Spaces:
Running
Running
| from cgi import test | |
| import xgboost as xgb | |
| import pandas as pd | |
| import pickle as pkl | |
| import numpy as np | |
| import os | |
| model = 'xgboost_ATS_no_odds_57.3%' | |
| current_directory = os.path.dirname(os.path.abspath(__file__)) | |
| parent_directory = os.path.dirname(current_directory) | |
| data_directory = os.path.join(parent_directory, 'Data') | |
| model_directory = os.path.join(parent_directory, 'Models') | |
| pickle_directory = os.path.join(parent_directory, 'Pickles') | |
| file_path = os.path.join(model_directory, f'{model}.json') | |
| xgb_ml = xgb.Booster() | |
| xgb_ml.load_model(file_path) | |
| file_path = os.path.join(pickle_directory, 'test_games_ATS_no_odds.pkl') | |
| with open(file_path,'rb') as f: | |
| test_games = pkl.load(f).tolist() | |
| file_path = os.path.join(data_directory, 'gbg_and_odds.csv') | |
| gbg_and_odds = pd.read_csv(file_path) | |
| test_data = gbg_and_odds.loc[gbg_and_odds['game_id'].isin(test_games)] | |
| test_data_matrix = xgb.DMatrix(test_data.drop(columns=['game_id','Home-Team-Win','Home-Team-Cover','Over','Season','home_team','away_team','game_date','Key','Home Score','Away Score','Home Odds Close','Away Odds Close','Home Winnings','Away Winnings','Away Odds','Home Odds']).astype(float).values) | |
| predicted_probas = xgb_ml.predict(test_data_matrix) | |
| predictions = np.argmax(predicted_probas, axis=1) | |
| test_data['predicted_proba'] = [i[1] for i in predicted_probas] | |
| test_data['prediction'] = predictions | |
| test_data['correct'] = test_data['Home-Team-Cover']==test_data['prediction'] | |
| print(test_data['predicted_proba']) | |
| print(test_data['correct'].mean()) | |
| bets = test_data.loc[(test_data['predicted_proba']>0.5) | (test_data['predicted_proba']<0.5)] | |
| bets['winnings'] = [0.91 if c==1 else -1 for c in bets['correct']] | |
| print('Actual') | |
| print(bets.loc[bets['Home-Team-Cover']==1].shape) | |
| print(bets.loc[bets['Home-Team-Cover']==0].shape) | |
| print(bets.loc[bets['Home-Team-Cover']==2].shape) | |
| print('Predicted') | |
| print(bets.loc[bets['prediction']==1].shape) | |
| print(bets.loc[bets['prediction']==0].shape) | |
| print(bets.loc[bets['prediction']==2].shape) | |
| import matplotlib.pyplot as plt | |
| fig = plt.figure(facecolor='black') | |
| ax = fig.add_subplot(1, 1, 1, facecolor='black') | |
| # Plot data with line color as RGB(0, 128, 0) | |
| ax.plot(bets['winnings'].cumsum().values*100, linewidth=3, color=(0/255, 128/255, 0/255)) | |
| # Set title and labels | |
| ax.set_title('MARCI 3.0 - Against the Spread', color='white') | |
| ax.set_xlabel('Games Bet On', color='white') | |
| ax.set_ylabel('Return (%)', color='white') | |
| # Change tick colors to white | |
| ax.tick_params(axis='x', colors='white') | |
| ax.tick_params(axis='y', colors='white') | |
| # Change axis edge colors | |
| ax.spines['bottom'].set_color('white') | |
| ax.spines['top'].set_color('white') | |
| ax.spines['left'].set_color('white') | |
| ax.spines['right'].set_color('white') | |
| plt.savefig(f'{model}_dark.png', facecolor='black') |