CFB — additional Python functions — Fox Sports API

fox_cfb_boxscore

fox_cfb_boxscore(game_id: 'Union[int, str]', *, return_parsed: 'bool' = True, return_as_pandas: 'bool' = False, **kwargs: 'Any') -> "Union[pl.DataFrame, 'pd.DataFrame', Dict[str, Any]]"

Fox Sports CFB boxscore (long: one row per player-stat).

Endpoint: GET https://api.foxsports.com/bifrost/v1/cfb/event/{game_id}/data (the boxscore block).

Parameters

Parameter	Type	Default	Description
game_id	Union[int, str]		Fox Bifrost event id (e.g. "41616").
return_parsed	bool	True	If True (default) flatten the per-team stat tables to long form; if False return the raw JSON dict.
return_as_pandas	bool	False	If True return a pandas DataFrame; otherwise polars. Ignored when return_parsed=False.

Returns

A polars DataFrame (default), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False.

col_name	type	description
game_id	character	ESPN game identifier.
team	character	Team name.
stat_group	character
player	character	Player name.
athlete_id	character	ESPN athlete id.
stat	character
value	character	Metric value.

Example

from sportsdataverse.cfb import fox_cfb_boxscore
df = fox_cfb_boxscore("41616")

fox_cfb_event_matchup

fox_cfb_event_matchup(*args: 'Any', **kwargs: 'Any') -> 'Any'

Fox Sports cfb pregame team-stat comparison (one row per stat).

Wraps cfb/event/{game_id}/matchup.

Returns

A polars DataFrame (default), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False.

Example

from sportsdataverse.cfb import fox_cfb_event_matchup
df = fox_cfb_event_matchup("...")

fox_cfb_event_recap

fox_cfb_event_recap(*args: 'Any', **kwargs: 'Any') -> 'Any'

Fox Sports cfb postgame top performers (one row per player).

Wraps cfb/event/{game_id}/recap.

Returns

A polars DataFrame (default), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False.

Example

from sportsdataverse.cfb import fox_cfb_event_recap
df = fox_cfb_event_recap("...")

fox_cfb_event_standings

fox_cfb_event_standings(*args: 'Any', **kwargs: 'Any') -> 'Any'

Fox Sports cfb the two teams' standings context.

Wraps cfb/event/{game_id}/standings.

Returns

A polars DataFrame (default), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False.

Example

from sportsdataverse.cfb import fox_cfb_event_standings
df = fox_cfb_event_standings("...")

fox_cfb_league_conferences

fox_cfb_league_conferences(*args: 'Any', **kwargs: 'Any') -> 'Any'

Fox Sports cfb conference / group directory.

Wraps cfb/league/conferences.

Returns

A polars DataFrame (default), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False.

col_name	type	description
group	character
fox_id	character	Fox group id of the conference as a string, the trailing number of content_uri (e.g. '9' for the ACC); the same ids are the groupId filters in the Fox scoreboard navigation.
abbreviation	character	Metric abbreviation.
name	character	Position name (e.g. Quarterback).
content_uri	character	Fox Bifrost content path of the conference (e.g. 'football/cfb/groups/9').
content_type	character	Fox entity type of the linked item; 'league' on every sampled conference row.
web_url	character	Site-relative foxsports.com path of the conference page (e.g. '/college-football/acc').
color	character	Primary team color (hex, no #).
logo_url	character

Example

from sportsdataverse.cfb import fox_cfb_league_conferences
df = fox_cfb_league_conferences()

fox_cfb_league_header

fox_cfb_league_header(*args: 'Any', **kwargs: 'Any') -> 'Any'

Fox Sports cfb league header (one row).

Wraps cfb/league/header.

Returns

A polars DataFrame (default), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False.

col_name	type	description
template	character	Name of the Fox layout template for the header payload, 'entity-header' in the sample.
title	character
entity_id	character	Fox id of the league entity as a string: the trailing number of the league's Fox contentUri.
content_uri	character	Fox Bifrost content path of the league entity (e.g. 'football/cfb/league/1'); entity_id is its trailing number.
content_type	character	Fox entity type of the header; 'league' for this league-level header.
color	character	Primary team color (hex, no #).
logo_url	character
image_alt_text	character	Alt text Fox attaches to the league logo image, 'College Football' in the sample.
rank	character	Position of the school within the poll for the given week (1 = top-ranked).
details	character	ESPN's headline line string (e.g. UGA -54.5).

