CFB — additional Python functions — Yahoo Sports Shangrila

yahoo_cfb_boxscore

yahoo_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]]"

Yahoo CFB box score: team and player stats, one row per entity stat.

Wraps the editorial boxscore/{game_id} resource. Its box score is a decoder-dictionary schema (player_stats[playerId][variation][stat_type] = value, same for team_stats) that this decodes against the payload's stat_types / stat_categories dictionaries into a long frame: one row per team stat and per player stat. Pivot on stat_type_id for a wide box. The editorial payload carries no player names; a player's team comes from the game's home/away lineups. Pass return_parsed=False for the raw payload, which also carries play-by-play and drives.

Parameters

Parameter	Type	Default	Description
game_id	Union[int, str]		Dotted Yahoo game id (e.g. "ncaaf.g.202509200023").
return_parsed	bool	True	If True (default) decode the box score into 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 by default (pandas when return_as_pandas=True) with one row per team or player stat, every column Utf8, and zero rows (same columns) for an empty payload; the raw editorial boxscore JSON dict when return_parsed=False: | Column | Type | Description | |---|---|---| | game_id | Utf8 | Dotted Yahoo game id (ncaaf.g.<date><n>). | | team_id | Utf8 | Dotted Yahoo team id (ncaaf.t.<n>); null for a player missing from the lineups. | | home_away | Utf8 | "home" or "away". | | player_id | Utf8 | Dotted Yahoo player id (ncaaf.p.<n>); null on team-stat rows. | | stat_category | Utf8 | Passing, Rushing, Receiving, Kicking, Returns, Punting, Defense or Team. | | stat_type_id | Utf8 | Yahoo stat type id (ncaaf.stat_type.105). | | stat_name | Utf8 | Stat name (Yards, Third Down Efficiency). | | stat_abbreviation | Utf8 | Short stat label (Yds, 3DE). | | stat_variation | Utf8 | Stat variation name (Game). | | value | Utf8 | Stat value as Yahoo sends it ("188", "73.2", "1-14"). |

col_name	type	description
game_id	character	ESPN game identifier.
team_id	character	ESPN team id.
home_away	character	home or away.
player_id	character	ESPN player id from the roster entry.
stat_category	character
stat_type_id	character
stat_name	character	Internal stat key (e.g. passingYards).
stat_abbreviation	character
stat_variation	character
value	character	Metric value.

Example

from sportsdataverse.cfb import yahoo_cfb_boxscore
box = yahoo_cfb_boxscore("ncaaf.g.202509200023")

# Raw JSON (includes play-by-play and drives)

raw = yahoo_cfb_boxscore("ncaaf.g.202509200023", return_parsed=False)

# Wide team box (one line)

box.filter(pl.col("player_id").is_null()).pivot("stat_name", index="team_id", values="value")

yahoo_cfb_player_season_stats

yahoo_cfb_player_season_stats(season: 'int' = 2024, *, league_structure: 'str' = 'ncaaf.struct.div.1', count: 'int' = 200, qualified: 'bool' = False, return_parsed: 'bool' = True, return_as_pandas: 'bool' = False, **kwargs: 'Any') -> "Union[pl.DataFrame, 'pd.DataFrame', Dict[str, Any]]"

Yahoo CFB player season stats (modern; one wide row per player).

Wraps the shangrila leagueStatsIndividual query, which returns every stat group (passing/rushing/receiving/...) in one call, pivoted wide with one column per statId. NCAAF data is available 2013-present.

Parameters

Parameter	Type	Default	Description
season	int	2024	Season year (2013-present). Defaults to 2024.
league_structure	str	'ncaaf.struct.div.1'	Yahoo league-structure id (division filter). Defaults to "ncaaf.struct.div.1" (FBS).
count	int	200	Maximum number of players to request. Defaults to 200.
qualified	bool	False	Restrict to qualified leaders only. Defaults to False.
return_parsed	bool	True	If True (default) flatten 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 wide polars DataFrame (default), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False. Includes a self-describing season column.

