def game_already_exist(self, game_info_array):
if len(game_info_array) == 19:
return True
team1_name = game_info_array[3]
team2_name = game_info_array[17]
game_hour = game_info_array[9]
game_date = game_info_array[10]
game_datetime = util.get_date_time_by_day_and_time(game_date, game_hour)
team1 = TeamDAO().getTeamByLikeName(str(team1_name))
if team1 is None:
team1 = TeamDAO().create_team(team1_name, "", None, None)
team2 = TeamDAO().getTeamByLikeName(str(team2_name))
if team2 is None:
team2 = TeamDAO().create_team(team2_name, "", None, None)
game = GameDAO().getGameByTeamsAndDateTime(team1.id_team, team2.id_team, game_datetime)
if game is not None:
return True
else:
return False
def get_analysis(self, team1_name, team2_name, maps):
team1 = TeamDAO().getTeamByLikeName(team1_name)
team2 = TeamDAO().getTeamByLikeName(team2_name)
team1_games_maps = GameDAO().list_team_top_games_maps(None, team1_name)
team2_games_maps = GameDAO().list_team_top_games_maps(None, team2_name)
team1_confidence = team_indicators.get_team_confidence(team1.id_team, team1_games_maps)
team2_confidence = team_indicators.get_team_confidence(team2.id_team, team2_games_maps)
winLostByRankAndMap1 = TeamIndicators().win_lost_percentage_by_rank_window_and_maps(team1_name, team1_games_maps)
winLostByRankAndMap2 = TeamIndicators().win_lost_percentage_by_rank_window_and_maps(team2_name, team2_games_maps)
winLostCountGameByRank1 = TeamIndicators().win_lost_number_maps_by_rank_window(team1_name, team1_games_maps)
winLostCountGameByRank2 = TeamIndicators().win_lost_number_maps_by_rank_window(team2_name, team2_games_maps)
team1Info = {"Team": team1_name, "Rank": team1.actual_rank, "Confidence": 0.0, "WinPercentageOppRank": {},
"MapsCountOppRank": {}}
team2Info = {"Team": team2_name, "Rank": team2.actual_rank, "Confidence": 0.0, "WinPercentageOppRank": {},
"MapsCountOppRank": {}}
team1Info["Confidence"] = (team1_confidence.get(maps[0])["Confidence"]) if team1_confidence.get(maps[0]) != None else 0.0
team2Info["Confidence"] = (team2_confidence.get(maps[1])["Confidence"]) if team2_confidence.get(maps[1]) != None else 0.0
team1Info["WinPercentageOppRank"] = TeamIndicators().get_win_percentage_by_maps_and_opp_rank_dictionary(winLostByRankAndMap1, team2.actual_rank, maps)
team2Info["WinPercentageOppRank"] = TeamIndicators().get_win_percentage_by_maps_and_opp_rank_dictionary(winLostByRankAndMap2, team1.actual_rank, maps)
team1Info["MapsCountOppRank"] = TeamIndicators().get_win_on_2maps_or_3maps_percentage_by_opp_rank(winLostCountGameByRank1, team2.actual_rank)
team2Info["MapsCountOppRank"] = TeamIndicators().get_win_on_2maps_or_3maps_percentage_by_opp_rank(winLostCountGameByRank2, team1.actual_rank)
print(team1Info)
print(team2Info)
def full_update_all_teams(self, number_of_matches):
teams = TeamDAO().listTeamsWithHomePage()
for item in teams:
site = item.homepage
if site is None or site == "":
continue
self.update_team_and_players_info(item, site)
self.matches_find_and_build_by_teams(teams, number_of_matches)
def full_update_by_team(self, team_name, number_of_matches):
item = TeamDAO().getTeamByLikeName(team_name)
site = item.homepage
self.update_team_and_players_info(item, site)
start_date = dt.now()
if item.hltv_id is not None and item.hltv_id != "":
results = "https://www.hltv.org/results?team=" + str(item.hltv_id)
item = self.matches_builder(item, results, number_of_matches)
end_date = dt.now()
print("Finish Matches Builder Team " + str(item.name) + ". Seconds " +
str((end_date - start_date).total_seconds()))
def update_matches_all_teams(self, number_of_matches):
teams = TeamDAO().listTeamsWithHomePage()
self.matches_find_and_build_by_teams(teams, number_of_matches)
def create_game(self, game_info_array, picks_remove_info_array,
maps_ct_tr_info_array, frames, team_rank_array,
rounds_detail_informations):
team1_name = game_info_array[3]
team2_name = game_info_array[17]
team1_score = int(game_info_array[5])
team2_score = int(game_info_array[19])
game_hour = game_info_array[9]
game_date = game_info_array[10]
game_datetime = util.get_date_time_by_day_and_time(
game_date, game_hour)
championship_name = game_info_array[11]
team1 = TeamDAO().getTeamByLikeName(str(team1_name))
if team1 is None:
team1 = TeamDAO().create_team(team1_name, "", None, None)
team2 = TeamDAO().getTeamByLikeName(str(team2_name))
if team2 is None:
team2 = TeamDAO().create_team(team2_name, "", None, None)
game = GameDAO().getGameByTeamsAndDateTime(team1.id_team,
team2.id_team,
game_datetime)
# if game != None or len(frames) == 0:
# return
team1_rank_ = "100" if "Unranked" in team_rank_array[0][
1:] else team_rank_array[0][1:]
team2_rank_ = "100" if "Unranked" in team_rank_array[
1][:-1] else team_rank_array[1][:-1]
team1_rank = int(team1_rank_)
team2_rank = int(team2_rank_)
best_of = int(picks_remove_info_array[0].split(" ")[2][:1])
if best_of == 1:
if team1_score > team2_score:
team1_score = 1
team2_score = 0
else:
team1_score = 0
team2_score = 1
map_left, team1_pick, team1_removes, team2_pick, team2_removes = self.fill_maps_picks_removes(
picks_remove_info_array, team1_name, team2_name)
championship = ChampionshipDAO().getChampionshipByNameAndStartDate(
championship_name, None)
if championship is None:
championship = ChampionshipDAO().createChampionship(
championship_name, None, None, None)
if len(maps_ct_tr_info_array) < (4 + (best_of - 1) * 26):
return
game = self.create_or_update_game(best_of, championship, game,
game_datetime, map_left, team1,
team1_pick, team1_rank,
team1_removes, team1_score, team2,
team2_pick, team2_rank,
team2_removes, team2_score)
maps_array = self.create_map(game, maps_ct_tr_info_array,
rounds_detail_informations, best_of)
