diff --git a/app/comp/moy_ue.py b/app/comp/moy_ue.py
index b0a534e51..e4aac3353 100644
--- a/app/comp/moy_ue.py
+++ b/app/comp/moy_ue.py
@@ -38,8 +38,8 @@ from app.comp import moy_mod
 from app.models.formsemestre import FormSemestre
 from app.scodoc import sco_codes_parcours
 from app.scodoc import sco_preferences
-from app.scodoc.sco_codes_parcours import UE_SPORT
-from app.scodoc.sco_utils import ModuleType
+from app.scodoc.sco_codes_parcours import NOTES_TOLERANCE, UE_SPORT
+from app.scodoc.sco_utils import NOTES_PRECISION, ModuleType
 
 
 def df_load_module_coefs(formation_id: int, semestre_idx: int = None) -> pd.DataFrame:
@@ -358,10 +358,12 @@ def compute_ue_moys_classic(
     )
     # nb_ue x nb_etuds x nb_mods : coefs prenant en compte NaN et inscriptions
     coefs = (modimpl_coefs_etuds_no_nan_stacked * ue_modules).swapaxes(1, 2)
-    with np.errstate(invalid="ignore"):  # ignore les 0/0 (-> NaN)
-        etud_moy_ue = (
-            np.sum(coefs * sem_matrix_inscrits, axis=2) / np.sum(coefs, axis=2)
-        ).T
+    # Ici c'est une division apr un scalaire, pas NumPy: il faut tester
+    sum_coefs = np.sum(coefs, axis=2)
+    if abs(sum_coefs) > NOTES_PRECISION:
+        etud_moy_ue = (np.sum(coefs * sem_matrix_inscrits, axis=2) / sum_coefs).T
+    else:
+        etud_moy_ue = np.nan
     etud_moy_ue_df = pd.DataFrame(
         etud_moy_ue, index=modimpl_inscr_df.index, columns=[ue.id for ue in ues]
     )