col_name	type	description
player_id	character	ESPN player id from the roster entry.
display_name	character	Human-readable metric name.
team	character	Team name.
team_abbreviation	character	Team abbreviation.
passing_completions	character	Pass completions (split from CFBD's C/ATT field).
rushing_attempts_per_game	character
sacks_yards_lost	character
solo_tackles	character
kickoff_return_touchdowns	character
field_goals_30_to_39	character
longest_punt	character
passing_touchdowns	character
field_goals_20_to_29	character
kickoff_returns	character
field_goals_made_20_29	character
games_rushing	character
games_defense	character
forced_fumbles	character
interception_return_yards	character
punt_return_touchdowns	character
longest_field_goal	character
sacks_taken	character
receiving_yards_per_reception	character
receiving_yards	character
field_goals_made_30_39	character
field_goals_made_50_plus	character
games_offense	character
punts	character
field_goals_made	character
field_goals_50_plus	character
all_purpose_yards	character
interception_return_touchdowns	character
field_goal_percentage	character
field_goals_made_0_19	character
rushing_touchdowns	character
punt_yards_per_punt	character
field_goal_attempts_40_49	character
sacks	character	Team sacks.
field_goals_made_40_49	character
longest_rush	character
games_returns	character
return_yards_per_kickoff	character
rushing_yards_per_game	character
longest_reception	character
rushing_yards	character	Team rushing yards.
games_kicking	character
passing_yards_per_attempt	character
rushing_yards_per_attempt	character
completion_percentage	character
total_tackles	character
games_punting	character
passing_yards_per_game	character
passes_defended	character
longest_pass	character
points_scored_kicking	character
passing_yards	character
receiving_yards_per_game	character
rushing_attempts	character	Team rushing attempts.
games_passing	character
field_goal_attempts_50_plus	character
targets	character
qb_rating	character
games_receiving	character
longest_kickoff_return	character
safeties	character
tackle_assists	character
passing_attempts	character	Pass attempts (split from CFBD's C/ATT field).
extra_point_attempts	character
interceptions_forced	character
extra_points_made	character
punt_yards	character
receptions	character
field_goal_attempts_30_39	character
field_goals_40_to_49	character
punt_return_yards	character	Team punt return yards.
field_goal_attempts	character
longest_punt_return	character
field_goal_attempts_20_29	character
field_goal_attempts_0_19	character
kickoff_return_yards	character
punt_returns	character	Number of punt returns.
sacks_yards	character
field_goals_0_to_19	character
receiving_touchdowns	character
extra_point_percentage	character
tackles_for_loss	character	Team tackles for a loss.
passing_interceptions	character
return_yards_per_punt	character
season	integer	Season (4-digit year).

Example

from sportsdataverse.cfb import yahoo_cfb_player_season_stats
df = yahoo_cfb_player_season_stats(season=2024)

yahoo_cfb_player_season_stats_legacy

yahoo_cfb_player_season_stats_legacy(season: 'int' = 2024, category: 'str' = 'Passing', sort_stat: 'str' = 'PASSING_YARDS', *, league_structure: 'str' = 'ncaaf.struct.div.1', count: 'int' = 200, return_parsed: 'bool' = True, return_as_pandas: 'bool' = False, **kwargs: 'Any') -> "Union[pl.DataFrame, 'pd.DataFrame', Dict[str, Any]]"

Yahoo CFB legacy per-category player leaders (one wide row per player).

Wraps the legacy seasonStatsFootball{Category}Ncaaf query (one stat category per call), pivoted wide with one column per statId.

Parameters

Parameter	Type	Default	Description
season	int	2024	Season year (2013-present). Defaults to 2024.
category	str	'Passing'	Stat category, one of {"Passing", "Rushing", "Receiving", "Defense", "Kicking", "Punting", "Returns"}. Defaults to "Passing".
sort_stat	str	'PASSING_YARDS'	Required FootballStatId to sort by (see the catalog vocab). Defaults to "PASSING_YARDS".
league_structure	str	'ncaaf.struct.div.1'	Yahoo league-structure id (division filter). Defaults to "ncaaf.struct.div.1" (FBS).
count	int	200	Maximum number of players to request. Defaults to 200.
return_parsed	bool	True	If True (default) flatten 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 wide polars DataFrame (default), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False. Includes self-describing season and category columns.

col_name	type	description
player_id	character	ESPN player id from the roster entry.
display_name	character	Human-readable metric name.
team	character	Team name.
team_abbreviation	character	Team abbreviation.
games_rushing	character
rushing_attempts	character	Team rushing attempts.
rushing_yards	character	Team rushing yards.
rushing_yards_per_game	character
rushing_yards_per_attempt	character
rushing_touchdowns	character
longest_rush	character
season	integer	Season (4-digit year).
category	character	CFBD stats category name (e.g. passing, rushing, defensive).

