diff --git a/tracking_result.py b/tracking_result.py
new file mode 100644
index 0000000..5a3e64e
--- /dev/null
+++ b/tracking_result.py
@@ -0,0 +1,72 @@
+import matplotlib.pyplot as plt
+import pandas as pd 
+import numpy as np
+import numbers as nb
+import os 
+
+class TrackingResult():
+    
+    def __init__(self, results_file) -> None:
+        super().__init__()
+        if not os.path.exists(results_file):
+            raise ValueError("File %s does not exist!" % results_file)
+        self._file_name = results_file
+        
+        self._data_frame = pd.read_hdf(results_file)
+        self._level_shape = self._data_frame.columns.levshape
+        self._scorer = self._data_frame.columns.levels[0].values
+        self._bodyparts = self._data_frame.columns.levels[1].values if self._level_shape[1] > 0 else []
+        self._positions = self._data_frame.columns.levels[2].values if self._level_shape[2] > 0 else []
+
+        
+    @property
+    def filename(self):
+        return self._file_name
+    
+    @property
+    def dataframe(self):
+        return self._data_frame
+    
+    @property
+    def scorer(self):
+        return self._scorer
+    
+    @property
+    def bodyparts(self):
+        return self._bodyparts
+    
+    @property
+    def positions(self):
+        return self._positions
+    
+    def position_values(self, scorer=0, bodypart=0, framerate=30):
+        if  isinstance(scorer, nb.Number):
+            sc = self._scorer[scorer]
+        elif isinstance(scorer, str) and scorer in self._scorer:
+            sc = scorer
+        else:
+            raise ValueError("Scorer %s is not in dataframe!" % scorer)
+        if  isinstance(bodypart, nb.Number):
+            bp = self._bodyparts[bodypart]
+        elif isinstance(bodypart, str) and bodypart in self._bodyparts:
+            bp = bodypart
+        else:
+            raise ValueError("Bodypart %s is not in dataframe!" % bodypart)
+    
+        x = self._data_frame[sc][bp]["x"] if "x" in self._positions else []
+        y = self._data_frame[sc][bp]["y"] if "y" in self._positions else []
+        l = self._data_frame[sc][bp]["likelihood"] if "likelihood" in self._positions else []
+        time = np.arange(len(self._data_frame))/framerate
+        return time, x, y, l, bp
+    
+    def plot(self, scorer=0, bodypart=0, threshold=0.9, framerate=30):
+        t, x, y, l, name  = self.position_values(scorer=scorer, bodypart=bodypart, framerate=framerate)
+        plt.scatter(x[l > threshold], y[l > threshold], c=t[l > threshold], label=name)
+        plt.plot(x[l > threshold], y[l > threshold])
+        plt.xlabel("x position")
+        plt.ylabel("y position")
+        plt.gca().invert_yaxis()
+        bar = plt.colorbar()
+        bar.set_label("time [s]")
+        plt.legend()
+        plt.show()
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