MBB — additional Python functions — Fox

fox_mbb_boxscore

fox_mbb_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]]"

MBB boxscore (long: one row per player-stat).

Parameters

Parameter	Type	Default	Description
game_id	Union[int, str]		Fox Bifrost event id.
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.

Example

from sportsdataverse.mbb import fox_mbb_boxscore
df = fox_mbb_boxscore("...")

fox_mbb_event_matchup

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

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

Wraps cbk/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.mbb import fox_mbb_event_matchup
df = fox_mbb_event_matchup("...")

fox_mbb_event_recap

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

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

Wraps cbk/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.mbb import fox_mbb_event_recap
df = fox_mbb_event_recap("...")

fox_mbb_event_standings

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

Fox Sports cbk the two teams' standings context.

Wraps cbk/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.mbb import fox_mbb_event_standings
df = fox_mbb_event_standings("...")

fox_mbb_league_conferences

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

Fox Sports cbk conference / group directory.

Wraps cbk/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	Group identifier (e.g. conference 'group_id').
fox_id	character	Fox Sports conference id as a string, the trailing number of content_uri; ids are assigned per feed and usually differ between the men's and women's feeds (ACC 11 vs 12), though some coincide (America East is 9 in both), so never join the two feeds on it.
abbreviation	character	Short abbreviation.
name	character	Display name.
content_uri	character	Fox Bifrost content URI identifying the conference (e.g. 'basketball/cbk/groups/11'); fox_id is its trailing number.
content_type	character	Fox entity type from the conference's entity link; always 'league' in sampled data, even though each row is a conference.
web_url	character	Site-relative foxsports.com path of the conference page (e.g. '/college-basketball/acc').
color	character	Primary color (hex without leading '#').
logo_url	character	NBA CDN primary logo URL.

Example

from sportsdataverse.mbb import fox_mbb_league_conferences
df = fox_mbb_league_conferences()

fox_mbb_league_header

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

Fox Sports cbk league header (one row).

Wraps cbk/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	Fox layout template name for the header block; always 'entity-header' in sampled data.
title	character	Title or label for the record.
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 URI of the league entity ('basketball/cbk/league/1' in sampled data).
content_type	character	Fox entity type of the header's entity; 'league' in sampled data.
color	character	Primary color (hex without leading '#').
logo_url	character	NBA CDN primary logo URL.
image_alt_text	character	Alt text Fox attaches to the header image, which reads as the league's display name ('College Basketball' in sampled data).
rank	character	Rank.
details	character	Details.

Example

from sportsdataverse.mbb import fox_mbb_league_header
df = fox_mbb_league_header()

fox_mbb_league_leaders

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

MBB statistical leaders (stats-con); who=player|team.

Parameters

Parameter	Type	Default	Description
category	str	'scoring'	Stat category. Defaults to "scoring".
who	str	'player'	"player" or "team". Defaults to "player".
page	int	0	0-based result page. Defaults to 0.
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	Nested list of per-player box scores.
v1	character	Leader's name as Fox abbreviates it, first initial plus surname (e.g. 'T. Moore'); the column is named v1 because its table header cell is blank.
gp	character	Games played.
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.
gs	character	Games started.
mpg	character	Minutes per game.
ppg	character	Points per game.
pts	character	Points scored.

Example

from sportsdataverse.mbb import fox_mbb_league_leaders
df = fox_mbb_league_leaders("scoring")

fox_mbb_league_odds

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

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

Wraps cbk/league/odds.

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.mbb import fox_mbb_league_odds
df = fox_mbb_league_odds()

fox_mbb_league_player_news

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

Fox Sports cbk league-wide player news feed.

Wraps cbk/league/playernews.

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.mbb import fox_mbb_league_player_news
df = fox_mbb_league_player_news()

fox_mbb_league_polls

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

Fox Sports cbk rankings / polls rendered as standings tables.

Wraps cbk/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	Ranking the row belongs to: 'ASSOCIATED PRESS', 'USA TODAY COACHES POLL' or 'RPI RANKINGS' (25 rows each in sampled data).
ranking	character	Team recruiting ranking.
v1	character	Unlabeled second table column whose meaning depends on section: in the two polls it is Fox's rank-change cell, an unsigned number string (e.g. '5') that is null when no change is shown; on 'RPI RANKINGS' rows it holds the team name.
v2	character	Team name on poll rows, with first-place votes in parentheses when the team received any (e.g. 'Michigan (57)'); null on 'RPI RANKINGS' rows, where the name is in v1.
pts	character	Points scored.
entity_id	character	Fox id of the row's linked team as a string: the trailing number of the row's entityLink contentUri.
rpi	character	RPI value as a decimal string with a leading dot (e.g. '.6808'); populated only on 'RPI RANKINGS' rows and null on both poll sections.
sos	character	Strength of schedule.
home	character	Home.
away	character	Away record.
neutral	character	Neutral.

