How the BetData AI football prediction algorithm works
Every prediction is generated before kick-off. The algorithm compares independent statistical signals, estimates market probabilities and then applies data-quality and risk filters.
Data used by the model
The model analyzes recent team form, separate home and away performance, head-to-head matches, goals scored and conceded, xG, available market odds and source-data coverage. Postponed, cancelled and unsuitable fixtures are filtered out.
From probability to recommendation
A high probability does not automatically become a recommended pick. The forecast must pass cross-market consistency, sample-size, nil-nil and one-goal risk, price-quality and other safety checks. This is why the public probability table contains more matches than the green recommendation cards.
Pre-match information only
The calculation must not use information that became known after kick-off. This reduces data leakage and keeps each published probability a genuine pre-match estimate.
How to read a prediction
A percentage is a model estimate, not a guarantee. A recommended card shows the market, algorithm selection and probability. Other fixtures are available in the market comparison table.