Add backtest pipeline, betting_brain filters, score coherence + social v3
betting_brain.py: - HARD_MIN_SAMPLES=50 floor for calibrator bypass - ev_edge < 0 + >= 0.20 hard vetoes - BTTS muted (grid search found no profitable config) - Per-market optimal envelopes (MS, OU25) - Score coherence filter: main_pick must agree with score prediction - HTFT reversal cross-check for MS picks feature_builder.py / data_loader.py: - Real home/away_position from data (was hardcoded 10) - Cup detection wired into UpsetEngine - _estimate_league_position with 300-day season filter New scripts: - diagnostic_backtest.py: per-bet diagnostic backtest with loss patterns - optimize_filters.py: grid search per-market optimal thresholds - analyze_backtest_csv.py: root-cause hypothesis testing on CSV - compare_backtests.py: side-by-side validation with verdict - test_score_coherence.py: smoke test for coherence filter (20/20 pass) Reports: - diagnostic_backtest_20260525_024437 (50-match smoke) - diagnostic_backtest_20260525_035649 (1000-match in-sample) - filter_optimization_patch.json (grid search winners per market) Social poster v3: - satori + resvg HTML/CSS rendering pipeline - Twemoji football/basketball + flag SVGs - caption SEO: 12 curated hashtags per post - image SEO: descriptive filenames + .json metadata sidecar - /health, /preview-png, /run-now endpoints Docs: - mds/SESSION_HANDOFF.md: full session state for cross-machine continuity - mds/SOCIAL_POSTER_SETUP.md: API keys + test commands Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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