self.createPlayerMapStats(maps_array, team1, team2, frames)
def get_predict_game_data_set(self, team1_name, team2_name, maps_array):
df = pd.DataFrame(columns=['Map1_Dust2', 'Map1_Vertigo', 'Map1_Inferno', 'Map1_Overpass', 'Map1_Train',
'Map1_Mirage', 'Map1_Nuke', 'Map2_Dust2', 'Map2_Vertigo', 'Map2_Inferno',
'Map2_Overpass', 'Map2_Train', 'Map2_Mirage', 'Map2_Nuke', 'Team1Rank', 'Team2Rank',
'Team1WinPercentageMirage', 'Team1WinPercentageDust2', 'Team1WinPercentageNuke',
'Team1WinPercentageOverpass', 'Team1WinPercentageInferno',
'Team1WinPercentageVertigo', 'Team1WinPercentageTrain', 'Team1WinPercentageCache',
'Team2WinPercentageMirage', 'Team2WinPercentageDust2', 'Team2WinPercentageNuke',
'Team2WinPercentageOverpass', 'Team2WinPercentageInferno',
'Team2WinPercentageVertigo', 'Team2WinPercentageTrain', 'Team2WinPercentageCache',
'Team1ConfidencePickMirage', 'Team1ConfidencePickDust2', 'Team1ConfidencePickNuke',
'Team1ConfidencePickOverpass', 'Team1ConfidencePickInferno',
'Team1ConfidencePickVertigo', 'Team1ConfidencePickTrain', 'Team1ConfidencePickCache',
'Team2ConfidencePickMirage', 'Team2ConfidencePickDust2', 'Team2ConfidencePickNuke',
'Team2ConfidencePickOverpass', 'Team2ConfidencePickInferno',
'Team2ConfidencePickVertigo', 'Team2ConfidencePickTrain', 'Team2ConfidencePickCache',
'Team1AverageOppRankMirage', 'Team1AverageOppRankDust2', 'Team1AverageOppRankNuke',
'Team1AverageOppRankOverpass', 'Team1AverageOppRankInferno',
'Team1AverageOppRankVertigo', 'Team1AverageOppRankTrain', 'Team1AverageOppRankCache',
'Team2AverageOppRankMirage', 'Team2AverageOppRankDust2', 'Team2AverageOppRankNuke',
'Team2AverageOppRankOverpass', 'Team2AverageOppRankInferno',
'Team2AverageOppRankVertigo', 'Team2AverageOppRankTrain', 'Team2AverageOppRankCache',
'Team1PlayersPlusMinosMirage', 'Team1PlayersPlusMinosDust2',
'Team1PlayersPlusMinosNuke', 'Team1PlayersPlusMinosOverpass',
'Team1PlayersPlusMinosInferno',
'Team1PlayersPlusMinosVertigo', 'Team1PlayersPlusMinosTrain',
'Team1PlayersPlusMinosCache',
'Team2PlayersPlusMinosMirage', 'Team2PlayersPlusMinosDust2',
'Team2PlayersPlusMinosNuke', 'Team2PlayersPlusMinosOverpass',
'Team2PlayersPlusMinosInferno',
'Team2PlayersPlusMinosVertigo', 'Team2PlayersPlusMinosTrain',
'Team2PlayersPlusMinosCache',
'Team1RoundsPlusMinosMirage', 'Team1RoundsPlusMinosDust2',
'Team1RoundsPlusMinosNuke', 'Team1RoundsPlusMinosOverpass',
'Team1RoundsPlusMinosInferno',
'Team1RoundsPlusMinosVertigo', 'Team1RoundsPlusMinosTrain',
'Team1RoundsPlusMinosCache',
'Team2RoundsPlusMinosMirage', 'Team2RoundsPlusMinosDust2',
'Team2RoundsPlusMinosNuke', 'Team2RoundsPlusMinosOverpass',
'Team2RoundsPlusMinosInferno',
'Team2RoundsPlusMinosVertigo', 'Team2RoundsPlusMinosTrain',
'Team2RoundsPlusMinosCache',
'Team1Winner'])
team1 = TeamDAO().getTeamByLikeName(team1_name)
team2 = TeamDAO().getTeamByLikeName(team2_name)
