small data and model improvement

app/src/flask-server/modele/modele.py

@@ -15,7 +15,7 @@ def LogisticRegression_predict_proba(position_x, position_y, distance_to_goalM,
 #xgBoost
 def xgboost_predict_proba(minute=0, position_name='Center Forward', shot_body_part_name='Right Foot', 
                           shot_technique_name='Normal', shot_type_name='Open Play', shot_first_time=False, 
-                          shot_one_on_one=False, shot_aerial_won=False, shot_deflected=False, 
+                          shot_one_on_one=False, shot_aerial_won=False,
                           shot_open_goal=False, shot_follows_dribble=False, shot_redirect=False, x1=0.0, y1=0.0,
                           number_of_players_opponents=0, number_of_players_teammates=0, 
                           angle=0.0, distance=0.0, x_player_opponent_Goalkeeper=np.nan, 
@@ -34,13 +34,13 @@ def xgboost_predict_proba(minute=0, position_name='Center Forward', shot_body_pa
                           y_player_teammate_4=np.nan, y_player_teammate_5=np.nan, y_player_teammate_6=np.nan, 
                           y_player_teammate_7=np.nan, y_player_teammate_8=np.nan, y_player_teammate_9=np.nan, 
                           y_player_teammate_10=np.nan, x_player_opponent_7=np.nan, y_player_opponent_7=np.nan, 
-                          x_player_teammate_Goalkeeper=np.nan, y_player_teammate_Goalkeeper=np.nan, shot_kick_off=False):
+                          x_player_teammate_Goalkeeper=np.nan, y_player_teammate_Goalkeeper=np.nan):
       
    model = load('xgboost.joblib')
 
    X_new = pd.DataFrame(columns=['minute', 'position_name', 'shot_body_part_name', 'shot_technique_name',
       'shot_type_name', 'shot_first_time', 'shot_one_on_one',
-      'shot_aerial_won', 'shot_deflected', 'shot_open_goal',
+      'shot_aerial_won', 'shot_open_goal',
       'shot_follows_dribble', 'shot_redirect', 'x1', 'y1',
       'number_of_players_opponents', 'number_of_players_teammates',
       'angle', 'distance', 'x_player_opponent_Goalkeeper',
@@ -59,12 +59,11 @@ def xgboost_predict_proba(minute=0, position_name='Center Forward', shot_body_pa
       'y_player_teammate_4', 'y_player_teammate_5', 'y_player_teammate_6',
       'y_player_teammate_7', 'y_player_teammate_8', 'y_player_teammate_9',
       'y_player_teammate_10', 'x_player_opponent_7', 'y_player_opponent_7',
-      'x_player_teammate_Goalkeeper', 'y_player_teammate_Goalkeeper',
-      'shot_kick_off'])
+      'x_player_teammate_Goalkeeper', 'y_player_teammate_Goalkeeper'])
     
    X_new.loc[len(X_new.index)] = [minute, position_name, shot_body_part_name, shot_technique_name,
       shot_type_name, shot_first_time, shot_one_on_one,
-      shot_aerial_won, shot_deflected, shot_open_goal,
+      shot_aerial_won, shot_open_goal,
       shot_follows_dribble, shot_redirect, x1, y1,
       number_of_players_opponents, number_of_players_teammates,
       angle, distance, x_player_opponent_Goalkeeper,
@@ -83,8 +82,7 @@ def xgboost_predict_proba(minute=0, position_name='Center Forward', shot_body_pa
       y_player_teammate_4, y_player_teammate_5, y_player_teammate_6,
       y_player_teammate_7, y_player_teammate_8, y_player_teammate_9,
       y_player_teammate_10, x_player_opponent_7, y_player_opponent_7,
-      x_player_teammate_Goalkeeper, y_player_teammate_Goalkeeper,
-      shot_kick_off]
+      x_player_teammate_Goalkeeper, y_player_teammate_Goalkeeper]
     
    X_new[['position_name', 
            'shot_technique_name', 
@@ -103,30 +101,26 @@ def xgboost_predict_proba(minute=0, position_name='Center Forward', shot_body_pa
    X_new[['shot_first_time', 
            'shot_one_on_one', 
            'shot_aerial_won', 
-           'shot_deflected', 
            'shot_open_goal', 
            'shot_follows_dribble', 
-           'shot_redirect', 
-           'shot_kick_off']] = X_new[['shot_first_time', 
+           'shot_redirect']] = X_new[['shot_first_time', 
                                       'shot_one_on_one', 
                                       'shot_aerial_won', 
-                                      'shot_deflected', 
                                        'shot_open_goal', 
                                        'shot_follows_dribble', 
-                                       'shot_redirect', 
-                                       'shot_kick_off']].astype(bool)
+                                       'shot_redirect']].astype(bool)
    
    return model.predict_proba(X_new)[0][1].round(3)
 
