Update analytics/recommendation_rules.py

analytics/recommendation_rules.py

@@ -5,10 +5,11 @@ from typing import Any
 
 def apply_recommendation_rules(edge_row: dict[str, Any]) -> dict[str, Any]:
     """
-    Converts edge/confidence into a recommendation tier.
+    Converts edge/confidence into recommendation tiers.
+    Focuses on HR market first for now.
     """
-    edge = float(edge_row.get("hr_edge", 0.0) or 0.0)
-    bet_ev = float(edge_row.get("hr_bet_ev", 0.0) or 0.0)
+    hr_edge = float(edge_row.get("hr_edge", 0.0) or 0.0)
+    hr_bet_ev = float(edge_row.get("hr_bet_ev", 0.0) or 0.0)
     confidence = float(edge_row.get("confidence", 0.0) or 0.0)
     slot = str(edge_row.get("slot", "") or "").strip().lower()
 
@@ -16,29 +17,39 @@ def apply_recommendation_rules(edge_row: dict[str, Any]) -> dict[str, Any]:
 
     slot_boost = 0.0
     if slot == "on deck":
-        slot_boost = 0.01
+        slot_boost = 0.012
         reason_tags.append("On-deck priority")
     elif slot == "in hole":
-        slot_boost = 0.005
+        slot_boost = 0.006
         reason_tags.append("In-hole visibility")
+    elif slot == "3 away":
+        slot_boost = 0.0
+        reason_tags.append("Farther from action window")
 
-    adjusted_edge = edge + slot_boost
+    adjusted_edge = hr_edge + slot_boost
 
     if confidence < 50:
         tier = "pass"
         reason_tags.append("Low confidence")
-    elif adjusted_edge >= 0.05 and bet_ev > 0 and confidence >= 75:
+    elif adjusted_edge >= 0.06 and hr_bet_ev > 0 and confidence >= 78:
         tier = "bet"
         reason_tags.append("Strong positive edge")
-    elif adjusted_edge >= 0.02 and confidence >= 60:
+    elif adjusted_edge >= 0.025 and confidence >= 62:
         tier = "watch"
         reason_tags.append("Watchlist edge")
     else:
         tier = "pass"
         reason_tags.append("Below action threshold")
 
+    priority_score = adjusted_edge * 100 + (confidence / 10.0)
+    if slot == "on deck":
+        priority_score += 2.0
+    elif slot == "in hole":
+        priority_score += 1.0
+
     return {
         "recommendation_tier": tier,
-        "reason_tags": reason_tags,
+        "reason_tags": reason_tags[:6],
         "adjusted_edge": adjusted_edge,
+        "priority_score": priority_score,
     }