def test_outputting_2019_regular_season_box_scores_for_avery_bradley_as_csv(
self):
regular_season_player_box_scores(
player_identifier="bradlav01",
season_end_year=2019,
output_type=OutputType.CSV,
output_file_path="./test-avery-2019.csv")
def set_season_schedule(player_ids):
df = pd.DataFrame()
for id in player_ids:
client.regular_season_player_box_scores(
player_identifier=id,
season_end_year=2020,
output_type=OutputType.CSV,
output_file_path=f"./csv/boxscores/{id}_box_scores.csv")
for id in player_ids:
df_season_schedule = pd.read_csv(
f"./csv/boxscores/{id}_box_scores.csv")
df_season_schedule['slug'] = id
df = pd.concat([df, df_season_schedule])
df['date'] = pd.to_datetime(df['date'])
dates = df['date']
dates = dates.reset_index()
dates = dates.date.unique()
dates.sort()
last_game_date = pd.Timestamp((max(dates))).to_datetime64()
game_fifteen_date = pd.Timestamp(dates[-14]).to_datetime64()
boxscores = (df.loc[(df['date'] >= game_fifteen_date)
& (df['date'] <= last_game_date)])
boxscores = boxscores.reset_index()
return boxscores
def test_outputting_2019_regular_season_box_scores_for_avery_bradley_as_csv(self):
output_file_path = os.path.join(
os.path.dirname(__file__),
"./output/test-avery-2019.csv",
)
regular_season_player_box_scores(
player_identifier="bradlav01",
season_end_year=2019,
output_type=OutputType.CSV,
output_file_path=output_file_path,
)
def test_get_first_20202_regular_season_box_score_for_russell_westbrook(
self):
result = regular_season_player_box_scores(
player_identifier="westbru01", season_end_year=2020)
self.assertEqual(
datetime.strptime("2019-10-24", "%Y-%m-%d").date(),
result[0]["date"])
self.assertEqual(Team.HOUSTON_ROCKETS, result[0]["team"])
self.assertEqual(Outcome.LOSS, result[0]["outcome"])
self.assertEqual(1972, result[0]["seconds_played"])
self.assertEqual(Team.MILWAUKEE_BUCKS, result[0]["opponent"])
self.assertEqual(7, result[0]["made_field_goals"])
self.assertEqual(17, result[0]["attempted_field_goals"])
self.assertEqual(3, result[0]["made_three_point_field_goals"])
self.assertEqual(7, result[0]["attempted_three_point_field_goals"])
self.assertEqual(7, result[0]["made_free_throws"])
self.assertEqual(11, result[0]["attempted_free_throws"])
self.assertEqual(4, result[0]["offensive_rebounds"])
self.assertEqual(12, result[0]["defensive_rebounds"])
self.assertEqual(7, result[0]["assists"])
self.assertEqual(2, result[0]["steals"])
self.assertEqual(1, result[0]["blocks"])
self.assertEqual(3, result[0]["turnovers"])
self.assertEqual(3, result[0]["personal_fouls"])
self.assertEqual(24, result[0]["points_scored"])
self.assertEqual(23.1, result[0]["game_score"])
self.assertEqual(0, result[0]["plus_minus"])
def test_outputting_2019_regular_season_box_scores_for_avery_bradley_as_json(self):
results = regular_season_player_box_scores(
player_identifier="bradlav01",
season_end_year=2019,
output_type=OutputType.JSON,
)
self.assertIsNotNone(results)
self.assertEqual(63, len(json.loads(results)))
def getSeasonHigh(season):
seasonHigh = client.regular_season_player_box_scores(
player_identifier="cartevi01",
season_end_year=season,
)
gameTotals = [dict_item['points_scored'] for dict_item in seasonHigh]
return max(gameTotals)
def test_get_season_box_scores_removes_games_that_player_did_not_participate_in(self):
# Jabari Brown was a DNP in his first game in the gamelog for the 2014-2015 season
# https://www.basketball-reference.com/players/b/brownja01/gamelog/2015
# The date for the DNP was 2015-03-10 while the first game he was active was on 2015-03-12
# The first game that is returned should be on 2015-03-12
results = regular_season_player_box_scores(player_identifier="brownja01", season_end_year=2015)
self.assertIsNotNone(results)
self.assertEqual(19, len(results))
self.assertEqual(datetime.strptime("2015-03-12", "%Y-%m-%d").date(), results[0]["date"])
def test_outputting_2019_regular_season_box_scores_for_avery_bradley_as_csv(
self):
output_file_path = os.path.join(
os.path.dirname(__file__),
"./output/test-avery-2019.csv",
)
expected_file_path = os.path.join(
os.path.dirname(__file__), "./output/expected/test-avery-2019.csv")
regular_season_player_box_scores(
player_identifier="bradlav01",
season_end_year=2019,
output_type=OutputType.CSV,
output_file_path=output_file_path,
)
with open(output_file_path, 'r', encoding="utf8") as output_file, \
open(expected_file_path, 'r', encoding="utf8") as expected_file:
output_lines = output_file.readlines()
expected_lines = expected_file.readlines()
self.assertEqual(output_lines, expected_lines)
os.remove(output_file_path)
def get_player_boxscores(starting_year, year_range, player):
player_avg = 0
total_games_vs_opp = 0
for val in range(year_range):
try:
boxscores = client.regular_season_player_box_scores(
player_identifier=play['identifier'],
season_end_year=starting_year + val,
)
except client.InvalidPlayerAndSeason:
continue
for game in boxscores:
if game['opponent'].name == opp:
player_avg += FantasySites.calculate_fantasy_value(
game, fantasy_site)
total_games_vs_opp += 1
