The NCAAB package offers multiple modules which can be used to retrieve information and statistics for Men's Division I College Basketball, such as team names, season stats, game schedules, and boxscore metrics.
The Boxscore module can be used to grab information from a specific game. Metrics range from number of points scored to the number of blocked shots, to the assist percentage and much more. The Boxscore can be easily queried by passing a boxscore's URI on sports-reference.com which can be retrieved from the Schedule class (see Schedule module below for more information on retrieving game-specific information).
from sportsipy.ncaab.boxscore import Boxscore
game_data = Boxscore('2018-04-02-21-villanova')
print(game_data.home_points) # Prints 79
print(game_data.away_points) # Prints 62
df = game_data.dataframe # Returns a Pandas DataFrame of game metricsThe Boxscore module also contains a Boxscores class which searches for all games played on a particular day and returns a dictionary of matchups between all teams on the requested day. The dictionary includes the names and abbreviations for each matchup as well as the boxscore link if applicable.
from datetime import datetime
from sportsipy.ncaab.boxscore import Boxscores
games_today = Boxscores(datetime.today())
print(games_today.games) # Prints a dictionary of all matchups for todayThe Boxscores class also allows the ability to query over a range of dates using a second optional parameter during instantiation of the class. To query a range of dates, enter the start date as the first parameter and the inclusive end date as the second parameter.
from datetime import datetime
from sportsipy.ncaab.boxscore import Boxscores
# Pulls all games between and including November 11, 2017 and November 12,
# 2017
games = Boxscores(datetime(2017, 11, 11), datetime(2017, 11, 12))
# Prints a dictionary of all results from November 11, 2017 and November 12,
# 2017
print(games.games)sportsipy.ncaab.boxscore
The Conference module allows conferences to be pulled for any season using the Conferences class. Accessing the class properties exposes various dictionaries containing the team and conference abbreviations as well as other information. To get a list of conference abbreviations for each team, query the team_conference property.
from sportsipy.ncaab.conferences import Conferences
conferences = Conferences()
# Prints a dictionary of the team abbrevation as a key and conference
# abbreviation as the value.
print(conferences.team_conference)The conferences property can also be queried to provide more details on the teams in every conference.
from sportsipy.ncaab.conferences import Conferences
conferences = Conferences()
# Prints a dictionary where each key is the conference abbreviation and
# each value is a dictionary containing the full conference name as well as
# another dictionary of all teams in the conference, including name and
# abbreviation for each team.
print(conferences.conferences)sportsipy.ncaab.conferences
The Player module contains an abstract base class that can be inherited by both the BoxscorePlayer and Player classes in the Boxscore and Roster modules, respectively. All of the properties that appear in the AbstractPlayer class can be read from either of the two child classes mentioned above.
sportsipy.ncaab.player
The Rankings module includes the Rankings class which can be used to easily query the NCAAB Men's Division-I Basketball rankings published by the Associated Press on a week-by-week basis. Different formats can be referenced, ranging from a lightweight dictionary of the most recent rankings containing only the team abbreviation and rank, to a much larger dictionary of all rankings for an entire season with results including full team name and abbreviation, current rank, week number, previous rank, and movement.
from sportsipy.ncaab.rankings import Rankings
rankings = Rankings()
# Prints a dictionary of just the team abbreviation and rank for the current
# week
print(rankings.current)
# Prints more detailed information including previous rank, full name, and
# movement for all teams in current week
print(rankings.current_extended)
# Prints detailed information for all teams for all weeks where rankings
# have been published for the requested season.
print(rankings.complete)sportsipy.ncaab.rankings
The Roster module contains detailed player information, allowing each player to be queried by their player ID using the Player class which has detailed information ranging from career points totals to single-season stats and player height and weight. The following is an example on collecting career information for Carsen Edwards.
from sportsipy.ncaab.roster import Player
carsen_edwards = Player('carsen-edwards-1')
print(carsen_edwards.name) # Prints 'Carsen Edwards'
print(carsen_edwards.points) # Prints Edwards' career points total
# Prints a Pandas DataFrame of all relevant stats per season for Edwards
print(carsen_edwards.dataframe)By default, the player's career stats are returns whenever a property is called. To get stats for a specific season, call the class instance with the season string. All future property requests will return the season-specific stats.
from sportsipy.ncaab.roster import Player
carsen_edwards = Player('carsen-edwards-1') # Currently pulling career stats
print(carsen_edwards.points) # Prints Edwards' CAREER points total
# Prints Edwards' points total only for the 2017-18 season.
print(carsen_edwards('2017-18').points)
# Prints the number of games Edwards played in the 2017-18 season.
print(carsen_edwards.games_played)After requesting single-season stats, the career stats can be requested again by calling the class without arguments or with the 'Career' string passed.
from sportsipy.ncaab.roster import Player
carsen_edwards = Player('carsen-edwards-1') # Currently pulling career stats
# Prints Edwards' points total only for the 2017-18 season.
print(carsen_edwards('2017-18').points)
print(carsen_edwards('Career').points) # Prints Edwards' career points totalIn addition, the Roster module also contains the Roster class which can be used to pull all players on a team's roster during a given season and creates instances of the Player class for each team member and adds them to a list to be easily queried.
from sportsipy.ncaab.roster import Roster
purdue = Roster('PURDUE')
for player in purdue.players:
# Prints the name of all players who played for Purdue in the most
# recent season.
print(player.name)sportsipy.ncaab.roster
The Schedule module can be used to iterate over all games in a team's schedule to get game information such as the date, score, result, and more. Each game also has a link to the Boxscore class which has much more detailed information on the game metrics.
from sportsipy.ncaab.schedule import Schedule
purdue_schedule = Schedule('PURDUE')
for game in purdue_schedule:
print(game.date) # Prints the date the game was played
print(game.result) # Prints whether the team won or lost
# Creates an instance of the Boxscore class for the game.
boxscore = game.boxscoresportsipy.ncaab.schedule
The Teams module exposes information for all NCAAB teams including the team name and abbreviation, the number of games they won during the season, the total number of shots they've blocked, and much more.
from sportsipy.ncaab.teams import Teams
teams = Teams()
for team in teams:
print(team.name) # Prints the team's name
print(team.blocks) # Prints the number of shots the team blockedA team can also be requested directly by calling the Team class which returns a Team instance identical to the one in each element in the loop above. To request a specific team, use the team's abbreviation while calling the Team class.
from sportsipy.ncaab.teams import Team
purdue = Team('PURDUE')Each Team instance contains a link to the Schedule class which enables easy iteration over all games for a particular team. A Pandas DataFrame can also be queried to easily grab all stats for all games.
from sportsipy.ncaab.teams import Teams
teams = Teams()
for team in teams:
schedule = team.schedule # Returns a Schedule instance for each team
# Returns a Pandas DataFrame of all metrics for all game Boxscores for
# a season.
df = team.schedule.dataframe_extendedLastly, each Team instance also contains a link to the Roster class which enables players from the team to be easily queried. Each Roster instance contains detailed stats and information for each player on the team.
from sportsipy.ncaab.teams import Teams
for team in Teams():
roster = team.roster # Gets each team's roster
for player in roster.players:
print(player.name) # Prints each players name on the rostersportsipy.ncaab.teams