The eurolig package provides a set of tools to obtain and analyze basketball data from the Euroleague.
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API wrapper around the official website of the Euroleague.
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Functions to obtain stats, play-by-play data and shot location data in a tidy format within R.
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Tools to analyze and visualize the data.
# install.packages("devtools")
devtools::install_github("solmos/eurolig")Let's say we want to analyze play-by-play data from the Championship game of the 2017-2018 season between Real Madrid and Fenerbache Dogus Istanbul. We can obtain the data by entering the game code and the season to the function extract_pbp(). The game code for the game can be found in the game's URL.
library(eurolig)
pbp <- extract_pbp(game_code = 260, season = 2017)
head(pbp)
#> # A tibble: 6 x 18
#> game_code play_number team_code player_name play_type time_remaining
#> <fct> <int> <fct> <fct> <fct> <chr>
#> 1 260 2 <NA> <NA> BP 10:00
#> 2 260 3 MAD AYON, GUST… TPOFF 09:59
#> 3 260 4 ULK GUDURIC, M… TPOFF 09:44
#> 4 260 5 ULK DUVERIOGLU… 2FGM 09:41
#> 5 260 6 ULK GUDURIC, M… AS 09:41
#> 6 260 7 ULK VESELY, JAN CM 09:29
#> # … with 12 more variables: quarter <fct>, points_home <dbl>,
#> # points_away <dbl>, team_name <fct>, player_id <fct>,
#> # player_dorsal <dbl>, play_info <chr>, seconds <dbl>, home_team <fct>,
#> # away_team <fct>, home <lgl>, season <int>From these data we can extract information about the assists in that game from, say, Real Madrid (MAD):
assists <- get_assists(pbp, team = "MAD")
head(assists)
#> # A tibble: 6 x 12
#> game_code season passer shooter shot_type points time_remaining quarter
#> <fct> <fct> <fct> <fct> <fct> <dbl> <chr> <fct>
#> 1 260 2017 FERNA… LLULL,… 3FG 3 01:15 1
#> 2 260 2017 LLULL… RANDOL… 3FG 3 00:05 1
#> 3 260 2017 FERNA… TAYLOR… 2FG 2 09:00 2
#> 4 260 2017 LLULL… TAVARE… 2FG 2 08:32 2
#> 5 260 2017 DONCI… CARROL… 2FG 2 04:25 2
#> 6 260 2017 TAYLO… THOMPK… 2FG 2 03:35 2
#> # … with 4 more variables: seconds <int>, foul <lgl>, and1 <dbl>,
#> # ftm <dbl>Moreover, eurolig provides some functions to visualize the data. We can use plot_heatmap() to show the distribution of assists among a given team. The package includes an example play-by-play data set of Real Madrid's entire 2017-2018 Euroleague season. We use these data to show Real Madrid's assists pattern on that season:
data(mad2017)
plot_heatmap(mad2017, team = "MAD") +
ggplot2::labs(title = "Real Madrid assist heatmap",
subtitle = "Euroleague 2017/2018")