Example

from sportsdataverse.cfb import fox_cfb_league_header
df = fox_cfb_league_header()

fox_cfb_league_leaders

fox_cfb_league_leaders(category: 'str' = 'passing', who: 'str' = 'player', page: 'int' = 0, group_id: 'Union[int, str]' = '2', *, return_parsed: 'bool' = True, return_as_pandas: 'bool' = False, **kwargs: 'Any') -> "Union[pl.DataFrame, 'pd.DataFrame', Dict[str, Any]]"

Fox Sports CFB statistical leaders (one row per player/team).

Endpoint: GET .../bifrost/v1/cfb/league/stats-con/{who}/{category}/{page}

Parameters

Parameter	Type	Default	Description
category	str	'passing'	Stat category -- passing, rushing, receiving, defense, kicking, returning, scoring, yardage (team adds downs, turnovers). Defaults to "passing".
who	str	'player'	"player" or "team". Defaults to "player".
page	int	0	0-based result page. Defaults to 0.
group_id	Union[int, str]	'2'	Conference/group filter. Defaults to "2".
return_parsed	bool	True	If True (default) flatten the leader tables to a DataFrame; if False return the raw JSON dict.
return_as_pandas	bool	False	If True return a pandas DataFrame; otherwise polars. Ignored when return_parsed=False.

Returns

A polars DataFrame (default), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False.

col_name	type	description
players	character
v1	character	Abbreviated player name, first initial plus surname (e.g. 'M. Alejado'), from Fox's untitled second column; the players column beside it holds the rank.
comp	character	Pass completions as a string (e.g. '81'). Filled only on the 25 rows of Fox's COMP table; null on the rows of the other two top-25 tables stacked into the default passing frame.
gp	character
entity_id	character	Fox id of the row's linked player or team as a string: the trailing number of the row's entityLink contentUri.
patt	character	Pass attempts as a string (e.g. '137'). Filled only on the 25 rows of Fox's PATT table; null on the rows of the other two top-25 tables stacked into the default passing frame.
att_g	character	Pass attempts per game with one decimal as a string (e.g. '45.7'). Filled only on the 25 rows of Fox's ATT/G table; null on the rows of the other two top-25 tables stacked into the default passing frame.

Example

from sportsdataverse.cfb import fox_cfb_league_leaders
df = fox_cfb_league_leaders("passing")

fox_cfb_league_odds

fox_cfb_league_odds(*args: 'Any', **kwargs: 'Any') -> 'Any'

Fox Sports cfb league odds board (one row per team per game).

Wraps cfb/league/odds.

Returns

A polars DataFrame (default), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False.

col_name	type	description
section	character	Title of the board section holding the game module; always 'GAMES' in sampled data.
game_id	character	ESPN game identifier.
event_time	character	Scheduled start of the game, an ISO-8601 UTC string with a trailing Z (e.g. '2026-09-19T16:00:00Z').
event_status	integer	Fox's numeric event-status code for the game; always 2 in the sampled board, where no listed game had started.
team	character	Team name.
spread	character	Pre-game point spread from the selected provider.
to_win	character	The team's moneyline in American odds, kept as a signed string (e.g. '-1818', '+923'); a bare '-' when no price is posted.
total	character

Example

from sportsdataverse.cfb import fox_cfb_league_odds
df = fox_cfb_league_odds()

fox_cfb_league_player_news

fox_cfb_league_player_news(*args: 'Any', **kwargs: 'Any') -> 'Any'

Fox Sports cfb league-wide player news feed.

Wraps cfb/league/playernews.

