fahricansecer
659110c806
Update handoff doc + add backtest checkpoint/resume
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2026-05-25 22:29:05 +03:00
fahricansecer
988ee2f50d
Add backtest pipeline, betting_brain filters, score coherence + social v3
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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 >
2026-05-25 20:43:28 +03:00
fahricansecer
21e05148c8
feat: league tier system + retrained V25 models (48 quality leagues)
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Deploy Iddaai Backend / build-and-deploy (push) Failing after 3m56s
- Add LeagueTier DB model and Prisma schema
- Add league-tiers service (CRUD, sync, retrain trigger)
- Add league-tiers controller with admin API endpoints
- Add /v1/admin/retrain endpoint in AI engine (extract→train→reload pipeline)
- Retrain V25 Pro with 48 quality leagues (MS accuracy: 26.9%→51.4%)
- Update qualified_leagues.json (443→48 leagues)
- Include V25 model files in repo for Docker deployment
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com >
2026-05-20 21:57:15 +03:00
fahricansecer
5645b38f20
main
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2026-05-05 17:09:11 +03:00
fahricansecer
9bb8f39bca
gg
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2026-05-05 14:06:20 +03:00
fahricansecer
a338d02244
main
Deploy Iddaai Backend / build-and-deploy (push) Successful in 2m42s
2026-04-26 03:07:18 +03:00
fahricansecer
3875f2a512
Create v28-pro-max-architecture.md
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2026-04-24 02:30:26 +03:00
fahricansecer
df428ed1e8
gg
2026-04-22 02:17:02 +03:00
fahricansecer
2f0b85a0c7
first (part 2: other directories)
Deploy Iddaai Backend / build-and-deploy (push) Failing after 18s
2026-04-16 15:11:25 +03:00
fahricansecer