Update analytics/recommendation_engine.py

analytics/recommendation_engine.py

@@ -9,6 +9,70 @@ from models.fair_odds import probability_to_american
 from models.live_fair_simulator_v3 import build_upcoming_simulated_rows
 from models.opportunity_model import estimate_plate_appearance_probability
 
+def _apply_opportunity_badges(recommendations: list[dict]) -> list[dict]:
+    if not recommendations:
+        return recommendations
+
+    rows = [dict(r) for r in recommendations]
+
+    for row in rows:
+        row["opportunity_badges"] = []
+
+    def _best_row_index(metric: str) -> int | None:
+        best_idx = None
+        best_val = None
+
+        for idx, row in enumerate(rows):
+            value = row.get(metric)
+            try:
+                numeric_value = float(value)
+            except Exception:
+                continue
+
+            if best_val is None or numeric_value > best_val:
+                best_val = numeric_value
+                best_idx = idx
+
+        return best_idx
+
+    best_overall_idx = _best_row_index("priority_score")
+    best_hr_idx = _best_row_index("hr_edge")
+    best_hit_idx = _best_row_index("hit_edge")
+    best_tb_idx = _best_row_index("tb2p_edge")
+
+    if best_overall_idx is not None:
+        rows[best_overall_idx]["opportunity_badges"].append("BEST OVERALL")
+
+    if best_hr_idx is not None:
+        rows[best_hr_idx]["opportunity_badges"].append("BEST HR EDGE")
+
+    if best_hit_idx is not None:
+        rows[best_hit_idx]["opportunity_badges"].append("BEST HIT EDGE")
+
+    if best_tb_idx is not None:
+        rows[best_tb_idx]["opportunity_badges"].append("BEST TB EDGE")
+
+    for row in rows:
+        tier = str(row.get("recommendation_tier", "") or "").strip().lower()
+
+        if tier == "bet":
+            row["opportunity_badges"].append("BET")
+        elif tier == "watch":
+            row["opportunity_badges"].append("WATCH")
+
+        # de-duplicate while preserving order
+        seen = set()
+        deduped = []
+        for badge in row["opportunity_badges"]:
+            if badge in seen:
+                continue
+            seen.add(badge)
+            deduped.append(badge)
+
+        row["opportunity_badges"] = deduped[:3]
+
+    return rows
+
 def _lineup_distance_from_slot(slot: str) -> int:
     s = str(slot or "").strip().lower()