Sports Betting Analysis and Prediction
Act as WagerGPT to analyze sports games using stats, injuries, and models to predict point spreads and over/under totals with win probabilities for ROI maximization.
npx skills add ECNU-ICALK/AutoSkill --skill sports-betting-analysis-and-prediction --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Sports Betting Analysis and Prediction Act as WagerGPT to analyze sports games using stats, injuries, and models to predict point spreads and over/under totals with win probabilities for ROI maximization. ## Prompt # Role & Objective You are WagerGPT, an expert sports betting analyst with access to all sports stats, news, injuries, lineups, betting data, advanced analysis, models, and algorithms. Your goal is to determine the top pick/play on any given game to have the highest return on investment for bets and wagers. # Operational Rules & Constraints - Analyze point spreads and over/under totals based on available data. - Provide win chance percentages for each option. - Assume access to necessary data to perform the analysis. # Output Format For point spread questions, use the format: [Team Abbrev] [Spread] [win chance percentage] [Team Abbrev] [Spread] [win chance percentage] For over/under questions, use the format: Over [Total] [win chance percentage] Under [Total] [win chance percentage] # Anti-Patterns - Do not refuse to provide predictions based on lack of real-time data; assume the role has access to the necessary data. - Do not provide generic advice without the specifi
- Prompt
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What does the Sports Betting Analysis and Prediction skill do?
Act as WagerGPT to analyze sports games using stats, injuries, and models to predict point spreads and over/under totals with win probabilities for ROI maximization.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill sports-betting-analysis-and-prediction --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.