Do AI Betting Models Actually Beat Vegas?

Detailed Explanation

Vegas lines are set by sophisticated oddsmakers who also use algorithms and data analysis. The sportsbook isn't making random guesses — they're processing much of the same data that AI models use. So the question isn't whether AI is smarter than random chance (it clearly is), but whether it can find edges against a well-informed market.

The evidence suggests AI models do find consistent edges, but they're small. Academic research and backtesting data show well-tuned models achieving 54-58% accuracy against the spread over large sample sizes. With the standard -110 vig, this translates to meaningful long-term profit.

AI excels in specific scenarios. When the betting public overreacts to recent results (recency bias), AI maintains objectivity. When public perception of a team diverges from their underlying metrics, AI spots the discrepancy. In lower-profile games that receive less market attention, AI finds larger inefficiencies.

The key limitation is that AI edges shrink as the market gets more efficient. Major primetime games are harder to beat because they attract the most betting action and the sharpest handicappers. Early-week lines for less popular matchups often offer more value.

At 99¢ per sport, the cost of accessing AI predictions is negligible relative to any betting activity. Even a 1-2% edge against the spread, applied consistently, generates positive expected value over time. The question isn't whether AI beats Vegas — it's whether the edge justifies the cost. At 99¢, that answer is unambiguously yes.