Exemplo n.º 1
0
def best_matches_combine_cashback(site, minimum_odd, bet, sport="football",
                                  freebet=True, combi_max=0, rate_cashback=1,
                                  nb_matches=2, date_max=None, time_max=None,
                                  date_min=None, time_min=None):
    """
    Calcule la répartition des mises lorsqu'un unique combiné est remboursé s'il est perdant
    """
    all_odds = sportsbetting.ODDS[sport]
    sportsbetting.ALL_ODDS_COMBINE = {}
    for combine in combinations(all_odds.items(), nb_matches):
        (sportsbetting
            .ALL_ODDS_COMBINE[" / "
            .join([match[0]
                   for match
                   in combine])]) = cotes_combine_all_sites(*[match[1]
                                                              for match
                                                              in combine])
    odds_function = lambda best_odds, odds_site, i: (best_odds[:i]
                                                     + [odds_site[i] * (1 + combi_max) - combi_max]
                                                     + best_odds[i + 1:])
    profit_function = lambda odds_to_check, i: gain_pari_rembourse_si_perdant(odds_to_check, bet, i,
                                                                              freebet,
                                                                              rate_cashback)
    criteria = lambda odds_to_check, i: (odds_to_check[i] + combi_max) / (
            1 + combi_max) >= minimum_odd
    display_function = lambda x, i: mises_pari_rembourse_si_perdant(x, bet, i, freebet,
                                                                    rate_cashback, True)
    return_function = lambda x, i: mises_pari_rembourse_si_perdant(x, bet, i, freebet,
                                                                   rate_cashback, False)
    best_match_base(odds_function, profit_function, criteria, display_function,
                    return_function, site, sport, date_max, time_max, date_min,
                    time_min, True, nb_matches)
Exemplo n.º 2
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def best_matches_combine_cashback_une_selection_perdante(site, cote_minimale_selection, combi_max=0,
                                                         nb_matches=2, date_max=None, time_max=None,
                                                         date_min=None, time_min=None):
    """
    Calcule la meilleure combinaison de matches et les mises à jouer pour une promotion du type
    "Combiné remboursé si une seule selection perdante, sans limite du nombre de paris remboursés"
    """
    sport = "football"
    bet = 10000
    all_odds = sportsbetting.ODDS[sport]
    sportsbetting.ALL_ODDS_COMBINE = {}
    for combine in combinations(all_odds.items(), nb_matches):
        try:
            if all([odd >= cote_minimale_selection for odds in list(all_odds[match[0]]["odds"][site]
                                                                    for match in combine)
                    for odd in odds]):
                (sportsbetting
                    .ALL_ODDS_COMBINE[" / "
                    .join([match[0]
                           for match
                           in combine])]) = cotes_combine_all_sites(*[match[1]
                                                                      for match
                                                                      in combine])
        except KeyError:
            pass
    odds_function = lambda best_odds, odds_site, i: list(
        map(lambda x: x * (1 + combi_max) - combi_max,
            odds_site))
    profit_function = lambda odds_to_check, i: gain(odds_to_check, bet) - bet
    criteria = lambda odds_to_check, i: (odds_to_check[i] + combi_max) / (1 + combi_max) >= 1.1
    display_function = lambda x, i: mises(x, bet, True)
    return_function = lambda x, i: mises(x, bet, False)
    best_match_base(odds_function, profit_function, criteria, display_function,
                    return_function, site, sport, date_max, time_max, date_min,
                    time_min, True, nb_matches, one_site=True, recalcul=True)
Exemplo n.º 3
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def best_matches_combine(site,
                         minimum_odd,
                         bet,
                         sport="football",
                         nb_matches=2,
                         one_site=False,
                         date_max=None,
                         time_max=None,
                         date_min=None,
                         time_min=None,
                         minimum_odd_selection=1.01):
    """
    Retourne les meilleurs matches sur lesquels miser lorsqu'on doit miser une somme
