-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathget_game.py
172 lines (150 loc) · 8.37 KB
/
get_game.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
import requests
import json
import pandas as pd
import numpy as np
import datetime as dt
import os.path
def get_box_score(box_url,headers,game_id):
r= requests.get(box_url, headers=headers, timeout = 7)
data = json.loads(r.text)
box = pd.DataFrame.from_dict(data['resultSets'][0]['rowSet'])
col_names = data['resultSets'][0]['headers']
box.columns = col_names
box.columns = box.columns.str.lower()
box.to_csv(f'box_scores/box_{game_id}.csv')
return box
def get_pbp(pbp_url,headers):
r= requests.get(pbp_url, headers=headers, timeout = 7)
data = json.loads(r.text)
pbp = pd.DataFrame.from_dict(data['resultSets'][0]['rowSet'])
col_names = data['resultSets'][0]['headers']
pbp.columns = col_names
pbp.columns = pbp.columns.str.lower()
pbp_times = pbp['pctimestring'].str.split(':', expand=True)
pbp_times[0] = pbp_times[0].astype(str).astype(int)
pbp_times[1] = pbp_times[1].astype(str).astype(int)
pbp['timeinseconds'] = (pbp_times[0]*60) + pbp_times[1]
pbp['play_elapsed_time'] = pbp['timeinseconds'].shift(1) - pbp['timeinseconds']
pbp['play_elapsed_time'] = pbp['play_elapsed_time'].fillna(0)
pbp['play_elapsed_time'] = np.where(pbp['period'] != pbp['period'].shift(1), 0, pbp['play_elapsed_time'])
pbp['total_elapsed_time'] = pbp.groupby(['game_id'])['play_elapsed_time'].cumsum()
pbp['max_time'] = pbp.groupby('game_id')['play_elapsed_time'].transform('sum')
pbp['time_remaining'] = pbp['max_time'] - pbp['total_elapsed_time']
pbp['scoremargin'] = np.where(pbp['scoremargin']=='TIE',0,pbp['scoremargin'])
pbp['scoremargin'] = pbp['scoremargin'].fillna(0).astype(int)
pbp = pbp[['game_id', 'eventnum', 'eventmsgtype', 'eventmsgactiontype', 'period',
'pctimestring', 'homedescription', 'neutraldescription',
'visitordescription', 'score', 'scoremargin',
'player1_id', 'player1_name', 'player1_team_abbreviation',
'player2_id', 'player2_name', 'player2_team_abbreviation',
'player3_id', 'player3_name', 'player3_team_abbreviation',
'timeinseconds', 'play_elapsed_time',
'total_elapsed_time', 'max_time', 'time_remaining']]
return pbp
def getQuarterStarters(quarter):
if quarter == 1:
start_range = 0
end_range = 50
elif quarter == 2:
start_range = 7201
end_range = 7493
elif quarter == 3:
start_range = 14410
end_range = 14840
elif quarter == 4:
start_range = 21621
end_range = 21913
starters_url = f'https://stats.nba.com/stats/boxscoretraditionalv2?EndPeriod=14&GameID={game_id}&RangeType=2&Season={season}&SeasonType={season_type}&StartPeriod=1&StartRange={str(start_range)}&EndRange={str(end_range)}'
r= requests.get(starters_url, headers=headers, timeout = 7)
data = json.loads(r.text)
starters = pd.DataFrame.from_dict(data['resultSets'][0]['rowSet'])
col_names = data['resultSets'][0]['headers']
starters.columns = col_names
starters.columns = starters.columns.str.lower()
return starters[['game_id', 'team_id', 'team_abbreviation', 'player_id',
'player_name']]
class Game():
def __init__(self,game_id,pbp_url,box_url,headers):
self.pbp = get_pbp(pbp_url,headers=headers)
self.box = get_box_score(box_url,headers=headers,game_id=game_id)
self.hteam = self.box.team_abbreviation.unique()[1]
self.ateam = self.box.team_abbreviation.unique()[0]
self.pbp['h_lineup'] = ''
self.pbp['a_lineup'] = ''
def compute_lineups(self):
#getting starters from boxscore df
print('home',self.hteam,'away',self.ateam)
self.h_starters = self.box.loc[(self.box.start_position != '') &
(self.box.team_abbreviation == self.hteam)].reset_index()['player_id'].to_list()
self.h_starters = sorted(self.h_starters)
