MLB analytics and forecasting
Advanced baseball intelligence for model-driven analysis.
StatcastEdge turns daily MLB data into probabilistic forecasts, simulation summaries, matchup context, and historical performance tracking for fans, analysts, and researchers.
View Forecasts10K+
simulation paths reviewed for slate context
45
production model features
13K+
historical MLB games in training data
3
ensemble model families
How The Model Works
A stacked machine-learning ensemble blends multiple model signals, then calibrates probabilities against historical MLB outcomes. Inputs include starters, bullpen usage, team form, ELO, park/weather context, lineup signals, defensive metrics, and simulation output.
Educational Analytics Workflow
Users can compare model probability, inspect feature context, review simulation-informed confidence, and revisit historical outcomes after games finish. The product is designed as a research and education layer.