Data-driven race analysis, probability modelling, and automated betting strategies for serious punters.
From raw data aggregation to automated bet execution, TurfOps covers every step of the quantitative punting workflow.
Live meetings, runners, and form guides from PuntingForm across AU, NZ, GB, IE, HK, SG, JP, and US racing.
Real-time market odds, Betfair Starting Price, and direct bet placement via MCP sidecar integration.
From simple ratings to the Benter model, Shin method, XGBoost ML, and model consensus. Build your own or combine existing ones.
Rule-based JSON configs or Python-coded strategies with full execution traces. Analyse any race with any strategy in seconds.
Test strategies against Betfair historical data with P/L, ROI, strike rate, drawdown, and equity curve metrics.
Simulate strategies with a virtual balance before risking real money. Track performance without financial exposure.
TurfOps connects your data sources, runs your analysis, and executes your strategy.
Aggregate race data from PuntingForm and Betfair Exchange via MCP sidecar services. Meetings, runners, odds, and form — all in one place.
Run probability models and strategies against today's races. Compare model outputs, identify value, and refine your approach with backtesting.
Place bets directly on Betfair Exchange or paper trade to validate your strategy before committing real funds.
Web, desktop, or API — TurfOps runs wherever you do.
Full-featured browser interface built with Vue 3. Access from any device, anywhere.
Native Rust/Dioxus client with 6 colour themes. Fast rendering, low resource usage, offline-capable.
Headless access for custom integrations. Build your own tools on top of the TurfOps engine.
Open-source foundations engineered for reliability and performance.
TurfOps is a non-commercial, personal project built purely for the joy of learning. It serves as a hands-on playground for exploring artificial intelligence, machine learning, applied statistics, and modern software engineering.
The platform brings together a wide range of disciplines — from Bayesian probability and conditional logit models to real-time data pipelines, full-stack web development, and native desktop applications in Rust. Every feature is an excuse to dig deeper into a new technique or technology.
XGBoost gradient boosting, feature engineering, model training pipelines, and AI-assisted development with Claude Code.
Bayesian inference, the Benter model, Shin's method, Harville formulas, market efficiency analysis, and probability calibration.
Full-stack development across Python, Rust, TypeScript, and Vue. Async architectures, MCP protocol integration, Docker orchestration, and CI/CD.
Historical data pipelines, real-time market feeds, PostgreSQL with async SQLAlchemy, ETL workflows, and backtesting infrastructure.
Prefect workflow orchestration, scheduled data fetching, automated bet settlement, odds snapshot capture, and background job processing.
Betfair Exchange API, PuntingForm data feeds, Model Context Protocol (MCP) sidecars, REST API design, and real-time streaming over HTTP.
This is not a commercial product or betting service. It's a solo developer's workshop for continuous learning and experimentation.