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vig_removal

vig_removal is a skill for Claude Code, Codex from DanielTomaro13/sportsdata-agents. It costs 22 tokens per session (347 once invoked), scanned A, original, MIT.

A method for removing the bookmaker’s margin from betting odds to estimate each outcome’s fair probability. The margin, also called vig or overround, is the extra probability built into the quoted prices.

In plain words
What is it for?
Use it to calculate overround and fair probabilities, then compare potential value across bookmakers without combining odds incorrectly.
Why use it?
It makes odds from a complete market easier to compare by separating the market’s implied probabilities from the bookmaker’s built-in advantage.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

not rated 9repo 5d ago A scan 22 tokens original MIT

Good fit Use it to calculate overround and fair probabilities, then compare potential value across bookmakers without combining odds incorrectly.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/danieltomaro13/sportsdata-agents/vig_removal
View source ↗ DanielTomaro13/sportsdata-agents sportsdata-ai.com
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add DanielTomaro13/sportsdata-agents --skill vig_removal
Clone the repo
git clone --depth 1 https://github.com/DanielTomaro13/sportsdata-agents

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for vig_removal

README.md
[![agentmods](https://agentmods.dev/badge/skills/danieltomaro13/sportsdata-agents/vig_removal/github.svg)](https://agentmods.dev/skills/danieltomaro13/sportsdata-agents/vig_removal)
Your own site
<a href="https://agentmods.dev/skills/danieltomaro13/sportsdata-agents/vig_removal"><img src="https://agentmods.dev/badge/skills/danieltomaro13/sportsdata-agents/vig_removal/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for vig_removal

Your own site · 80×15
<a href="https://agentmods.dev/skills/danieltomaro13/sportsdata-agents/vig_removal"><img src="https://agentmods.dev/badge/skills/danieltomaro13/sportsdata-agents/vig_removal.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 22 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 347 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00022 $0.00347
Opus 5.5 $0.00009 $0.00139
Sonnet 5.5 $0.00004 $0.00069
Haiku 4.5 $0.00002 $0.00035

Measured 2mo ago against content hash 6f210a471ec5, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

vig_removal scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

src/sportsdata_agents/skills/vig_removal/SKILL.md · 26 lines

What it actually says

Removing the vig

A bookmaker's quoted prices imply probabilities that sum to MORE than 1 — the excess is the margin (vig / overround / juice). To estimate what the market really thinks, remove it.

Procedure

  1. Collect the decimal odds for every selection in the same market at one bookmaker (all runners / both sides). Partial markets give wrong answers.
  2. Call the vig_removal tool with those prices. It returns:
    • overround — e.g. 1.052 means a 5.2% margin
    • fair_probabilities — each selection's implied probability normalised to sum to 1
  3. To compare value across books: get the fair probability from the sharpest market available (Pinnacle / Betfair exchange when present — lowest overround), then call expected_value with that probability against each book's offered odds.

Rules

  • Never average odds across books before removing vig — remove per book, then compare.
  • A two-way 1.90/1.90 market is ~5.26% vig and 0.50/0.50 fair — a useful sanity check.
  • If you cannot get the FULL market at one book, say so; do not normalise a partial set.
  • Report the overround alongside any "fair" number so the user sees the margin you removed.
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2mo ago First seen · 26 lines · 22 tokens per session scan A 6f210a471ec5

Subscribe to this mod's changes

vig_removal is a skill published in the GitHub repository DanielTomaro13/sportsdata-agents (9 stars, last pushed 5d ago), licensed MIT. It adds 22 tokens to every session and 347 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Finance and fintechPythonai-agentsmcpsports-bettingsports-data
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