def add_team_clusters_to_csv(input_filename, output_filename):
reader = csv.reader(open(input_filename, 'r'))
writer = csv.writer(open(output_filename, 'w'))
headers = reader.next()
headers.append('home_oclass')
headers.append('home_dclass')
headers.append('home_tclass')
headers.append('away_oclass')
headers.append('away_dclass')
headers.append('away_tclass')
writer.writerow(headers)
team_oclusters, off_gmm = compute_team_clusters('team_features_offense_w_id.csv')
team_dclusters, def_gmm = compute_team_clusters('team_features_defense_w_id.csv')
team_tclusters, tot_gmm = compute_team_clusters('team_features_combined.csv')
for line in reader:
home_team = int(line[3].strip())
away_team = int(line[4].strip())
home_oclass = find_member_in_clusters(team_oclusters, home_team)
home_dclass = find_member_in_clusters(team_dclusters, home_team)
home_tclass = find_member_in_clusters(team_tclusters, home_team)
away_oclass = find_member_in_clusters(team_oclusters, away_team)
away_dclass = find_member_in_clusters(team_dclusters, away_team)
away_tclass = find_member_in_clusters(team_tclusters, away_team)
writer.writerow(line + [home_oclass, home_dclass, home_tclass, away_oclass, away_dclass, away_tclass])
def add_team_clusters_to_csv(input_filename, output_filename):
reader = csv.reader(open(input_filename, 'r'))
writer = csv.writer(open(output_filename, 'w'))
headers = reader.next()
headers.append('home_oclass')
headers.append('home_dclass')
headers.append('home_tclass')
headers.append('away_oclass')
headers.append('away_dclass')
headers.append('away_tclass')
writer.writerow(headers)
team_oclusters, off_gmm = compute_team_clusters(
'team_features_offense_w_id.csv')
team_dclusters, def_gmm = compute_team_clusters(
'team_features_defense_w_id.csv')
team_tclusters, tot_gmm = compute_team_clusters(
'team_features_combined.csv')
for line in reader:
home_team = int(line[3].strip())
away_team = int(line[4].strip())
home_oclass = find_member_in_clusters(team_oclusters, home_team)
home_dclass = find_member_in_clusters(team_dclusters, home_team)
home_tclass = find_member_in_clusters(team_tclusters, home_team)
away_oclass = find_member_in_clusters(team_oclusters, away_team)
away_dclass = find_member_in_clusters(team_dclusters, away_team)
away_tclass = find_member_in_clusters(team_tclusters, away_team)
writer.writerow(line + [
home_oclass, home_dclass, home_tclass, away_oclass, away_dclass,
away_tclass
])
def construct_odds_csv(input_filename, output_filename):
reader = csv.reader(open(input_filename, 'r'))
stat_cats = ['PTS', 'FG%', '3P%', 'DRB%', 'ORB%', 'AST', 'BLK', 'STL',
'TOV', 'FT%', 'PIP', 'PTO', '2CP', 'FBP', 'PFL', 'DRTG', 'ORTG', 'REST']
stat_headers = {'PTS': 'points',
'FG%': 'field_goal_pct',
'3P%': '3_pt_pct',
'DRB%': 'def_reb_pct',
'ORB%': 'off_reb_pct',
'AST': 'assists',
'BLK': 'blocks',
'STL': 'steals',
'TOV': 'turnovers',
'FT%': 'free_throw_pct',
'PIP': 'pts_in_paint',
'PTO': 'pts_off_tov',
'2CP': '2nd_chance_pts',
'FBP': 'fast_break_pts',
'PFL': 'fouls',
'DRTG': 'def_rtg',
'ORTG': 'off_rtg'}
output_headers = reader.next() + ['home_points',
'home_field_goal_pct',
'home_3_pt_pct',
'home_def_reb_pct',
'home_off_reb_pct',
'home_assists',
'home_blocks',
'home_steals',
'home_turnovers',
'home_free_throw_pct',
'home_pts_in_paint',
'home_pts_off_tov',
'home_2nd_chance_pts',
