diff --git a/msmarco-v2-vector/track.py b/msmarco-v2-vector/track.py
index a4753d170..f846aa16b 100644
--- a/msmarco-v2-vector/track.py
+++ b/msmarco-v2-vector/track.py
@@ -98,7 +98,7 @@ def params(self):
         num_candidates = self._params.get("num-candidates", 50)
         query_vec = self._queries[self._iters]
         knn_query = {"field": "emb", "query_vector": query_vec, "k": top_k, "num_candidates": num_candidates}
-        if self._params.get("oversample-rescore", 0) > 0:
+        if self._params.get("oversample-rescore", -1) >= 0:
             knn_query["rescore_vector"] = {"oversample": self._params.get("oversample-rescore")}
         if "filter" in self._params:
             knn_query["filter"] = self._params["filter"]
@@ -136,7 +136,7 @@ def params(self):
             "cache": self._params.get("cache", False),
             "size": self._params.get("k", 10),
             "num_candidates": self._params.get("num-candidates", 100),
-            "oversample_rescore": self._params.get("oversample-rescore", 0),
+            "oversample_rescore": self._params.get("oversample-rescore", -1),
         }
 
 
@@ -161,7 +161,7 @@ async def __call__(self, es, params):
                 query_id = query["query_id"]
 
                 knn_query = {"field": "emb", "query_vector": query["emb"], "k": top_k, "num_candidates": num_candidates}
-                if params["oversample_rescore"] > 0:
+                if params["oversample_rescore"] >= 0:
                     knn_query["rescore_vector"] = {"oversample": params["oversample_rescore"]}
                 body = {
                     "knn": knn_query,
diff --git a/openai_vector/track.py b/openai_vector/track.py
index b1ae8c849..7e33a9e26 100644
--- a/openai_vector/track.py
+++ b/openai_vector/track.py
@@ -47,7 +47,7 @@ def partition(self, partition_index, total_partitions):
     def params(self):
         result = {"index": self._index_name, "cache": self._params.get("cache", False), "size": self._params.get("k", 10)}
         num_candidates = self._params.get("num-candidates", 50)
-        oversample = self._params.get("oversample", 0)
+        oversample = self._params.get("oversample", -1)
         query_vec = self._queries[self._iters]
         knn_query = {
             "knn": {
@@ -59,7 +59,7 @@ def params(self):
         }
         if "filter" in self._params:
             knn_query["knn"]["filter"] = self._params["filter"]
-        if oversample > 0:
+        if oversample >= 0:
             knn_query["knn"]["rescore_vector"] = {"oversample": oversample}
         result["body"] = {"query": knn_query, "_source": False}
         self._iters += 1
@@ -113,7 +113,7 @@ def params(self):
             "cache": self._params.get("cache", False),
             "size": self._params.get("k", 10),
             "num_candidates": self._params.get("num-candidates", 50),
-            "oversample": self._params.get("oversample", 0),
+            "oversample": self._params.get("oversample", -1),
             "knn_vector_store": KnnVectorStore(),
         }
 
@@ -130,7 +130,7 @@ def get_knn_query(self, query_vec, k, num_candidates, oversample):
                 "num_candidates": num_candidates,
             }
         }
-        if oversample > 0:
+        if oversample >= 0:
             knn_query["knn"]["rescore_vector"] = {"oversample": oversample}
         return {"query": knn_query, "_source": False}