return player_avg / total_games_vs_opp, total_games_vs_opp
def player_stats(value):
data = []
for i in range(2020, 1990, -1):
total_assists = 0
total_steals = 0
total_blocks = 0
total_rebounds = 0
total_points = 0
total_seconds_played = 0
try:
current_season = client.regular_season_player_box_scores(
player_identifier=value, season_end_year=i)
for game in current_season:
total_assists += game["assists"]
total_steals += game["steals"]
total_blocks += game["blocks"]
total_rebounds += game["offensive_rebounds"] + game[
"defensive_rebounds"]
total_points += game["points_scored"]
total_seconds_played += game["seconds_played"]
total_assists /= len(current_season)
total_steals /= len(current_season)
total_blocks /= len(current_season)
total_rebounds /= len(current_season)
total_points /= len(current_season)
total_seconds_played /= len(current_season)
total_seconds_played /= 60
data.append({
"season": i,
"assist": total_assists,
"steal": total_steals,
"block": total_blocks,
"rebound": total_rebounds,
"point": total_points,
"minutes": total_seconds_played
})
except InvalidPlayerAndSeason:
break
return data
from basketball_reference_web_scraper import client
from basketball_reference_web_scraper.data import OutputType
import csv
import sys
bbref_name_map = {}
with open('./nba/inputs/{}/bbref.csv'.format(sys.argv[1]), 'rt') as f:
data = csv.reader(f)
for row in data:
if row[0] == 'Player Name':
continue
else:
bbref_name_map[row[0]] = row[1]
for name in bbref_name_map.keys():
print(name.replace(" ", "").replace(".", "").lower())
client.regular_season_player_box_scores(
player_identifier=bbref_name_map[name],
season_end_year=sys.argv[2],
output_type=OutputType.CSV,
output_file_path="./nba/inputs/{}/players/{}.csv".format(
sys.argv[1],
name.replace(" ", "").replace(".", "").lower()))
season_end_year=2020,
output_type=OutputType.CSV,
output_file_path=
"C:\\Users\\NWHAL\\Documents\\nba_project\\2020_player_season_totals.csv"
)
print("collecting advanced player stats")
client.players_advanced_season_totals(
season_end_year=2020,
output_type=OutputType.CSV,
output_file_path=
"C:\\Users\\NWHAL\\Documents\\nba_project\\2020_advanced_player_season_totals.csv"
)
'''client.play_by_play(
home_team=Team.BOSTON_CELTICS,
year=2018, month=10, day=16,
output_type=OutputType.CSV,
output_file_path="./2018_10_06_BOS_PBP.csv"
)
client.regular_season_player_box_scores(
player_identifier="westbru01",
season_end_year=2018,
output_type=OutputType.CSV,
output_file_path="./2017_2018_russell_westbrook_regular_season_box_scores.csv"
)
client.search(
term="Ko",
def test_get_2019_regular_season_box_scores_for_russell_westbrook(self):
result = regular_season_player_box_scores(player_identifier="westbru01", season_end_year=2019)
self.assertIsNotNone(result)
self.assertEqual(len(result), 73)
def get_player_box_scores(player_slug_year):
'''
Get game by game player box scores.
Input:
player_slug_year: pandas data frame of name, slug, and season_end_year
(see the function find_player_name_active_years for more info)
Returns:
player_game_raw_data: game by game box score data for every player queried.
Returns raw data.
'''
player_slug_year = player_slug_year.reset_index()
player_slug_year = player_slug_year.drop(columns=['index'])
player_game_raw_data = pd.DataFrame()
counter = 0
error_counter = 0
error_gate = 0
while counter < len(player_slug_year):
player_name = player_slug_year['name'][counter]
identifier = player_slug_year['slug'][counter]
year = player_slug_year['season_end_year'][counter]
try:
temp = pd.DataFrame(
client.regular_season_player_box_scores(
player_identifier=identifier, season_end_year=year))
temp['name'] = player_name
temp['slug'] = identifier
temp['season_end_year'] = year
player_game_raw_data = pd.concat([player_game_raw_data, temp],
axis=0)
except:
temp = pd.DataFrame()
if len(temp) > 0:
print(
f'Player {counter + 1} out of {len(player_slug_year)} completed'
)
counter += 1
else:
print(
f'!!Player {counter + 1} out of {len(player_slug_year)} retrying'
)
from basketball_reference_web_scraper import client
time.sleep(5)
error_counter += 1
if error_counter == 9:
print(
f'!!SKIPPED Player {counter + 1} out of {len(player_slug_year)} retrying'
)
counter += 1
error_counter = 0
error_gate = 1
player_game_raw_data = player_game_raw_data.reset_index()
player_game_raw_data = player_game_raw_data.drop(columns=['index'])
return player_game_raw_data, error_gate
from basketball_reference_web_scraper import client
from basketball_reference_web_scraper.data import OutputType, Team
print(client.season_schedule(season_end_year=2021))
client.players_advanced_season_totals(
season_end_year=2018,
output_type=OutputType.CSV,
output_file_path="./2017_2018_player_season_totals.csv"
)
client.play_by_play(
home_team=Team.BOSTON_CELTICS,
year=2018, month=10, day=16,
output_type=OutputType.CSV,
output_file_path="./2018_10_06_BOS_PBP.csv"
)
client.regular_season_player_box_scores(
player_identifier="westbru01",
season_end_year=2018,
output_type=OutputType.CSV,
output_file_path="./2017_2018_russell_westbrook_regular_season_box_scores.csv"
)
