diff --git a/posthog/hogql_queries/experiments/test/test_experiment_trends_query_runner.py b/posthog/hogql_queries/experiments/test/test_experiment_trends_query_runner.py
index bba1366c33418..9ed6636bc2324 100644
--- a/posthog/hogql_queries/experiments/test/test_experiment_trends_query_runner.py
+++ b/posthog/hogql_queries/experiments/test/test_experiment_trends_query_runner.py
@@ -1522,6 +1522,221 @@ def test_query_runner_standard_flow_v2_stats(self):
         self.assertEqual(test_variant.count, 5.0)
         self.assertEqual(test_variant.exposure, 1.0)
 
+    @freeze_time("2020-01-01T12:00:00Z")
+    def test_query_runner_property_math_sum(self):
+        self._test_query_runner_property_math(
+            math="sum",
+            expected_control={
+                "count": 10,
+                "absolute_exposure": 5,
+                "data": [0.0, 0.0, 1.0, 3.0, 6.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0],
+            },
+            expected_test={
+                "count": 90,
+                "absolute_exposure": 10,
+                "data": [0.0, 0.0, 2.0, 6.0, 12.0, 20.0, 30.0, 42.0, 56.0, 72.0, 90.0, 90.0, 90.0, 90.0, 90.0],
+            },
+        )
+
+    @freeze_time("2020-01-01T12:00:00Z")
+    def test_query_runner_property_math_avg(self):
+        self._test_query_runner_property_math(
+            math="avg",
+            expected_control={
+                "count": 10,
+                "absolute_exposure": 5,
+                "data": [0.0, 0.0, 1.0, 3.0, 6.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0],
+            },
+            expected_test={
+                "count": 90,
+                "absolute_exposure": 10,
+                "data": [0.0, 0.0, 2.0, 6.0, 12.0, 20.0, 30.0, 42.0, 56.0, 72.0, 90.0, 90.0, 90.0, 90.0, 90.0],
+            },
+        )
+
+    @freeze_time("2020-01-01T12:00:00Z")
+    def test_query_runner_property_math_min(self):
+        self._test_query_runner_property_math(
+            math="min",
+            expected_control={
+                "count": 5,
+                "absolute_exposure": 5,
+                "data": [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0],
+            },
+            expected_test={
+                "count": 10,
+                "absolute_exposure": 10,
+                "data": [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 10.0, 10.0, 10.0, 10.0],
+            },
+        )
+
+    @freeze_time("2020-01-01T12:00:00Z")
+    def test_query_runner_property_math_max(self):
+        self._test_query_runner_property_math(
+            math="max",
+            expected_control={
+                "count": 5,
+                "absolute_exposure": 5,
+                "data": [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0],
+            },
+            expected_test={
+                "count": 10,
+                "absolute_exposure": 10,
+                "data": [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 10.0, 10.0, 10.0, 10.0],
+            },
+        )
+
+    @freeze_time("2020-01-01T12:00:00Z")
+    def test_query_runner_property_math_median(self):
+        self._test_query_runner_property_math(
+            math="median",
+            expected_control={
+                "count": 5,
+                "absolute_exposure": 5,
+                "data": [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0],
+            },
+            expected_test={
+                "count": 10,
+                "absolute_exposure": 10,
+                "data": [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 10.0, 10.0, 10.0, 10.0],
+            },
+        )
+
+    @freeze_time("2020-01-01T12:00:00Z")
+    def test_query_runner_property_math_p90(self):
+        self._test_query_runner_property_math(
+            math="p90",
+            expected_control={
+                "count": 5,
+                "absolute_exposure": 5,
+                "data": [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0],
+            },
+            expected_test={
+                "count": 10,
+                "absolute_exposure": 10,
+                "data": [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 10.0, 10.0, 10.0, 10.0],
+            },
+        )
+
+    @freeze_time("2020-01-01T12:00:00Z")
+    def test_query_runner_property_math_p95(self):
+        self._test_query_runner_property_math(
+            math="p95",
+            expected_control={
+                "count": 5,
+                "absolute_exposure": 5,
+                "data": [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0],