    donnée à une cote donnée sur un combiné
    """
    all_odds = filter_dict_dates(sportsbetting.ODDS[sport], date_max, time_max,
                                 date_min, time_min)
    sportsbetting.ALL_ODDS_COMBINE = {}
    for combine in combinations(all_odds.items(), nb_matches):
        try:
            if all([
                    odd >= minimum_odd_selection for odds in list(
                        all_odds[match[0]]["odds"][site] for match in combine)
                    for odd in odds
            ]):
                (sportsbetting.ALL_ODDS_COMBINE[" / ".join([
                    match[0] for match in combine
                ])]) = cotes_combine_all_sites(
                    *[match[1] for match in combine])
        except KeyError:
            pass
    odds_function = lambda best_odds, odds_site, i: (
        (best_odds[:i] + [odds_site[i]] + best_odds[i + 1:])
        if not one_site else odds_site)
    profit_function = lambda odds_to_check, i: (gain(odds_to_check, bet) - bet
                                                if one_site else gain2(
                                                    odds_to_check, i, bet))
    criteria = lambda odds_to_check, i: (
        (not one_site and odds_to_check[i] >= minimum_odd) or
        (one_site and all(odd >= minimum_odd for odd in odds_to_check)))
    display_function = lambda best_overall_odds, best_rank: (
        mises2(best_overall_odds, bet, best_rank, True)
        if not one_site else mises(best_overall_odds, bet, True))
    result_function = lambda best_overall_odds, best_rank: (
        mises2(best_overall_odds, bet, best_rank, False)
        if not one_site else mises(best_overall_odds, bet, False))
    best_match_base(odds_function,
                    profit_function,
                    criteria,
                    display_function,
                    result_function,
                    site,
                    sport,
                    date_max,
                    time_max,
                    date_min,
                    time_min,
                    True,
                    nb_matches,
                    one_site=one_site)
Exemplo n.º 4
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 def compute_all_odds_combine(nb_combine, combine):
     sb.PROGRESS += 100/nb_combine
     try:
         sb.ALL_ODDS_COMBINE[" / ".join([match[0] for match in combine])] = cotes_combine_all_sites(*[match[1]
                                                                                     for match
                                                                                     in combine])
     except KeyError:
         pass
def best_matches_freebet_one_site(site,
                                  freebet,
                                  sport="football",
                                  nb_matches=2,
                                  minimum_odd=1.1,
                                  date_max=None,
                                  time_max=None,
                                  date_min=None,
                                  time_min=None):
    """
    Calcule la répartition des paris gratuits sur un unique site
    """
    all_odds = sportsbetting.ODDS[sport]
    sportsbetting.ALL_ODDS_COMBINE = {}
    for combine in combinations(all_odds.items(), nb_matches):
        (sportsbetting.ALL_ODDS_COMBINE[" / ".join([
            match[0] for match in combine
        ])]) = cotes_combine_all_sites(*[match[1] for match in combine])
    odds_function = lambda best_odds, odds_site, i: cotes_freebet(odds_site)
    profit_function = lambda odds_to_check, i: gain(odds_to_check, freebet
                                                    ) - freebet
    criteria = lambda odds_to_check, i: all(odd >= minimum_odd
                                            for odd in odds_to_check)
    display_function = lambda best_overall_odds, best_rank: mises(
        best_overall_odds, freebet, True)
    result_function = lambda best_overall_odds, best_rank: mises(
        best_overall_odds, freebet, False)
    best_match_base(odds_function,
                    profit_function,
                    criteria,
                    display_function,
                    result_function,
                    site,
                    sport,
                    date_max,
                    time_max,
                    date_min,
                    time_min,
                    True,
                    nb_matches,
                    True,
                    one_site=True)
Exemplo n.º 6
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def best_matches_freebet(main_sites, freebets, sport="football", *matches):
    """
    Compute of best way to bet freebets following the model
    [[bet, bookmaker], ...]
