diff --git a/rslib/src/revlog/mod.rs b/rslib/src/revlog/mod.rs
index 2155bfcdc..2cd734b0a 100644
--- a/rslib/src/revlog/mod.rs
+++ b/rslib/src/revlog/mod.rs
@@ -85,6 +85,13 @@ impl RevlogEntry {
         .unwrap()
     }
 
+    /// Returns true if this entry represents a reset operation.
+    /// These entries are created when a card is reset using
+    /// [`Collection::reschedule_cards_as_new`].
+    pub(crate) fn is_reset(&self) -> bool {
+        self.review_kind == RevlogReviewKind::Manual && self.ease_factor == 0
+    }
+
     /// Returns true if the review entry is not manually rescheduled and not
     /// cramming. Used to filter out entries that shouldn't be considered
     /// for statistics and scheduling.
diff --git a/rslib/src/scheduler/fsrs/memory_state.rs b/rslib/src/scheduler/fsrs/memory_state.rs
index 28b8fd636..062f5bcca 100644
--- a/rslib/src/scheduler/fsrs/memory_state.rs
+++ b/rslib/src/scheduler/fsrs/memory_state.rs
@@ -325,6 +325,8 @@ pub(crate) fn get_last_revlog_info(revlogs: &[RevlogEntry]) -> HashMap<CardId, L
             for e in group.into_iter() {
                 if e.has_rating_and_affects_scheduling() {
                     last_reviewed_at = Some(e.id.as_secs());
+                } else if e.is_reset() {
+                    last_reviewed_at = None;
                 }
             }
             out.insert(card_id, LastRevlogInfo { last_reviewed_at });
diff --git a/rslib/src/scheduler/fsrs/params.rs b/rslib/src/scheduler/fsrs/params.rs
index 63bdebe79..7d556367b 100644
--- a/rslib/src/scheduler/fsrs/params.rs
+++ b/rslib/src/scheduler/fsrs/params.rs
@@ -409,10 +409,7 @@ pub(crate) fn reviews_for_fsrs(
         if user_graded && entry.review_kind == RevlogReviewKind::Learning {
             first_of_last_learn_entries = Some(index);
             revlogs_complete = true;
-        } else if matches!(
-            (entry.review_kind, entry.ease_factor),
-            (RevlogReviewKind::Manual, 0)
-        ) {
+        } else if entry.is_reset() {
             // Ignore entries prior to a `Reset` if a learning step has come after,
             // but consider revlogs complete.
             if first_of_last_learn_entries.is_some() {