def play_off_picture(self,
idx_data,
league_id=enums.LeagueID.Default,
season_id=enums.Season.Default):
"""
Get information on how current playoff matchups and conference standings are.
:param idx_data: the index to retrieve data from json.
:type idx_data: int
:param league_id: league to filter for.
:type league_id: nba.enums.LeagueID
:param season_id: Season for which to get stat leaders.
:type season_id: nba.enums.Season
:returns: A view of playoff or standings, as show in idx_data table breakdown below.
:rtype: DataFrame
======== ======================= ==================================================================
idx_data Name Description
======== ======================= ==================================================================
0 EastConfPlayoffPicture Breakdown of how East Conference playoff matchups currently look.
1 WestConfPlayoffPicture Breakdown of how West Conference playoff matchups currently look.
2 EastConfStandings Current standing for East Conference.
3 WestConfStandings Current standing for West Conference.
4 EastConfRemainingGames Breakdown of games remaining in East Conference.
5 WestConfRemainingGames Breakdown of games remaining in East Conference.
======== ======================= ==================================================================
"""
params = clean_locals(locals())
endpoint = "playoffpicture"
r = self.request(endpoint, params)
df = self.process_response(r, idx_data, "resultSets")
return df
def team_roster(self, team_id, idx_data, season=enums.Season.Default):
"""
Get team roster breakdown.
:param team_id: id of the team whose roster to retrieve
:type team_id: int
:param idx_data: the index to retrieve data from json.
:type idx_data: int
:param season: season for which we require data.
:type season: str('%Y-%y')
:returns: roster breakdown of player details.
:rtype: Dataframe
======== ================== ====================================================================
idx_data Name Description
======== ================== ====================================================================
0 Players Players roster.
1 Coaches Coaching staff roster.
======== ================== ====================================================================
"""
params = clean_locals(locals())
endpoint = "commonteamroster"
r = self.request(endpoint, params)
df = self.process_response(r, idx_data, "resultSets")
return df
def other_leaders(
self,
idx_data,
league_id=enums.LeagueID.Default,
stat_type=enums.StatType.Default,
season=enums.Season.Default,
season_type=enums.SeasonType.Default,
player_or_team=enums.PlayerOrTeam.Default,
game_scope=enums.GameScope.Default,
player_scope=enums.PlayerScope.Default,
):
"""
Get top 5 players/teams by a particular stat type.
:param idx_data: the index to retrieve data from json.
:type idx_data: int
:param league_id: league to filter for.
:type league_id: nba.enums.LeagueID
:param stat_type: Stat to sort leaders table by.
:type stat_type: nba.enums.StatType
:param season: Season for which to get stat leaders.
:type season: nba.enums.Season
:param season_type: Regular Season or Playoffs.
:type season_type: nba.enums.SeasonType
:param player_or_team: whether to get individual players or by team.
:type player_or_team: nba.enums.PlayerOrTeam
:param game_scope: what games to include in the data.
:type game_scope: nba.enums.GameScope
:param player_scope: filter by rookies only or all players
:type player_scope: nba.enums.PlayerScope
:returns: top 5 players for given stat type, as defined below by idx_data.
:rtype: DataFrame
======== =============== ==================================================================
idx_data Name Description
======== =============== ==================================================================
0 HomePageStat1 Traditional=PTS, Advanced=OFF_RATING, Tracking=DIST_MILES
1 HomePageStat2 Traditional=REB, Advanced=DEF_RATING, Tracking=AST_POINTS_CREATED
2 HomePageStat3 Traditional=AST, Advanced=NET_RATING, Tracking=DRIVES
3 HomePageStat4 Traditional=STL, Advanced=PIE, Tracking=NUM_TOUCHES
4 HomePageStat5 Traditional=FG_PCT, Advanced=REB_PCT, Tracking=POST_TOUCHES
5 HomePageStat6 Traditional=FT_PCT, Advanced=AST_PCT, Tracking=REB_CONTEST
6 HomePageStat7 Traditional=FG3_PCT, Advanced=TS_PCT, Tracking=CATCH_SHOOT_PTS
7 HomePageStat8 Traditional=BLK, Advanced=EFG_PCT, Tracking=PULL_UP_PTS
======== =============== ==================================================================
"""
params = clean_locals(locals())
endpoint = "homepagev2"
r = self.request(endpoint, params)
df = self.process_response(r, idx_data, "resultSets")
return df
def summary(
self,
game_id,
idx_data,
start_period=enums.StartPeriod.Default,
end_period=enums.EndPeriod.Default,
start_range=enums.StartRange.Default,
end_range=enums.EndRange.Default,
range_type=enums.RangeType.Default,
):
"""
Get high level game summary stats for a given game.
