Women's college basketball — additional Python functions — Models and calculators: wbb_team–win_prob
wbb_team_ratings
wbb_team_ratings(seasons: 'Union[int, list[int]]', *, return_as_pandas: 'bool' = False) -> 'Union[pl.DataFrame, pd.DataFrame]'
Women's opponent-adjusted team ratings (AdjO/AdjD/AdjEM/AdjTempo).
Delegates to sportsdataverse.mbb.mbb_team_ratings.mbb_team_ratings
with league="womens" (WBB loaders + women's fitted constants).
Parameters
| Parameter | Type | Default | Description |
|---|---|---|---|
seasons | Union[int, list[int]] | A season (e.g. 2024) or list of seasons. | |
return_as_pandas | bool | False | Return a pandas frame instead of polars. |
Returns
One row per (season, team_id) -- see the mbb core for the schema.
| col_name | type | description |
|---|---|---|
season | Int64 | Season identifier (4-digit year or 'YYYY-YY' string). |
team_id | String | Unique team identifier. |
adj_o | Float64 | Adj o. |
adj_d | Float64 | Adj d. |
adj_em | Float64 | Adj em. |
adj_tempo | Float64 | |
raw_o | Float64 | Raw o. |
raw_d | Float64 | Raw d. |
games | Int64 | Games played. |
rank | Int64 | Rank. |
adj_em_z | Float64 |
Example
from sportsdataverse.wbb import wbb_team_ratings
wbb_team_ratings(2024).sort("rank").head()
win_prob_from_margin
win_prob_from_margin(exp_margin: 'float') -> 'float'
Women's home win probability from an expected margin.
Delegates to sportsdataverse.mbb.mbb_game_predict.win_prob_from_margin with league="womens".
Parameters
| Parameter | Type | Default | Description |
|---|---|---|---|
exp_margin | float | Expected home-minus-away margin in points. |
Returns
Probability the home team wins, in (0, 1).
Example
from sportsdataverse.wbb.wbb_game_predict import win_prob_from_margin
win_prob_from_margin(5.0)