diff --git a/mlair/plotting/postprocessing_plotting.py b/mlair/plotting/postprocessing_plotting.py
index 55f74a1e943ad7ab3c56ebaa74e8ca038e3ced69..bf73f1858aba4749cb9e949c6f3d7df48536083c 100644
--- a/mlair/plotting/postprocessing_plotting.py
+++ b/mlair/plotting/postprocessing_plotting.py
@@ -146,8 +146,10 @@ class PlotOversamplingContingency(AbstractPlotClass):
             logging.info(f"{station}: load pred")
             predictions = [forecast_file.sel(type=self._model_name)]
             logging.info(f"{station}: load comp")
-            competitors = [self._load_competitors(station, [comp]).sel(type=comp) for comp in self._comp_names]
-            predictions.extend(competitors)
+            for comp in self._comp_names:
+                c = self._load_competitors(station, [comp])
+                if c 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):
diff --git a/run_with_oversampling.py b/run_with_oversampling.py
index 0effa8c5dafd645de18dc24a59d70728cf4f52fa..39cf7e12d6375cffbbdd9ea832be937c00c65c67 100644
--- a/run_with_oversampling.py
+++ b/run_with_oversampling.py
@@ -31,7 +31,7 @@ def main(parser_args):
         model=IntelliO3_ts_architecture, oversampling_method="bin_oversampling",
         evaluate_bootstraps=False,  # plot_list=["PlotCompetitiveSkillScore"],
         competitors=["IntelliO3"],
-        competitor_path=os.path.join(os.getcwd(), "data", "comp_test"),
+        competitor_path="/p/project/deepacf/intelliaq/gramlich1/mlair/competitors/o3",
         window_lead_time=1, oversampling_bins=10, oversampling_rates_cap=100,
         **parser_args.__dict__)
     workflow.run()