Returns

A polars DataFrame (default), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False.

col_name	type	description
title	character
subtitle	character	Team abbreviation, jersey number and position of the player, formatted like 'LSU #10 - QB'.
headline	character	Headline ESPN attaches to the poll release.
description	character	ESPN's description of the stat.
impact_title	character	Heading Fox shows above the impact paragraph; always 'Impact' in sampled data.
impact	character	Fox's analysis paragraph under the 'Impact' heading, explaining what the news means for the player (e.g. 'Leavitt was listed as doubtful in LSU's initial injury report...').
date	character	Date of the poll release.
source	character
athlete_id	character	ESPN athlete id.
content_uri	character	Fox Bifrost content path of the athlete the item is about (e.g. 'football/cfb/athletes/212300'); athlete_id is its trailing number.
web_url	character	Site-relative foxsports.com path of the player's page (e.g. '/college-football/sam-leavitt-player').

Example

from sportsdataverse.cfb import fox_cfb_league_player_news
df = fox_cfb_league_player_news()

fox_cfb_league_polls

fox_cfb_league_polls(*args: 'Any', **kwargs: 'Any') -> 'Any'

Fox Sports cfb rankings / polls rendered as standings tables.

Wraps cfb/league/polls.

Returns

A polars DataFrame (default), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False.

col_name	type	description
section	character	Poll the row belongs to: 'ASSOCIATED PRESS' or 'USA TODAY COACHES POLL'.
ranking	character	National rank of the team's overall SP+ rating (1 = best).
v1	character	Places the team moved since the previous poll, as an unsigned string (e.g. '3'); null when Fox shows no movement. The parser drops Fox's up/down flag, so a rise and a fall look the same.
v2	character	Team short name as Fox prints it in the poll, with first-place votes in parentheses when it got any (e.g. 'Texas (56)', 'Ohio State', 'Miami (FL) (4)').
pts	character
entity_id	character	Fox id of the row's linked team as a string: the trailing number of the row's entityLink contentUri.
team	character	Team name.
rank_change	integer

Example

from sportsdataverse.cfb import fox_cfb_league_polls
df = fox_cfb_league_polls()

fox_cfb_league_schedule

fox_cfb_league_schedule(*args: 'Any', **kwargs: 'Any') -> 'Any'

Fox Sports cfb league schedule nav selections.

Wraps cfb/league/schedule.

Returns

A polars DataFrame (default), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False.

col_name	type	description
selection_list	character	Which Fox navigation list the row came from: 'groupList' (group filters such as FEATURED, TOP 25, ACC) or 'selectionList' (the season's week segments); the parser also emits 'dailyList', which CFB samples never show.
id	character	247Sports referencing id for the recruit.
title	character
date	character	Date of the poll release.
uri	character	Absolute Bifrost API URL of the week segment (e.g. 'https://api.foxsports.com/bifrost/v1/cfb/league/schedule-segment/2026-1-1?groupId=-4'); null on every groupList row.
web_url	character	Site-relative foxsports.com path for the selection, e.g. '/college-football/schedule?groupId=9' on a group row.
selected	logical	Fox's default-selection flag: True on the one group filter (a groupList row) Fox pre-selects, and null (never False) on every other row.
group_id	character	ESPN group (conference) id for the season.

Example

from sportsdataverse.cfb import fox_cfb_league_schedule
df = fox_cfb_league_schedule()

fox_cfb_league_scores

fox_cfb_league_scores(*args: 'Any', **kwargs: 'Any') -> 'Any'

Fox Sports cfb league scores nav selections.

Wraps cfb/league/scores.

Returns

A polars DataFrame (default), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False.

col_name	type	description
selection_list	character	Which Fox navigation list the row came from: 'groupList' (group filters such as FEATURED, TOP 25, ACC) or 'selectionList' (the season's week segments); the parser also emits 'dailyList', which CFB samples never show.
id	character	247Sports referencing id for the recruit.
title	character
date	character	Date of the poll release.
uri	character	Absolute Bifrost API URL of the week segment (e.g. 'https://api.foxsports.com/bifrost/v1/cfb/league/scores-segment/2026-1-1?groupId=-4'); null on every groupList row.
web_url	character	Site-relative foxsports.com path for the selection, e.g. '/college-football/scores?groupId=9' on a group row.
selected	logical	Fox's default-selection flag: True on the one group filter (a groupList row) Fox pre-selects, and null (never False) on every other row.
group_id	character	ESPN group (conference) id for the season.

