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Basketball Intelligence

Basketball intelligence exposes sport-filtered betting views for anomalies, value, injuries, market movement, and micro predictions.

Backing views​

betting_intelligence.basketball_odds_anomalies
betting_intelligence.basketball_value_signals
betting_intelligence.basketball_injury_news_signals
betting_intelligence.basketball_market_movement_signals
betting_intelligence.basketball_micro_predictions

Each view is a basketball-only projection over the shared betting_intelligence tables.

Suggested flow​

  1. Start with basketball_odds_anomalies when you need unusual prices or deviations from baseline.
  2. Load basketball_value_signals for model-vs-market edge and expected value.
  3. Review basketball_injury_news_signals for team or player availability changes.
  4. Check basketball_market_movement_signals when prices are moving across books.
  5. Use basketball_micro_predictions for short-horizon outcome projections.

Shared behavior​

  • every row is already filtered to sport = 'basketball'
  • updated_at is maintained by the betting_intelligence.set_updated_at() trigger function
  • expires_at can be used to exclude stale intelligence records
  • metadata and state_snapshot fields are stored as jsonb

Common join keys​

  • match_id for match-level joins
  • bookmaker_id for book-specific views
  • market_type, market_scope, and selection for market-level comparisons

Notes​

  • All row ids are UUIDs generated with gen_random_uuid().
  • Use the endpoint pages in this section for field-level filters and example queries.