How to evaluate AI sports betting picks
A polished pick is easy to publish. A complete, timestamped record that preserves losses is harder—and far more useful.
Published · Reviewed by Viral Worx LLC · UpdatedUse this seven-point check
- Publication time: Was the selection recorded before the event began and before its outcome was known?
- Complete history: Are losses, pushes, voids, and quiet days still visible?
- Sample size: Does every percentage show the number of settled selections behind it?
- Recorded terms: Are the market, price, and any spread point fixed with the original entry?
- Consistent comparison: Are returns calculated with one disclosed stake convention?
- Overlapping tracks: Does the publisher explain when one selection appears in more than one category?
- Withholding discipline: Can the system publish no pick when its information is not good enough?
Hit rate and return answer different questions
Hit rate is wins divided by settled decisions after handling pushes and voids consistently. It does not show what prices were paid. A record can win more than half its selections and still lose money if the prices are poor; a lower hit rate can be profitable at larger positive prices.
Return adds the price and stake convention, but it still needs a meaningful sample and a forward-only record. Neither measure predicts what the next pick will do.
Watch for misleading presentation
- A winning screenshot with no link to the full history.
- A percentage with no date range or denominator.
- Results calculated from a price that was not available when published.
- Deleted losses or renamed picks after an event.
- Several overlapping records added together as separate performance.