Example

from sportsdataverse.cfb import fox_cfb_league_scores
df = fox_cfb_league_scores()

fox_cfb_league_standings

fox_cfb_league_standings(*args: 'Any', **kwargs: 'Any') -> 'Any'

Fox Sports cfb league-wide standings tables.

Wraps cfb/league/standings.

Returns

A polars DataFrame (default), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False.

Example

from sportsdataverse.cfb import fox_cfb_league_standings
df = fox_cfb_league_standings()

fox_cfb_league_stat_leaders

fox_cfb_league_stat_leaders(*args: 'Any', **kwargs: 'Any') -> 'Any'

Fox Sports cfb league stats landing leaders.

Wraps cfb/league/stats.

Returns

A polars DataFrame (default), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False.

col_name	type	description
category	character	CFBD stats category name (e.g. passing, rushing, defensive).
stat	character
stat_abbreviation	character	Fox's short code for the leader's stat (e.g. 'PYDS', 'PTD', 'RECYDS'); some codes contain a space, such as 'KR YDS'.
player	character	Player name.
value	character	Metric value.

Example

from sportsdataverse.cfb import fox_cfb_league_stat_leaders
df = fox_cfb_league_stat_leaders()

fox_cfb_odds

fox_cfb_odds(game_id: 'Union[int, str]', *, return_parsed: 'bool' = True, return_as_pandas: 'bool' = False, **kwargs: 'Any') -> "Union[pl.DataFrame, 'pd.DataFrame', Dict[str, Any]]"

Fox Sports CFB game odds six-pack (spread / to win / total per team).

Endpoint: GET https://api.foxsports.com/bifrost/v1/cfb/event/{game_id}/odds

Parameters

Parameter	Type	Default	Description
game_id	Union[int, str]		Fox Bifrost event id (e.g. "41616").
return_parsed	bool	True	If True (default) flatten the six-pack market to a DataFrame; if False return the raw JSON dict.
return_as_pandas	bool	False	If True return a pandas DataFrame; otherwise polars. Ignored when return_parsed=False.

Returns

A polars DataFrame (default; empty when no market is posted), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False.

col_name	type	description
game_id	character	ESPN game identifier.
team	character	Team name.
spread	character	Pre-game point spread from the selected provider.
to_win	character
total	character

Example

from sportsdataverse.cfb import fox_cfb_odds
df = fox_cfb_odds("41616")

fox_cfb_pbp

fox_cfb_pbp(game_id: 'Union[int, str]', *, return_parsed: 'bool' = True, return_as_pandas: 'bool' = False, **kwargs: 'Any') -> "Union[pl.DataFrame, 'pd.DataFrame', Dict[str, Any]]"

Fox Sports CFB play-by-play (one row per play).

Endpoint: GET https://api.foxsports.com/bifrost/v1/cfb/event/{game_id}/data

Parameters

Parameter	Type	Default	Description
game_id	Union[int, str]		Fox Bifrost event id (e.g. "41616") -- not the ESPN id.
return_parsed	bool	True	If True (default) flatten the pbp layout to a DataFrame; if False return the raw JSON dict.
return_as_pandas	bool	False	If True return a pandas DataFrame; otherwise polars. Ignored when return_parsed=False.

Returns

A polars DataFrame (default), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False.

col_name	type	description
game_id	character	ESPN game identifier.
quarter	character
drive_id	character	CFBD drive identifier the play belongs to.
drive_result	character	Drive result code (drive_-prefixed; every drive-level column is carried with this prefix).
drive_summary	character
drive_team	character
play_id	character	ESPN play id.
period	character	Period (quarter) number.
clock	character	Game clock display value at the play (MM:SS).
field_position	character	Ball spot expressed on Yahoo's 0-100 field scale, measured toward the offense's target goal line.
play_text	character	Free-form text description of the play from the CFBD feed.
play_team	character

Example

from sportsdataverse.cfb import fox_cfb_pbp
df = fox_cfb_pbp("41616")

fox_cfb_play_process

fox_cfb_play_process(event_id, odds_override: 'Optional[Dict[str, Any]]' = None, process: 'bool' = True, raw: 'bool' = False, **kwargs) -> 'Dict[str, Any]'

Build a processed CFB play-by-play game from FoxSports as a backup to ESPN.