team1_last_10_games = GameDAO().list_team_last_maps_games(None, team1.id_team, number_maps_to_consider)
team2_last_10_games = GameDAO().list_team_last_maps_games(None, team2.id_team, number_maps_to_consider)
if len(team1_last_10_games) < number_maps_to_consider or len(team2_last_10_games) < number_maps_to_consider:
return None
team1_confidence = team_indicators.get_team_confidence(team1_last_10_games, team1.id_team)
team2_confidence = team_indicators.get_team_confidence(team2_last_10_games, team2.id_team)
win_percentage_team1 = TeamIndicators().win_lost_percentage_by_rank_window_and_maps(team1.id_team,
team1_last_10_games)
win_percentage_team2 = TeamIndicators().win_lost_percentage_by_rank_window_and_maps(team2.id_team,
team2_last_10_games)
win_percentage_team1_by_map = TeamIndicators().get_win_percentage_by_maps_and_opp_rank_dictionary(
win_percentage_team1, team2.actual_rank,
["Dust2", "Inferno", "Overpass", "Vertigo", "Nuke", "Mirage", "Train", "Cache"])
win_percentage_team2_by_map = TeamIndicators().get_win_percentage_by_maps_and_opp_rank_dictionary(
win_percentage_team2, team1.actual_rank,
["Dust2", "Inferno", "Overpass", "Vertigo", "Nuke", "Mirage", "Train", "Cache"])
average_opp_rank_team1 = team_indicators.get_average_opp_rank_by_map(team1_last_10_games, team1.id_team)
average_opp_rank_team2 = team_indicators.get_average_opp_rank_by_map(team2_last_10_games, team2.id_team)
plus_minos_rounds_team1 = team_indicators.get_plus_minos_rounds_team(team1_last_10_games, team1.id_team)
plus_minos_rounds_team2 = team_indicators.get_plus_minos_rounds_team(team2_last_10_games, team2.id_team)
gamesWithTeam1PlayersStats = GameDAO().list_team_last_games_with_players_stats(None, team1.id_team,
15 * number_maps_to_consider)
gamesWithTeam2PlayersStats = GameDAO().list_team_last_games_with_players_stats(None, team2.id_team,
15 * number_maps_to_consider)
plus_minos_players_team1 = team_indicators.get_plus_minos_players_team(gamesWithTeam1PlayersStats)
plus_minos_players_team2 = team_indicators.get_plus_minos_players_team(gamesWithTeam2PlayersStats)
df.loc[0, 'Team1Rank'] = team1.actual_rank
df.loc[0, 'Team2Rank'] = team2.actual_rank
df.loc[0, 'Map1_Mirage'] = 0
df.loc[0, 'Map1_Dust2'] = 0
df.loc[0, 'Map1_Vertigo'] = 0
df.loc[0, 'Map1_Inferno'] = 0
df.loc[0, 'Map1_Overpass'] = 0
df.loc[0, 'Map1_Train'] = 0
df.loc[0, 'Map1_Nuke'] = 0
df.loc[0, 'Map2_Mirage'] = 0
df.loc[0, 'Map2_Dust2'] = 0
df.loc[0, 'Map2_Vertigo'] = 0
df.loc[0, 'Map2_Inferno'] = 0
df.loc[0, 'Map2_Overpass'] = 0
df.loc[0, 'Map2_Train'] = 0
df.loc[0, 'Map2_Nuke'] = 0
if "Mirage" in maps_array[0]:
df.loc[0, 'Map1_Mirage'] = 1
elif "Dust2" in maps_array[0]:
df.loc[0, 'Map1_Dust2'] = 1
elif "Vertigo" in maps_array[0]:
df.loc[0, 'Map1_Vertigo'] = 1
elif "Inferno" in maps_array[0]:
df.loc[0, 'Map1_Inferno'] = 1
elif "Overpass" in maps_array[0]:
df.loc[0, 'Map1_Overpass'] = 1
