def get_stats(name, stat_type='PER_GAME', season=0, playoffs=False, career=False):
try:
suffix1 = get_player_suffix(name, False).replace('/', '%2F')
for i in range(1, 6):
suffix = suffix1[:-6] + str(i) + ".html"
selector = stat_type.lower()
if playoffs:
selector = 'playoffs_'+selector
r = get(f'https://widgets.sports-reference.com/wg.fcgi?css=1&site=bbr&url={suffix}&div=div_{selector}')
if r.status_code==200:
soup = BeautifulSoup(r.content, 'html.parser')
table = soup.find('table')
df = pd.read_html(str(table))[0]
df.rename(columns={'Season': 'SEASON', 'Age': 'AGE',
'Tm': 'TEAM', 'Lg': 'LEAGUE', 'Pos': 'POS'}, inplace=True)
career_index = df[df['SEASON']=='Career'].index[0]
if career:
df = df.iloc[career_index+2:, :]
else:
df = df.iloc[:career_index, :]
df = df.reset_index().dropna(axis=1).drop('index', axis=1)
if season and season >= 1949 and season <= int(date.today().year):
season1 = str(season - 1) + "-" + str(season)[2:]
if len(df.loc[df['SEASON']==season1].head(1)) != 0:
return df.loc[df['SEASON']==season1].head(1).reset_index(drop=True)
else:
return df
except:
suffix1 = get_player_suffix(name, True).replace('/', '%2F')
for i in range(1, 6):
suffix = suffix1[:-6] + str(i) + ".html"
selector = stat_type.lower()
if playoffs:
selector = 'playoffs_'+selector
r = get(f'https://widgets.sports-reference.com/wg.fcgi?css=1&site=bbr&url={suffix}&div=div_{selector}')
if r.status_code==200:
soup = BeautifulSoup(r.content, 'html.parser')
table = soup.find('table')
df = pd.read_html(str(table))[0]
df.rename(columns={'Season': 'SEASON', 'Age': 'AGE',
'Tm': 'TEAM', 'Lg': 'LEAGUE', 'Pos': 'POS'}, inplace=True)
career_index = df[df['SEASON']=='Career'].index[0]
if career:
df = df.iloc[career_index+2:, :]
else:
df = df.iloc[:career_index, :]
df = df.reset_index().dropna(axis=1).drop('index', axis=1)
if season and season >= 1949 and season <= int(date.today().year):
season1 = str(season - 1) + "-" + str(season)[2:]
if len(df.loc[df['SEASON']==season1].head(1)) != 0:
return df.loc[df['SEASON']==season1].head(1).reset_index(drop=True)
else:
return df
return df
def get_stats(name, stat_type='PER_GAME', playoffs=False, career=False):
suffix = get_player_suffix(name).replace('/', '%2F')
selector = stat_type.lower()
if playoffs:
selector = 'playoffs_' + selector
r = get(
f'https://widgets.sports-reference.com/wg.fcgi?css=1&site=bbr&url={suffix}&div=div_{selector}'
)
if r.status_code == 200:
soup = BeautifulSoup(r.content, 'html.parser')
table = soup.find('table')
df = pd.read_html(str(table))[0]
df.rename(columns={
'Season': 'SEASON',
'Age': 'AGE',
'Tm': 'TEAM',
'Lg': 'LEAGUE',
'Pos': 'POS'
},
inplace=True)
if 'FG.1' in df.columns:
df.rename(columns={'FG.1': 'FG%'}, inplace=True)
if 'eFG' in df.columns:
df.rename(columns={'eFG': 'eFG%'}, inplace=True)
if 'FT.1' in df.columns:
df.rename(columns={'FT.1': 'FT%'}, inplace=True)
career_index = df[df['SEASON'] == 'Career'].index[0]
if career:
df = df.iloc[career_index + 2:, :]
else:
df = df.iloc[:career_index, :]
df = df.reset_index().drop('index', axis=1)
return df
def get_game_logs(name, start_date, end_date, playoffs=False):
suffix = get_player_suffix(name).replace('/', '%2F').replace('.html', '')
start_date_str = start_date
end_date_str = end_date
start_date = pd.to_datetime(start_date)
end_date = pd.to_datetime(end_date)
years = list(range(start_date.year, end_date.year+2))
if playoffs:
selector = 'div_pgl_basic_playoffs'
else:
selector = 'div_pgl_basic'
final_df = None
for year in years:
r = get(f'https://widgets.sports-reference.com/wg.fcgi?css=1&site=bbr&url={suffix}%2Fgamelog%2F{year}&div={selector}')
if r.status_code==200:
soup = BeautifulSoup(r.content, 'html.parser')
table = soup.find('table')
df = pd.read_html(str(table))[0]
df.rename(columns = {'Date': 'DATE', 'Age': 'AGE', 'Tm': 'TEAM', 'Unnamed: 5': 'HOME/AWAY', 'Opp': 'OPPONENT',
'Unnamed: 7': 'RESULT', 'GmSc': 'GAME_SCORE'}, inplace=True)
df['HOME/AWAY'] = df['HOME/AWAY'].apply(lambda x: 'AWAY' if x=='@' else 'HOME')
df = df[df['Rk']!='Rk']
df = df.drop(['Rk', 'G'], axis=1)
df = df.loc[(df['DATE'] >= start_date_str) & (df['DATE'] <= end_date_str)]
active_df = pd.DataFrame(columns = list(df.columns))
for index, row in df.iterrows():
if len(row['GS'])>1:
continue
active_df = active_df.append(row)
if final_df is None:
final_df = pd.DataFrame(columns=list(active_df.columns))
final_df = final_df.append(active_df)
return final_df
def get_stats(name, stat_type='PER_GAME', playoffs=False, career=False):