Where ~sportsdataverse.cfb.cfb_fox_ext.fox_cfb_pbp returns the raw Fox play-by-play rows, this runs Fox data through the full ESPN play processor: it fetches FoxSports Bifrost cfb/event/{event_id}/data, adapts it into the ESPN-summary shape via fox_to_espn_summary, and runs the same ~sportsdataverse.cfb.cfb_pbp.CFBPlayProcess pipeline ESPN games use -- producing EPA / WPA / advanced box score. The result carries source="fox" so downstream consumers know the provenance (and that text-derived columns are lower fidelity than the ESPN path).

Parameters

Parameter	Type	Default	Description
event_id			FoxSports CFB event id (e.g. 41616).
odds_override	Optional[Dict[str, Any]]	None	Optional {gameSpread, overUnder, homeFavorite, gameSpreadAvailable} dict. Fox does not expose a clean pre-game spread, so when omitted a neutral pick'em line is used (EPA is unaffected; only the WP model's spread term is neutralized).
process	bool	True	If True (default) run the full ~sportsdataverse.cfb.cfb_pbp.CFBPlayProcess.run_processing_pipeline (EPA/WPA/box). If False run the lighter ~sportsdataverse.cfb.cfb_pbp.CFBPlayProcess.run_cleaning_pipeline.
raw	bool	False	If True skip the processor entirely and return the adapted ESPN-summary dict (the input the processor would consume).

Returns

The processed game payload (same keys as CFBPlayProcess.run_processing_pipeline) with an added source="fox" key. When raw=True, the adapted summary dict.

Example

from sportsdataverse.cfb import fox_cfb_play_process
game = fox_cfb_play_process(41616)
print(len(game["plays"]), game["source"])

fox_cfb_schedule

fox_cfb_schedule(season: 'Optional[int]' = None, *, segment_id: 'Optional[str]' = None, group_id: 'Union[int, str]' = '2', return_parsed: 'bool' = True, return_as_pandas: 'bool' = False, **kwargs: 'Any') -> "Union[pl.DataFrame, 'pd.DataFrame', Dict[str, Any]]"

Fox Sports CFB full-season schedule (one row per game).

Fox lists games behind a two-step selector -> segment flow: scoreboard/main enumerates the season's segments (its selectionGroupList), and league/scores-segment/{segmentId} returns the games for one segment. Pass a season to scrape the whole season -- every regular week plus conference championships, bowls, and every College Football Playoff round -- enumerated from the live selector and unioned, deduplicated by game_id.

Segment ids encode the phase, not an ESPN-style integer week: "{season}-{week}-1" for a regular-season week, "{season}-bowls-2" for the bowls, "{season}-cfp-2" for the CFP (conference championships fall in the final regular-season week). Pass segment_id to fetch just one of them.

The numeric game_id is the Fox Bifrost event id that fox_cfb_pbp / fox_cfb_odds accept; week_label is the section title.

Parameters

Parameter	Type	Default	Description
season	Optional[int]	None	Season year -> scrape the full season. Ignored when segment_id is given; if both are None the current segment is returned.
segment_id	Optional[str]	None	Explicit Fox segment id (e.g. "2025-5-1", "2025-cfp-2") -> fetch just that segment.
group_id	Union[int, str]	'2'	Conference/division group filter. Defaults to "2" (FBS).
return_parsed	bool	True	If True (default) flatten to a DataFrame; if False return the raw JSON (a single segment's dict, or a {segment_id: dict} map in full-season mode).
return_as_pandas	bool	False	If True return a pandas DataFrame; otherwise polars. Ignored when return_parsed=False.

