def __init__(self, player_id, rating=None):
self._player_id = player_id
self._fetch_and_init()
if rating is None:
self._rating = Player()
else:
self._rating = Player(rating[0], rating[1])
def getGlickoDataMatrix(years):
glicko_df_reg = pd.read_csv('./data/RegularSeasonCompactResults.csv')
glicko_df_tourny = pd.read_csv('./data/NCAATourneyCompactResults.csv')
glicko_df = pd.concat([glicko_df_reg,glicko_df_tourny])
glicko_df.sort_values(by=['Season','DayNum'])
glicko_years = list(range(1985, min(years)))
glicko_df_sp = glicko_df.loc[glicko_df['Season'].isin(glicko_years)]
team_ids = set(glicko_df.WTeamID).union(set(glicko_df.LTeamID))
glicko = dict(zip(list(team_ids), [Player() for _ in range(len(team_ids))]))
preds = []
glicko_rounds(glicko, preds, glicko_df_sp)
df_reg_season = pd.read_csv('data/RegularSeasonDetailedResults.csv')
df_reg_season['tourny'] = 0
df_ncaa_tourny = pd.read_csv('data/NCAATourneyDetailedResults.csv')
df_ncaa_tourny['tourny'] = 1
df = pd.concat([df_reg_season,df_ncaa_tourny])
df.sort_values(by=['Season','DayNum'])
df_sp = df.loc[df['Season'].isin(years)]
team_results = {}
team_stats = {}
for id in team_ids:
team_results[id] = []
team_stats[id] = {'games': 0.0, 'points': 0.0, 'fgm': 0.0, 'fga': 0.0, 'fgm3': 0.0, 'fga3': 0.0, 'ftm': 0.0, 'fta': 0.0, 'or': 0.0, 'dr': 0.0, 'to': 0.0, 'ast': 0.0, 'stl': 0.0, 'blk': 0.0, 'pf': 0.0,'opp_points': 0.0, 'opp_fgm': 0.0, 'opp_fga': 0.0, 'opp_fgm3': 0.0, 'opp_fga3': 0.0, 'opp_ftm': 0.0, 'opp_fta': 0.0, 'opp_or': 0.0, 'opp_dr': 0.0, 'opp_to': 0.0, 'opp_ast': 0.0, 'opp_stl': 0.0, 'opp_blk': 0.0, 'opp_pf': 0.0, 'possesions': 0}
data_matrix = pd.DataFrame()
for row in df_sp.itertuples():
data_matrix = data_matrix.append(make_row(team_stats, team_results, glicko, min(row.WTeamID, row.LTeamID), max(row.WTeamID, row.LTeamID), row.Season, row.tourny, 1 if row.WTeamID > row.LTeamID else 0))
team_stats, team_results, glicko = update_stats(team_stats, team_results, glicko, row)
return data_matrix, team_stats, team_results, glicko
def readElo(playerInfoInput, playerDict):
fileToOpen = open("player.txt", "r")
file = fileToOpen.read()
file = file.splitlines()
try:
file.pop(0)
except:
pass
#list containing all info
playerInfo = list()
for line in file:
for person in line.split():
playerInfo.append(person)
#create player objects
#x is name, x+1 is rating, x+2 is rd, x+3 is vol
for x in range(0, len(playerInfo), 4):
playerDict[playerInfo[x]] = Player(playerInfo[x])
playerDict[playerInfo[x]].rating = float(playerInfo[x+1])
playerDict[playerInfo[x]].rd = float(playerInfo[x+2])
playerDict[playerInfo[x]].vol = float(playerInfo[x+3])
return playerDict
def updatePlayerList(inputPlayerDict, inputDictionary):
#read matches.txt file and updates dictionary
for key, value in inputDictionary.items():
if value not in inputPlayerDict:
userChoice = input("New player: " + value + ". Add as new player or existing?\nType in add to add as new player, edit to add to existing tag, or type exit to exit.\n")
if userChoice.lower() == "add":
inputPlayerDict[value] = Player(value)
#if not userChoice.lower() == "edit":
#break
if userChoice.lower() == "edit":
existingTag = input("Enter the correct tag: ")
if existingTag in inputPlayerDict:
inputPlayerDict[value] = inputPlayerDict[existingTag]
if existingTag not in inputPlayerDict:
newTag = input("Tag not found. Enter the new tag: ")
inputPlayerDict[newTag] = Player(newTag)
if userChoice.lower() == "exit":
break
return inputPlayerDict
team_stats[row.Losing]['num_rushes_against'] += int(row.Winning_Rushes)
team_stats[row.Losing]['rush_yards_against'] += int(row.Winning_Rush_Yards)
team_stats[row.Losing]['num_plays_against'] += int(row.Winning_Plays)
team_stats[row.Losing]['total_yards_against'] += int(row.Winning_Total_Yards)
team_stats[row.Losing]['num_turnovers_against'] += int(row.Winning_TO)
