diff --git a/voting_lib/voting_analysis.py b/voting_lib/voting_analysis.py
index 254a0ff..624c388 100644
--- a/voting_lib/voting_analysis.py
+++ b/voting_lib/voting_analysis.py
@@ -34,13 +34,16 @@ def predict(model, data, grid_h, grid_w, comparison_data=pd.DataFrame()):
     prediction = model.predict(X)
     print(f'prediction: {prediction}')
 
+    # Plot hit map
+    plot_hits(prediction, grid_w, grid_h)
+    
     # converting to x and y coordinates
     ys, xs = np.unravel_index(np.argmax(prediction, axis=1), (grid_h, grid_w))
 
     # plotting mps
     party_affiliation = data[:,1]
     plot_mps(data[:,0], xs, ys, party_affiliation, randomize_positions=True)
-    plt.show()
+    plt.show()    
 
     # calculating party positions based on mps
     party_pos = calc_party_pos(np.column_stack((xs, ys)), party_affiliation)
@@ -51,7 +54,7 @@ def predict(model, data, grid_h, grid_w, comparison_data=pd.DataFrame()):
     plt.figure()
     weight = model.weight.reshape((model.n_inputs, grid_h, grid_w))
     heatmap = compute_heatmap(weight, grid_h, grid_w)
-    plt.imshow(heatmap, interpolation='nearest',zorder=1)
+    plt.imshow(heatmap, cmap ='Blues', interpolation='nearest',zorder=1)
     plt.axis('off')
     plt.colorbar()
     
@@ -238,7 +241,11 @@ def plot_party_distances(distances):
     ax.tick_params(axis="x", bottom=False, top=True, labelbottom=False, labeltop=True)
     sn.heatmap(distances, cmap='Oranges', annot=True)
 
-
+def plot_hits(prediction, grid_w, grid_h):    
+    hits = (prediction.sum(axis=0)).reshape(grid_w, grid_h)
+    plt.figure()
+    sn.heatmap(hits, annot=True, xticklabels=False, yticklabels=False, cbar=False)
+    
 def normalize_df(dataframe):
     df = dataframe.copy(deep=True)
     df = df - np.min(df.to_numpy())