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Momus Football Match Odds & Correct-Score Model
x402
Momus Football Match Odds & Correct-Score Model is a paid API for AI agents from x402.momusai.io, paid per call via x402, $0.05/call, status unknown (last checked 2026-10-13).
Returns Dixon-Coles model probabilities, fair odds, correct-score grid, and derived markets for a single football (soccer) fixture given home and away team names.
Price / call$0.05
Success—
StatusUnknown
How this service works
Momus football model: 1X2 probabilities, fair odds, correct-score grid and derived markets for one fixture. Deterministic Dixon-Coles, no LLM. Team names are matched loosely.
Output
Returns a structured response containing 1X2 (home win / draw / away win) probabilities and fair odds, a correct-score probability grid across likely scorelines, and additional derived betting markets — all computed deterministically via the Dixon-Coles football model, with no LLM inference involved.
Example use cases
Pre-match betting research
“Can you pull up the 1X2 probabilities and fair odds for the Arsenal vs Tottenham match? I want to compare them against the bookmaker lines I'm seeing.”
Correct score market analysis
“Get me the full correct-score probability grid for Manchester City vs Liverpool — I want to see which scorelines the Momus football model thinks are most likely.”
Quantitative fantasy sports prep
“What does the statistical model say about Bayern Munich vs Borussia Dortmund? I need the win/draw/loss probabilities and any derived markets for my analysis.”
Technical details
Endpoint
GEThttps://x402.momusai.io/quote?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, deterministic, model-based football match probabilities (1X2, correct score, derived markets) without relying on an LLM. It is ideal for quantitative betting research, odds comparison, or fantasy sports analysis. Prefer it over LLM-based prediction services when you want statistically grounded Dixon-Coles outputs. It is more appropriate than generic sports data APIs when you need fair odds and a full correct-score grid rather than raw historical stats.
Side effects
- Team names not recognized even after loose matching — returns an error or empty result
- Fixture not in the model's dataset — model may lack calibrated parameters for obscure leagues
- Invalid or missing homeTeam/awayTeam query parameters — returns a 400-level error
- Payment of $0.05 USDC not completed — returns a 402 Payment Required response
- Network timeout if the computation is unexpectedly slow
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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