Partners & Integrations

Partners can define and tune models based on their own strategies. Depending on plan, partners can:

• Select input features (form windows, home/away weighting, historical depth)
• Adjust confidence thresholds and risk profiles
• Choose conservative vs aggressive market focus
• Run multiple model variants in parallel

Custom models are versioned, auditable, and delivered via the same APIs as standard models.

Full exposure of model metadata and historical performance. Transparency enables trust and informed evaluation of prediction quality.

Flexible architecture supporting multiple sports and leagues. Coverage scope depends on contract terms.

Outputs designed for direct UI/UX integration: probabilities, confidence signals, explanations/feature highlights (where available), and stable identifiers.

Platform Capabilities

Exact field names can be aligned to partner conventions.

Upcoming events by date range, league, or team. Stable IDs for events and participants.

Common use:Match lists, Calendars, Deep-linking

Probabilities per market (1X2, moneyline, totals, spreads depending on sport). Model confidence score, timestamp, versioning, and update cadence.

Common use:Today's Picks, Trending Matches, Home feeds

Full breakdown for a specific prediction. Model name and parameters (if enabled). Optional reasoning snippets.

Common use:Prediction detail pages, Tooltips

Accuracy / hit rate by sport, league, timeframe. Profit / ROI-style metrics if units are tracked. Optional calibration metrics.

Common use:Model profile pages, Trust dashboards

Push updates when predictions are published or updated.

Common use:Alerting, Cache refresh, Newsroom workflows

A) Predictions tab in match details

Display prediction data on an event detail page

1. Call Fixtures API to get match ID
2. Call Prediction Details API with match ID
3. Render probability, confidence, model name, last updated time

B) Home feed / daily picks

Show top predictions on a home screen

1. Call Prediction Feed filtered by date and league
2. Sort by confidence or expected value (if available)
3. Display top N predictions with key metrics

C) Model profile page

Build a transparency page for model performance

1. Call Model Performance API with model ID
2. Render accuracy/profit charts and summary metrics
3. Display historical performance breakdowns

Pricing

Pricing is indicative and finalized after scope confirmation.