team_stats[row.Losing]['penalty_yards_against'] += int(row.Winning_Pen_Yards)
team_stats[row.Losing]['time_of_possession_against'] += int(row.Winning_TOP)
return team_stats, glicko
df = pd.read_csv('data.csv')
df = df[df['Year'] == 2017]
team_ids = set(df['Winning']).union(df['Losing'])
#print(team_ids)
team_results = {}
team_stats = {}
glicko = dict(zip(list(team_ids), [Player() for _ in range(len(team_ids))]))
#print(team_ids)
for id in team_ids:
team_results[id] = []
team_stats[id] = {'games':0,'points':0,'num_passes':0,'pass_yards':0,'num_rushes':0,'rush_yards':0,'num_plays':0,'total_yards':0,'num_turnovers':0,'penalty_yards':0,'time_of_possession':0,'points_against':0,'num_passes_against':0,'pass_yards_against':0,'num_rushes_against':0,'rush_yards_against':0,'num_plays_against':0,'total_yards_against':0,'num_turnovers_against':0,'penalty_yards_against':0,'time_of_possession_against':0}
data_matrix = pd.DataFrame()
results_matrix = pd.DataFrame()
for row in df.itertuples():
id0 = row.Winning if row.Winning < row.Losing else row.Losing
id1 = row.Winning if row.Winning > row.Losing else row.Losing
data_matrix = data_matrix.append(make_row(team_stats,id0,id1,glicko,team_results))
results_matrix = results_matrix.append(pd.DataFrame({'id0':id0,'id1':id1,'points_0':(row.Winning_Points if row.Winning < row.Losing else row.Losing_Points), 'points_1':(row.Winning_Points if row.Winning > row.Losing else row.Losing_Points)}, index=[0]))
team_stats, glicko = update_stats(team_stats, row, glicko)
#print(update_stats(team_stats, row), 0 if row.Winning < row.Losing else 1)
#print(team_stats['Michigan State'])
#print(data_matrix.iloc[715])
def get_data_matrix(year):
df = pd.read_csv('data.csv')
df = df[df['Year'].isin([year - 1, year])]
team_ids = set(df['Winning']).union(df['Losing'])
team_results = {}
team_stats = {}
glicko = dict(zip(list(team_ids),
[Player() for _ in range(len(team_ids))]))
for id in team_ids:
team_results[id] = []
team_stats[id] = {
'games': 0,
'points': 0,
'num_passes': 0,
'pass_yards': 0,
'num_rushes': 0,
'rush_yards': 0,
'num_plays': 0,
'total_yards': 0,
'num_turnovers': 0,
'penalty_yards': 0,
'time_of_possession': 0,
'points_against': 0,
'num_passes_against': 0,
'pass_yards_against': 0,
'num_rushes_against': 0,
'rush_yards_against': 0,
'num_plays_against': 0,
'total_yards_against': 0,
'num_turnovers_against': 0,
'penalty_yards_against': 0,
'time_of_possession_against': 0
}
data_matrix = pd.DataFrame()
results_matrix = pd.DataFrame()
vegas_predictions = pd.DataFrame()
for row in df.itertuples():
id0 = row.Winning if row.Winning < row.Losing else row.Losing
id1 = row.Winning if row.Winning > row.Losing else row.Losing
if row.Year == year:
data_matrix = data_matrix.append(
make_row(team_stats, id0, id1, glicko, team_results))
results_matrix = results_matrix.append(
pd.DataFrame(
{
'id0':
id0,
'id1':
id1,
'points_0':
(row.Winning_Points
if row.Winning < row.Losing else row.Losing_Points),
'points_1':
(row.Winning_Points
if row.Winning > row.Losing else row.Losing_Points)
},
index=[0]))
vegas_predictions = vegas_predictions.append(
pd.DataFrame(
{
'id0':
id0,
"id1":
id1,
'points_0':
int((row.Winning_Points if row.Winning < row.Losing
else row.Losing_Points)),
'points_1':
int((row.Winning_Points if row.Winning > row.Losing
else row.Losing_Points)),
"spread": (1 if row.WinningFU == "F" else -1) *
float(row.Spread),
"over_under": (row.Over_Under if isinstance(
row.Over_Under, str) else "None")
},
index=[0]))
team_stats, glicko, team_results = update_stats(
team_stats, row, glicko, team_results)
data_matrix.to_csv(str(year) + "dataMatrix.csv")
results_matrix.to_csv(str(year) + "resultsMatrix.csv")
vegas_predictions.to_csv(str(year) + "vegasPredictions.csv")
print(str(year) + ": Done")
return data_matrix, results_matrix, vegas_predictions