Example

from sportsdataverse.cfb import yahoo_cfb_player_season_stats_legacy
df = yahoo_cfb_player_season_stats_legacy(
    season=2024, category="Rushing", sort_stat="RUSHING_YARDS"
)

yahoo_cfb_scoreboard

yahoo_cfb_scoreboard(season: 'int', week: 'int' = 1, *, count: 'int' = 500, return_parsed: 'bool' = True, return_as_pandas: 'bool' = False, **kwargs: 'Any') -> "Union[pl.DataFrame, 'pd.DataFrame', Dict[str, Any]]"

Yahoo CFB scoreboard (one row per game).

Wraps the editorial scoreboard resource and flattens the games map. season is required — there is no meaningful default for a weekly scoreboard and the API has no concept of "current season". The full raw payload also carries teams/leagues/odds maps (use return_parsed=False).

Parameters

Parameter	Type	Default	Description
season	int		Season year (required).
week	int	1	Schedule week number. Defaults to 1.
count	int	500	Maximum number of games to request. Defaults to 500.
return_parsed	bool	True	If True (default) flatten the games map 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 one row per game, a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False. Includes self-describing season and week columns.

col_name	type	description
gameid	character	Date-encoded Yahoo composite game id for this row (e.g., "ncaaf.g.202509200023").
global_gameid	character	Yahoo cross-provider game id, distinct from the date-encoded gameid (e.g., "ncaaf.g.13556882").
start_time	character	Game start time.
is_time_tba	logical	Flag indicating that the scheduled start time has not yet been announced.
season_phase_id	character	Identifier of the season phase the game falls in (e.g., "season.phase.season").
game_type	character
winning_team_id	character	Composite Yahoo team id of the side that won the game (e.g., "ncaaf.t.29").
is_rank_upset	logical	Flag indicating that the lower-ranked side won, judged against the teams' poll rankings.
is_spread_upset	logical	Flag indicating that the winning side was the betting underdog against the closing spread.
outcome_type	character	Outcome classification for a completed game (e.g., "outcome.type.won", "outcome.type.tied").
home_team_id	character	ESPN home team id (parsed from home_team_ref).
away_team_id	character	ESPN away team id (parsed from away_team_ref).
week_number	character
navigation_links	character
sportacular_url	character	Deep link into the Yahoo Sportacular mobile app for this game (a "ysportacular://" URL).
status_display_name	character	Short game or event status as shown on the scoreboard (e.g., "Final", "12:00 pm ET").
status_description	character
status_type	character	Status type.
total_away_points	character	Points scored by the away team in the game.
current_period_id	character	Ordinal number of the period currently in progress, counting from 1.
total_home_points	character	Points scored by the home team in the game.
total_away_shootout_points	character	Shootout goals converted by the away team, populated only for sports that break ties by shootout.
total_home_shootout_points	character	Shootout goals converted by the home team, populated only for sports that break ties by shootout.
home_team_stats	character	JSON-encoded team-stat block for the home team, populated once the game is under way.
away_team_stats	character	JSON-encoded team-stat block for the away team, populated once the game is under way.
game_period_balls	character	Balls in the count for the at-bat in progress; baseball only.
game_period_strikes	character	Strikes in the count for the at-bat in progress; baseball only.
game_period_outs	character	Outs recorded so far in the current half-inning; baseball only.
yards_to_endzone	character	Distance from the current ball spot to the opponent's goal line, in yards.
start_yardline	character	Yard line at the drive start.
distance	character	Yards to gain for a first down (or to the goal line in goal-to-go situations).
down	character	Down of the play (1-4).
team_in_possession	character	Yahoo team id of the side currently in possession of the ball.
power_play_strength_home	character	Number of skaters the home team has on the ice during special-teams play; hockey only.
power_play_strength_away	character	Number of skaters the away team has on the ice during special-teams play; hockey only.
game_time_elapsed	character	Playing time elapsed in the game, in seconds.
game_time_elapsed_display	character	Playing time elapsed formatted for display (e.g., "67:12"), used by sports whose clock counts up.
inning_status	character	Half-inning indicator for a game in progress (e.g., "Top", "Bottom"); baseball only.
away_timeouts	character	Away-team timeouts remaining.
home_timeouts	character	Home-team timeouts remaining.
is_halftime	character	Flag indicating that the game is currently stopped at halftime.
minimum_periods	integer	Number of periods a game of this sport runs before overtime is required (4 for football, 9 for baseball).