:param game_id: id for the game to get data for.
:type game_id: str
:param idx_data: the index to retrieve data from json.
:type idx_data: int
:param start_period: filter starting quarter to retrieve data for.
:type start_period: nba.nba.bin.enums.StartPeriod
:param end_period: filter upper quarter cutoff for data.
:type end_period: nba.nba.bin.enums.EndPeriod
:param start_range: mandatory in url build, appear to have no effect.
:type start_range: nba.nba.bin.enums.StartRange
:param end_range: mandatory in url build, appear to have no effect.
:type end_range: nba.nba.bin.enums.EndRange
:param range_type: mandatory in url build, appear to have no effect.
:type range_type: nba.nba.bin.enums.RangeType
:returns: high level game information, as defined below by idx_data table below.
:rtype: Dataframe
======== ================ ==================================================
idx_data Name Description
======== ================ ==================================================
0 GameSummary High level overview of game information.
1 OtherStats Other high level game stats.
2 Officials Officials names and id's.
3 InactivePlayers Players not on roster for game.
4 GameInfo Date, attendance, time.
5 LineScore Scores by period.
6 LastMeeting Most recent meeting score and game info.
7 SeasonSeries Series results so far this season.
8 AvailableVideo Availability by video type.
======== ================ ==================================================
"""
params = clean_locals(locals())
endpoint = "boxscoresummaryv2"
r = self.request(endpoint, params)
df = self.process_response(r, idx_data, "resultSets")
return df
def history(self, league_id=enums.LeagueID.Default):
"""
Breakdown of pick number and player data for historical drafts.
:param league_id: define league to look at, nba.
:type league_id: nba.enums.LeagueID
:returns: Player pick numbers for historic drafts.
:rtype: Dataframe
"""
params = clean_locals(locals())
endpoint = "drafthistory"
r = self.request(endpoint, params)
df = self.process_response(r, 0, "resultSets")
return df
def player_info(self, player_id):
"""
Get detailed information for a player.
:param player_id: id of player to get information for.
:type player_id: int
:returns: detailed player information.
:rtype: Dataframe
"""
params = clean_locals(locals())
endpoint = "commonplayerinfo"
r = self.request(endpoint, params)
df = self.process_response(r, 0, "resultSets")
return df
def leaders_tiles(
self,
idx_data,
league_id=enums.LeagueID.Default,
stat=enums.Stat.Default,
season=enums.Season.Default,
season_type=enums.SeasonType.Default,
player_or_team=enums.PlayerOrTeam.Default,
game_scope=enums.GameScope.Default,
player_scope=enums.PlayerScope.Default,
):
"""
Get top 5 players/teams by a particular stat.
:param idx_data: the index to retrieve data from json.
:type idx_data: int
:param league_id: league to filter for.
:type league_id: nba.enums.LeagueID
:param stat: Stat to sort leaders table by.
:type stat: nba.enums.Stat
:param season: Season for which to get stat leaders.
:type season: nba.enums.Season
:param season_type: Regular Season or Playoffs.
:type season_type: nba.enums.SeasonType
:param player_or_team: whether to get individual players or by team.
:type player_or_team: nba.enums.PlayerOrTeam
:param game_scope: what games to include in the data.
:type game_scope: nba.enums.GameScope
:param player_scope: filter by rookies only or all players
:type player_scope: nba.enums.PlayerScope
:returns: data for specified filters, as defined below by idx_data.
:rtype: DataFrame
======== ================== ====================================================
idx_data Name Description
======== ================== ====================================================
0 LeadersTiles Top 5 players/teams by stat specified with id info.
1 AllTimeSeasonHigh Details of the all time high of the stat specified.
2 LastSeasonHigh Details of prior seasons high of stat specified.
3 LastSeasonHigh Details of prior seasons low of stat specified.
======== ================== ====================================================
"""
params = clean_locals(locals())
endpoint = "leaderstiles"
r = self.request(endpoint, params)
df = self.process_response(r, idx_data, "resultSet")
return df
def leaders(
self,
idx_data,
league_id=enums.LeagueID.Default,
stat_category=enums.StatCategory.Default,
season=enums.Season.Default,
season_type=enums.SeasonType.Default,
player_or_team=enums.PlayerOrTeam.Default,
game_scope=enums.GameScope.Default,
player_scope=enums.PlayerScope.Default,
):
"""
Get top 5 players/teams by a particular stat.
