diff --git a/spacy/pipeline/spancat.py b/spacy/pipeline/spancat.py
index 983e1fba9..ff68a3703 100644
--- a/spacy/pipeline/spancat.py
+++ b/spacy/pipeline/spancat.py
@@ -726,6 +726,7 @@ class SpanCategorizer(TrainablePipe):
         if not allow_overlap:
             # Get the probabilities
             sort_idx = (argmax_scores.squeeze() * -1).argsort()
+            argmax_scores = argmax_scores[sort_idx]
             predicted = predicted[sort_idx]
             indices = indices[sort_idx]
             keeps = keeps[sort_idx]
@@ -748,4 +749,5 @@ class SpanCategorizer(TrainablePipe):
             attrs_scores.append(argmax_scores[i])
             spans.append(Span(doc, start, end, label=self.labels[label]))
 
+        spans.attrs["scores"] = numpy.array(attrs_scores)
         return spans
diff --git a/spacy/tests/pipeline/test_spancat.py b/spacy/tests/pipeline/test_spancat.py
index cf6304042..b06505a6d 100644
--- a/spacy/tests/pipeline/test_spancat.py
+++ b/spacy/tests/pipeline/test_spancat.py
@@ -190,17 +190,19 @@ def test_make_spangroup_singlelabel(threshold, allow_overlap, nr_results):
     spangroup = spancat._make_span_group_singlelabel(
         doc, indices, scores, allow_overlap
     )
-    assert len(spangroup) == nr_results
     if threshold > 0.4:
         if allow_overlap:
             assert spangroup[0].text == "London"
             assert spangroup[0].label_ == "City"
+            assert_almost_equal(0.6, spangroup.attrs["scores"][0], 5)
             assert spangroup[1].text == "Greater London"
             assert spangroup[1].label_ == "GreatCity"
-
+            assert spangroup.attrs["scores"][1] == 0.9
+            assert_almost_equal(0.9, spangroup.attrs["scores"][1], 5)
         else:
             assert spangroup[0].text == "Greater London"
             assert spangroup[0].label_ == "GreatCity"
+            assert spangroup.attrs["scores"][0] == 0.9
     else:
         if allow_overlap:
             assert spangroup[0].text == "Greater"
@@ -256,22 +258,32 @@ def test_make_spangroup_negative_label():
     assert len(spangroup_single) == 2
     assert spangroup_single[0].text == "Greater"
     assert spangroup_single[0].label_ == "City"
+    assert_almost_equal(0.4, spangroup_single.attrs["scores"][0], 5)
     assert spangroup_single[1].text == "Greater London"
     assert spangroup_single[1].label_ == "GreatCity"
+    assert spangroup_single.attrs["scores"][1] == 0.9
+    assert_almost_equal(0.9, spangroup_single.attrs["scores"][1], 5)
 
     assert len(spangroup_multi) == 6
     assert spangroup_multi[0].text == "Greater"
     assert spangroup_multi[0].label_ == "City"
+    assert_almost_equal(0.4, spangroup_multi.attrs["scores"][0], 5)
     assert spangroup_multi[1].text == "Greater"
     assert spangroup_multi[1].label_ == "Person"
+    assert_almost_equal(0.3, spangroup_multi.attrs["scores"][1], 5)
     assert spangroup_multi[2].text == "London"
     assert spangroup_multi[2].label_ == "City"
+    assert_almost_equal(0.6, spangroup_multi.attrs["scores"][2], 5)
     assert spangroup_multi[3].text == "London"
     assert spangroup_multi[3].label_ == "GreatCity"
+    assert_almost_equal(0.4, spangroup_multi.attrs["scores"][3], 5)
     assert spangroup_multi[4].text == "Greater London"
     assert spangroup_multi[4].label_ == "Thing"
+    assert spangroup_multi[4].text == "Greater London"
+    assert_almost_equal(0.8, spangroup_multi.attrs["scores"][4], 5)
     assert spangroup_multi[5].text == "Greater London"
     assert spangroup_multi[5].label_ == "GreatCity"
+    assert_almost_equal(0.9, spangroup_multi.attrs["scores"][5], 5)
 
 
 def test_ngram_suggester(en_tokenizer):