diff --git a/src/oxonfair/learners/fair.py b/src/oxonfair/learners/fair.py
index 16ad4a9..342435e 100644
--- a/src/oxonfair/learners/fair.py
+++ b/src/oxonfair/learners/fair.py
@@ -8,7 +8,7 @@
 from sklearn.preprocessing import OneHotEncoder
 from ..utils import group_metrics
 from .. utils.scipy_metrics_cont_wrapper import ScorerRequiresContPred
-from ..utils.group_metric_classes import BaseGroupMetric
+from ..utils.group_metric_classes import BaseGroupMetric, Overall
 
 from ..utils import performance as perf
 from . import efficient_compute, fair_frontier
@@ -1093,6 +1093,9 @@ def fix_groups(metric, groups):
 
     groups = groups_to_masks(groups)
 
+    if isinstance(metric, Overall):  # Performance hack. If metric is of type overall, groups don't matter -- assign all groups to 1.
+        groups = np.ones(groups.shape[0])
+
     def new_metric(y_true: np.ndarray, y_pred: np.ndarray) -> np.ndarray:
         return metric(y_true, y_pred, groups)
     return new_metric
@@ -1146,6 +1149,10 @@ def fix_groups_and_conditioning(metric, groups, conditioning_factor, y_true):
     weights = metric.cond_weights(conditioning_factor, groups, y_true)
     groups = groups_to_masks(groups)
 
+    if isinstance(metric, Overall):  # Performance hack. If metric is of type overall, groups don't matter -- assign all groups to 1.
+        groups = np.ones(groups.shape[0])
+
+
     def new_metric(y_true: np.ndarray, y_pred: np.ndarray) -> np.ndarray:
         return metric(y_true, y_pred, groups, weights)
     return new_metric