NilsBriggen
f3b2a69b31
- 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>
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2.7 KiB
JSON
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2.7 KiB
JSON
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