Basketball - uwaggs/usportspy GitHub Wiki
Basketball Functions
The usportspy package provides various functions to retrieve basketball-related data, such as schedules, team box scores, player box scores, and play-by-play data.
Functions
basketball_get_schedule
Fetches the basketball schedule for the specified gender.
Parameters:
gender(str): Specifies the gender of the teams. Must be either"m"or"w".
Returns:
pd.DataFrame: A DataFrame containing the basketball schedule. The columns of the returned DataFrame are: date, away, away_score, home, home_score, status, notes, month, box_scores, conference, division, exhibition, postseason, and season.
Example:
from usportspy import basketball_get_schedule
# Get the schedule for male teams
male_schedule = basketball_get_schedule("m")
print(male_schedule.head())
# Get the schedule for female teams
female_schedule = basketball_get_schedule("w")
print(female_schedule.head())
Expected output:
date away away_score home home_score status notes month box_scores conference division exhibition postseason season
0 Thu. 24 Guelph NaN Brock NaN 8:00 PM EDT NaN October 2024 NaN 1 0 0 0 2024-25
1 Fri. 25 Toronto NaN Laurentian NaN 8:00 PM EDT NaN October 2024 NaN 1 0 0 0 2024-25
2 Fri. 25 Toronto Metropolitan NaN Nipissing NaN 8:00 PM EDT NaN October 2024 NaN 1 0 0 0 2024-25
3 Fri. 25 Laurier NaN York NaN 8:00 PM EDT NaN October 2024 NaN 1 0 0 0 2024-25
4 Fri. 25 Windsor NaN Ottawa NaN 8:00 PM EDT NaN October 2024 NaN 1 0 0 0 2024-25
date away away_score home home_score status ... box_scores conference division exhibition postseason season
0 Tue. 6 South Carolina State 70.0 UQAM 65.0 Final ... https://en.usports.ca/sports/wbkb/2024-25/boxs... 0 0 1 0 2024-25
1 Wed. 7 South Carolina State 69.0 Laval 73.0 Final ... https://en.usports.ca/sports/wbkb/2024-25/boxs... 0 0 1 0 2024-25
2 Thu. 8 South Carolina State NaN Concordia NaN 6:00 PM EDT ... NaN 0 0 1 0 2024-25
3 Sat. 17 Assumption NaN Concordia NaN 6:00 PM EDT ... NaN 0 0 1 0 2024-25
4 Fri. 20 StFX NaN Mount Allison NaN TBA ... NaN 0 0 1 0 2024-25
[5 rows x 14 columns]
basketball_get_team_box_score
Fetches the team box score data for basketball teams over specified seasons.
Parameters:
gender(str): Specifies the gender of the teams. Must be either"m"or"w".seasons(list of int, optional): List of seasons (starting year) to filter by. If nothing is provided, data for all seasons will be returned.
Returns:
pd.DataFrame: A DataFrame containing the team box scores. The columns of the returned DataFrame are: field_goals_made, field_goals_attempted, field_goal_percentage, three_point_field_goals_made, three_point_field_goals_attempted, three_point_field_goal_percentage, free_throws_made, free_throws_attempted, free_throw_percentage, rebounds, assists, turnovers, points_off_turnovers, second_chance_points, points_in_the_paint, fastbreak_points, bench_points, largest_lead, trends, team_name, game_id, date, q1, q2, q3, q4, total, time_of_largest_lead, ot, x2ot, x3ot, season, and season_type.
