betting_game_model

shallow

io.github.Jorgeperez0825/v12-dfs · Verify this server

Game Model MODEL the GAME run markets — TEAM TOTALS (over/under) and NRFI/YRFI — vs the FanDuel line, MARKET-ANCHORED: expected_runs = the book's de-vigged implied mean + 0.25×(structural model − book), and every edge is computed vs the FAIR (de-vigged) probability, never the raw vig price. The structural inputs (season runs/game, opposing STARTER + BULLPEN run factors, park; negative-binomial tails) supply only the tilt. Entries with anchored=false / model_only=true carry edge=null — present them as context, NEVER as value. A SCREEN vs the market, not a lock — validate with CLV. For raw lines on every market use betting_market. ### Responses: **200**: Successful Response (Success Response) Content-Type: application/json **422**: Validation Error Content-Type: application/json **Example Response:** ```json { "detail": [ { "loc": [], "msg": "Message", "type": "Error Type", "ctx": {} } ] } ```

100.0/100

1 trials · measured 8 days ago

betting_game_model scores 100.0/100 on Vouch's measured behaviour index, from 1 real invocation trials against io.github.Jorgeperez0825/v12-dfs, measured 25 Aug 2026 under methodology v0.2.0. Every measured component scored 100.

Component breakdown

ComponentWeightValue
Reliability35%not applicable
Schema integrity25%100.0
Failure behaviour15%not applicable
Latency15%not applicable
Concurrency10%not applicable

Tool details

Transport
remote
Credential class
open
Input schema
not declared
Output schema
not declared
Side-effect classification
unclassified

Score history

DayScoreTierMethodology
2026-08-25100.0shallowv0.2.0

Probe evidence

ProbeOutcomes
schema_integritypass: 1

Raw request/response logs are not archived yet — the outcome counts above are drawn directly from every recorded trial.

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Vouch score: betting_game_model
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betting_game_model — Vouch