- src/lib/model/teamDc.ts: per-team attack/defence Dixon-Coles via weighted MLE
(Maher iterations), exponential time-decay, shrinkage for thin histories,
learned home multiplier; log-pool of score matrices. 7 vitest cases.
- buildBacktest.ts rewritten as a strict three-way-split bake-off: params
pre-2018, tune (xi, k, w) on 2018-2022 validation, final scores on untouched
2022-2026 test (4,448 matches). Result: ensemble RPS 0.1721 beats Elo-DC
0.1726 and Team-DC 0.1801; ECE stays 0.01. Tuned: xi=0.5 k=5 w=0.75.
- Runtime now IS the backtested model: ratings.json carries teamDc+ensembleW;
matchMatrix() pools both members for predictions, Monte Carlo and advance
probs; ModelEngine re-rating preserves ensemble params; lambdas reported as
matrix expectations (drives in-play).
- scripts/buildSquadValues.ts: Transfermarkt FIWC participants page -> all 48
squad market values (France 1.52bn ... Qatar 20m). Display/availability layer
only — June-2026 values are NOT in the backtested model (would leak).
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