diff --git a/src/Solver/Mage.py b/src/Solver/Mage.py
index 60ef7132..242e7c73 100644
--- a/src/Solver/Mage.py
+++ b/src/Solver/Mage.py
@@ -1627,16 +1627,15 @@ class Mage8(Mage):
             res["q_min"] = q
             res["q_max"] = q
 
-            res["res_z_min"] = [(run_number, np.min(z, axis=0))]
-            res["res_z_mean"] = [(run_number, np.mean(z, axis=0))]
-            res["res_z_max"] = [(run_number, np.max(z, axis=0))]
+            res["res_z_min"] = []
+            res["res_z_mean"] = []
+            res["res_z_max"] = []
 
-            res["res_q_min"] = [(run_number, np.min(q, axis=0))]
-            res["res_q_mean"] = [(run_number, np.mean(q, axis=0))]
-            res["res_q_max"] = [(run_number, np.max(q, axis=0))]
+            res["res_q_min"] = []
+            res["res_q_mean"] = []
+            res["res_q_max"] = []
 
-            # FIXME: Keep all results ?
-            res["traces"] = [(run_number, tables)]
+            res["traces"] = []
         else:
             # Get mean results for Z and Q
             res["z_mean"] = (res["z_mean"] + z) / 2
@@ -1648,17 +1647,17 @@ class Mage8(Mage):
             res["q_min"] = np.minimum(q, res["q_min"])
             res["q_max"] = np.maximum(q, res["q_max"])
 
-            # Keep results min, mean and max
-            res["res_z_min"].append((run_number, np.min(z, axis=0)))
-            res["res_z_mean"].append((run_number, np.mean(z, axis=0)))
-            res["res_z_max"].append((run_number, np.max(z, axis=0)))
+        # Keep results min, mean and max
+        res["res_z_min"].append((run_number, np.min(z, axis=0)))
+        res["res_z_mean"].append((run_number, np.mean(z, axis=0)))
+        res["res_z_max"].append((run_number, np.max(z, axis=0)))
 
-            res["res_q_min"].append((run_number, np.min(q, axis=0)))
-            res["res_q_mean"].append((run_number, np.mean(q, axis=0)))
-            res["res_q_max"].append((run_number, np.max(q, axis=0)))
+        res["res_q_min"].append((run_number, np.min(q, axis=0)))
+        res["res_q_mean"].append((run_number, np.mean(q, axis=0)))
+        res["res_q_max"].append((run_number, np.max(q, axis=0)))
 
-            # FIXME: Keep all results ?
-            res["traces"].append((run_number, tables))
+        # FIXME: Keep all results ?
+        res["traces"].append((run_number, tables))
 
     @timer
     def results_ensemble(self, study, repertory,