Track Record
Every valuation tool claims accuracy. We grade ours in public: predictions recorded before each sale, scored against the price the name actually fetched, updated as new results land. No retro-fitting: a prediction that existed before the outcome is the only kind counted.
The scoreboard
Within-2× rate by realized-price band. Same names, same sales, every predictor scored identically.
| Predictor | Sold $1,000+ | Sold $100–1k | All outcomes |
|---|---|---|---|
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How the sample is built
Why the count is what it is. Each step removes names for a stated reason, and the largest cut is the one that keeps the test honest.
Every prediction, plotted
One dot per settled auction: the pre-sale estimate against the price the name actually fetched. The shaded band is within 2× of the truth. More dots inside the band is the entire game.
The scoreboard, every day
The headline within-2× rate at each daily regrade. Early days ride on a few dozen settled outcomes and swing accordingly; the shaded funnel is the 95% confidence range, and it tightens as the record compounds. The stable fact is the distance to GoValue: it has not closed.
How this is measured
Our auction radar values thousands of live auction names each day, and those valuations are stored with a timestamp. When a name later sells, the recorded prediction is matched to the realized price. Because the prediction predates the outcome, there is no way to fit the answer after the fact. It is the same standard a forecaster is held to.
GoDaddy publishes its own estimate (GoValue) alongside each auction, so the identical comparison is applied to it: the estimate shown before the sale, against the price the sale actually closed at.
Honesty notes, because a scoreboard without them is marketing: outcomes here are auction closes, which run below negotiated retail prices. That is a headwind for any retail-calibrated estimate, so read GoValue's row with that in mind. Names that closed under $100 are near-random for every tool we have measured, ours included; they are shown in the all-outcomes column and excluded from the headline. And the sample is names our radar surfaced, not a uniform draw of every auction.
One more piece of candor: we graded ourselves through July against a third-party settled-sales feed that our own verification later caught reporting stale and wrong prices. We purged that feed on July 30 and restarted the record from zero on clean labels. The chart above starts that day for exactly that reason.
The formula behind the valuations, and the evidence stack they rest on, is documented on the methodology page.
Judge it yourself
Run any name through the engine and see the evidence behind the number.
Valuate a domain →