'home_fast_break_pts',
'home_fouls',
'home_def_rtg',
'home_off_rtg',
'home_days_rest',
## features for individual players
## 7 offensive players, ranked by minutes
'home_p1_off',
'home_p2_off',
'home_p3_off',
'home_p4_off',
'home_p5_off',
'home_p6_off',
'home_p7_off',
## 7 defensive players, ranked by minutes
'home_p1_def',
'home_p2_def',
'home_p3_def',
'home_p4_def',
'home_p5_def',
'home_p6_def',
'home_p7_def',
## away team
'away_points',
'away_field_goal_pct',
'away_3_pt_pct',
'away_def_reb_pct',
'away_off_reb_pct',
'away_assists',
'away_blocks',
'away_steals',
'away_turnovers',
'away_free_throw_pct',
'away_pts_in_paint',
'away_pts_off_tov',
'away_2nd_chance_pts',
'away_fast_break_pts',
'away_fouls',
'away_def_rtg',
'away_off_rtg',
'away_days_rest',
## features for individual players
## 7 offensive players, ranked by minutes
'away_p1_off',
'away_p2_off',
'away_p3_off',
'away_p4_off',
'away_p5_off',
'away_p6_off',
'away_p7_off',
## 7 defensive players, ranked by minutes
'away_p1_def',
'away_p2_def',
'away_p3_def',
'away_p4_def',
'away_p5_def',
'away_p6_def',
'away_p7_def',]
off_data = pylab.genfromtxt('offense_clusters_w_id.csv', delimiter=',')
def_data = pylab.genfromtxt('defense_clusters_w_id.csv', delimiter=',')
print 'Clustering offense...'
player_oclusters, off_gmm = compute_player_clusters('offense_clusters_w_id.csv', clusters=10, method='GMM')
print 'Clustering defense...'
player_dclusters, def_gmm = compute_player_clusters('defense_clusters_w_id.csv', clusters=10, method='GMM')
print 'Constructing odds data...'
output_lines = [output_headers]
writer = csv.writer(open(output_filename, 'w'))
writer.writerow(output_headers)
for line in reader:
year = int(line[0].strip())
month = int(line[1].strip())
day = int(line[2].strip())
game_day = dt.date(year=year, month=month, day=day)
home_team = int(line[3].strip())
away_team = int(line[4].strip())
print game_day, home_team, away_team
try:
game_id = look_up_contest_id(game_day, home_team)
home_players = game_players(game_id, home_team)[0:7]
away_players = game_players(game_id, away_team)[0:7]
home_box, away_box = boxscore_stats(game_day, home_team)
# insert the home stats
for stat in stat_cats:
line.append(home_box[stat])
for hp in home_players:
player_oclass = find_member_in_clusters(player_oclusters, hp)
line.append(player_oclass)
for hp in home_players:
player_dclass = find_member_in_clusters(player_dclusters, hp)
line.append(player_dclass)
# insert the away stats
for stat in stat_cats:
line.append(away_box[stat])
for ap in away_players:
player_oclass = find_member_in_clusters(player_oclusters, ap)
line.append(player_oclass)
for ap in away_players:
player_dclass = find_member_in_clusters(player_dclusters, ap)
line.append(player_dclass)
except Exception as ex:
print ex
print 'Game not found... possibly a game was postponed/canceled'
writer.writerow(line)
output_lines.append(line)
def construct_odds_csv(input_filename, output_filename):
reader = csv.reader(open(input_filename, 'r'))
stat_cats = [
'PTS', 'FG%', '3P%', 'DRB%', 'ORB%', 'AST', 'BLK', 'STL', 'TOV', 'FT%',
'PIP', 'PTO', '2CP', 'FBP', 'PFL', 'DRTG', 'ORTG', 'REST'
]
stat_headers = {
'PTS': 'points',
'FG%': 'field_goal_pct',
'3P%': '3_pt_pct',
'DRB%': 'def_reb_pct',
'ORB%': 'off_reb_pct',
'AST': 'assists',
'BLK': 'blocks',
'STL': 'steals',
'TOV': 'turnovers',
