What's inside
- Fixtures and forecasts for 22 competitions: score probabilities, expected goals, over 2.5 and both teams to score.
- Match spotlight with the most likely score, an AI-written preview for upcoming fixtures, and a question box that answers from the forecast facts shown on the page.
- Weekly AI recaps summarising the last seven days of results for each competition, using only the saved scores.
- Match simulator with formations, a replay, events, pause and skip, reproducible seeds, and a 10,000-run comparison.
- Club and player profiles: squads, form, managers, stadiums, honours and career histories.
- Honest backtests: outcome and exact-score hit rates, log loss and Brier score, with the forecast cutoff shown.
How it works
- Forecasts come from a Rust model in
crates/predictor, built from saved match data. Every forecast is dated, so the cutoff is always visible.
- The site is built from saved data.
tools/build_website.cjs compiles the dashboard and packages it as static pages with on-demand JSON. No server is needed to view it.
- Results refresh daily. A scheduled workflow pulls open results from openfootball, moves the forecast date to today, rebuilds, and republishes. It only commits when the data changes.
- AI features are cached. Fixture previews (
data/ai/previews.json) and weekly recaps (data/ai/recaps.json) are generated once per item by the DeepSeek API. The question box runs as a Vercel serverless function (api/match-question.js), with a per-visitor limit.
Build and run
Requirements: stable Rust and Node.js 20 or later.
node tools/build_website.cjs # build the site into dist/
node tools/serve_dashboard.cjs dist/index.html
Open http://127.0.0.1:8765/. Previews need a DEEPSEEK_API_KEY in the environment. Without one, the site builds and simply shows no previews.
Run the checks:
cargo test --locked -p predictor
node --test crates/predictor/web/*.test.cjs
Configuration
| Variable | Where | Purpose |
|---|
DEEPSEEK_API_KEY | GitHub Actions secret | AI match previews during the scheduled build |
DEEPSEEK_MODEL | Optional | Model name. Defaults to deepseek-chat. |
Data and licences
- Results: openfootball, public domain.
- Team and player profiles and images: bundled from the sources recorded in
data/. Each image keeps its own credit and licence, which the site shows.
- Code: dual-licensed under MIT or Apache-2.0.
Forecasts are statistical estimates for analysis and entertainment. They are not betting advice.
Project structure
crates/
predictor/ forecasting model, backtests and the dashboard generator
football_ai/ match simulation engine
football_sandbox/ tactical sandbox (development tool)
data/ saved results, catalog, profiles and AI previews
tools/ build, refresh and publishing scripts
.github/workflows/ scheduled refresh and publishing
docs/ website publishing notes and screenshots
Licence
MIT or Apache-2.0, at your option.
