knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "README-" ) Sys.setenv(TZ="Europe/London")
The bballR package uses tidyverse packages to efficiently scrape data from basketball-reference and return it in the tidy data format.
devtools::install_github("bobbyingram/bballR")
To scrape high-level player information for players in the basketball-reference player database use
library(bballR) players <- scrape_all_players() dplyr::glimpse(players)
To scrape high-level information for teams in the the basketball-reference team database use
all_teams <- scrape_teams() active_teams <- scrape_teams(status = "active") defunct_teams <- scrape_teams(status = "defunct") dplyr::glimpse(all_teams)
To scrape summary player performance data for an individual season use
season <- 2017 per_game_2017 <- scrape_season_per_game(season) per_100_2017 <- scrape_season_per_100_poss(season) per_36_2017 <- scrape_season_per_36_minute(season) adv_2017 <- scrape_season_advanced(season) totals_2017 <- scrape_season_totals(season) dplyr::glimpse(per_game_2017)
To scrape an individual players regular season game logs from a single season you need to know use unique player Id from the players lookup:
player <- "Dwyane Wade" wade <- dplyr::filter(players, Player == player) wade_logs <- scrape_game_logs(wade$PlayerId, season) dplyr::glimpse(wade_logs)
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