Merhabalar İddaa Programı Hazırlayacağım Kalıp Temel bir kod yapısına ihtiyacım var Yardımcı Olabilecek var ise eğer sevinirim Şimdiden Teşekkürler.
Konu hakkında bilgim yok ancak internette yapmak istediğinizi arayınca bir kaç sayfa buldum. Aşağıdaki sitede incelenebilir kodlar mevcut.
Verileri csv dosyasında olan bir siteden futbol verileri indirdim. Yukarıda verilen ilk sitede gösterilen kodlarda csv modülü kullanılıyor. Bir tane dosya buldum, indirdim ve yukarıdaki sitede gösterilen programı çalıştırmayı denedim. Önce bir hata aldım. Kodlarda tau ile işlem yapılıyor ama tau tanımlanmamış.
tanberk@kutlu:~$ python underdogs.py
Traceback (most recent call last):
File "underdogs.py", line 88, in <module>
prob = tau * poisson(i, home_team_exp) * poisson(j, away_team_exp)
NameError: name 'tau' is not definedSonra sayfada paylaşılan parçalı kodlara baktım. Bütün kodlar olarak sunulan kodların 88. satırı hata veriyordu. Ancak parça parça verilen kodlarda tau tanımlanmamıştı. O parçaları birleştirdim, programı tekrar çalıştırdım, hata almadım. Bir de aşağıdaki gibi bir çıktı aldım.
tanberk@kutlu:~$ python underdogs.py
Bet on 'Draw' (EV = 2.3)
-1
Bet on 'Draw' (EV = 2.4)
1.4
Bet on 'Burnley' (EV = 10.2400368429)
0.4
Bet on 'Draw' (EV = 2.25)
-0.6
Bet on 'Draw' (EV = 1.5751560882)
5.4
Bet on 'Draw' (EV = 5.0)
4.4
Bet on 'West Brom' (EV = 0.504446664819)
3.4
Bet on 'Chelsea' (EV = 0.0901819574665)
2.4
Bet on 'Man United' (EV = 0.290790203163)
2.76
Bet on 'Draw' (EV = 2.25)
5.01
Bet on 'Draw' (EV = 3.0)
4.01
Bet on 'Leicester' (EV = 1.48319223645)
3.01
Bet on 'Man City' (EV = 0.0819859055926)
3.15
Bet on 'Draw' (EV = 2.8)
2.15
Bet on 'Draw' (EV = 0.508305708801)
1.15
Bet on 'Watford' (EV = 1.05439145406)
3.4
Bet on 'Draw' (EV = 0.59291798027)
2.4
Bet on 'Draw' (EV = 2.1)
1.4
Bet on 'Draw' (EV = 4.5)
0.4
Bet on 'Leicester' (EV = 0.580301118507)
-0.6
Bet on 'Draw' (EV = 2.3)
-1.6
Bet on 'Draw' (EV = 3.75)
-2.6
Bet on 'Man United' (EV = 0.139055978428)
-2.43
Bet on 'Draw' (EV = 2.2)
-3.43
Bet on 'Draw' (EV = 2.2)
-1.23
Bet on 'Draw' (EV = 0.287578044099)
-2.23
Bet on 'Draw' (EV = 1.39121636761)
-3.23
Bet on 'Draw' (EV = 2.6)
-4.23
Bet on 'Draw' (EV = 2.8)
-1.43
Çalışır durumda olan kodlar:
import csv, math, ast, numpy as np
def poisson(actual, mean):
return math.pow(mean, actual) * math.exp(-mean) / math.factorial(actual)
csvFile = '20152016.csv'
team_list = []
k = open('team_list.txt', 'w')
k.write("""{
""")
csvRead = csv.reader(open(csvFile))
next(csvRead)
for row in csvRead:
if row[2] not in team_list:
team_list.append(row[2])
if row[3] not in team_list:
team_list.append(row[3])
team_list.sort()
for team in team_list:
k.write(""" '%s': {'home_goals': 0, 'away_goals': 0, 'home_conceded': 0, 'away_conceded': 0, 'home_games': 0, 'away_games': 0, 'alpha_h': 0, 'beta_h': 0, 'alpha_a': 0, 'beta_a': 0},
""" % (team))
k.write("}")
k.close()
s = open('team_list.txt', 'r').read()
dict = ast.literal_eval(s)
GAMES_PLAYED = 0
WEEKS_WAIT = 4
TOTAL_VALUE = 0
csvRead = csv.reader(open(csvFile))
next(csvRead)
for game in csvRead:
home_team = game[2]
away_team = game[3]
home_goals = int(game[4])
away_goals = int(game[5])
home_win_prob = 0
draw_win_prob = 0
away_win_prob = 0