elif "Train" in maps_array[0]:
df.loc[0, 'Map1_Train'] = 1
elif "Nuke" in maps_array[0]:
df.loc[0, 'Map1_Nuke'] = 1
if "Mirage" in maps_array[1]:
df.loc[0, 'Map2_Mirage'] = 1
elif "Dust2" in maps_array[1]:
df.loc[0, 'Map2_Dust2'] = 1
elif "Vertigo" in maps_array[1]:
df.loc[0, 'Map2_Vertigo'] = 1
elif "Inferno" in maps_array[1]:
df.loc[0, 'Map2_Inferno'] = 1
elif "Overpass" in maps_array[1]:
df.loc[0, 'Map2_Overpass'] = 1
elif "Train" in maps_array[1]:
df.loc[0, 'Map2_Train'] = 1
elif "Nuke" in maps_array[1]:
df.loc[0, 'Map2_Nuke'] = 1
df.loc[0, 'Team1WinPercentageMirage'] = win_percentage_team1_by_map["Mirage"]
df.loc[0, 'Team1WinPercentageDust2'] = win_percentage_team1_by_map["Dust2"]
df.loc[0, 'Team1WinPercentageNuke'] = win_percentage_team1_by_map["Nuke"]
df.loc[0, 'Team1WinPercentageOverpass'] = win_percentage_team1_by_map["Overpass"]
df.loc[0, 'Team1WinPercentageInferno'] = win_percentage_team1_by_map["Inferno"]
df.loc[0, 'Team1WinPercentageVertigo'] = win_percentage_team1_by_map["Vertigo"]
df.loc[0, 'Team1WinPercentageTrain'] = win_percentage_team1_by_map["Train"]
df.loc[0, 'Team1WinPercentageCache'] = win_percentage_team1_by_map["Cache"]
df.loc[0, 'Team2WinPercentageMirage'] = win_percentage_team2_by_map["Mirage"]
df.loc[0, 'Team2WinPercentageDust2'] = win_percentage_team2_by_map["Dust2"]
df.loc[0, 'Team2WinPercentageNuke'] = win_percentage_team2_by_map["Nuke"]
df.loc[0, 'Team2WinPercentageOverpass'] = win_percentage_team2_by_map["Overpass"]
df.loc[0, 'Team2WinPercentageInferno'] = win_percentage_team2_by_map["Inferno"]
df.loc[0, 'Team2WinPercentageVertigo'] = win_percentage_team2_by_map["Vertigo"]
df.loc[0, 'Team2WinPercentageTrain'] = win_percentage_team2_by_map["Train"]
df.loc[0, 'Team2WinPercentageCache'] = win_percentage_team2_by_map["Cache"]
df.loc[0, 'Team1ConfidencePickMirage'] = team1_confidence["Mirage"]["Confidence"]
df.loc[0, 'Team1ConfidencePickDust2'] = team1_confidence["Dust2"]["Confidence"]
df.loc[0, 'Team1ConfidencePickNuke'] = team1_confidence["Nuke"]["Confidence"]
df.loc[0, 'Team1ConfidencePickOverpass'] = team1_confidence["Overpass"]["Confidence"]
df.loc[0, 'Team1ConfidencePickInferno'] = team1_confidence["Inferno"]["Confidence"]
df.loc[0, 'Team1ConfidencePickVertigo'] = team1_confidence["Vertigo"]["Confidence"]
df.loc[0, 'Team1ConfidencePickTrain'] = team1_confidence["Train"]["Confidence"]
df.loc[0, 'Team1ConfidencePickCache'] = team1_confidence["Cache"]["Confidence"]
df.loc[0, 'Team2ConfidencePickMirage'] = team2_confidence["Mirage"]["Confidence"]
df.loc[0, 'Team2ConfidencePickDust2'] = team2_confidence["Dust2"]["Confidence"]
df.loc[0, 'Team2ConfidencePickNuke'] = team2_confidence["Nuke"]["Confidence"]
df.loc[0, 'Team2ConfidencePickOverpass'] = team2_confidence["Overpass"]["Confidence"]
df.loc[0, 'Team2ConfidencePickInferno'] = team2_confidence["Inferno"]["Confidence"]
