The problem

Most bettors focus on picking winners rather than finding mispriced odds. They chase moved lines, pay too much vig, and fail to distinguish between a likely outcome and a positive expected value (+EV) opportunity.

What it does

• Identifies market inefficiencies by comparing opening lines, current odds, and book-to-book spreads.
• Differentiates between sharp action, public drift, and noise-driven line movement.
• Calculates whether an edge remains after accounting for market vig and liquidity.
• Generates a disciplined "Pass or Play" verdict based on price sensitivity and timing windows.
• Audits specific betting scenarios for closing-line value (CLV) and model-vs-market discrepancies.

Why this beats prompting it yourself

Generic LLM prompts often prioritize sports trivia or team sentiment over market mechanics. This skill enforces a strict mathematical framework that treats betting as a pricing problem, preventing the agent from recommending "likely" winners that are actually bad bets at current market prices.

Use cases

• Analyzing whether a line move is sharp pressure or a public overreaction trap.
• Evaluating cross-book price spreads to find slow-market windows before they close.
• Determining if a specific prop bet is mispriced relative to player-specific news.
• Deciding if a bet is worth the vig or if the edge is too thin to justify the variance.

Known limitations

Requires specific market context like current odds or line movement data to function. It cannot predict outcomes without price data and will halt if market context is missing.