SportIQ

football_find_value_bets

Read-onlyIdempotent

Find football betting value by comparing model win probabilities to de-vigged market odds and flagging outcomes with positive expected value above a set edge 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. Flags outcomes where the model beats the de-vigged market by min_edge and the offered price has positive expected value, with the edge, the expected value and the model's fair odds. Events that have already started are skipped.

Args: team: Optional FIFA code or team name to filter events (matched against both sides; an unrecognised value falls back to a case-insensitive substring match). 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, ev_pct, bookmaker, price_updated_at}, sorted by edge descending. data.events_analysed: not-yet-started events with both teams in the draw. meta.estimated: true. meta.is_stale reflects the odds freshness.

Input Schema

Name	Required	Description	Default
`team`	No	Optional FIFA code or team name to filter events (matched against both sides; an unrecognised value falls back to a case-insensitive substring match). 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

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedv0.4.0Oct 29, 2026

changedInput schema / properties / team / description

Previous value: -"Optional team name to filter events (case-insensitive substring, matched against both sides). Omit to scan every WC 2026 odds event."New value: +"Optional FIFA code or team name to filter events (matched against both sides; an unrecognised value falls back to a case-insensitive substring match). Omit to scan every WC 2026 odds event."

First observedv0.3.1Jul 10, 2026

TDQS

A4.4/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the read-only annotations, the description discloses the de-vigging methodology, the condition that min_edge and positive EV must both be met, and that started events are skipped. It also notes `meta.estimated: true` and `meta.is_stale` for odds freshness, giving useful behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with purpose and methodology, then structured into Args and Returns. It is generally efficient, though the Returns section overlaps with the existing output schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given rich annotations, full schema coverage, and an output schema, the description supplies enough context to call the tool correctly. It covers the methodology, filtering behavior, edge threshold, skipped events, and freshness metadata.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so both parameters are already documented in the schema. The description repeats the `team` fallback behavior and the `min_edge` formula, but adds no additional parameter semantics beyond what the schema provides.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: it surfaces value bets by comparing model win probabilities against de-vigged market odds. It also explains how this differs from related tools through the de-vig and Elo/Poisson model path, making the tool's distinct function clear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear usage context: omit `team` to scan every WC 2026 odds event, and events that have already started are skipped. It does not explicitly say when to use this instead of `football_get_odds` or `football_match_predictor`, so it lacks full alternative routing guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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