diff --git a/mlair/plotting/postprocessing_plotting.py b/mlair/plotting/postprocessing_plotting.py
index bf73f1858aba4749cb9e949c6f3d7df48536083c..da477718b77ee2e2b8cb20580b77f2ec8c1c3b7c 100644
--- a/mlair/plotting/postprocessing_plotting.py
+++ b/mlair/plotting/postprocessing_plotting.py
@@ -145,15 +145,15 @@ class PlotOversamplingContingency(AbstractPlotClass):
             obs = forecast_file.sel(type=self._obs_name)
             logging.info(f"{station}: load pred")
             predictions = [forecast_file.sel(type=self._model_name)]
-            logging.info(f"{station}: load comp")
+            logging.info(f"{station}: load comp, comp_list:{self._comp_names}")
             for comp in self._comp_names:
                 c = self._load_competitors(station, [comp])
                 if c is not None:
+                    logging.info(f"{station}: {comp} is not None")
                     predictions.append(c.sel(type=comp))
             logging.info(f"itearate over thresholds")
             for threshold in range(self._min_threshold, self._max_threshold):
-                for i, pred in enumerate(predictions):
-                    logging.info(i)
+                for pred in predictions:
                     ta, fa, fb, tb = self._single_contingency(obs, pred, threshold)
                     contingency_array.loc[dict(thresholds=threshold, contingency_cell="ta", type=pred.type.values)] = ta
                     contingency_array.loc[dict(thresholds=threshold, contingency_cell="fa", type=pred.type.values)] = fa