Example:
from usportspy import basketball_get_team_box_score
# Get team box scores for male teams for the 2018 and 2019 seasons
male_team_box_score = basketball_get_team_box_score("m", [2018, 2019])
print(male_team_box_score.head())
# Get team box scores for female teams for the 2018 and 2019 seasons
female_team_box_score = basketball_get_team_box_score("w", [2018, 2019])
print(female_team_box_score.head())
Expected output:
field_goals_made field_goals_attempted field_goal_percentage three_point_field_goals_made three_point_field_goals_attempted ... ot x2ot x3ot season season_type
0 26 69 37.7% 10 29 ... NaN NaN NaN 2018-19 p
1 37 72 51.4% 6 23 ... NaN NaN NaN 2018-19 p
2 19 56 33.9% 5 18 ... NaN NaN NaN 2018-19 p
3 25 71 35.2% 8 29 ... NaN NaN NaN 2018-19 p
4 29 70 41.4% 5 19 ... NaN NaN NaN 2018-19 p
[5 rows x 33 columns]
field_goals_made field_goals_attempted field_goal_percentage three_point_field_goals_made three_point_field_goals_attempted ... ot x2ot x3ot season season_type
0 22 81 27.2% 2 20 ... NaN NaN NaN 2018-19 p
1 38 88 43.2% 9 25 ... NaN NaN NaN 2018-19 p
2 28 59 47.5% 8 17 ... NaN NaN NaN 2018-19 p
3 31 73 42.5% 6 18 ... NaN NaN NaN 2018-19 p
4 23 63 36.5% 7 18 ... NaN NaN NaN 2018-19 p
[5 rows x 33 columns]
basketball_get_player_box_score
Fetches the player box score data for basketball players over specified seasons.
Parameters:
gender(str): Specifies the gender of the teams. Must be either"m"or"w".seasons(list of int, optional): List of seasons (starting year) to filter by. If nothing is provided, data for all seasons will be returned.
Returns:
pd.DataFrame: A DataFrame containing the player box scores. The columns of the returned DataFrame are: player, min, fgm, fga, three_pm, three_pa, ftm, fta, oreb, dreb, reb, ast, stl, blk, to, pf, pts, starter, player_number, player_links, date, game_id, team_name, season, and season_type.
Example:
from usportspy import basketball_get_player_box_score
# Get player box scores for male teams for the 2018 and 2019 seasons
male_player_box_score = basketball_get_player_box_score("m", [2018, 2019])
print(male_player_box_score.head())
# Get player box scores for female teams for the 2018 and 2019 seasons
female_player_box_score = basketball_get_player_box_score("w", [2018, 2019])
print(female_player_box_score.head())
Expected output:
player min fgm fga three_pm three_pa ftm fta oreb dreb reb ... to pf pts starter player_number player_links date game_id team_name season season_type
0 Keiran Zziwa 23.0 0.0 5.0 0.0 3.0 1.0 2.0 0.0 0.0 0.0 ... 4.0 2.0 1.0 1 1.0 NaN February 7, 2019 - 7:00pm 20190207_q3pq Manitoba 2018-19 p
1 Rashawn Browne 35.0 8.0 17.0 3.0 8.0 4.0 4.0 0.0 3.0 3.0 ... 6.0 1.0 23.0 1 4.0 NaN February 7, 2019 - 7:00pm 20190207_q3pq Manitoba 2018-19 p
2 James Wagner 40.0 5.0 12.0 0.0 2.0 6.0 7.0 5.0 5.0 10.0 ... 1.0 4.0 16.0 1 10.0 NaN February 7, 2019 - 7:00pm 20190207_q3pq Manitoba 2018-19 p
3 Andre Arruda 34.0 6.0 19.0 1.0 6.0 2.0 2.0 3.0 2.0 5.0 ... 2.0 3.0 15.0 1 11.0 NaN February 7, 2019 - 7:00pm 20190207_q3pq Manitoba 2018-19 p