df.loc[0, 'Team2ConfidencePickVertigo'] = team2_confidence["Vertigo"]["Confidence"]
df.loc[0, 'Team2ConfidencePickTrain'] = team2_confidence["Train"]["Confidence"]
df.loc[0, 'Team2ConfidencePickCache'] = team2_confidence["Cache"]["Confidence"]
df.loc[0, 'Team1AverageOppRankMirage'] = average_opp_rank_team1["Mirage"]["average"] if \
average_opp_rank_team1.get("Mirage") is not None else 0.0
df.loc[0, 'Team1AverageOppRankDust2'] = average_opp_rank_team1["Dust2"]["average"] if \
average_opp_rank_team1.get("Dust2") is not None else 0.0
df.loc[0, 'Team1AverageOppRankNuke'] = average_opp_rank_team1["Nuke"]["average"] if \
average_opp_rank_team1.get("Nuke") is not None else 0.0
df.loc[0, 'Team1AverageOppRankOverpass'] = average_opp_rank_team1["Overpass"]["average"] if \
average_opp_rank_team1.get("Overpass") is not None else 0.0
df.loc[0, 'Team1AverageOppRankInferno'] = average_opp_rank_team1["Inferno"]["average"] if \
average_opp_rank_team1.get("Inferno") is not None else 0.0
df.loc[0, 'Team1AverageOppRankVertigo'] = average_opp_rank_team1["Vertigo"]["average"] if \
average_opp_rank_team1.get("Vertigo") is not None else 0.0
df.loc[0, 'Team1AverageOppRankTrain'] = average_opp_rank_team1["Train"]["average"] if \
average_opp_rank_team1.get("Train") is not None else 0.0
df.loc[0, 'Team1AverageOppRankCache'] = average_opp_rank_team1["Cache"]["average"] if \
average_opp_rank_team1.get("Cache") is not None else 0.0
df.loc[0, 'Team2AverageOppRankMirage'] = average_opp_rank_team2["Mirage"]["average"] if \
average_opp_rank_team2.get("Mirage") is not None else 0.0
df.loc[0, 'Team2AverageOppRankDust2'] = average_opp_rank_team2["Dust2"]["average"] if \
average_opp_rank_team2.get("Dust2") is not None else 0.0
df.loc[0, 'Team2AverageOppRankNuke'] = average_opp_rank_team2["Nuke"]["average"] if \
average_opp_rank_team2.get("Nuke") is not None else 0.0
df.loc[0, 'Team2AverageOppRankOverpass'] = average_opp_rank_team2["Overpass"]["average"] if \
average_opp_rank_team2.get("Overpass") is not None else 0.0
df.loc[0, 'Team2AverageOppRankInferno'] = average_opp_rank_team2["Inferno"]["average"] if \
average_opp_rank_team2.get("Inferno") is not None else 0.0
df.loc[0, 'Team2AverageOppRankVertigo'] = average_opp_rank_team2["Vertigo"]["average"] if \
average_opp_rank_team2.get("Vertigo") is not None else 0.0
df.loc[0, 'Team2AverageOppRankTrain'] = average_opp_rank_team2["Train"]["average"] if \
average_opp_rank_team2.get("Train") is not None else 0.0
df.loc[0, 'Team2AverageOppRankCache'] = average_opp_rank_team2["Cache"]["average"] if \
average_opp_rank_team2.get("Cache") is not None else 0.0
df.loc[0, 'Team1PlayersPlusMinosMirage'] = plus_minos_players_team1["Mirage"]["plusMinosPlayers"]
df.loc[0, 'Team1PlayersPlusMinosDust2'] = plus_minos_players_team1["Dust2"]["plusMinosPlayers"]
df.loc[0, 'Team1PlayersPlusMinosNuke'] = plus_minos_players_team1["Nuke"]["plusMinosPlayers"]