:param idx_data: the index to retrieve data from json.
:type idx_data: int
:param league_id: league to filter for.
:type league_id: nba.enums.LeagueID
:param stat_category: Stat to sort leaders table by.
:type stat_category: nba.enums.StatCategory
:param season: Season for which to get stat leaders.
:type season: nba.enums.Season
:param season_type: Regular Season or Playoffs.
:type season_type: nba.enums.SeasonType
:param player_or_team: whether to get individual players or by team.
:type player_or_team: nba.enums.PlayerOrTeam
:param game_scope: what games to include in the data.
:type game_scope: nba.enums.GameScope
:param player_scope: filter by rookies only or all players
:type player_scope: nba.enums.PlayerScope
:returns: data for specified filters, as defined below by idx_data.
:rtype: DataFrame
======== ================ ==================================================
idx_data Name Description
======== ================ ==================================================
0 HomePageLeaders Top 5 players/teams by stat specified.
1 LeagueAverage League average of the stat specified.
2 LeagueMax League max of each stat column.
======== ================ ==================================================
"""
params = clean_locals(locals())
endpoint = "homepageleaders"
r = self.request(endpoint, params)
df = self.process_response(r, idx_data, "resultSets")
return df
def combine_stats(self, league_id=enums.LeagueID.Default, season_year="2016-17"):
"""
Get combine results for a draft year.
:param league_id: define league to look at, nba.
:type league_id: nba.enums.LeagueID
:param season_year: draft season.
:type season_year: str('%Y-%y')
:returns: Combine results by player.
:rtype: Dataframe
"""
params = clean_locals(locals())
endpoint = "draftcombinestats"
r = self.request(endpoint, params)
df = self.process_response(r, 0, "resultSets")
return df
def get_moments(self, game_id, event_id):
"""
***Blocked Cannot Access***
Get location moments for each player throughout a single game event.
:param game_id: ID of the game to get location data from.
:type game_id: str
:param event_id: ID of specific game event.
:type event_id: int
:returns: location data for each snapshot in the event.
:rtype: DataFrame
"""
raise DeprecationWarning("This endpoint has been closed to public access")
endpoint = "locations_getmoments"
params = clean_locals(locals())
r = self.request(endpoint, params)
if len(r) > 0:
try:
headers = [
"TeamID",
"PlayerID",
"x_loc",
"y_loc",
"Radius",
"MomentID",
"GameClock",
"ShotClock",
"EventID",
]
player_moments = []
moments = r["moments"]
for moment in moments:
for player in moment[5]:
player.extend(
(moments.index(moment), moment[2], moment[3], event_id)
)
player_moments.append(player)
df = pd.DataFrame(player_moments, columns=headers)
except:
df = pd.DataFrame()
else:
df = pd.DataFrame()
return df
def usage(
self,
game_id,
idx_data,
start_period=enums.StartPeriod.Default,
end_period=enums.EndPeriod.Default,
start_range=enums.StartRange.Default,
end_range=enums.EndRange.Default,
range_type=enums.RangeType.Default,
):
"""
Get usage stats for a given game.
:param game_id: id for the game to get data for.
:type game_id: str
:param idx_data: the index to retrieve data from json.
:type idx_data: int
:param start_period: filter starting quarter to retrieve data for.
:type start_period: nba.nba.bin.enums.StartPeriod
:param end_period: filter upper quarter cutoff for data.
:type end_period: nba.nba.bin.enums.EndPeriod
:param start_range: mandatory in url build, appear to have no effect.
:type start_range: nba.nba.bin.enums.StartRange
:param end_range: mandatory in url build, appear to have no effect.
:type end_range: nba.nba.bin.enums.EndRange
:param range_type: mandatory in url build, appear to have no effect.
:type range_type: nba.nba.bin.enums.RangeType
:returns: Usage stats on a player/team, as defined below by idx_data.
:rtype: Dataframe
======== ================ ==================================================
idx_data Name Description
======== ================ ==================================================
0 sqlPlayersUsage Usage stats on an individual player basis.
1 sqlTeamsUsage Usage stats on a team basis.