4 Cameron O'Hara 13.0 0.0 2.0 0.0 0.0 0.0 0.0 0.0 2.0 2.0 ... 0.0 0.0 0.0 1 13.0 NaN February 7, 2019 - 7:00pm 20190207_q3pq Manitoba 2018-19 p
[5 rows x 25 columns]
player min fgm fga three_pm three_pa ftm fta oreb dreb reb ... to pf pts starter team_name player_number player_links date game_id season season_type
0 Taylor Randall 31.0 5.0 23.0 0.0 7.0 5.0 5.0 1.0 0.0 1.0 ... 4.0 1.0 15.0 1 Manitoba 3.0 NaN February 8, 2019 - 6:00 pm 20190208_pfog 2018-19 p
1 Tianna Mighty 13.0 0.0 2.0 0.0 0.0 0.0 0.0 1.0 1.0 2.0 ... 0.0 2.0 0.0 1 Manitoba 5.0 NaN February 8, 2019 - 6:00 pm 20190208_pfog 2018-19 p
2 Emma Thompson 20.0 0.0 5.0 0.0 3.0 0.0 0.0 0.0 2.0 2.0 ... 0.0 2.0 0.0 1 Manitoba 8.0 NaN February 8, 2019 - 6:00 pm 20190208_pfog 2018-19 p
3 Nicole Konieczny 33.0 6.0 18.0 1.0 4.0 4.0 6.0 0.0 8.0 8.0 ... 1.0 1.0 17.0 1 Manitoba 10.0 NaN February 8, 2019 - 6:00 pm 20190208_pfog 2018-19 p
4 Claire Harvey 21.0 3.0 10.0 0.0 1.0 0.0 1.0 4.0 5.0 9.0 ... 3.0 2.0 6.0 1 Manitoba 11.0 NaN February 8, 2019 - 6:00 pm 20190208_pfog 2018-19 p
[5 rows x 25 columns]
basketball_get_pbp
Fetches the play-by-play (PBP) data for basketball games over specified seasons.
Parameters:
gender(str): Specifies the gender of the teams. Must be either"m"or"w".seasons(list of int, optional): List of seasons (starting year) to filter by. If nothing is provided, data for all seasons will be returned.
Returns:
pd.DataFrame: A DataFrame containing the play-by-play data. The columns of the returned DataFrame are: time, away, away_score, home_score, home, quarter, game_id, away_team, home_team, season, and season_type.
Example:
from usportspy import basketball_get_pbp
# Get PBP data for male teams for the 2018 and 2019 seasons
male_pbp = basketball_get_pbp("m", [2018, 2019])
print(male_pbp.head())
# Get PBP data for female teams for the 2018 and 2019 seasons
female_pbp = basketball_get_pbp("w", [2018, 2019])
print(female_pbp.head())
Expected output:
time away away_score home_score home quarter game_id away_team home_team season season_type
0 09:51 NaN 0 2 AMBANZA,NARCISSE made jump shot 1st 20190207_q3pq Manitoba Winnipeg 2018-19 p
1 09:45 Turnover by ARRUDA,ANDRE 0 2 NaN 1st 20190207_q3pq Manitoba Winnipeg 2018-19 p
2 09:43 NaN 0 2 Steal by TARVER,SEAN 1st 20190207_q3pq Manitoba Winnipeg 2018-19 p
3 09:30 NaN 0 4 AMBANZA,NARCISSE made jump shot 1st 20190207_q3pq Manitoba Winnipeg 2018-19 p
4 09:28 Turnover by BROWNE,RASHAWN 0 4 NaN 1st 20190207_q3pq Manitoba Winnipeg 2018-19 p
time away away_score home_score home quarter game_id away_team home_team season season_type
0 09:50 NaN 0.0 0.0 FRITZKE,DANIELLE missed 3-pt. jump shot 1st 20190208_pfog Manitoba Lethbridge 2018-19 p
1 09:50 NaN 0.0 0.0 ZAROWNY,JESSICA offensive rebound 1st 20190208_pfog Manitoba Lethbridge 2018-19 p
2 09:39 NaN 0.0 0.0 BOSCH,KACIE missed jump shot 1st 20190208_pfog Manitoba Lethbridge 2018-19 p
3 09:39 NaN 0.0 0.0 BOSCH,KACIE offensive rebound 1st 20190208_pfog Manitoba Lethbridge 2018-19 p
4 09:26 NaN 0.0 0.0 FOMINA,ASNATE missed jump shot 1st 20190208_pfog Manitoba Lethbridge 2018-19 p