df.loc[0, 'Team1PlayersPlusMinosOverpass'] = plus_minos_players_team1["Overpass"]["plusMinosPlayers"]
df.loc[0, 'Team1PlayersPlusMinosInferno'] = plus_minos_players_team1["Inferno"]["plusMinosPlayers"]
df.loc[0, 'Team1PlayersPlusMinosVertigo'] = plus_minos_players_team1["Vertigo"]["plusMinosPlayers"]
df.loc[0, 'Team1PlayersPlusMinosTrain'] = plus_minos_players_team1["Train"]["plusMinosPlayers"]
df.loc[0, 'Team1PlayersPlusMinosCache'] = plus_minos_players_team1["Cache"]["plusMinosPlayers"]
df.loc[0, 'Team2PlayersPlusMinosMirage'] = plus_minos_players_team2["Mirage"]["plusMinosPlayers"]
df.loc[0, 'Team2PlayersPlusMinosDust2'] = plus_minos_players_team2["Dust2"]["plusMinosPlayers"]
df.loc[0, 'Team2PlayersPlusMinosNuke'] = plus_minos_players_team2["Nuke"]["plusMinosPlayers"]
df.loc[0, 'Team2PlayersPlusMinosOverpass'] = plus_minos_players_team2["Overpass"]["plusMinosPlayers"]
df.loc[0, 'Team2PlayersPlusMinosInferno'] = plus_minos_players_team2["Inferno"]["plusMinosPlayers"]
df.loc[0, 'Team2PlayersPlusMinosVertigo'] = plus_minos_players_team2["Vertigo"]["plusMinosPlayers"]
df.loc[0, 'Team2PlayersPlusMinosTrain'] = plus_minos_players_team2["Train"]["plusMinosPlayers"]
df.loc[0, 'Team2PlayersPlusMinosCache'] = plus_minos_players_team2["Cache"]["plusMinosPlayers"]
df.loc[0, 'Team1RoundsPlusMinosMirage'] = plus_minos_rounds_team1["Mirage"]["plusMinosRounds"]
df.loc[0, 'Team1RoundsPlusMinosDust2'] = plus_minos_rounds_team1["Dust2"]["plusMinosRounds"]
df.loc[0, 'Team1RoundsPlusMinosNuke'] = plus_minos_rounds_team1["Nuke"]["plusMinosRounds"]
df.loc[0, 'Team1RoundsPlusMinosOverpass'] = plus_minos_rounds_team1["Overpass"]["plusMinosRounds"]
df.loc[0, 'Team1RoundsPlusMinosInferno'] = plus_minos_rounds_team1["Inferno"]["plusMinosRounds"]
df.loc[0, 'Team1RoundsPlusMinosVertigo'] = plus_minos_rounds_team1["Vertigo"]["plusMinosRounds"]
df.loc[0, 'Team1RoundsPlusMinosTrain'] = plus_minos_rounds_team1["Train"]["plusMinosRounds"]
df.loc[0, 'Team1RoundsPlusMinosCache'] = plus_minos_rounds_team1["Cache"]["plusMinosRounds"]
df.loc[0, 'Team2RoundsPlusMinosMirage'] = plus_minos_rounds_team2["Mirage"]["plusMinosRounds"]
df.loc[0, 'Team2RoundsPlusMinosDust2'] = plus_minos_rounds_team2["Dust2"]["plusMinosRounds"]
df.loc[0, 'Team2RoundsPlusMinosNuke'] = plus_minos_rounds_team2["Nuke"]["plusMinosRounds"]
df.loc[0, 'Team2RoundsPlusMinosOverpass'] = plus_minos_rounds_team2["Overpass"]["plusMinosRounds"]
df.loc[0, 'Team2RoundsPlusMinosInferno'] = plus_minos_rounds_team2["Inferno"]["plusMinosRounds"]
df.loc[0, 'Team2RoundsPlusMinosVertigo'] = plus_minos_rounds_team2["Vertigo"]["plusMinosRounds"]
df.loc[0, 'Team2RoundsPlusMinosTrain'] = plus_minos_rounds_team2["Train"]["plusMinosRounds"]
df.loc[0, 'Team2RoundsPlusMinosCache'] = plus_minos_rounds_team2["Cache"]["plusMinosRounds"]
df.loc[0, 'Team1Winner'] = 0
return df