AI Engine
The intelligence layer under every signal.
PrediShark AI is not one model — it is an orchestrated ensemble of transformer sequence models, graph neural networks and Bayesian calibrators trained on decades of match data and continuously refined by live market feedback.
Pipeline
Six layers, one signal
01
Ingestion
Real-time telemetry, lineups, weather, referee history and market flow from 200+ sources.
02
Feature Fabric
3,400+ engineered features per event: xG chains, fatigue, tactical priors, travel load, motivation index.
03
Neural Ensemble
Transformer sequence models + gradient-boosted priors + graph networks for team relationships.
04
Bayesian Calibration
Isotonic + temperature scaling so a 72% confidence means 72% empirical hit rate.
05
Market Reconciliation
Cross-checks against sharp books to expose true edge and detect line drift in real time.
06
Signal Delivery
Streaming API + terminal push. Sub-second latency from state change to updated projection.
Specs
Model benchmarks
Log Loss
0.512
vs 0.601 market
Brier Score
0.184
top-decile calibration
Inference Latency
<180ms
p95 end-to-end
Signals / day
12,400+
across all sports
Training
Continuous learning loop
Retraining cadence
Full ensemble retrain every 24h; delta-updates every hour during live windows. Match outcomes are back-fed within 90 seconds of the final whistle.
Adversarial validation
Every signal is stress-tested against out-of-distribution scenarios — new coach, weather anomaly, roster shock — before it reaches the terminal.