#credit: https://github.com/vishaalagartha/basketball_reference_scraper
try:
from utils import get_player_suffix
except:
from basketball_reference_scraper.utils import get_player_suffix
suffix = get_player_suffix(name).replace('/', '%2F')
selector = stat_type.lower()
if playoffs:
selector = 'playoffs_'+selector
r = get(f'https://widgets.sports-reference.com/wg.fcgi?css=1&site=bbr&url={suffix}&div=div_{selector}')
if r.status_code==200:
soup = BeautifulSoup(r.content, 'html.parser')
table = soup.find('table')
df = pd.read_html(str(table))[0]
df.rename(columns={'Season': 'SEASON', 'Age': 'AGE',
'Tm': 'TEAM', 'Lg': 'LEAGUE', 'Pos': 'POS'}, inplace=True)
career_index = df[df['SEASON']=='Career'].index[0]
if career:
df = df.iloc[career_index+2:, :]
else:
df = df.iloc[:career_index, :]
df = df.reset_index().dropna(axis=1).drop('index', axis=1)
return df
def get_game_logs(name, start_date, end_date, playoffs=False, num_games = None):
"""
Will get the raw gamelogs for a given player in the given date ranges
Args:
name (str): Name of player whose games you want
start_date (str): Inclusive start date of game logs in format 'YYYY-MM-DD'
end_date (str): Inclusive end date of game logs in format 'YYYY-MM-DD'
playoffs (bool): Whetehr or not to include playoff games
Returns:
returns a dataframe with a record of games between the dates, including categories ['Rk', 'G', 'DATE', 'AGE', 'TEAM', 'HOME/AWAY', 'OPPONENT', 'RESULT', 'GS', 'MP', 'FG', 'FGA', 'FG%', '3P', '3PA', '3P%', 'FT', 'FTA', 'FT%', 'ORB', 'DRB', 'TRB', 'AST', 'STL', 'BLK', 'TOV', 'PF', 'PTS', 'GAME_SCORE', '+/-']
"""
suffix = utils.get_player_suffix(name).replace('/', '%2F').replace('.html', '')
start_date_str = start_date
end_date_str = end_date
start_date = pd.to_datetime(start_date)
end_date = pd.to_datetime(end_date)
years = list(range(start_date.year, end_date.year+2))
if playoffs:
selector = 'div_pgl_basic_playoffs'
else:
selector = 'div_pgl_basic'
final_df = None
for year in years:
url = f'https://widgets.sports-reference.com/wg.fcgi?css=1&site=bbr&url={suffix}%2Fgamelog%2F{year}&div={selector}'
r = get(url)
if r.status_code==200:
soup = BeautifulSoup(r.content, 'html.parser')
table = soup.find('table')
try:
df = pd.read_html(str(table))[0]
except ValueError as e:
continue
df.rename(columns = {'Date': 'DATE', 'Age': 'AGE', 'Tm': 'TEAM', 'Unnamed: 5': 'HOME/AWAY', 'Opp': 'OPPONENT','Unnamed: 7': 'RESULT', 'GmSc': 'GAME_SCORE'}, inplace=True)
df['HOME/AWAY'] = df['HOME/AWAY'].apply(lambda x: 'AWAY' if x=='@' else 'HOME')
df = df[df['Rk']!='Rk']
try:
df = df.drop(['Unnamed: 30'], axis=1)
except Exception as e:
pass
df = df.loc[(df['DATE'] >= start_date_str) & (df['DATE'] <= end_date_str)]
active_df = pd.DataFrame(columns = list(df.columns))
for index, row in df.iterrows():
if len(row['GS'])>1:
empty_game = pd.DataFrame([[row['Rk'], row['G'], row['DATE'], row['AGE'], row['TEAM'], row['HOME/AWAY'], row['OPPONENT'], row['RESULT'], 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
empty_game.columns = list(df.columns)
active_df = active_df.append(empty_game)
continue
active_df = active_df.append(row)
if final_df is None:
final_df = pd.DataFrame(columns=list(active_df.columns))
final_df = final_df.append(active_df)
if num_games != None:
final_df = final_df[(final_df['Rk'].astype(int) <= num_games)]
return final_df
def get_game_logs(_name, year, playoffs=False, ask_matches=True):
name = lookup(_name, ask_matches)
suffix = get_player_suffix(name).replace('/', '%2F').replace('.html', '')
if playoffs:
selector = 'div_pgl_basic_playoffs'
else:
selector = 'div_pgl_basic'
r = get(f'https://widgets.sports-reference.com/wg.fcgi?css=1&site=bbr&url={suffix}%2Fgamelog%2F{year}%2F&div={selector}')
if r.status_code==200:
soup = BeautifulSoup(r.content, 'html.parser')
table = soup.find('table')
if table:
df = pd.read_html(str(table))[0]
df.rename(columns = {'Date': 'DATE', 'Age': 'AGE', 'Tm': 'TEAM', 'Unnamed: 5': 'HOME/AWAY', 'Opp': 'OPPONENT',
'Unnamed: 7': 'RESULT', 'GmSc': 'GAME_SCORE'}, inplace=True)
df['HOME/AWAY'] = df['HOME/AWAY'].apply(lambda x: 'AWAY' if x=='@' else 'HOME')
df = df[df['Rk']!='Rk']
df = df.drop(['Rk', 'G'], axis=1)
df['DATE'] = pd.to_datetime(df['DATE'])
df = df[df['GS'] == '1'].reset_index(drop=True)
return df
def get_player_headshot(name):
suffix = get_player_suffix(name)
jpg = suffix.split('/')[-1].replace('html', 'jpg')
url = 'https://d2cwpp38twqe55.cloudfront.net/req/202006192/images/players/' + jpg
return url
