gm

ai-engine/services/single_match_orchestrator.py

@@ -668,7 +668,28 @@ class SingleMatchOrchestrator(
                 base_package.setdefault("analysis_details", {})
                 base_package["analysis_details"]["v27_loaded"] = False
 
-        base_package = self._apply_upper_brain_guards(base_package)
+        base_package = self._apply_upper_brain_guards(base_package, data)
+
+        # V35c: the brain rebuilt main/value/supporting/bet_summary AFTER the
+        # market anchor ran inside _build_prediction_package — re-stamp the
+        # calibrated display fields (Güven/CI/Model%/edge) so they stay
+        # consistent, BEFORE the commentary reads the package.
+        self._apply_anchor_to_picks(
+            base_package.get("market_board") or {},
+            base_package.get("main_pick"),
+            base_package.get("value_pick"),
+            base_package.get("aggressive_pick"),
+            base_package.get("supporting_picks"),
+            base_package.get("bet_summary"),
+        )
+        _mp = base_package.get("main_pick")
+        _advice = base_package.get("bet_advice")
+        if isinstance(_mp, dict) and isinstance(_advice, dict) and _mp.get("confidence_band"):
+            _advice["confidence_band"] = _mp["confidence_band"]
+        # no fabricated value bets: a value pick must carry measured positive edge
+        _vp = base_package.get("value_pick")
+        if isinstance(_vp, dict) and float(_vp.get("ev_edge", 0.0) or 0.0) <= 0.0:
+            base_package["value_pick"] = None
 
         # ── Match Commentary: human-readable summary ──────────────
         try: