Our Prediction Methodology
Powered by a multi-agent AI ensemble that analyzes 50+ statistical dimensions per game
Important: Our predictions are for informational and entertainment purposes only. Sports outcomes are inherently unpredictable, and past performance does not guarantee future results.
How Our AI Ensemble Works
Comprehensive Data Collection
We continuously collect data from multiple verified sources: official game statistics, advanced team metrics, player performance data, injury reports from official sources and news extraction, bookmaker odds from multiple markets, schedule data, referee assignments, and team news. This creates a rich context of 50+ dimensions for every game.
Multi-Agent AI Debate
Seven independent AI analysts examine each game simultaneously from different perspectives. Each analyst specializes in a specific domain and provides an independent prediction with reasoning. This mirrors how a panel of human experts might debate a game — but at machine speed.
Bayesian Confidence Calibration
Individual predictions are aggregated using Bayesian inference — a mathematically rigorous approach that weights each analyst by their historical accuracy. Market-derived probabilities serve as an informed prior. The result: when we say 80% confident, we mean it. Our calibration system continuously verifies that confidence scores match actual outcomes.
Self-Improving System
After every game, our system evaluates its predictions and learns from errors. Weekly meta-analysis identifies systematic biases (e.g., overconfidence in specific leagues) and automatically adjusts agent behavior. Historical pattern matching lets the system recognize similar game situations and learn from past outcomes.
CourtFrame Power Index (CPI)
Our proprietary team strength metric combines 8 statistical dimensions into a single 0-100 score, updated daily:
Understanding Confidence Scores
Strong Consensus
All 7 analysts agree with high individual confidence. Strong statistical and market signals.
Moderate Consensus
Most analysts agree but some see mixed signals. Competitive matchup expected.
Split Decision
Analysts are divided. Close game with no clear statistical edge.
Transparent Accuracy Tracking
Every prediction we publish is tracked against the actual outcome. We never delete incorrect predictions. Our full archive is publicly available with calibration metrics showing how well our confidence scores match reality.
Winner Accuracy
Percentage of games where we correctly predicted the winning team.
Calibration Score
How well our stated confidence matches actual outcomes. Perfect calibration means 80% confidence = 80% accuracy.
Playoff-Aware Predictions
Our system automatically detects playoff games and adjusts its analysis. In the postseason, momentum and matchup analysis receive higher weight, while contrarian signals are de-emphasized. The system tracks series scores, identifies elimination games, and factors in playoff experience when generating predictions. Regular season standings are supplemented with playoff-specific performance data.
Acknowledged Limitations
- •Sports outcomes are inherently uncertain — no model can predict with certainty.
- •Last-minute changes (injuries, lineup decisions) may not be captured before game time.
- •Human intangibles like team chemistry, motivation, and crowd energy are difficult to quantify.
- •Our system learns and improves over time, meaning early-season predictions may be less accurate.