sports-betting-analyzer_skill

This skill analyzes betting markets to identify value bets using historical trends and situational stats for educational, entertainment purposes.
  • Python

36

GitHub Stars

1

Bundled Files

2 months ago

Catalog Refreshed

4 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill onewave-ai/claude-skills --skill sports-betting-analyzer

  • SKILL.md1.4 KB

Overview

This skill analyzes betting markets—spreads, over/unders, and prop bets—using historical trends and situational statistics to identify potential value bets. It is designed for entertainment and education only and includes responsible gambling guidance. The goal is to turn raw data into concise, actionable insights you can use to learn market behavior and refine betting strategy.

How this skill works

The analyzer ingests historical game logs, market lines, and situational metadata (injuries, rest, weather, travel). It calculates trend signals, implied probabilities, and edge versus market prices to flag mismatches. Outputs include value indicators, confidence tiers, and short rationale for each recommendation, plus suggested stake sizing frameworks and a responsible-gambling reminder.

When to use it

  • Before placing bets to compare your view with market-implied probabilities
  • When researching specific matchups for spreads, totals, or player props
  • To evaluate historical tendencies and situational edges (home/away, rest, matchups)
  • When testing new models or backtesting hypothesis about line movement
  • To generate teaching examples for improving decision-making and bankroll rules

Best practices

  • Always treat outputs as educational guidance; do not consider guarantees
  • Cross-check live injury and lineup news before acting on a recommendation
  • Use a disciplined staking plan (fractional Kelly, fixed units) to manage variance
  • Verify dataset recency and sample size before trusting model signals
  • Log bets and outcomes to refine inputs and calibrate confidence levels

Example use cases

  • Identify a potential value spread where historical matchups favor the underdog in coach-adjusted metrics
  • Spot an over/under line where total points are mispriced given recent tempo and pace changes
  • Compare multiple sportsbook prices for arbitrage or best-value shop opportunities
  • Produce a simple prop-bet checklist (player usage, matchup, injury risk) and score candidate props
  • Create short educational reports demonstrating how small edges compound over a season

FAQ

No. This tool identifies edges and educates on probability; gambling outcomes remain uncertain and losses are possible.

Do you provide live odds feeds or betting execution?

No. The analyzer provides analysis and recommendations. Users must verify current odds and place bets through their chosen bookmakers.

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