NFL Function Index
sportsdataverse.nfl package
sportsdataverse.nfl.load_nfl_pbp(seasons: List[int])
Load NFL play by play data going back to 1999
Example:
nfl_df = sportsdataverse.nfl.load_nfl_pbp(seasons=range(1999,2021))
Args:
seasons (list): Used to define different seasons. 1999 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 1999.
sportsdataverse.nfl.load_nfl_player_stats()
Load NFL player stats data
Example:
nfl_df = sportsdataverse.nfl.load_nfl_player_stats()
Args:
Returns:
pd.DataFrame: Pandas dataframe containing player stats.
sportsdataverse.nfl.load_nfl_rosters()
Load NFL roster data for all seasons
Example:
nfl_df = sportsdataverse.nfl.load_nfl_rosters(seasons=range(1999,2021))
Returns:
pd.DataFrame: Pandas dataframe containing rosters available for the requested seasons.
sportsdataverse.nfl.load_nfl_schedule(seasons: List[int])
Load NFL schedule data
Example:
nfl_df = sportsdataverse.nfl.load_nfl_schedule(seasons=range(1999,2021))
Args:
seasons (list): Used to define different seasons. 1999 is the earliest available season.
Returns:
pd.DataFrame: Pandas dataframe containing the schedule for the requested seasons.
Raises:
ValueError: If season is less than 1999.
sportsdataverse.nfl.load_nfl_teams()
Load NFL team ID information and logos
Example:
nfl_df = sportsdataverse.nfl.load_nfl_teams()
Args:
Returns:
pd.DataFrame: Pandas dataframe containing teams available for the requested seasons.
class sportsdataverse.nfl.NFLPlayProcess(gameId=0)
Bases: object
__init__(gameId=0)
Initialize self. See help(type(self)) for accurate signature.
create_box_score()
gameId( = 0)
espn_nfl_pbp()
espn_nfl_pbp() - Pull the game by id - Data from API endpoints - nfl/playbyplay, nfl/summary
Args:
game_id (int): Unique game_id, can be obtained from nfl_schedule().
Returns:
Dict: Dictionary of game data with keys - “gameId”, “plays”, “boxscore”, “header”, “broadcasts”, “videos”,
“playByPlaySource”, “standings”, “leaders”, “timeouts”, “homeTeamSpread”, “overUnder”, “pickcenter”,
“againstTheSpread”, “odds”, “predictor”, “winprobability”, “espnWP”, “gameInfo”, “season”
Example:
nfl_df = sportsdataverse.nfl.NFLPlayProcess(game_id=401220403).espn_nfl_pbp()
ran_pipeline( = False)
run_processing_pipeline()
sportsdataverse.nfl.espn_nfl_calendar(season=None)
espn_nfl_calendar - look up the NFL calendar for a given season from ESPN
Args:
season (int): Used to define different seasons. 2002 is the earliest available season.
Returns:
pd.DataFrame: Pandas dataframe containing calendar dates for the requested season.
Raises:
ValueError: If season is less than 2002.
sportsdataverse.nfl.espn_nfl_schedule(dates=None, week=None, season_type=None)
espn_nfl_schedule - look up the NFL schedule for a given date from ESPN
Args:
dates (int): Used to define different seasons. 2002 is the earliest available season.
week (int): Used to define different weeks.
season_type (int): season type, 1 for pre-season, 2 for regular season, 3 for post-season, 4 for all-star, 5 for off-season
Returns:
pd.DataFrame: Pandas dataframe containing
schedule events for the requested season.