sportsdataverse.mbb package
Submodules
sportsdataverse.mbb.mbb_game_rosters module
sportsdataverse.mbb.mbb_game_rosters.espn_mbb_game_rosters(game_id: int, raw=False)
espn_mbb_game_rosters() - Pull the game by id.
Args:
game_id (int): Unique game_id, can be obtained from mbb_schedule().
Returns:
pd.DataFrame: Data frame of game roster data with columns:
‘athlete_id’, ‘athlete_uid’, ‘athlete_guid’, ‘athlete_type’,
‘first_name’, ‘last_name’, ‘full_name’, ‘athlete_display_name’,
‘short_name’, ‘weight’, ‘display_weight’, ‘height’, ‘display_height’,
‘age’, ‘date_of_birth’, ‘slug’, ‘jersey’, ‘linked’, ‘active’,
‘alternate_ids_sdr’, ‘birth_place_city’, ‘birth_place_state’,
‘birth_place_country’, ‘headshot_href’, ‘headshot_alt’,
‘experience_years’, ‘experience_display_value’,
‘experience_abbreviation’, ‘status_id’, ‘status_name’, ‘status_type’,
‘status_abbreviation’, ‘hand_type’, ‘hand_abbreviation’,
‘hand_display_value’, ‘draft_display_text’, ‘draft_round’, ‘draft_year’,
‘draft_selection’, ‘player_id’, ‘starter’, ‘valid’, ‘did_not_play’,
‘display_name’, ‘ejected’, ‘athlete_href’, ‘position_href’,
‘statistics_href’, ‘team_id’, ‘team_guid’, ‘team_uid’, ‘team_slug’,
‘team_location’, ‘team_name’, ‘team_nickname’, ‘team_abbreviation’,
‘team_display_name’, ‘team_short_display_name’, ‘team_color’,
‘team_alternate_color’, ‘is_active’, ‘is_all_star’,
‘team_alternate_ids_sdr’, ‘logo_href’, ‘logo_dark_href’, ‘game_id’
Example:
mbb_df = sportsdataverse.mbb.espn_mbb_game_rosters(game_id=401265031)
sportsdataverse.mbb.mbb_game_rosters.helper_mbb_athlete_items(teams_rosters)
sportsdataverse.mbb.mbb_game_rosters.helper_mbb_game_items(summary)
sportsdataverse.mbb.mbb_game_rosters.helper_mbb_roster_items(items, summary_url)
sportsdataverse.mbb.mbb_game_rosters.helper_mbb_team_items(items)
sportsdataverse.mbb.mbb_loaders module
sportsdataverse.mbb.mbb_loaders.load_mbb_pbp(seasons: List[int])
Load men’s college basketball play by play data going back to 2002
Example:
mbb_df = sportsdataverse.mbb.load_mbb_pbp(seasons=range(2002,2022))
Args:
seasons (list): Used to define different seasons. 2002 is the earliest available season.
Returns:
pd.DataFrame: Pandas dataframe containing the
play-by-plays available for the requested seasons.
Raises:
ValueError: If season is less than 2002.
sportsdataverse.mbb.mbb_loaders.load_mbb_player_boxscore(seasons: List[int])
Load men’s college basketball player boxscore data
Example:
mbb_df = sportsdataverse.mbb.load_mbb_player_boxscore(seasons=range(2002,2022))
Args:
seasons (list): Used to define different seasons. 2002 is the earliest available season.
Returns:
pd.DataFrame: Pandas dataframe containing the
player boxscores available for the requested seasons.
Raises:
ValueError: If season is less than 2002.
sportsdataverse.mbb.mbb_loaders.load_mbb_schedule(seasons: List[int])
Load men’s college basketball schedule data
Example:
mbb_df = sportsdataverse.mbb.load_mbb_schedule(seasons=range(2002,2022))
Args:
seasons (list): Used to define different seasons. 2002 is the earliest available season.
Returns:
pd.DataFrame: Pandas dataframe containing the
schedule for the requested seasons.
Raises:
ValueError: If season is less than 2002.
sportsdataverse.mbb.mbb_loaders.load_mbb_team_boxscore(seasons: List[int])
Load men’s college basketball team boxscore data
Example:
mbb_df = sportsdataverse.mbb.load_mbb_team_boxscore(seasons=range(2002,2022))
Args:
seasons (list): Used to define different seasons. 2002 is the earliest available season.
Returns:
pd.DataFrame: Pandas dataframe containing the
team boxscores available for the requested seasons.
Raises:
ValueError: If season is less than 2002.
sportsdataverse.mbb.mbb_pbp module
sportsdataverse.mbb.mbb_pbp.espn_mbb_pbp(game_id: int, raw=False)
espn_mbb_pbp() - Pull the game by id. Data from API endpoints: mens-college-basketball/playbyplay, mens-college-basketball/summary
Args:
game_id (int): Unique game_id, can be obtained from mbb_schedule().
Returns:
Dict: Dictionary of game data with keys: “gameId”, “plays”, “winprobability”, “boxscore”, “header”, “broadcasts”,
“videos”, “playByPlaySource”, “standings”, “leaders”, “timeouts”, “pickcenter”, “againstTheSpread”, “odds”, “predictor”,
“espnWP”, “gameInfo”, “season”
Example:
mbb_df = sportsdataverse.mbb.espn_mbb_pbp(game_id=401265031)
sportsdataverse.mbb.mbb_pbp.helper_mbb_pbp(game_id, pbp_txt)
sportsdataverse.mbb.mbb_pbp.helper_mbb_pbp_features(game_id, pbp_txt, gameSpread, homeFavorite, gameSpreadAvailable, homeTeamId, awayTeamId, homeTeamMascot, awayTeamMascot, homeTeamName, awayTeamName, homeTeamAbbrev, awayTeamAbbrev, homeTeamNameAlt, awayTeamNameAlt)
sportsdataverse.mbb.mbb_pbp.helper_mbb_pickcenter(pbp_txt)
sportsdataverse.mbb.mbb_pbp.mbb_pbp_disk(game_id, path_to_json)
sportsdataverse.mbb.mbb_schedule module
sportsdataverse.mbb.mbb_schedule.espn_mbb_calendar(season=None, ondays=None)
espn_mbb_calendar - look up the men’s college basketball calendar for a given season
Args:
season (int): Used to define different seasons. 2002 is the earliest available season.
ondays (boolean): Used to return dates for calendar ondays
Returns:
pd.DataFrame: Pandas dataframe containing
calendar dates for the requested season.
Raises:
ValueError: If season is less than 2002.
sportsdataverse.mbb.mbb_schedule.espn_mbb_schedule(dates=None, groups=50, season_type=None, limit=500)
espn_mbb_schedule - look up the men’s college basketball scheduler for a given season
Args:
dates (int): Used to define different seasons. 2002 is the earliest available season.
groups (int): Used to define different divisions. 50 is Division I, 51 is Division II/Division III.
season_type (int): 2 for regular season, 3 for post-season, 4 for off-season.
limit (int): number of records to return, default: 500.
Returns:
pd.DataFrame: Pandas dataframe containing schedule dates for the requested season.
sportsdataverse.mbb.mbb_schedule.most_recent_mbb_season()
sportsdataverse.mbb.mbb_teams module
sportsdataverse.mbb.mbb_teams.espn_mbb_teams(groups=None)
espn_mbb_teams - look up the men’s college basketball teams
Args:
groups (int): Used to define different divisions. 50 is Division I, 51 is Division II/Division III.
Returns:
pd.DataFrame: Pandas dataframe containing teams for the requested league.