Example

from sportsdataverse.mbb import fox_mbb_league_polls
df = fox_mbb_league_polls()

fox_mbb_league_schedule

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

Fox Sports cbk league schedule nav selections.

Wraps cbk/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 and each conference; uri is null) or 'dailyList' (one row per game date).
id	character	Id.
title	character	Title or label for the record.
date	character	Date in YYYY-MM-DD format.
uri	character	Absolute api.foxsports.com Bifrost URL of that date's segment payload (.../league/schedule-segment/-YYYYMMDD?groupId=...); null on groupList rows.
web_url	character	Site-relative foxsports.com path of the page the selection opens (e.g. '/college-basketball/schedule?groupId=top25').
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 id.

Example

from sportsdataverse.mbb import fox_mbb_league_schedule
df = fox_mbb_league_schedule()

fox_mbb_league_scores

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

Fox Sports cbk league scores nav selections.

Wraps cbk/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 and each conference; uri is null) or 'dailyList' (one row per game date).
id	character	Id.
title	character	Title or label for the record.
date	character	Date in YYYY-MM-DD format.
uri	character	Absolute api.foxsports.com Bifrost URL of that date's segment payload (.../league/scores-segment/YYYYMMDD?groupId=...); null on groupList rows.
web_url	character	Site-relative foxsports.com path of the page the selection opens (e.g. '/college-basketball/scores?groupId=top25').
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 id.

Example

from sportsdataverse.mbb import fox_mbb_league_scores
df = fox_mbb_league_scores()

fox_mbb_league_standings

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

Fox Sports cbk league-wide standings tables.

Wraps cbk/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.mbb import fox_mbb_league_standings
df = fox_mbb_league_standings()

fox_mbb_league_stat_leaders

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

Fox Sports cbk league stats landing leaders.

Wraps cbk/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	Category label.
stat	character	Stat.
stat_abbreviation	character	Fox's short code for the leader stat, such as 'PPG', 'RPG', '3FGM/G', 'TS%' or 'HIGH'; the spelled-out name is in stat.
player	character	Player name.
value	character	Numeric or string value field.

Example

from sportsdataverse.mbb import fox_mbb_league_stat_leaders
df = fox_mbb_league_stat_leaders()

fox_mbb_odds

fox_mbb_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]]"

MBB game odds six-pack (spread / to-win / total per team).

Parameters

Parameter	Type	Default	Description
game_id	Union[int, str]		Fox Bifrost event id.
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), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False.

Example

from sportsdataverse.mbb import fox_mbb_odds
df = fox_mbb_odds("...")

fox_mbb_pbp

fox_mbb_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]]"

MBB play-by-play (one row per play; period-based).

Parameters

Parameter	Type	Default	Description
game_id	Union[int, str]		Fox Bifrost event 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.

Example

from sportsdataverse.mbb import fox_mbb_pbp
df = fox_mbb_pbp("...")

fox_mbb_scoreboard

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

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

Wraps cbk/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 and each conference; uri is null) or 'dailyList' (one row per game date).
id	character	Id.
title	character	Title or label for the record.
date	character	Date in YYYY-MM-DD format.
uri	character	Absolute api.foxsports.com Bifrost URL of that date's segment payload (.../scoreboard/segment/YYYYMMDD?groupId=...); null on groupList rows.
web_url	character	Site-relative foxsports.com path of the page the selection opens (e.g. '/scores/college-basketball?groupId=top25').
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 id.

Example

from sportsdataverse.mbb import fox_mbb_scoreboard
df = fox_mbb_scoreboard()

fox_mbb_scorechip

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

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

Wraps cbk/scorechip/{chip_id}.

Returns

The raw JSON dict.

Example

from sportsdataverse.mbb import fox_mbb_scorechip
df = fox_mbb_scorechip("nfl12345")

fox_mbb_scores_segment

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

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

Wraps cbk/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.mbb import fox_mbb_scores_segment
df = fox_mbb_scores_segment("...")

fox_mbb_standings

fox_mbb_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]]"

MBB standings for a team's conference/division.

Parameters

Parameter	Type	Default	Description
team_id	Union[int, str]		Fox Bifrost team id.
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.

