diff --git a/mlair/plotting/postprocessing_plotting.py b/mlair/plotting/postprocessing_plotting.py
index ed114830cadaf1509c1131299da19313e9b54901..6801addb7276d2638f44dd29fd7d521f6efa46a5 100644
--- a/mlair/plotting/postprocessing_plotting.py
+++ b/mlair/plotting/postprocessing_plotting.py
@@ -35,7 +35,7 @@ class PlotOversamplingContingency(AbstractPlotClass):
     def __init__(self, station_names, file_path, comp_path, file_name, plot_folder: str = ".", model_name: str = "nn",
                  obs_name: str = "obs", comp_names: str = "IntelliO3",
                  plot_names=["oversampling_threat_score", "oversampling_hit_rate", "oversampling_false_alarm_rate",
-                             "oversampling_all_scores"]):
+                             "oversampling_bias", "oversampling_all_scores"]):
 
         super().__init__(plot_folder, plot_names[0])
         self._stations = station_names
@@ -50,7 +50,7 @@ class PlotOversamplingContingency(AbstractPlotClass):
         self._plot_names = plot_names
         self._min_threshold, self._max_threshold = self._min_max_threshold()
         contingency_array = self._calculate_contingencies()
-        self._scores = ["ts", "h", "f"]
+        self._scores = ["ts", "h", "f", "b"]
         score_array = self._calculate_all_scores(contingency_array)
         self._plot_counter = 0
 
@@ -60,6 +60,8 @@ class PlotOversamplingContingency(AbstractPlotClass):
         self._save()
         self._plot(score_array, "f")
         self._save()
+        self._plot(score_array, "b")
+        self._save()
         self._plot(score_array, "all_scores")
         self._save()
 
@@ -70,6 +72,7 @@ class PlotOversamplingContingency(AbstractPlotClass):
         else:
             for type in data.type.values.tolist():
                 plt.plot(range(self._min_threshold, self._max_threshold), data.loc[dict(type=type, scores=score)], label=type)
+        plt.title(self._plot_names[self._plot_counter][13:])
         plt.legend()
         self.plot_name = self._plot_names[self._plot_counter]
         self._plot_counter = self._plot_counter + 1
@@ -132,7 +135,7 @@ class PlotOversamplingContingency(AbstractPlotClass):
         contingency_cell = ["ta", "fa", "fb", "tb"]
         contingency_array = xr.DataArray(dims=["thresholds", "contingency_cell", "type"],
                                          coords=[thresholds, contingency_cell, self._all_names])
-        contingency_array = contingency_array.fillna(0)
+        contingency_array = contingency_array.fillna(1)
         for station in self._stations:
             file = os.path.join(self._file_path, self._file_name % station)
             forecast_file = xr.open_dataarray(file)
@@ -193,14 +196,19 @@ class PlotOversamplingContingency(AbstractPlotClass):
                 score_value = true_above/(true_above + false_above + false_below)
         elif score == "h":
             if (true_above + false_below) == 0:
-                score_value = 1
+                score_value = 0
             else:
                 score_value = true_above/(true_above + false_below)
         elif score == "f":
             if (false_above + true_below) == 0:
-                score_value = 1
+                score_value = 0
             else:
                 score_value = false_above/(false_above + true_below)
+        elif score == "b":
+            if (true_above + false_below) == 0:
+                score_value = 0
+            else:
+                score_value = (true_above + false_above)/(true_above + false_below)
         return score_value