This package is designed to allow users to extract various world football results and player statistics from the following popular football (soccer) data sites:
You can install the
worldfootballR package from github with:
# install.packages("devtools") devtools::install_github("JaseZiv/worldfootballR")
Package vignettes have been built to help you get started with the package.
This vignette will cover the functions to extract data from transfermarkt.com
To be able to join data player between FBref and Transfermarkt,
player_dictionary_mapping() has been created. There are over 6,100 players who have been listed for teams in the Big 5 Euro leagues on FBref since the start of the 2017-18 seasons, with all of these mapped together. This is expected to be updated and grow over time. The raw data is stored here
mapped_players <- player_dictionary_mapping() dplyr::glimpse(mapped_players) #> Rows: 6,167 #> Columns: 4 #> $ PlayerFBref <chr> "Ömer Toprak", "Šime Vrsaljko", "Šimon Štefanec", "Ørjan N… #> $ UrlFBref <chr> "https://fbref.com/en/players/c5fd13e9/Omer-Toprak", "http… #> $ UrlTmarkt <chr> "https://www.transfermarkt.com/omer-toprak/profil/spieler/… #> $ TmPos <chr> "Centre-Back", "Right-Back", "Attacking Midfield", "Goalke…
The following section will outline the various functions available to find different URLs to be able to pass through the Transfermarkt suite of functions outlined in this vignette.
To get a list of URLs for each team in a particular season from transfermarkt.com, the
tm_league_team_urls() function can be used. If the country/countries aren’t available in the main data set, the function can also accept a League URL from transfermarkt.com. To get the league URL, use the filtering options towards the top of transfermarkt.com, select the country and league you want to collect data from, head to that page, and copy the URL.
This section will cover the functions to aid in the extraction of season team statistics.
To be able to extract league tables for select matchday(s), the below function can be used.
The function can accept either the country name, season start year and matchday number(s), or for leagues not contained in the worldfootballR_data repository, it can accept the league URL, season start year and matchday number(s).
# to get the EPL table after matchday 1 of the 20/21 season: epl_matchday_1_table <- tm_matchday_table(country_name="England", start_year="2020", matchday=1) # to get the EPL table after each matchdays from matchday 1 to matchday 35 of the 20/21 season: epl_matchday_1to35_table <- tm_matchday_table(country_name="England", start_year="2020", matchday=c(1:35)) # to get the EPL table after each matchdays from matchday 1 to matchday 35 of the 20/21 season: league_one_matchday_1_table <- tm_matchday_table(start_year="2020", matchday=1, league_url="https://www.transfermarkt.com/league-one/startseite/wettbewerb/GB3")
This section will cover off the functions to get team-level data from Transfermarkt.
To get all the arrivals and departures for a team (or teams) in a season and data regarding the transfer (transfer value, contract length, where they came from/went to, etc), the
tm_team_transfers() function can be used. This function can return either
all for both
# for one team: bayern <- tm_team_transfers(team_url = "https://www.transfermarkt.com/fc-bayern-munchen/startseite/verein/27/saison_id/2020", transfer_window = "all") # or for multiple teams: team_urls <- tm_league_team_urls(country_name = "England", start_year = 2020) epl_xfers_2020 <- tm_team_transfers(team_url = team_urls, transfer_window = "all")
To get basic statistics (goals, appearances, minutes played, etc) for all games played by players for a squad season, the
tm_squad_stats() function can be used:
# for one team: bayern <- tm_squad_stats(team_url = "https://www.transfermarkt.com/fc-bayern-munchen/startseite/verein/27/saison_id/2020") # or for multiple teams: team_urls <- tm_league_team_urls(country_name = "England", start_year = 2020) epl_team_players_2020 <- tm_squad_stats(team_url = team_urls)
This section will cover the functions available to aid in the extraction of player data.
To get information about a player, like their age, foot, where they were born, who they play for, their contract details, social media accounts and a whole lot more, use the
# for a single player hazard_bio <- tm_player_bio(player_url = "https://www.transfermarkt.com/eden-hazard/profil/spieler/50202") # for multiple players: # can make use of a tm helper function: burnley_player_urls <- tm_team_player_urls(team_url = "https://www.transfermarkt.com/fc-burnley/startseite/verein/1132/saison_id/2020") # then pass all those URLs to the tm_player_bio burnley_bios <- tm_player_bio(player_urls = burnley_player_urls)