    """
    second_sites = {freebet[1] for freebet in freebets}
    if not second_sites:
        print("Veuillez sélectionner des freebets secondaires")
        return
    if matches:
        new_odds = {}
        for match in matches:
            match_name, odds = odds_match(match)
            new_odds[match_name] = odds
    else:
        new_odds = sportsbetting.ODDS[sport]
    all_odds = {}
    for match in new_odds:
        if (not (any([site not in new_odds[match]["odds"].keys() for site in main_sites])
                 or any([site not in new_odds[match]["odds"].keys() for site in second_sites]))):
            if new_odds[match]["odds"]:
                all_odds[match] = new_odds[match]
    best_rate = 0
    nb_matches = 2
    n = 3 ** nb_matches
    nb_freebets = len(freebets)
    all_odds_combine = {}
    combis = list(combinations(all_odds.items(), nb_matches))
    nb_combis = len(combis)
    progress = 10
    start = time.time()
    for i, combine in enumerate(combis):
        #         if i == 20:
        #             print("appr. time to wait:", int((time.time()-start)*nb_combis/20), "s")
        #         if i/nb_combis*100 > progress:
        #             print(str(progress)+"%")
        #             progress += 10
        match_combine = " / ".join([match[0] for match in combine])
        all_odds_combine[match_combine] = cotes_combine_all_sites(*[match[1] for match in combine],
                                                                  freebet=True)
        main_sites_distribution = [main_sites[0] for _ in range(n)]
        main_site_odds = copy.deepcopy(all_odds_combine[match_combine]["odds"][main_sites[0]])
        for main in main_sites[1:]:
            potential_odds = all_odds_combine[match_combine]["odds"][main]
            for j, odd in enumerate(potential_odds):
                if odd > main_site_odds[j]:
                    main_site_odds[j] = odd
                    main_sites_distribution[j] = main
        second_odds = {second_site: all_odds_combine[match_combine]["odds"][second_site]
                       for second_site in second_sites}
        dict_combine_odds = copy.deepcopy(second_odds)
        for perm in permutations(range(n), nb_freebets):
            defined_second_sites = [[perm[i], freebet[0], freebet[1]]
                                    for i, freebet in enumerate(freebets)]
            defined_bets_temp = defined_bets(main_site_odds, dict_combine_odds,
                                             main_sites_distribution,
                                             defined_second_sites)
            if defined_bets_temp[0] / np.sum(defined_bets_temp[1]) > best_rate:
                best_rate = defined_bets_temp[0] / np.sum(defined_bets_temp[1])
                best_combine = combine
                best_bets = defined_bets_temp
    #     print("Temps d'exécution =", time.time()-start)
    best_match_combine = " / ".join([match[0] for match in best_combine])
    odds_best_match = copy.deepcopy(all_odds_combine[best_match_combine])
    all_sites = main_sites + list(second_sites)
    for site in all_odds_combine[best_match_combine]["odds"]:
        if site not in all_sites:
            del odds_best_match["odds"][site]
    print(best_match_combine)
    pprint(odds_best_match, compact=1)
    print("Taux =", best_rate)
    print("Gain référence =", best_bets[0])
    print("Somme des mises =", np.sum(best_bets[1]))
    afficher_mises_combine([x[0] for x in best_combine], best_bets[2], best_bets[1],
                           all_odds_combine[best_match_combine]["odds"], "football",
                           uniquement_freebet=True)
Exemplo n.º 7
0
def best_match_stakes_to_bet(stakes, nb_matches=1, sport="football", date_max=None, time_max=None):
    second_sites = {stake[1] for stake in stakes}
    main_sites = ['betclic', 'betstars', 'bwin', 'france_pari', 'joa', 'netbet',
                  'parionssport', 'pasinobet', 'pmu', 'unibet', 'winamax', 'zebet']
    new_odds = sportsbetting.ODDS[sport]
    all_odds = {}
    hour_max, minute_max = 0, 0
    if time_max:
        if time_max[-1] == 'h':
            hour_max = int(time_max[:-1])