Example

from sportsdataverse.mbb import fox_mbb_standings
df = fox_mbb_standings("...")

fox_mbb_team_gamelog

fox_mbb_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]]"

MBB team game log (long: one row per game-stat).

Parameters

Parameter	Type	Default	Description
team_id	Union[int, str]		Fox Bifrost team id.
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.

Example

from sportsdataverse.mbb import fox_mbb_team_gamelog
df = fox_mbb_team_gamelog("...")

fox_mbb_team_header

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

Fox Sports cbk team header (one row).

Wraps cbk/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.mbb import fox_mbb_team_header
df = fox_mbb_team_header("...")

fox_mbb_team_roster

fox_mbb_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]]"

MBB team roster (one row per player).

Parameters

Parameter	Type	Default	Description
team_id	Union[int, str]		Fox Bifrost team id.
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.

Example

from sportsdataverse.mbb import fox_mbb_team_roster
df = fox_mbb_team_roster("...")

fox_mbb_team_stats

fox_mbb_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]]"

MBB team stat leaders by category.

Parameters

Parameter	Type	Default	Description
team_id	Union[int, str]		Fox Bifrost team id.
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.

Example

from sportsdataverse.mbb import fox_mbb_team_stats
df = fox_mbb_team_stats("...")

fox_mbb_teamnav

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

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

Wraps cbk/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	Group identifier (e.g. conference 'group_id').
fox_id	character	Fox Sports team id as a string, the trailing number of content_uri; ids are league-specific, so a school can have different ids in the men's and women's feeds.
abbreviation	character	Short abbreviation.
name	character	Display name.
content_uri	character	Fox Bifrost content URI identifying the team, shaped 'basketball/cbk/teams/<fox_id>'.
content_type	character	Fox entity type from the team's entity link; always 'team' in sampled data.
web_url	character	Site-relative foxsports.com path of the team page (e.g. '/college-basketball/michigan-wolverines-team').
color	character	Primary color (hex without leading '#').
logo_url	character	NBA CDN primary logo URL.

Example

from sportsdataverse.mbb import fox_mbb_teamnav
df = fox_mbb_teamnav()

fox_mbb_teams

fox_mbb_teams(team_id: 'Union[int, str]' = '150', *, return_parsed: 'bool' = True, return_as_pandas: 'bool' = False, **kwargs: 'Any') -> "Union[pl.DataFrame, 'pd.DataFrame', Dict[str, Any]]"

MBB team directory for one seed team's conference.

College basketball standings are per-conference, so one call returns only the seed team's league. Use fox_mbb_teams_all for the full directory the hoopR MBB team crosswalk consumes.

Parameters

Parameter	Type	Default	Description
team_id	Union[int, str]	'150'	Seed Fox Bifrost team id whose standings page is read. Defaults to "150".
return_parsed	bool	True	If True (default) flatten the standings to the team directory; 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
fox_team_id	character	Fox Bifrost team id (NA if unmatched).
fox_team_name	character	Fox team name (NA if unmatched).
fox_section	character	Fox conference/section label (NA if unmatched).

Example

from sportsdataverse.mbb import fox_mbb_teams
df = fox_mbb_teams("150")

fox_mbb_teams_all

fox_mbb_teams_all(max_id: 'int' = 500, max_calls: 'int' = 60, *, return_as_pandas: 'bool' = False, **kwargs: 'Any') -> "Union[pl.DataFrame, 'pd.DataFrame']"

Full MBB team directory by walking seed ids across conferences.

A single fox_mbb_teams call only returns the seed team's conference, so this walks candidate team ids (skipping ids already seen in an earlier conference) and unions the results, spending at most max_calls standings fetches. Mirrors fox_wbb_teams_all.

Parameters

Parameter	Type	Default	Description
max_id	int	500	Highest candidate team id to try. Defaults to 500.
max_calls	int	60	Budget of standings fetches. Defaults to 60.
return_as_pandas	bool	False	If True return a pandas DataFrame; otherwise polars.

Returns

A polars DataFrame (default) or pandas DataFrame, one row per team: fox_team_id / fox_team_name / fox_section.

col_name	type	description
fox_team_id	character	Fox Bifrost team id (NA if unmatched).
fox_team_name	character	Fox team name (NA if unmatched).
fox_section	character	Fox conference/section label (NA if unmatched).

Example

from sportsdataverse.mbb import fox_mbb_teams_all
df = fox_mbb_teams_all()

# Pipeline next step (one line)

df.group_by("fox_section").len().sort("len", descending=True).head()