'FT%': 'free_throw_pct',
'PIP': 'pts_in_paint',
'PTO': 'pts_off_tov',
'2CP': '2nd_chance_pts',
'FBP': 'fast_break_pts',
'PFL': 'fouls',
'DRTG': 'def_rtg',
'ORTG': 'off_rtg'
}
output_headers = reader.next() + [
'home_points',
'home_field_goal_pct',
'home_3_pt_pct',
'home_def_reb_pct',
'home_off_reb_pct',
'home_assists',
'home_blocks',
'home_steals',
'home_turnovers',
'home_free_throw_pct',
'home_pts_in_paint',
'home_pts_off_tov',
'home_2nd_chance_pts',
'home_fast_break_pts',
'home_fouls',
'home_def_rtg',
'home_off_rtg',
'home_days_rest',
## features for individual players
## 7 offensive players, ranked by minutes
'home_p1_off',
'home_p2_off',
'home_p3_off',
'home_p4_off',
'home_p5_off',
'home_p6_off',
'home_p7_off',
## 7 defensive players, ranked by minutes
'home_p1_def',
'home_p2_def',
'home_p3_def',
'home_p4_def',
'home_p5_def',
'home_p6_def',
'home_p7_def',
## away team
'away_points',
'away_field_goal_pct',
'away_3_pt_pct',
'away_def_reb_pct',
'away_off_reb_pct',
'away_assists',
'away_blocks',
'away_steals',
'away_turnovers',
'away_free_throw_pct',
'away_pts_in_paint',
'away_pts_off_tov',
'away_2nd_chance_pts',
'away_fast_break_pts',
'away_fouls',
'away_def_rtg',
'away_off_rtg',
'away_days_rest',
## features for individual players
## 7 offensive players, ranked by minutes
'away_p1_off',
'away_p2_off',
'away_p3_off',
'away_p4_off',
'away_p5_off',
'away_p6_off',
'away_p7_off',
## 7 defensive players, ranked by minutes
'away_p1_def',
'away_p2_def',
'away_p3_def',
'away_p4_def',
'away_p5_def',
'away_p6_def',
'away_p7_def',
]
off_data = pylab.genfromtxt('offense_clusters_w_id.csv', delimiter=',')
def_data = pylab.genfromtxt('defense_clusters_w_id.csv', delimiter=',')
print 'Clustering offense...'
player_oclusters, off_gmm = compute_player_clusters(
'offense_clusters_w_id.csv', clusters=10, method='GMM')
print 'Clustering defense...'
player_dclusters, def_gmm = compute_player_clusters(
'defense_clusters_w_id.csv', clusters=10, method='GMM')
print 'Constructing odds data...'
output_lines = [output_headers]
writer = csv.writer(open(output_filename, 'w'))
writer.writerow(output_headers)
for line in reader:
year = int(line[0].strip())
month = int(line[1].strip())
day = int(line[2].strip())
game_day = dt.date(year=year, month=month, day=day)
home_team = int(line[3].strip())
away_team = int(line[4].strip())
print game_day, home_team, away_team
try:
game_id = look_up_contest_id(game_day, home_team)
home_players = game_players(game_id, home_team)[0:7]
away_players = game_players(game_id, away_team)[0:7]
home_box, away_box = boxscore_stats(game_day, home_team)
# insert the home stats
for stat in stat_cats:
line.append(home_box[stat])
for hp in home_players:
player_oclass = find_member_in_clusters(player_oclusters, hp)
line.append(player_oclass)
for hp in home_players:
player_dclass = find_member_in_clusters(player_dclusters, hp)
line.append(player_dclass)
# insert the away stats
for stat in stat_cats:
line.append(away_box[stat])
for ap in away_players:
player_oclass = find_member_in_clusters(player_oclusters, ap)
line.append(player_oclass)
for ap in away_players:
player_dclass = find_member_in_clusters(player_dclusters, ap)
line.append(player_dclass)
except Exception as ex:
print ex
print 'Game not found... possibly a game was postponed/canceled'
writer.writerow(line)
output_lines.append(line)