        else:
            hour_max, minute_max = (int(_) for _ in time_max.split('h'))
    if date_max:
        day_max, month_max, year_max = (int(_) for _ in date_max.split('/'))
        datetime_max = datetime.datetime(year_max, month_max, day_max,
                                         hour_max, minute_max)
    else:
        datetime_max = None
    for match in new_odds:
        if (((datetime_max and new_odds[match]["date"] <= datetime_max) or not datetime_max)
                and not any([site not in new_odds[match]["odds"].keys() for site in second_sites])):
            if new_odds[match]["odds"]:
                all_odds[match] = new_odds[match]
    best_profit = -sum(stake[0] for stake in stakes)
    n = 3 ** nb_matches
    nb_stakes = len(stakes)
    all_odds_combine = {}
    combis = list(combinations(all_odds.items(), nb_matches))
    nb_combis = len(combis)
    best_combine = None
    best_bets = None
    main_site_odds = []
    main_sites_distribution = []
    progress = 10
    start = time.time()
    sportsbetting.PROGRESS = 0
    for i, combine in enumerate(combis):
        sportsbetting.PROGRESS += 100 / nb_combis
        #         if i == 20:
        #             print("appr. time to wait:", int((time.time()-start)*nb_combis/20), "s")
        #         if i/nb_combis*100 > progress:
        #             print(str(progress)+"%")
        #             progress += 10
        match_combine = " / ".join([match[0] for match in combine])
        all_odds_combine[match_combine] = cotes_combine_all_sites(*[match[1] for match in combine])
        for main0 in main_sites:
            try:
                main_sites_distribution = [main0 for _ in range(n)]
                main_site_odds = copy.deepcopy(all_odds_combine[match_combine]["odds"][main0])
                break
            except KeyError:
                pass
        for main in main_sites[:i] + main_sites[i + 1:]:
            try:
                potential_odds = all_odds_combine[match_combine]["odds"][main]
                for j, odd in enumerate(potential_odds):
                    if odd > main_site_odds[j]:
                        main_site_odds[j] = odd
                        main_sites_distribution[j] = main
            except KeyError:
                pass
        second_odds = {second_site: all_odds_combine[match_combine]["odds"][second_site]
                       for second_site in second_sites}
        dict_combine_odds = copy.deepcopy(second_odds)
        for perm in permutations(range(n), nb_stakes):
            valid_perm = True
            defined_second_sites = [[perm[j], stake[0], stake[1]]
                                    for j, stake in enumerate(stakes)]
            for j, stake in enumerate(stakes):
                if dict_combine_odds[defined_second_sites[j][2]][defined_second_sites[j][0]] < \
                        stake[2]:
                    valid_perm = False
                    break
            if not valid_perm:
                continue
            defined_bets_temp = defined_bets(main_site_odds, dict_combine_odds,
                                             main_sites_distribution,
                                             defined_second_sites)
            profit = defined_bets_temp[0] - np.sum(defined_bets_temp[1])
            if profit > best_profit:
                best_profit = profit
                best_combine = combine
                best_bets = defined_bets_temp
    #     print("Temps d'exécution =", time.time()-start)
    if best_combine:
        best_match_combine = " / ".join([match[0] for match in best_combine])
        odds_best_match = copy.deepcopy(all_odds_combine[best_match_combine])
        all_sites = main_sites + list(second_sites)
        for site in all_odds_combine[best_match_combine]["odds"]:
            if site not in all_sites:
                del odds_best_match["odds"][site]
        print(best_match_combine)
        pprint(odds_best_match, compact=1)
        print("Plus-value =", best_profit)
        print("Gain référence =", best_bets[0])
        print("Somme des mises =", np.sum(best_bets[1]))
        afficher_mises_combine([x[0] for x in best_combine], best_bets[2], best_bets[1],