 #XgBoost_2 
 
 def xgboost_predict_proba_v2(shooter,goalkeeper,teamMatesList,opponentsList, minute,position_name,shot_body_part_name,
-                             shot_technique_name,shot_type_name,shot_first_time,shot_aerial_won,shot_deflected,shot_open_goal,
-                             shot_follows_dribble,shot_redirect, shot_kick_off):
+                             shot_technique_name,shot_type_name,shot_first_time,shot_aerial_won,shot_open_goal,
+                             shot_follows_dribble,shot_redirect):
    model = load('xgboost.joblib')
    X_new = pd.DataFrame(columns=['minute', 'position_name', 'shot_body_part_name',
        'shot_technique_name','shot_type_name', 'shot_first_time',
-       'shot_one_on_one','shot_aerial_won', 'shot_deflected',
+       'shot_one_on_one','shot_aerial_won',
        'shot_open_goal','shot_follows_dribble', 'shot_redirect',
        'x1', 'y1','number_of_players_opponents',
        'number_of_players_teammates','angle', 'distance', 
@@ -146,8 +140,7 @@ def xgboost_predict_proba_v2(shooter,goalkeeper,teamMatesList,opponentsList, min
        'y_player_teammate_4', 'y_player_teammate_5', 'y_player_teammate_6',
        'y_player_teammate_7', 'y_player_teammate_8', 'y_player_teammate_9',
        'y_player_teammate_10', 'x_player_opponent_7', 'y_player_opponent_7',
-       'x_player_teammate_Goalkeeper', 'y_player_teammate_Goalkeeper',
-       'shot_kick_off'])
+       'x_player_teammate_Goalkeeper', 'y_player_teammate_Goalkeeper'])
    
   
    shooter = konwertujDoListy(shooter)
@@ -183,7 +176,7 @@ def xgboost_predict_proba_v2(shooter,goalkeeper,teamMatesList,opponentsList, min
    #Reszta Zawodnikow 
    X_new.loc[len(X_new.index)] = [minute, position_name, shot_body_part_name,
        shot_technique_name,shot_type_name, shot_first_time,
-       shot_one_on_one,shot_aerial_won, shot_deflected,
+       shot_one_on_one,shot_aerial_won,
        shot_open_goal,shot_follows_dribble, shot_redirect, 
        shooter[0], shooter[1],number_of_players_opponents, 
        number_of_players_teammates,angle, distance,
@@ -204,8 +197,7 @@ def xgboost_predict_proba_v2(shooter,goalkeeper,teamMatesList,opponentsList, min
        teamMatesList[0][1],teamMatesList[1][1],  teamMatesList[2][1],
        teamMatesList[4][1],teamMatesList[5][1], teamMatesList[6][1], teamMatesList[7][1],
        teamMatesList[8][1], teamMatesList[9][1],
-       x_player_teammate_Goalkeeper, y_player_teammate_Goalkeeper,
-       shot_kick_off]
+       x_player_teammate_Goalkeeper, y_player_teammate_Goalkeeper]
    
    categorical_columns = ['position_name', 'shot_technique_name', 'shot_type_name', 'number_of_players_opponents', 'number_of_players_teammates', 'shot_body_part_name']  # list all your object columns here
    # X_new = pd.get_dummies(X_new, columns=categorical_columns)

app/src/flask-server/server.py

@@ -164,11 +164,9 @@ def get_model():
                                      shot_first_time=shot_first_time, 
                                      shot_one_on_one=shot_one_on_one, 
                                      shot_aerial_won=shot_aerial_won, 
-                                     shot_deflected=False, 
                                      shot_open_goal=shot_open_goal, 
                                      shot_follows_dribble=shot_follows_dribble, 
                                      shot_redirect=shot_redirect,
-                                     shot_kick_off=False,  
                                      x1=shooter_x, y1=shooter_y,
                                      number_of_players_opponents=number_of_players_opponents, 
                                      number_of_players_teammates=number_of_players_teammates,