The NCAAF package offers multiple modules which can be used to retrieve information and statistics for Division-I College Football, 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 pass yards, to the yards from penalties 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 sportsreference.ncaaf.boxscore import Boxscore
game_data = Boxscore('2018-01-08-georgia')
print(game_data.home_points) # Prints 23
print(game_data.away_points) # Prints 26
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 sportsreference.ncaaf.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 sportsreference.ncaaf.boxscore import Boxscores
# Pulls all games between and including August 30, 2017 and August 31, 2017
games = Boxscores(datetime(2017, 8, 30), datetime(2017, 8, 31))
# Prints a dictionary of all results from August 30, 2017 and August 31,
# 2017
print(games.games)sportsreference.ncaaf.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 sportsreference.ncaaf.conferences import Conferences
conferences = Conferences()
# Prints a dictionary of the team abbreviation 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 sportsreference.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)sportsreference.ncaaf.conferences
The Rankings module include the Rankings class which can be used to easily query the NCAA Men's Division-I Football 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 sportsreference.ncaaf.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 for the 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)sportsreference.ncaaf.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 touchdowns to single-season stats and player height, weight, and nationality. The following is an example on collecting career information for David Blough.
from sportsreference.ncaaf.roster import Player
blough = Player('david-blough-1')
print(blough.name) # Prints 'David Blough'
print(blough.passing_yards) # Prints Blough's career passing yards
# Prints a Pandas DataFrame of all relevant stats per season for Blough
print(blough.dataframe)By default, the player's career stats are returned whenever a property is called. To get stats for a specific team, call the class instance with the season string. All future property requests will return the season-specific stats.
from sportsreference.ncaaf.roster import Player
blough = Player('david-blough-1') # Currently pulling career stats
print(blough.passing_yards) # Prints Blough's CAREER passing yards total
# Prints Blough's passing yards total only for the 2017 season
print(blough('2017').passing_yards)
# Prints Blough's passing touchdowns for the 2017 season only
print(blough.passing_touchdowns)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 sportsreference.ncaaf.roster import Player
blough = Player('david-blough-1') # Currently pulling career stats
# Prints Blough's passing yards total only for the 2017 season
print(blough('2017').passing_yards)
print(blough('Career').passing_yards) # Prints Blough's career passing yardsIn 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 sportsreference.ncaaf.roster import Roster
boilermakers = Roster('PURDUE')
for player in boilermakers.players:
# Prints the name of all players who played for the Purdue Boilermakers
# in the most recent season.
print(player.name)sportsreference.ncaaf.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 sportsreference.ncaaf.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.boxscoresportsreference.ncaaf.schedule
The Teams module exposes information for all NCAAF teams including the team name and abbreviation, the number of games they won during the season, the total number of pass yards, and much more.
from sportsreference.ncaaf.teams import Teams
teams = Teams()
for team in teams:
print(team.name) # Prints the team's name
print(team.pass_yards) # Prints the team's total passing yardsEach 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 sportsreference.ncaaf.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 sportsreference.ncaaf.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 rostersportsreference.ncaaf.teams