curr_home_goals = 0
curr_away_goals = 0
avg_home_goals = 1
avg_away_goals = 1
team_bet = ''
ev_bet = ''
for key, value in dict.items():
curr_home_goals += dict[key]['home_goals']
curr_away_goals += dict[key]['away_goals']
if GAMES_PLAYED > (WEEKS_WAIT * 10):
avg_home_goals = curr_home_goals / (GAMES_PLAYED)
avg_away_goals = curr_away_goals / (GAMES_PLAYED)
if GAMES_PLAYED > (WEEKS_WAIT * 10):
home_team_a = (dict[home_team]['alpha_h'] + dict[home_team]['alpha_a']) / 2
away_team_a = (dict[away_team]['alpha_h'] + dict[away_team]['alpha_a']) / 2
home_team_d = (dict[home_team]['beta_h'] + dict[home_team]['beta_a']) / 2
away_team_d = (dict[away_team]['beta_h'] + dict[away_team]['beta_a']) / 2
home_team_exp = avg_home_goals * home_team_a * away_team_d
away_team_exp = avg_away_goals * away_team_a * home_team_d
l = open('poisson.txt', 'w')
for i in range(10):
for j in range(10):
prob = poisson(i, home_team_exp) * poisson(j, away_team_exp)
l.write("Prob%s%s = %s\n" % (i, j, prob))
l.close()
with open('poisson.txt') as f:
for line in f:
home_goals_m = int(line.split(' = ')[0][4])
away_goals_m = int(line.split(' = ')[0][5])
prob = float(line.split(' = ')[1])
if home_goals_m > away_goals_m:
home_win_prob += prob
elif home_goals_m == away_goals_m:
draw_win_prob += prob
elif home_goals_m < away_goals_m:
away_win_prob += prob
#CALCULATE VALUE
bet365odds_h, bet365odds_d, bet365odds_a = float(game[23]), float(game[24]), float(game[25])
ev_h = (home_win_prob * (bet365odds_h - 1)) - (1 - home_win_prob)
ev_d = (draw_win_prob * (bet365odds_d - 1)) - (1 - draw_win_prob)
ev_a = (away_win_prob * (bet365odds_a - 1)) - (1 - away_win_prob)
highestEV = max(ev_h, ev_d, ev_a)
if (ev_h == highestEV) and (ev_h > 0):
team_bet = home_team
ev_bet = ev_h
if home_goals > away_goals:
TOTAL_VALUE += (bet365odds_h - 1)
else:
TOTAL_VALUE -= 1
elif (ev_d == highestEV) and (ev_d > 0):
team_bet = 'Draw'
ev_bet = ev_d
if home_goals == away_goals:
TOTAL_VALUE += (bet365odds_d - 1)
else:
TOTAL_VALUE -= 1
elif (ev_a == highestEV) and (ev_a > 0):
team_bet = away_team
ev_bet = ev_a
if home_goals < away_goals:
TOTAL_VALUE += (bet365odds_a - 1)
else:
TOTAL_VALUE -= 1
if (team_bet != '') and (ev_bet != ''):
print ("Bet on '%s' (EV = %s)" % (team_bet, ev_bet))
print (TOTAL_VALUE)
# UPDATE VARIABLES AFTER MATCH HAS BEEN PLAYED
dict[home_team]['home_goals'] += home_goals
dict[home_team]['home_conceded'] += away_goals
dict[home_team]['home_games'] += 1
dict[away_team]['away_goals'] += away_goals
dict[away_team]['away_conceded'] += home_goals
dict[away_team]['away_games'] += 1
GAMES_PLAYED += 1
# CREATE FACTORS
if GAMES_PLAYED > (WEEKS_WAIT * 10):
for key, value in dict.items():
alpha_h = (dict[key]['home_goals'] / dict[key]['home_games']) / avg_home_goals
beta_h = (dict[key]['home_conceded'] / dict[key]['home_games']) / avg_away_goals
alpha_a = (dict[key]['away_goals'] / dict[key]['away_games']) / avg_away_goals
beta_a = (dict[key]['away_conceded'] / dict[key]['away_games']) / avg_home_goals
dict[key]['alpha_h'] = alpha_h
dict[key]['beta_h'] = beta_h
dict[key]['alpha_a'] = alpha_a
dict[key]['beta_a'] = beta_a
Futbol verileriyle alakalı site:
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