game_periods	integer	JSON-encoded list of the game's period nodes, each carrying a period number and its display names.
baserunners	character	JSON-encoded baserunner occupancy for the game in progress; baseball only.
season	integer	Season (4-digit year).
subleague	character	Sub-league the game belongs to, for leagues split into constituent circuits.
subleague_display_name	character	Display name of the sub-league the game belongs to.
agg_score	character	Aggregate score across the legs of a two-leg tie, populated only for competitions decided on aggregate.
leg_number	character	Ordinal of this leg within a multi-leg tie, counting from 1.
tv_coverage	character	Network carrying the game, as a short broadcast abbreviation (e.g., "CBS", "ESPN").
provider_coverage	character
seatgeek_id	character	SeatGeek performer or event identifier used to build the ticket-purchase link.
last_updated	character	Timestamp ESPN last refreshed the power index.
teams	character
play_by_play	character	JSON-encoded data-island pointer to the game's play-by-play collection in the same editorial payload.
pitches	character	JSON-encoded data-island pointer to the game's pitch-level feed; baseball only.
at_bat	character	JSON-encoded data-island pointer to the game's current at-bat feed; baseball only.
penalty_summary	character
scoring_summary	character
stat_categories	character	JSON-encoded pointer to the stat-category dictionary that groups this feed's statistics.
stadium	character
stadium_id	character
stadium_image	character	JSON-encoded data-island pointer to the venue photograph used on the game page.
attendance	character	Reported attendance at the game.
lineups	character	JSON-encoded data-island pointer to the game's lineup collection.
top_performer	character	JSON-encoded data-island pointer to the game's top-performing players.
players	character
byline	character
highlight	character	JSON-encoded data-island pointer to the game's highlight video.
highlights	character	Game highlight urls.
live_video	character	JSON-encoded data-island pointer to the live video stream for the game.
odds	character	JSON-encoded data-island pointer to the game's odds collection.
current_players	character	JSON-encoded data-island pointer to the players currently on the field, ice or court.
last_play	character	Free-text description of the most recent play.
series_type	character	JSON-encoded data-island pointer to the kind of series the game belongs to.
series_status	character	JSON-encoded data-island pointer to the current state of the series the game belongs to.
games	character	Number of games included in the ATS summary.
series_games	character	JSON-encoded data-island pointer to the games making up the series.
game_details	character	JSON-encoded data-island pointer to supplementary detail notes for the game.
section_notes	character	JSON-encoded data-island pointer to editorial section notes attached to the game page.
articles	character	JSON-encoded data-island pointer to the editorial articles attached to the game.
tweets	character	JSON-encoded data-island pointer to the social posts attached to the game page.
playoff_round	character
media_stream	character	JSON-encoded data-island pointer to the game's media-stream collection.
playoff_series_status	character	JSON-encoded data-island pointer to the current state of the playoff series the game belongs to.
playoff_series_details	character	JSON-encoded data-island pointer to detail about the playoff series the game belongs to.
drives	character	JSON-encoded data-island pointer to the game's drive collection; football only.
user_teams_game	character	JSON-encoded data-island pointer to the viewer's followed-team context for the game.
page_metadata	character	JSON-encoded data-island pointer to the SEO and page metadata for the entity.
penalty_box	character	JSON-encoded data-island pointer to the game's penalty-box feed; hockey only.
starting_pitchers	character	JSON-encoded data-island pointer to the game's announced starting pitchers; baseball only.
unrestricted_streams	character	JSON-encoded data-island pointer to the streams viewable without a subscription.
tv_details	character	JSON-encoded list of broadcast entries for the game, each carrying a network abbreviation and full channel name (e.g., [{"abbr": "NBC", "name": "NBC/Peacock"}]).
away_seed	character
home_seed	character
week	integer	Game week of the season.

Example

from sportsdataverse.cfb import yahoo_cfb_scoreboard
df = yahoo_cfb_scoreboard(season=2024, week=1)

yahoo_cfb_team_season_stats

yahoo_cfb_team_season_stats(season: 'int' = 2024, *, league_structure: 'str' = 'ncaaf.struct.div.1', count: 'int' = 200, return_parsed: 'bool' = True, return_as_pandas: 'bool' = False, **kwargs: 'Any') -> "Union[pl.DataFrame, 'pd.DataFrame', Dict[str, Any]]"

Yahoo CFB team season stats (modern; one wide row per team).

Wraps the shangrila leagueStatsByTeam query (all stat groups in one call, pivoted wide with one column per statId).

Parameters

Parameter	Type	Default	Description
season	int	2024	Season year (2013-present). Defaults to 2024.
league_structure	str	'ncaaf.struct.div.1'	Yahoo league-structure id (division filter). Defaults to "ncaaf.struct.div.1" (FBS).
count	int	200	Maximum number of teams to request. Defaults to 200.
return_parsed	bool	True	If True (default) flatten 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 wide polars DataFrame (default), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False. Includes a self-describing season column.

col_name	type	description
team	character	Team name.
team_abbreviation	character	Team abbreviation.
receiving_yards_rank	character
passing_touchdowns	character
rushing_attempts	character	Team rushing attempts.
rushing_yards_allowed_per_attempt	character
points_per_game	character
receiving_first_downs_allowed	character
receiving_yards_allowed_per_game	character
passing_yards_per_game	character
total_offensive_yards_per_game	character
interceptions_forced_rank	character
rushing_yards_allowed_per_game	character
total_offensive_yards_per_game_rank	character
receiving_yards	character
points_per_game_rank	character
rushing_yards_rank	character
receiving_yards_allowed	character
rushing_touchdowns	character
points_allowed_per_game_rank	character
third_down_attempts	character
sacks_taken	character
total_yards_allowed_per_game_rank	character
rushing_yards_per_attempt	character
rushing_touchdowns_allowed_per_game	character
longest_pass	character
completion_percentage	character
receptions	character
receiving_yards_per_reception	character
interceptions_forced	character
passing_completions_per_game	character
team_penalties	character
rushing_first_downs_allowed	character
receiving_yards_per_game	character
points_allowed	character	Points for the opponent.
points_allowed_rank	character
total_yards_allowed_per_game	character
rushing_attempts_allowed	character	Opponent rushing attempts.
games_kicking	character
completion_percentage_allowed	character
rushing_yards_allowed_per_game_rank	character
receiving_touchdowns	character
games_punting	character
total_offensive_yards	character
points	character	Total points accumulated by the school in the poll's weighted voting.
rushing_yards_per_game_rank	character
passing_yards_per_attempt	character
receptions_per_game	character
rushing_first_downs	character
receiving_first_downs	character
passing_first_downs	character
points_rank	character
passing_yards_allowed_per_game	character
fourth_down_conversions	character
receptions_allowed	character
passing_attempts_per_game	character
passing_yards	character
rushing_touchdowns_allowed	character
receiving_touchdowns_allowed	character
receptions_allowed_per_game	character
rushing_yards_allowed	character	Opponent rushing yards.
games_receiving	character
sacks_rank	character
points_allowed_per_game	character
rushing_yards	character	Team rushing yards.
games_rushing	character
longest_rush	character
games_offense	character
fourth_down_conversion_percentage	character
receiving_touchdowns_allowed_per_game	character
passing_attempts_allowed_per_game	character
passing_first_downs_allowed	character
passing_completions	character	Pass completions (split from CFBD's C/ATT field).
total_offensive_yards_rank	character
time_of_possession_per_game_rank	character
offensive_penalty_yards_lost	character
team_penalty_yards_lost	character
passing_yards_per_game_rank	character
interception_return_touchdowns	character
passing_yards_allowed_per_game_rank	character
sacks_yards_lost	character
games_defense	character
passing_yards_allowed	character
passing_touchdowns_allowed	character
games_passing	character
passing_completions_allowed_per_game	character
passing_touchdowns_allowed_per_game	character
rushing_yards_per_game	character
fourth_down_attempts	character
passing_yards_rank	character
rushing_attempts_per_game	character
third_down_conversion_percentage	character
passing_attempts	character	Pass attempts (split from CFBD's C/ATT field).
passing_interceptions	character
first_downs	character	First downs earned by the team.
first_downs_per_game	character
rushing_attempts_allowed_per_game	character
third_down_conversions	character
time_of_possession_per_game	character
offensive_penalties	character
season	integer	Season (4-digit year).

Example

from sportsdataverse.cfb import yahoo_cfb_team_season_stats
df = yahoo_cfb_team_season_stats(season=2024)

yahoo_cfb_team_season_stats_legacy

yahoo_cfb_team_season_stats_legacy(season: 'int' = 2024, category: 'str' = 'Passing', sort_stat: 'str' = 'PASSING_YARDS', *, league_structure: 'str' = 'ncaaf.struct.div.1', count: 'int' = 200, return_parsed: 'bool' = True, return_as_pandas: 'bool' = False, **kwargs: 'Any') -> "Union[pl.DataFrame, 'pd.DataFrame', Dict[str, Any]]"

Yahoo CFB legacy per-category team stats (one wide row per team).

Wraps the legacy seasonTeamStatsFootball{Category} query (one stat category per call), pivoted wide with one column per statId.

Parameters

Parameter	Type	Default	Description
season	int	2024	Season year (2013-present). Defaults to 2024.
category	str	'Passing'	Stat category, one of {"Passing", "Rushing", "Receiving", "Defense", "Kicking", "Punting", "Returns", "Kickoffs", "Offense"}. Defaults to "Passing".
sort_stat	str	'PASSING_YARDS'	Required FootballStatId to sort by. Defaults to "PASSING_YARDS".
league_structure	str	'ncaaf.struct.div.1'	Yahoo league-structure id (division filter). Defaults to "ncaaf.struct.div.1" (FBS).
count	int	200	Maximum number of teams to request. Defaults to 200.
return_parsed	bool	True	If True (default) flatten 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 wide polars DataFrame (default), a pandas DataFrame when return_as_pandas=True, or the raw JSON dict when return_parsed=False. Includes self-describing season and category columns.

col_name	type	description
team	character	Team name.
team_abbreviation	character	Team abbreviation.
games_rushing	character
rushing_attempts	character	Team rushing attempts.
rushing_yards	character	Team rushing yards.
rushing_yards_per_attempt	character
rushing_attempts_per_game	character
rushing_yards_per_game	character
rushing_touchdowns	character
rushing_first_downs	character
longest_rush	character
rushing_fumbles	character
rushing_fumbles_lost	character
season	integer	Season (4-digit year).
category	character	CFBD stats category name (e.g. passing, rushing, defensive).

Example

from sportsdataverse.cfb import yahoo_cfb_team_season_stats_legacy
df = yahoo_cfb_team_season_stats_legacy(
    season=2024, category="Rushing", sort_stat="RUSHING_YARDS"
)

yahoo_cfb_teams

yahoo_cfb_teams(season: 'int', week: 'int' = 1, *, return_parsed: 'bool' = True, return_as_pandas: 'bool' = False, **kwargs: 'Any') -> "Union[pl.DataFrame, 'pd.DataFrame', Dict[str, Any]]"

Yahoo CFB team directory (one row per team).

Yahoo has no standalone teams resource (the documented sports.league.teams resource 404s without auth). Instead the editorial scoreboard payload is "fat": one call embeds the full ~186-team directory under service.scoreboard.teams keyed by the dotted ncaaf.t.<id> team id. This wrapper pulls that map for the requested (season, week) and projects it to the directory columns -- it is the Yahoo side of sportsdataverse.cfb.cfb_teams_crosswalk.

Parameters

Parameter	Type	Default	Description
season	int		Season year (required; the scoreboard is fetched to obtain the embedded teams map).
week	int	1	Schedule week used to fetch the scoreboard. Defaults to 1. The embedded directory is the full league list regardless of week.
return_parsed	bool	True	If True (default) flatten the teams map to a DataFrame; if False return the raw scoreboard 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 one row per team -- columns team_id, abbreviation, display_name, full_name, location, nickname, conference, conference_abbreviation, conference_id, division, division_id, seatgeek_id -- a pandas DataFrame when return_as_pandas=True, or the raw scoreboard JSON dict when return_parsed=False.

col_name	type	description
team_id	character	ESPN team id.
abbreviation	character	Metric abbreviation.
display_name	character	Human-readable metric name.
full_name	character	Venue full name (e.g. Tenney Stadium).
location	character	Team location / school name.
nickname	character	Team nickname / location label.
conference	character	Conference of the team.
conference_abbreviation	character
conference_id	character	Referencing conference id.
division	character	Division in the conference for the team.
division_id	character
seatgeek_id	character	SeatGeek performer or event identifier used to build the ticket-purchase link.

Example

from sportsdataverse.cfb import yahoo_cfb_teams
teams = yahoo_cfb_teams(season=2024)
abbr = dict(zip(teams["team_id"], teams["abbreviation"]))