Returns

A polars DataFrame (default) with columns game_id, date, status, week_label, home_team, home_team_id, away_team, away_team_id, segment_id; a pandas DataFrame when return_as_pandas=True; or raw JSON when return_parsed=False.

col_name	type	description
game_id	character	ESPN game identifier.
date	character	Date of the poll release.
status	character	Game status (e.g. "scheduled", "in_progress", "completed").
week_label	character	Title of the Fox segment section that listed the game (e.g. 'WEEK 3'); often null because Fox leaves most section titles blank.
home_team	character	Home team name.
home_team_id	character	ESPN home team id (parsed from home_team_ref).
away_team	character	Away team name.
away_team_id	character	ESPN away team id (parsed from away_team_ref).
segment_id	character	Fox scoreboard segment the game was fetched from: '{season}-{week}-1' for a regular-season week (sampled '2026-3-1'), '{season}-bowls-2' or '{season}-cfp-2' for the postseason.

Example

from sportsdataverse.cfb import fox_cfb_schedule
season = fox_cfb_schedule(2025)

# Fetch just one segment (a week, or the playoff)

wk5 = fox_cfb_schedule(segment_id="2025-5-1")
cfp = fox_cfb_schedule(segment_id="2025-cfp-2")

fox_cfb_scoreboard

fox_cfb_scoreboard(*args: 'Any', **kwargs: 'Any') -> 'Any'

Fox Sports cfb scoreboard nav selections (weeks / dates / groups).

Wraps cfb/scoreboard/main.

Returns

A polars DataFrame (default), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False.

col_name	type	description
selection_list	character	Which Fox navigation list the row came from: 'groupList' (group filters such as FEATURED, TOP 25, ACC) or 'selectionList' (the season's week segments); the parser also emits 'dailyList', which CFB samples never show.
id	character	247Sports referencing id for the recruit.
title	character
date	character	Date of the poll release.
uri	character	Absolute Bifrost API URL of the week segment (e.g. 'https://api.foxsports.com/bifrost/v1/cfb/scoreboard/segment/2026-1-1?groupId=-4'); null on every groupList row.
web_url	character	Site-relative foxsports.com path for the selection, e.g. '/scores/college-football?groupId=9' on a group row; week rows add seasonType and week parameters ('...?groupId=-4&seasonType=reg&week=1').
selected	logical	Fox's default-selection flag: True on the one group filter (a groupList row) Fox pre-selects, and null (never False) on every other row.
group_id	character	ESPN group (conference) id for the season.

Example

from sportsdataverse.cfb import fox_cfb_scoreboard
df = fox_cfb_scoreboard()

fox_cfb_scorechip

fox_cfb_scorechip(*args: 'Any', **kwargs: 'Any') -> 'Any'

Fox Sports cfb compact live score chip (raw dict -- live-only, uncaptured shape).

Wraps cfb/scorechip/{chip_id}.

Returns

The raw JSON dict.

Example

from sportsdataverse.cfb import fox_cfb_scorechip
df = fox_cfb_scorechip("nfl12345")

fox_cfb_scores_segment

fox_cfb_scores_segment(*args: 'Any', **kwargs: 'Any') -> 'Any'

Fox Sports cfb one row per game in a scoreboard segment.

Wraps cfb/league/scores-segment/{segment_id}.

Returns

A polars DataFrame (default), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False.

Example

from sportsdataverse.cfb import fox_cfb_scores_segment
df = fox_cfb_scores_segment("...")

fox_cfb_standings

fox_cfb_standings(team_id: 'Union[int, str]', *, return_parsed: 'bool' = True, return_as_pandas: 'bool' = False, **kwargs: 'Any') -> "Union[pl.DataFrame, 'pd.DataFrame', Dict[str, Any]]"

Fox Sports CFB conference standings for a team's conference.

Endpoint: GET https://api.foxsports.com/bifrost/v1/cfb/team/{team_id}/standings (the league-wide league/standings endpoint returns header-only tables, so standings are keyed by team).

Parameters

Parameter	Type	Default	Description
team_id	Union[int, str]		Fox Bifrost team id (e.g. "11" = Miami (FL)).
return_parsed	bool	True	If True (default) flatten the standings tables to a DataFrame; if False return the raw JSON dict.
return_as_pandas	bool	False	If True return a pandas DataFrame; otherwise polars. Ignored when return_parsed=False.

