly and your lists refresh with them.

The fine print, in plain sight

Past advantage does not guarantee next year's. The model tracks properties with an EPC match — most of a sector, not all of it. A probability on a list is calibrated, meaning that across many homes marked 10%, about one in ten has listed; it is not a promise about any single door. Canvassing results depend on your letters and follow-up as much as the list.