fix: recalibrate saved recommendation snapshots

platform/backend/app/analytics/daily_card_generator.py

@@ -451,6 +451,89 @@ def _finalize_confidence_score(
 
   return round(_clamp(adjusted, floor, ceiling), 1)
 
+
+
+def _market_tier_from_item(item: dict[str, Any]) -> str:
+  market_type = str(item.get('market_type') or '')
+  risk_level = str(item.get('risk_level') or '')
+  if market_type == '跨場串關' or risk_level == 'parlay':
+    return 'parlay'
+  if market_type == '同場串關' or risk_level == 'sgp':
+    return 'sgp'
+  if market_type == '正確比分':
+    return 'exact_score'
+  if risk_level == 'speculative':
+    return 'speculative'
+  if market_type.startswith('大小球'):
+    return 'totals'
+  if market_type == '雙方進球':
+    return 'btts'
+  if market_type == '隊伍總進球':
+    return 'team_total'
+  return 'core'
+
+
+def recalibrate_daily_card_confidence_payload(card_payload: dict[str, Any]) -> dict[str, Any]:
+  """Re-label stored pre-match snapshots with the current public confidence scale.
+
+  This intentionally does not create, remove, or reorder picks. It only prevents
+  older saved snapshots from showing stale 0.0 or hard-capped template scores.
+  """
+
+  payload = dict(card_payload)
+  bucket_names = ('safe_singles', 'high_risk_singles', 'safe_parlays', 'sgp_lotteries')
+  changed_count = 0
+
+  for bucket_name in bucket_names:
+    next_group: list[dict[str, Any]] = []
+    for raw_item in payload.get(bucket_name, []) or []:
+      if not isinstance(raw_item, dict):
+        continue
+      item = dict(raw_item)
+      try:
+        market_tier = _market_tier_from_item(item)
+        risk_level = str(item.get('risk_level') or ('parlay' if market_tier == 'parlay' else 'sgp' if market_tier == 'sgp' else 'core'))
+        has_market_odds = bool(item.get('has_market_odds'))
+        target_odds = _safe_float(item.get('target_odds'), 1.0)
+        true_prob = _safe_float(item.get('win_prob'), 0.0) / 100.0
+        ev_percent = _safe_float(item.get('ev_percent'), 0.0)
+        edge_percent = _safe_float(item.get('edge_percent'), 0.0)
+        previous_score = _safe_float(item.get('confidence_score'), 0.0)
+        next_score = _finalize_confidence_score(
+          previous_score,
+          match_id=str(item.get('match_id') or ''),
+          market_type=str(item.get('market_type') or ''),
+          selection=str(item.get('selection') or ''),
+          recommendation=str(item.get('recommendation') or ''),
+          risk_level=risk_level,
+          market_tier=market_tier,
+          data_quality=str(item.get('data_quality') or 'observed'),
+          has_market_odds=has_market_odds,
+          odds_source_kind=str(item.get('odds_source_kind') or 'market'),
+          target_odds=target_odds,
+          true_prob=true_prob,
+          ev_percent=ev_percent,
+          edge_percent=edge_percent,
+        )
+        if next_score != previous_score:
+          changed_count += 1
+        item['confidence_score'] = next_score
+        item['confidence_band'] = _confidence_band(next_score, has_market_odds, risk_level)
+        factors = list(item.get('confidence_factors') or [])
+        if '信心分數已套用新版資料品質校準' not in factors:
+          factors.append('信心分數已套用新版資料品質校準')
+        item['confidence_factors'] = factors[:8]
+      except Exception:
+        pass
+      next_group.append(item)
+    payload[bucket_name] = next_group
+
+  if changed_count:
+    quality_summary = dict(payload.get('data_quality_summary') or {})
+    quality_summary['confidence_recalibrated_items'] = changed_count
+    payload['data_quality_summary'] = quality_summary
+  return payload
+
 def _confidence_band(score: float, has_market_odds: bool, risk_level: str) -> str:
   if not has_market_odds:
     if score >= 64:

platform/backend/app/main.py

@@ -20,7 +20,7 @@ from pydantic import BaseModel, Field
 from redis.asyncio import Redis
 from .db.base import SessionFactory
 from .db.models import Bookmaker, DailyRecommendationSnapshot, Match, MatchStatus, OddsHistory, SmartMoneyFlow, Team, Venue
-from .analytics.daily_card_generator import generate_daily_card
+from .analytics.daily_card_generator import generate_daily_card, recalibrate_daily_card_confidence_payload
 from .analytics.localization import (
   localize_city,
   localize_country,
@@ -1815,7 +1815,7 @@ async def _read_daily_recommendation_snapshot_payload(target_date: str) -> dict[
     snapshot = await session.get(DailyRecommendationSnapshot, snapshot_id)
     if snapshot is None or not snapshot.payload:
       return None
-    payload = dict(snapshot.payload)
+    payload = recalibrate_daily_card_confidence_payload(dict(snapshot.payload))
     payload.setdefault('snapshot_status', 'saved_snapshot')
     return payload