+            },
+            expected_test={
+                "count": 10,
+                "absolute_exposure": 10,
+                "data": [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 10.0, 10.0, 10.0, 10.0],
+            },
+        )
+
+    @freeze_time("2020-01-01T12:00:00Z")
+    def test_query_runner_property_math_p99(self):
+        self._test_query_runner_property_math(
+            math="p99",
+            expected_control={
+                "count": 5,
+                "absolute_exposure": 5,
+                "data": [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0],
+            },
+            expected_test={
+                "count": 10,
+                "absolute_exposure": 10,
+                "data": [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 10.0, 10.0, 10.0, 10.0],
+            },
+        )
+
+    def _test_query_runner_property_math(self, math, expected_control, expected_test):
+        feature_flag = self.create_feature_flag()
+        experiment = self.create_experiment(feature_flag=feature_flag, start_date=datetime(2020, 1, 1))
+
+        feature_flag_property = f"$feature/{feature_flag.key}"
+
+        # control values are 0, 1, 2, 3, 4
+        # test values are 0, 2, 4, 6, 8, 10, 12, 14, 16, 18
+
+        # Populate metric + exposure events
+        for variant, count in [("control", 5), ("test", 10)]:
+            for i in range(count):
+                _create_event(
+                    team=self.team,
+                    event="$feature_flag_called",
+                    distinct_id=f"user_{variant}_{i}",
+                    properties={
+                        "$feature_flag_response": variant,
+                        feature_flag_property: variant,
+                        "$feature_flag": feature_flag.key,
+                    },
+                    timestamp=datetime(2020, 1, i + 1),
+                )
+                _create_event(
+                    team=self.team,
+                    event="purchase",
+                    distinct_id=f"user_{variant}_{i}",
+                    properties={
+                        feature_flag_property: variant,
+                        "amount": i * (1 if variant == "control" else 2),
+                    },
+                    timestamp=datetime(2020, 1, i + 2),
+                )
+
+        count_query = TrendsQuery(
+            series=[
+                EventsNode(
+                    event="purchase",
+                    math=math,
+                    math_property="amount",
+                    math_property_type="event_properties",
+                )
+            ]
+        )
+        exposure_query = TrendsQuery(series=[EventsNode(event="$feature_flag_called")])
+        experiment_query = ExperimentTrendsQuery(
+            experiment_id=experiment.id,
+            kind="ExperimentTrendsQuery",
+            count_query=count_query,
+            exposure_query=exposure_query,
+        )
+
+        experiment.metrics = [{"type": "primary", "query": experiment_query.model_dump()}]
+        experiment.save()
+
+        query_runner = ExperimentTrendsQueryRunner(
+            query=ExperimentTrendsQuery(**experiment.metrics[0]["query"]), team=self.team
+        )
+
+        flush_persons_and_events()
+
+        result = query_runner.calculate()
+
+        trend_result = cast(ExperimentTrendsQueryResponse, result)
+
+        self.assertEqual(len(result.variants), 2)
+
+        control_result = next(variant for variant in trend_result.variants if variant.key == "control")
+        test_result = next(variant for variant in trend_result.variants if variant.key == "test")
+
+        control_insight = next(variant for variant in trend_result.insight if variant["breakdown_value"] == "control")
+        test_insight = next(variant for variant in trend_result.insight if variant["breakdown_value"] == "test")
+
+        self.assertEqual(control_result.count, expected_control["count"])
+        self.assertEqual(test_result.count, expected_test["count"])
+        self.assertEqual(control_result.absolute_exposure, expected_control["absolute_exposure"])
+        self.assertEqual(test_result.absolute_exposure, expected_test["absolute_exposure"])
+
+        self.assertEqual(
+            control_insight["data"],
+            expected_control["data"],
+        )
+        self.assertEqual(
+            test_insight["data"],
+            expected_test["data"],
+        )
+
     @freeze_time("2020-01-01T12:00:00Z")
     def test_validate_event_variants_no_events(self):
         feature_flag = self.create_feature_flag()