======== ================ ==================================================
"""
params = clean_locals(locals())
endpoint = "boxscoreusagev2"
r = self.request(endpoint, params)
df = self.process_response(r, idx_data, "resultSets")
return df
def play_off_series(self,
league_id=enums.LeagueID.Default,
season=enums.Season.Default):
"""
Get playoff series match ups for a given season.
:param league_id: league to retrieve data for.
:type league_id: str
:param season: Season for which we require data.
:type season: str('%Y-%y')
:returns: match up by home/away team id and series id.
:rtype: Dataframe
"""
params = clean_locals(locals())
endpoint = "commonplayoffseries"
r = self.request(endpoint, params)
df = self.process_response(r, 0, "resultSets")
return df
def combine_player_anthropology(
self, league_id=enums.LeagueID.Default, season_year="2016-17"
):
"""
Detailed breakdown of players measurements and physical stats.
:param league_id: define league to look at, nba.
:type league_id: nba.enums.LeagueID
:param season_year: draft season.
:type season_year: str('%Y-%y')
:returns: Measurements and physical information by player.
:rtype: Dataframe
"""
params = clean_locals(locals())
endpoint = "draftcombineplayeranthro"
r = self.request(endpoint, params)
df = self.process_response(r, 0, "resultSets")
return df
def combine_stationary_shooting(
self, league_id=enums.LeagueID.Default, season_year="2016-17"
):
"""
Moving shooting scores broken down by movement type.
:param league_id: define league to look at, nba.
:type league_id: nba.enums.LeagueID
:param season_year: draft season.
:type season_year: str('%Y-%y')
:returns: Movement shooting results by player.
:rtype: Dataframe
"""
params = clean_locals(locals())
endpoint = "draftcombinenonstationaryshooting"
r = self.request(endpoint, params)
df = self.process_response(r, 0, "resultSets")
return df
def video_status(
self,
game_date=datetime.datetime.today().strftime("%Y-%m-%d"),
league_id=enums.LeagueID.Default,
):
"""
Breakdown of which games are available on video on a given date.
:param game_date: date to check.
:type game_date: str('%Y-%m-%d')
:param league_id: league to filter for.
:type league_id: nba.enums.LeagueID
:returns: games on the given date and whether they are available on video.
:rtype: DataFrame
"""
params = clean_locals(locals())
endpoint = "videoStatus"
r = self.request(endpoint, params)
df = self.process_response(r, 0, "resultSets")
return df
def scoreboard(
self, game_date, idx_data, day_off_set=0, league_id=enums.LeagueID.Default
):
"""
Get the scoreboard and game data from a give date/date with offset.
:param game_date: reference date to get data for.
:type game_date: str('%Y-%m-%d')
:param idx_data: the index to retrieve data from json.
:type idx_data: int
:param day_off_set: Number days prior to GameDate to get data for.
:type day_off_set: int
:param league_id: league to retrieve data for.
:type league_id: str
:returns:
:rtype: DataFrame
======== ======================= ======================================================
idx_data Name Description
======== ======================= ======================================================
0 GameHeader Overview of games returned.
1 LineScore Score by period on a team basis and some basic stats.
2 SeriesStandings Season series current standing.
3 LastMeeting Last game info id, time, and scores
4 EastConfStandingsByDay Full standings for the Eastern Conference.
5 WestConfStandingsByDay Full standings for the Eastern Conference.
6 Available Whether video is available for each game.
7 TeamLeaders Top players for each team by basic stats.
8 TicketLinks Links to buy tickets.
9 WinProbability Probability of team winning, often empty.
======== ======================= ======================================================
"""
params = clean_locals(locals())
endpoint = "scoreboardV2"
r = self.request(endpoint, params, referer="scores")
df = self.process_response(r, idx_data, "resultSets")
return df
def all_players(
self,
league_id=enums.LeagueID.Default,
season=enums.Season.Default,
is_only_current_season=1,
):
"""
Get individual player details.
:param league_id: league to retrieve data for.
:type league_id: str
:param season: Season for which we require data.
:type season: str('%Y-%y')
:param is_only_current_season: define whether to only get players on a roster in current season.
:type is_only_current_season: bool(1|0)
:returns: player information.
:rtype: Dataframe
"""
params = clean_locals(locals())
endpoint = "commonallplayers"
r = self.request(endpoint, params)
df = self.process_response(r, 0, "resultSets")
return df