Returns

A polars DataFrame (default), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False.

col_name	type	description
team_id	character	ESPN team id.
section	character
atlantic_coast	character
v1	character
conf	character
w_l	character
home	character	Home team name.
away	character	Away team name.
pf	character
pa	character
strk	character
entity_id	character	Composite Yahoo id this editorial row was keyed under, surfaced from the collection map key (e.g., "ncaaf.g.202509200023" for a game, "ncaaf.t.29" for a team); always carried as Utf8.

Example

from sportsdataverse.cfb import fox_cfb_standings
df = fox_cfb_standings("11")

fox_cfb_team_gamelog

fox_cfb_team_gamelog(team_id: 'Union[int, str]', *, return_parsed: 'bool' = True, return_as_pandas: 'bool' = False, **kwargs: 'Any') -> "Union[pl.DataFrame, 'pd.DataFrame', Dict[str, Any]]"

Fox Sports CFB team game log -- tidy long: one row per (game, stat).

Endpoint: GET https://api.foxsports.com/bifrost/v1/cfb/team/{team_id}/gamelog The endpoint groups team per-game stats by category (passing, rushing, defense, ...) and season-type split; this flattens to columns team_id, season_type, category, game_id, game_date, opponent, stat, value.

Parameters

Parameter	Type	Default	Description
team_id	Union[int, str]		Fox Bifrost team id (e.g. "11" = Miami (FL)).
return_parsed	bool	True	If True (default) flatten to long form; if False return the raw JSON dict.
return_as_pandas	bool	False	If True return a pandas DataFrame; otherwise polars. Ignored when return_parsed=False.

Returns

A polars DataFrame (default), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False.

col_name	type	description
team_id	character	ESPN team id.
season_type	character	ESPN season type (2 = regular, 3 = postseason).
category	character	CFBD stats category name (e.g. passing, rushing, defensive).
game_id	character	ESPN game identifier.
game_date	character	Kickoff date-time (ISO 8601, UTC).
opponent	character	Opponent team name.
stat	character
value	character	Metric value.

Example

from sportsdataverse.cfb import fox_cfb_team_gamelog
df = fox_cfb_team_gamelog("11")

fox_cfb_team_header

fox_cfb_team_header(*args: 'Any', **kwargs: 'Any') -> 'Any'

Fox Sports cfb team header (one row).

Wraps cfb/team/{team_id}/header.

Returns

A polars DataFrame (default), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False.

Example

from sportsdataverse.cfb import fox_cfb_team_header
df = fox_cfb_team_header("...")

fox_cfb_team_roster

fox_cfb_team_roster(team_id: 'Union[int, str]', *, return_parsed: 'bool' = True, return_as_pandas: 'bool' = False, **kwargs: 'Any') -> "Union[pl.DataFrame, 'pd.DataFrame', Dict[str, Any]]"

Fox Sports CFB team roster (one row per player).

Endpoint: GET https://api.foxsports.com/bifrost/v1/cfb/team/{team_id}/roster

Parameters

Parameter	Type	Default	Description
team_id	Union[int, str]		Fox Bifrost team id (e.g. "11" = Miami (FL)); discover via the league team directory (cfb/league/teamnav).
return_parsed	bool	True	If True (default) flatten the position-group tables to a DataFrame; if False return the raw JSON dict.
return_as_pandas	bool	False	If True return a pandas DataFrame; otherwise polars. Ignored when return_parsed=False.

Returns

A polars DataFrame (default), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False.

col_name	type	description
team_id	character	ESPN team id.
position_group	character	Position group of the recruits (e.g. Offensive Line, Defensive Back).
player	character	Player name.
pos	character
cls	character
ht	character
wt	character
athlete_id	character	ESPN athlete id.

Example

from sportsdataverse.cfb import fox_cfb_team_roster
df = fox_cfb_team_roster("11")

fox_cfb_team_stats

fox_cfb_team_stats(team_id: 'Union[int, str]', *, return_parsed: 'bool' = True, return_as_pandas: 'bool' = False, **kwargs: 'Any') -> "Union[pl.DataFrame, 'pd.DataFrame', Dict[str, Any]]"

Fox Sports CFB team stat leaders (one row per category leader).

