football_find_value_bets
Surfaces gaps between model win probabilities and market odds, flagging value bets where the model's edge exceeds a minimum threshold.
Instructions
Surface the largest gaps between the model's win probability and the market.
De-vigs each market's 1X2 decimal odds (removes the margin so implied
probabilities sum to 1) and compares them to this server's own match-outcome
probabilities — the same Elo/Poisson path football_match_predictor uses.
Where the model probability exceeds the de-vigged market probability by at
least min_edge, the outcome is flagged with its edge and the
model's fair odds.
Args: team: Optional team name to filter events (case-insensitive substring, matched against both sides). Omit to scan every WC 2026 odds event. min_edge: Minimum edge (model_prob - devigged_market_prob), 0..1. Default 0.05 (5 percentage points).
Returns: data.value_bets: list of {event_id, home, away, outcome, model_prob, fair_odds, market_odds, edge, bookmaker}, sorted by edge descending. data.events_analysed: events with both teams rated (model-comparable). meta.estimated: true. meta.is_stale reflects the odds freshness.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| team | No | Optional team name to filter events (case-insensitive substring, matched against both sides). Omit to scan every WC 2026 odds event. | |
| min_edge | No | Minimum edge (model_prob - devigged_market_prob), 0..1. Default 0.05 (5 percentage points). |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| data | No | ||
| meta | No | ||
| error | No |