diff --git a/timely_beliefs/beliefs/classes.py b/timely_beliefs/beliefs/classes.py
index 9715d1be..0b795e67 100644
--- a/timely_beliefs/beliefs/classes.py
+++ b/timely_beliefs/beliefs/classes.py
@@ -488,13 +488,10 @@ def apply_belief_timing_filters(q):
             q = q.join(source_class).filter(cls.source_id.in_([s.id for s in sources]))
 
         # Apply most recent beliefs filter as subquery
-        most_recent_beliefs_only_incompatible_criteria = (
+        most_recent_only_incompatible_criteria = (
             beliefs_before is not None or beliefs_after is not None
         ) and sensor.knowledge_horizon_fnc not in (ex_ante.__name__, ex_post.__name__)
-        if (
-            most_recent_beliefs_only
-            and not most_recent_beliefs_only_incompatible_criteria
-        ):
+        if most_recent_beliefs_only and not most_recent_only_incompatible_criteria:
             subq = select(
                 cls.event_start,
                 cls.source_id,
@@ -519,7 +516,7 @@ def apply_belief_timing_filters(q):
             )
 
         # Apply most recent events filter as subquery
-        if most_recent_events_only:
+        if most_recent_events_only and not most_recent_only_incompatible_criteria:
             subq_most_recent_events = select(
                 cls.source_id,
                 func.max(cls.event_start).label("most_recent_event_start"),
@@ -576,8 +573,10 @@ def apply_belief_timing_filters(q):
         if beliefs_before is not None:
             df = df[df.index.get_level_values("belief_time") <= beliefs_before]
 
-        # Select most recent beliefs using postprocessing in case of incompatible search criteria
-        if most_recent_beliefs_only and most_recent_beliefs_only_incompatible_criteria:
+        # Select most recent events/beliefs using postprocessing in case of incompatible search criteria
+        if most_recent_events_only and most_recent_only_incompatible_criteria:
+            df = df[df.index.get_level_values("event_start") == df.event_starts.max()]
+        if most_recent_beliefs_only and most_recent_only_incompatible_criteria:
             df = belief_utils.select_most_recent_belief(df)
 
         # Convert timezone of beliefs and events to sensor timezone