gm

ai-engine/services/betting_brain.py

@@ -263,7 +263,14 @@ class BettingBrain:
         "OE": -12.0,
     }
 
-    def judge(self, package: Dict[str, Any]) -> Dict[str, Any]:
+    def judge(
+        self,
+        package: Dict[str, Any],
+        ms_real_odds: Optional[Dict[str, float]] = None,
+    ) -> Dict[str, Any]:
+        # V35c: real bookmaker MS odds (from odds_data) for reference rows —
+        # the brain must never display synthetic 1/p "fair odds" as offered.
+        self._ms_real_odds = ms_real_odds if isinstance(ms_real_odds, dict) else {}
         v27_engine = package.get("v27_engine")
         if not isinstance(v27_engine, dict):
             return package
@@ -916,9 +923,13 @@ class BettingBrain:
             prob = self._safe_float(probs.get(pick), 0.0)
             if prob is None or prob <= 0.0:
                 continue
-            implied_odd = round(1.0 / prob, 2) if prob > 0.01 else 0.0
-            ref_odd = existing_odds_by_pick.get(pick) or implied_odd
-            rows[key] = {
+            # V35c: only REAL bookmaker odds may be displayed. The old fallback
+            # showed synthetic fair-odds (1/prob) as "Oran" — users could read
+            # it as an offered price (e.g. X shown at 4.53 while the bulletin
+            # offered ~3.58). No real price → odds 0.0 and the FE renders "-".
+            real = self._safe_float(getattr(self, "_ms_real_odds", {}).get(pick), 0.0) or 0.0
+            ref_odd = existing_odds_by_pick.get(pick) or (real if real > 1.01 else 0.0)
+            row = {
                 "market": "MS",
                 "pick": pick,
                 "probability": round(prob, 4),
@@ -932,6 +943,12 @@ class BettingBrain:
                 "bet_grade": "PASS",
                 "decision_reasons": ["underdog_reference_for_completeness"],
             }
+            if ref_odd > 1.01:
+                # honest economics vs the real price (vig shows as it truly is)
+                row["implied_prob"] = round(1.0 / ref_odd, 4)
+                row["ev_edge"] = round(prob * ref_odd - 1.0, 4)
+                row["edge"] = row["ev_edge"]
+            rows[key] = row
 
     @staticmethod
     def _merge_row(existing: Optional[Dict[str, Any]], incoming: Dict[str, Any]) -> Dict[str, Any]: