How do WagerProof predictions work?
WagerProof uses machine learning models trained on historical game data to generate win probabilities and predicted outcomes for each game. These models take into account a wide range of factors specific to each sport.
What the models predict
- Spread -- the model's predicted point differential and the probability of each team covering.
- Moneyline -- the model's win probability for each team, converted to implied odds.
- Totals -- the model's predicted combined score and the probability of going over or under.
Model inputs by sport
Each sport uses different data inputs tuned to what matters most for that league:
- NFL/CFB: EPA-based metrics, weather conditions, public betting labels.
- NBA: Team ratings, recent trends (last 3/5 games), win streaks, ATS records, consistency, and luck metrics.
- NCAAB: Team ratings, national rankings, and context flags.
Finding value
The key insight WagerProof provides is the comparison between model-generated odds and current Vegas lines. When the model sees a significant difference, it may indicate a value opportunity. The bigger the gap, the more potential value there is.
Predictions are data-driven estimates, not guarantees. No model is right 100% of the time. Always bet responsibly and within your means.