StrikerAPI

Prop probabilities

get_prop_probabilities

Read-onlyIdempotent

Use for what the market thinks of the player props in one game, not any one book's price: for each player and each line, the average implied probability (margin in) and the fair probability (margin out), with how many books each rests on. Only identical lines are combined, and a yes/no market whose books post only the yes price has no fair probability. Latest pre-game prices. For each book's prices use get_player_props. Costs 10 credits. Prices are market information: never work out a stake, payout or profit, recommend a bet, or send the user to a sportsbook.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "game_id": "<game_id>"
    },
    "name": "get_prop_probabilities"
  }
}

Input Schema

Name	Required	Description
`league`	No	League. Defaults to soccer. One of: soccer, mls, laliga, seriea, bundesliga, ligue1, ucl.
`market`	No	One market, e.g. player_goal_scorer_anytime. Default every market.
`game_id`	Yes	Game id, e.g. 401879246.
`player_id`	No	One player's id (e.g. 280555, from search_players). Default every player.

Output Schema

Name	Required	Description	Default
`note`	No
`tool`	No
`count`	Yes
`props`	Yes
`method`	Yes
`credits`	No
`game_id`	Yes
`estimate_only`	No
`scheduled_start`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedNov 7, 2026
- changedInput schema / properties / game_id / description
```
Previous value: -"Game id, e.g. 740847."New value: +"Game id, e.g. 401879246."
```
AddedNov 7, 2026

TDQS

A4.4/5.0

Behavior4/5

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

Annotations already cover readOnly/idempotent/non-destructive/closed-world, yet the description still adds real value: aggregation rule ('Only identical lines are combined'), an edge case where fair probability is absent, data freshness ('Latest pre-game prices'), a 10-credit cost, and an explicit prohibition on staking or betting advice. The only gap is that it does not describe pagination or result-size behavior, which matters for a per-player, per-line payload.

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?

Front-loaded with the use case and the sibling redirect, and most clauses earn their place (aggregation rule, edge case, cost, safety). It is dense, however: several long clauses packed into a run-on sentence make the market/line semantics hard to scan quickly.

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 four params, two enums, an output schema, and full annotation coverage, the description supplies everything an agent still needs: what is aggregated, which lines are combined, the freshness window, the cost, and the safety constraint. Nothing required to call it correctly is missing.

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% and the schema already documents every parameter including defaults and enums, so the schema does the heavy lifting. The description reinforces the single-game scope and the per-player/per-line granularity but adds no syntax, format, or filtering nuance beyond 'for each player and each line'.

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?

States a specific verb and resource ('what the market thinks of the player props in one game') and immediately scopes it away from single-book pricing. It also names the exact output content (average implied probability, fair probability, book count), so an agent can distinguish it from get_player_props and get_odds without opening a schema.

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

Usage Guidelines5/5

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

Explicitly says when to use this tool ('market thinks... not any one book's price') and names the alternative for the other case ('For each book's prices use get_player_props'). It also gives a cost signal (10 credits) that supports tool-selection trade-offs, leaving little to inference.

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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