api.update_with_media(filepath, status=message)
def write_to_google_sheet(row):
# use creds to create a client to interact with the Google Drive API
scope = ['https://spreadsheets.google.com/feeds',
'https://www.googleapis.com/auth/drive']
credentials = ServiceAccountCredentials.from_json_keyfile_name('./client_secret.json', scope)
client = gspread.authorize(credentials)
sheet = client.open("2017-2018-PL-tips").sheet1
sheet.append_row(row)
if __name__ == '__main__':
data = read_player_data(season='2017-2018')
cached_players = {}
for gui, name in data.items():
if 'pereira' in name['name'] and name['general position'] == 'goalkeeper':
gui_to_delete = gui
del data[gui_to_delete]
matches = get_lineups_from_flashscores()
for match in matches:
player_home_team = constants.FLASH_SCORES_TEAM_TO_PLAYER_RATINGS[match['home_team']]
player_away_team = constants.FLASH_SCORES_TEAM_TO_PLAYER_RATINGS[match['away_team']]
len(midfield))
assert len(
attack) <= 4, "No more than 4 attackers allowed, there is {}".format(
len(attack))
defence = defence + [0] * (6 - len(defence))
midfield = midfield + [0] * (7 - len(midfield))
attack = attack + [0] * (4 - len(attack))
return goalkeeper + defence + midfield + attack
if __name__ == '__main__':
errors = []
data = read_player_data()
match_data = read_match_data(league='SP1', season='2013-2014')
football_data = read_all_football_data(league='SP1')
match_data = assign_odds_to_match(match_data, football_data)
feature_vectors = []
targets = []
errors = []
cached_players = {}
for i, test_match in enumerate(reversed(match_data)):
def main():
bet_tracker = BetTracker()
league = 'E0'
match_data = read_match_data(season='2016-2017', league=league)
match_data = assign_odds_to_match(match_data, read_all_football_data(league=league))
player_data = read_player_data(season='2016-2017')
net = NeuralNet()
bank = [100]
all_odds = []
errors = []
cached_players = {}
feature_vectors = []
for match in match_data:
try:
home_players_matched, cached_players = match_lineups_to_fifa_players(match['info']['home lineup names'],
match['info']['home lineup raw names'],
match['info']['home lineup numbers'],
match['info'][
'home lineup nationalities'],
constants.LINEUP_TO_PLAYER_TEAM_MAPPINGS[
'ALL'][
match['info']['home team']],
match['info']['season'],
player_data, cached_players)
away_players_matched, cached_players = match_lineups_to_fifa_players(match['info']['away lineup names'],
match['info']['away lineup raw names'],
match['info']['away lineup numbers'],
match['info'][
'away lineup nationalities'],
constants.LINEUP_TO_PLAYER_TEAM_MAPPINGS[
'ALL'][
match['info']['away team']],
match['info']['season'],
player_data, cached_players)
home_feature_vector = create_feature_vector_from_players(home_players_matched)
away_feature_vector = create_feature_vector_from_players(away_players_matched)
feature_vector = np.array(home_feature_vector + away_feature_vector).reshape(-1, 36)
feature_vectors.append(normalise_features(feature_vector))
except Exception as exception:
print(match['info']['date'], match['info']['home team'], match['info']['away team'])
print(exception)
errors.append(match['match number'])
feature_vectors = np.vstack((x for x in feature_vectors))
probabilities = net.predict(feature_vectors, model_name='./models/' + league + '/deep')
match_data = [match for match in match_data if match['match number'] not in errors]
for match, probability in zip(match_data, probabilities):
# print(match['info']['date'], match['info']['home team'], match['info']['away team'])
pred_home_odds, pred_draw_odds, pred_away_odds = [1 / x for x in probability]
home_odds, draw_odds, away_odds = match['info']['home odds'], match['info']['draw odds'], match['info'][
'away odds']
all_odds.append((pred_home_odds, home_odds))
all_odds.append((pred_away_odds, away_odds))
if pred_home_odds < home_odds < 3.2 and 0.02 <= probability[0] - 1 / home_odds:
stake = calculate_stake(home_odds, probability=1 / pred_home_odds, method='kelly',
constant_profit=20) * bet_tracker.bankroll
profit = stake * home_odds - stake
bet = Bet(true_odds=home_odds, predicted_odds=pred_home_odds, stake=stake, profit=profit, match=match,
type='home')
bet_tracker.make_bet(bet)
if match['info']['home goals'] > match['info']['away goals']:
bet_tracker.bet_won()
else:
bet_tracker.bet_lost()
bank.append(bet_tracker.bankroll)
elif pred_away_odds < away_odds < 3.2 and 0.02 <= probability[2] - 1 / away_odds:
stake = calculate_stake(away_odds, probability=1 / pred_away_odds, method='kelly',
constant_profit=20) * bet_tracker.bankroll
profit = stake * away_odds - stake
bet = Bet(true_odds=away_odds, predicted_odds=pred_away_odds, stake=stake, profit=profit, match=match,
type='away')
bet_tracker.make_bet(bet)
if match['info']['home goals'] < match['info']['away goals']:
bet_tracker.bet_won()
else:
bet_tracker.bet_lost()
bank.append(bet_tracker.bankroll)
return bet_tracker, bank, all_odds