                               all_odds_combine[best_match_combine]["odds"], "football")
    else:
        print("No match found")
Exemplo n.º 8
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def best_match_stakes_to_bet(stakes, nb_matches=1, sport="football", date_max=None, time_max=None, identical_stakes=False):
    second_sites = {stake[1] for stake in stakes}
    main_sites = ['betclic', 'betstars', 'bwin', 'france_pari', 'joa', 'netbet',
                  'parionssport', 'pasinobet', 'pmu', 'unibet', 'winamax', 'zebet']
    all_odds = filter_dict_dates(sb.ODDS[sport], date_max, time_max)
    best_profit = -sum(stake[0] for stake in stakes)
    n = get_nb_issues(sport) ** nb_matches
    nb_stakes = len(stakes)
    all_odds_combine = {}
    combis = list(combinations(all_odds.items(), nb_matches))
    nb_combis = len(combis)
    best_combine = None
    best_bets = None
    main_site_odds = []
    main_sites_distribution = []
    sb.PROGRESS = 0
    for i, combine in enumerate(combis):
        sb.PROGRESS += 100 / nb_combis
        match_combine = " / ".join([match[0] for match in combine])
        all_odds_combine[match_combine] = cotes_combine_all_sites(*[match[1] for match in combine])
        for main0 in main_sites:
            try:
                main_sites_distribution = [main0 for _ in range(n)]
                main_site_odds = copy.deepcopy(all_odds_combine[match_combine]["odds"][main0])
                break
            except KeyError:
                pass
        for main in main_sites[:i] + main_sites[i + 1:]:
            try:
                potential_odds = all_odds_combine[match_combine]["odds"][main]
                for j, odd in enumerate(potential_odds):
                    if odd > main_site_odds[j]:
                        main_site_odds[j] = odd
                        main_sites_distribution[j] = main
            except KeyError:
                pass
        second_odds = {second_site: all_odds_combine[match_combine]["odds"][second_site]
                       for second_site in second_sites if second_site in all_odds_combine[match_combine]["odds"]}
        if not second_odds:
            continue
        dict_combine_odds = copy.deepcopy(second_odds)
        for perm in permutations(range(n), nb_stakes):
            valid_perm = True
            defined_second_sites = [[perm[j], stake[0], stake[1]]
                                    for j, stake in enumerate(stakes)]
            for j, stake in enumerate(stakes):
                if dict_combine_odds[defined_second_sites[j][2]][defined_second_sites[j][0]] < stake[2]:
                    valid_perm = False
                    break
            if not valid_perm:
                if identical_stakes:
                    break
                continue
            defined_bets_temp = defined_bets(main_site_odds, dict_combine_odds,
                                             main_sites_distribution,
                                             defined_second_sites)
            profit = defined_bets_temp[0] - np.sum(defined_bets_temp[1])
            if profit > best_profit:
                best_profit = profit
                best_combine = combine
                best_bets = defined_bets_temp
            if identical_stakes:
                break
    if best_combine:
        best_match_combine = " / ".join([match[0] for match in best_combine])
        odds_best_match = copy.deepcopy(all_odds_combine[best_match_combine])
        all_sites = main_sites + list(second_sites)
        for site in all_odds_combine[best_match_combine]["odds"]:
            if site not in all_sites:
                del odds_best_match["odds"][site]
        print(best_match_combine)
        pprint(odds_best_match, compact=1)
        print("Plus-value =", round(best_profit, 2))
        print("Gain référence =", round(best_bets[0], 2))
        print("Somme des mises =", round(np.sum(best_bets[1]), 2))
        afficher_mises_combine([x[0] for x in best_combine], best_bets[2], best_bets[1],
                               all_odds_combine[best_match_combine]["odds"], sport)
    else:
        print("No match found")