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sportsdataverse.nfl package

Submodules​

sportsdataverse.nfl.model_vars module​

sportsdataverse.nfl.nfl_loaders module​

sportsdataverse.nfl.nfl_loaders.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.nfl_loaders.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.nfl_loaders.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.nfl_loaders.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.nfl_loaders.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.

sportsdataverse.nfl.nfl_pbp module​

class sportsdataverse.nfl.nfl_pbp.NFLPlayProcess(gameId=0, raw=False, path_to_json='/')​

Bases: object

__init__(gameId=0, raw=False, path_to_json='/')​

Initialize self. See help(type(self)) for accurate signature.

create_box_score()​

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(gameId=401256137).espn_nfl_pbp()

gameId( = 0)​

nfl_pbp_disk()​

path_to_json( = '/')​

ran_cleaning_pipeline( = False)​

ran_pipeline( = False)​

raw( = False)​

run_cleaning_pipeline()​

run_processing_pipeline()​

sportsdataverse.nfl.nfl_schedule module​

sportsdataverse.nfl.nfl_schedule.espn_nfl_calendar(season=None, ondays=None)​

espn_nfl_calendar - look up the NFL 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.nfl.nfl_schedule.espn_nfl_schedule(dates=None, week=None, season_type=None, limit=500)​

espn_nfl_schedule - look up the NFL schedule for a given season

Args:

dates (int): Used to define different seasons. 2002 is the earliest available season.
week (int): Week of the schedule.
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.nfl.nfl_teams module​

sportsdataverse.nfl.nfl_teams.espn_nfl_teams()​

espn_nfl_teams - look up NFL teams

Returns:

pd.DataFrame: Pandas dataframe containing teams for the requested league.

Module contents​