self.a_starters = self.box.loc[(self.box.start_position != '') &
(self.box.team_abbreviation == self.ateam)].reset_index()['player_id'].to_list()
self.a_starters = sorted(self.a_starters)
#assigning starters to lineup for start of game
self.pbp.at[0,'h_lineup'] = self.h_starters
self.pbp.at[0,'a_lineup'] = self.a_starters
self.pbp.at[1,'h_lineup'] = self.h_starters
self.pbp.at[1,'a_lineup'] = self.a_starters
#assigning quarter starters from quarter box scores
for idx, row in self.pbp.iterrows():
if row.pctimestring == '12:00' and row.period != 1:
qstart = getQuarterStarters(row.period)
qstart_h = qstart.loc[qstart.team_abbreviation == self.hteam]
qstart_a = qstart.loc[qstart.team_abbreviation != self.hteam]
self.pbp.at[idx,'h_lineup'] = sorted(qstart_h.player_id.to_list())
self.pbp.at[idx,'a_lineup'] = sorted(qstart_a.player_id.to_list())
prev_h_lineup = self.h_starters.copy() # Initialize with the starting lineup
prev_a_lineup = self.a_starters.copy() # Initialize with the starting lineup
for idx, row in self.pbp.iterrows():
if row.pctimestring == '12:00' and row.period == 1:
h_lineup = sorted(self.h_starters)
a_lineup = sorted(self.a_starters)
elif row.pctimestring == '12:00' and row.period != 1:
h_lineup = sorted(row['h_lineup']) # Use the existing lineup for the beginning of the quarter
a_lineup = sorted(row['a_lineup']) # Use the existing lineup for the beginning of the quarter
else:
h_lineup = prev_h_lineup.copy() # Create a copy of the previous h_lineup
a_lineup = prev_a_lineup.copy() # Create a copy of the previous a_lineup
if isinstance(row['homedescription'], str) and row['homedescription'].startswith('SUB'):
try:
h_lineup.remove(row['player1_id'])
h_lineup.append(row['player2_id'])
except:
print(row.player1_id,row.player2_id,h_lineup,row.pctimestring,row.period)
if isinstance(row['visitordescription'], str) and row['visitordescription'].startswith('SUB'):
try:
a_lineup.remove(row['player1_id'])
a_lineup.append(row['player2_id'])
except:
print(row.player1_id,row.player2_id,a_lineup,row.pctimestring,row.period)
self.pbp.at[idx, 'h_lineup'] = sorted(h_lineup)
self.pbp.at[idx, 'a_lineup'] = sorted(a_lineup)
prev_h_lineup = h_lineup # Update the previous h_lineup for the next iteration
prev_a_lineup = a_lineup # Update the previous a_lineup for the next iteration
self.pbp['a_lineup'] = self.pbp['a_lineup'].apply(lambda x: tuple(x))
self.pbp['h_lineup'] = self.pbp['h_lineup'].apply(lambda x: tuple(x))
return
game_ids = pd.read_csv('game_ids.csv')
dubs = game_ids.loc[(game_ids.home=='GSW') | (game_ids.away=='GSW')]['game_id'].to_list()
season = '2022-23'
season_type = 'Regular+Season'
failed = []
for id in dubs[0:2]:
game_id = '00'+str(id)
path = f'pbp_raw/{game_id}_pbp.csv'
if os.path.isfile(path):
try:
print(game_id)
start_range = '0'
box_url = f'https://stats.nba.com/stats/boxscoretraditionalv2?EndPeriod=10&EndRange=28800&GameID={game_id}&RangeType=0&Season={season}&SeasonType={season_type}&StartPeriod=1&StartRange={start_range}'
pbp_url = f'https://stats.nba.com/stats/playbyplayv2?EndPeriod=10&EndRange=55800&GameID={game_id}&RangeType=2&Season={season}&SeasonType={season_type}&StartPeriod=1&StartRange={start_range}'
headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/117.0.0.0 Safari/537.36', 'x-nba-stats-origin': 'stats', 'x-nba-stats-token': 'true', 'Host':'stats.nba.com', 'Referer':f'https://stats.nba.com/game/{game_id}/'}
print(pbp_url)
x = Game(game_id=game_id,pbp_url=pbp_url,box_url=box_url,headers=headers)
x.compute_lineups()
print(f'{game_id} is done')
x.pbp.to_csv(f'pbp_raw/{game_id}_pbp.csv')
except:
failed.append(game_id)
failed_ids = pd.DataFrame(failed)
failed_ids.to_csv('failed_ids.csv',index=False)