diff --git a/etl/customers/stonewater/Wave 3 Preparation.py b/etl/customers/stonewater/Wave 3 Preparation.py
index 5b1e2f91..d2110de8 100644
--- a/etl/customers/stonewater/Wave 3 Preparation.py	
+++ b/etl/customers/stonewater/Wave 3 Preparation.py	
@@ -1777,8 +1777,9 @@ def propsed_wave_3_sample():
             "2 - same archetype", region_assets["Confidence Tier"]
         )
 
-        region_assets["Current EPC Band"] = region_assets["Current EPC Band"].fillna(
-            region_assets["Current EPC Band_method2"].astype(str),
+        region_assets["Current EPC Band"] = np.where(
+            pd.isnull(region_assets["Current EPC Band"]) & pd.notnull(region_assets["Current EPC Band_method2"]),
+            region_assets["Current EPC Band_method2"], region_assets["Current EPC Band"]
         )
 
         region_assets = region_assets.drop(columns=["Current EPC Band_method2"])
@@ -1822,12 +1823,26 @@ def propsed_wave_3_sample():
                 final_missed_matches.append(
                     {
                         "Address ID": a_id,
-                        "Confidence Tier": "5 - no similar property, needs survey to confirm"
+                        "Confidence Tier": "5 - no similar property, needs survey to confirm",
+                        "Current EPC Band": "Unknown"
                     }
                 )
                 continue
+            # We take an average
+            expected_sap = surveyed_similar["Current SAP Rating"].mean()
+            expected_epc = sap_to_epc(expected_sap)
+            if expected_epc in ["C", "B", "A"]:
+                tier = "6 - EPC C or above"
+            else:
+                tier = "3 - similar property"
 
-            raise NotImplementedError("Implement me")
+            final_missed_matches.append(
+                {
+                    "Address ID": a_id,
+                    "Confidence Tier": tier,
+                    "Current EPC Band": "Unknown"
+                }
+            )
 
         final_missed_matches = pd.DataFrame(final_missed_matches)
 
@@ -1841,14 +1856,13 @@ def propsed_wave_3_sample():
         region_assets["Confidence Tier"] = region_assets["Confidence Tier"].fillna(
             region_assets["Confidence Tier_method3"]
         )
+        region_assets["Current EPC Band"] = np.where(
+            pd.isnull(region_assets["Current EPC Band"]),
+            region_assets["Current EPC Band_method3"], region_assets["Current EPC Band"]
+        )
 
         region_assets = region_assets.drop(columns=["Confidence Tier_method3"])
 
-        region_assets["Current EPC Band"] = np.where(
-            region_assets["Confidence Tier"] == "5 - no similar property, needs survey to confirm",
-            "Unknown", region_assets["Current EPC Band"]
-        )
-
         if pd.isnull(region_assets["Current EPC Band"]).sum():
             raise Exception("Something went wrong")