Get NFL Season Schedules

fast_scraper_schedules(seasons, pp = FALSE)

Arguments

seasons	Vector of numeric or character 4 digit seasons
pp	Logical - either `TRUE` or `FALSE` (see details for further information)

Value

Data frame containing the following detailed game information:

game_id: Character identifier including season, week, away team and home team
season: 4 digit season year.
game_type: One of 'REG', 'WC', 'DIV', 'CON', 'SB' indicating if a game was a regular season game or one of the playoff rounds.
week: Numeric week number.
gameday: Game date in format yyyy/mm/dd.
weekday: The day of the week on which the game occcured.
gametime: The kickoff time of the game. This is represented in 24-hour time and the Eastern time zone, regardless of what time zone the game was being played in.
away_team: Away team abbreviation.
home_team: Home team abbreviation.
away_score: The number of points the away team scored. Is 'NA' for games which haven't yet been played.
home_score: The number of points the home team scored. Is 'NA' for games which haven't yet been played.
home_result: Equals home_score - away_score and means the game outcome from the perspective of the home team.
stadium: Name of the stadium the game was or will be played in. (Source: Pro-Football-Reference)
location: Either 'Home' o 'Neutral' indicating if the home team played at home or at a neutral site.
roof: One of 'dome', 'outdoors', 'closed', 'open' indicating indicating the roof status of the stadium the game was played in. (Source: Pro-Football-Reference)
surface: What type of ground the game was played on. (Source: Pro-Football-Reference)
old_game_id: Unique game identifier of the old NFL API.

Details

This functions now incorporates the games file provided and maintained by Lee Sharpe.

The pp parameter controls if the scraper should use parallel processing. Please note that the initiating process takes a few seconds which means it may be better to set pp = FALSE if you are scraping less than 10 seasons.

Examples

if (FALSE) {
# Get schedules for the whole 2015 - 2018 seasons
seasons <- 2015:2018
schedules <- fast_scraper_schedules(seasons)
}