Update app.py

app.py

@@ -84,6 +84,8 @@ model = joblib.load('joblib_model/tjstuff_model_20240318.joblib')
 y_pred_mean = 0.0011434511
 y_pred_std = 0.006554768
 
+xwoba_model = joblib.load('joblib_model/xwoba_model.joblib')
+
 features = ['start_speed','spin_rate','extension','ivb','hb','x0','z0','fb_max_velo_diff','fb_max_ivb_diff','fb_max_hb_diff']
 
 targets = ['delta_run_exp_mean']
@@ -93,6 +95,12 @@ df_2024_update['y_pred'] = model.predict(df_2024_update[features])
 
 df_2024_update['tj_stuff_plus'] = 100 + 10*((-df_2024_update.y_pred +y_pred_mean) / y_pred_std)
 
+df_2024_update['woba_pred'] = np.nan
+
+df_2024_update.loc[df_2024_update[['launch_angle','launch_speed']].isnull().sum(axis=1)==0,'woba_pred']  = [sum(x) for x in xwoba_model.predict_proba(df_2024_update.loc[df_2024_update[['launch_angle','launch_speed']].isnull().sum(axis=1)==0][['launch_angle','launch_speed']]) * ([0, 0.883,1.244,1.569,2.004])]
+
+
+
 team_logos = pd.read_csv('team_logos.csv')
 
 mlb_stats = MLB_Scrape()