- scripts/buildBacktest.ts: honest walk-forward validation — params fit on
pre-2018 internationals, tested out-of-sample on 7,988 matches (2018-2026)
predicting each game from prior data only. Proper scoring (Brier/log-loss/RPS/
accuracy) vs uniform / base-rate / Elo-only baselines + a calibration analysis
(reliability bins + ECE). Results: 60% accuracy, RPS 0.171 (beats all
baselines), ECE 0.01 (excellent calibration).
- Methodology page (/methodology): plain-language model walkthrough, the backtest
scorecard, a custom-SVG reliability diagram, and honest limits. Transparency is
the differentiator — no market odds, no overclaiming.
- ReliabilityDiagram component; 'Model' nav entry.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
- buildStatsbombViz.ts: processes the 2022 WC Final (Argentina 3-3 France) from
StatsBomb open data → shots+xG, cumulative xG race, starting-XI pass networks,
totals, shootout result. Output committed (11KB) to avoid build-time fetch
- Custom SVG viz (no chart lib): reusable Pitch (StatsBomb 120x80 coords),
ShotMap (xG-sized dots, teams attacking opposite goals), XgRace (stepped
cumulative xG with goal markers, d3-scale), PassNetwork (nodes ∝ involvement,
links ∝ pass volume)
- StoryPage: narrative with hero scoreline, by-the-numbers bars, and the three
visualizations with explanatory copy
- Verified in browser: all three render correctly, no console errors
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
NilsBriggen