Endpoint: GET https://api.foxsports.com/bifrost/v1/cfb/team/{team_id}/stats

Parameters

Parameter	Type	Default	Description
team_id	Union[int, str]		Fox Bifrost team id (e.g. "11" = Miami (FL)).
return_parsed	bool	True	If True (default) flatten the leader sections to a DataFrame; if False return the raw JSON dict.
return_as_pandas	bool	False	If True return a pandas DataFrame; otherwise polars. Ignored when return_parsed=False.

Returns

A polars DataFrame (default), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False.

col_name	type	description
team_id	character	ESPN team id.
category	character	CFBD stats category name (e.g. passing, rushing, defensive).
stat	character
stat_abbreviation	character
player	character	Player name.
value	character	Metric value.

Example

from sportsdataverse.cfb import fox_cfb_team_stats
df = fox_cfb_team_stats("11")

fox_cfb_teamnav

fox_cfb_teamnav(*args: 'Any', **kwargs: 'Any') -> 'Any'

Fox Sports cfb team directory (one row per team).

Wraps cfb/league/teamnav.

Returns

A polars DataFrame (default), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False.

col_name	type	description
group	character
fox_id	character	Fox Bifrost team id as a string, the trailing number of content_uri; the same id fox_cfb_teams returns as fox_team_id from this endpoint.
abbreviation	character	Metric abbreviation.
name	character	Position name (e.g. Quarterback).
content_uri	character	Fox Bifrost content path of the team (e.g. 'football/cfb/teams/25').
content_type	character	Fox entity type of the linked item; 'team' on every sampled row.
web_url	character	Site-relative foxsports.com team page path (e.g. '/college-football/ohio-state-buckeyes-team'); null for some teams.
color	character	Primary team color (hex, no #).
logo_url	character

Example

from sportsdataverse.cfb import fox_cfb_teamnav
df = fox_cfb_teamnav()

fox_cfb_teams

fox_cfb_teams(*, return_parsed: 'bool' = True, return_as_pandas: 'bool' = False, **kwargs: 'Any') -> "Union[pl.DataFrame, 'pd.DataFrame', Dict[str, Any]]"

Fox Sports CFB team directory (one row per team).

Endpoint: GET https://api.foxsports.com/bifrost/v1/cfb/league/teamnav

The team-nav payload is the canonical Fox directory: it maps every team's Bifrost id to its abbreviation, full name, and web slug. This is the lookup you need to translate a human team name into the numeric team_id the other fox_cfb_* wrappers expect, and it is the Fox side of sportsdataverse.cfb.cfb_teams_crosswalk.

Parameters

Parameter	Type	Default	Description
return_parsed	bool	True	If True (default) flatten the nav items to a DataFrame; if False return the raw JSON dict.
return_as_pandas	bool	False	If True return a pandas DataFrame; otherwise polars. Ignored when return_parsed=False.

Returns

A polars DataFrame (default) with columns fox_team_id, abbreviation, name, slug, color, logo_url; a pandas DataFrame when return_as_pandas=True; or the raw JSON dict when return_parsed=False.

col_name	type	description
fox_team_id	character
abbreviation	character	Metric abbreviation.
name	character	Position name (e.g. Quarterback).
slug	character	URL slug for the team.
color	character	Primary team color (hex, no #).
logo_url	character

Example

from sportsdataverse.cfb import fox_cfb_teams
teams = fox_cfb_teams()
fox_id = dict(zip(teams["abbreviation"], teams["fox_team_id"]))

fox_to_espn_summary

fox_to_espn_summary(fox_data: 'Dict[str, Any]') -> 'Dict[str, Any]'

Adapt a Fox cfb/event/{id}/data payload into the ESPN-summary shape.

Parameters

Parameter	Type	Default	Description
fox_data	Dict[str, Any]		Parsed JSON from api.foxsports.com/bifrost/v1/cfb/event/{id}/data.

Returns

A dict shaped like ESPN's college-football/summary response (header + drives + stub pickcenter/boxscore/...), ready to assign onto CFBPlayProcess(...).json.