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iddaai-be/ai-engine/reports/diagnostic_backtest_20260525_024437.txt
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fahricansecer 988ee2f50d 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>
2026-05-25 20:43:28 +03:00

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==============================================================================
DIAGNOSTIC BACKTEST REPORT
==============================================================================
Generated: 2026-05-25T02:44:37
Sample window: start=-3d, end=now
Max matches: 50
Excluded days: ['2026-04-29', '2026-05-03']
OVERALL
------------------------------------------------------------------------------
n_total : 50
n_playable_settled : 27
wins : 15
losses : 12
hit_rate_pct : 55.56
unit_profit : -0.862
staked : 5.4
roi_pct : -15.96
PER MARKET
------------------------------------------------------------------------------
market n hit% profit roi%
OU25 13 53.85 -0.6 -23.08
BTTS 12 50.0 -0.392 -16.33
MS 2 100.0 0.13 32.5
PER CALIBRATED CONFIDENCE BAND
------------------------------------------------------------------------------
band n hit% roi%
55-60 4 50.0 -23.75
60-65 1 0.0 -100.0
65-70 22 59.09 -10.73
PER ODDS BAND
------------------------------------------------------------------------------
band n hit% roi%
1.3-1.5 11 81.82 12.73
1.5-1.8 10 50.0 -17.6
1.8-2.2 6 16.67 -65.83
LEAGUE vs CUP
------------------------------------------------------------------------------
league n= 27 hit=55.56% roi=-15.96%
LOSS DIAGNOSTICS
------------------------------------------------------------------------------
total losses: 12
total lost units: -2.4
By market: [('BTTS', 6), ('OU25', 6)]
Loss patterns (count, % of losses):
high_htft_reversal_prob (>=0.20) 0 (0.0%)
cup_match 0 (0.0%)
low_league_reliability (<0.45) 0 (0.0%)
v27_disagree 3 (25.0%)
trap_market_flagged 4 (33.33%)
low_calibrated_conf (<55) 0 (0.0%)
high_odds_underdog (>=2.5) 0 (0.0%)
low_data_quality (<0.55) 0 (0.0%)
high_risk_level 3 (25.0%)
inferred_features 12 (100.0%)
Top betting_brain issues seen in losses:
inferred_statistical_features 12
triple_value_not_confirmed 12
trap_market_market_overpriced 4
Top betting_brain vetoes (in losses — i.e. veto fired but bet still went through value-sniper override):
RECOMMENDATIONS
------------------------------------------------------------------------------
(none surfaced — sample too small or no clear pattern)
==============================================================================