Quant & forecasting
This section shows analytical breadth: public-signal ingestion, forecasting baselines, model comparison, Brier score, historical backtesting, and verification-heavy reporting.
Flagship analytical systems
Local-first agentic market intelligence workbench with public-signal ingestion, retrieval/storage services, planner agents, verification rules, structured reports, and Docker architecture.
Sports analytics forecasting and backtesting lab using 25+ years of historical NFL data, Elo baselines, XGBoost, logistic regression, ensembles, calibration, and probability-quality evaluation.
AlphaQuant workbench
Public signals move through adapters, storage, retrieval, planner agents, verification rules, and report surfaces.
Sports Forecasting Lab
Historical NFL results are framed around model comparison, calibration, Brier score, and backtesting.
Architecture
AlphaQuant emphasizes agent orchestration and evidence verification. The NFL lab emphasizes baselines, model comparison, calibration, and historical backtesting.
A local-first agentic system with separate ingestion, memory, planning, verification, and Fusion report surfaces.
A model-evaluation architecture where baselines, supervised models, calibration, and historical backtests are visible.
Responsible use
Not investment advice, financial advice, betting advice, gambling advice, live trading automation, or a wagering product.