ggsoccer provides a handful of functions that make it easy to plot soccer event data in R/ggplot2.
ggsoccer is available via CRAN:
Alternatively, you can download the development version from github like so:
# install.packages("remotes") remotes::install_github("torvaney/ggsoccer")
The following example uses ggsoccer to solve a realistic problem: plotting a set of passes onto a soccer pitch.
pass_data <- data.frame(x = c(24, 18, 64, 78, 53), y = c(43, 55, 88, 18, 44), x2 = c(34, 44, 81, 85, 64), y2 = c(40, 62, 89, 44, 28)) ggplot(pass_data) + annotate_pitch() + geom_segment(aes(x = x, y = y, xend = x2, yend = y2), arrow = arrow(length = unit(0.25, "cm"), type = "closed")) + theme_pitch() + direction_label() + ggtitle("Simple passmap", "ggsoccer example")
Because ggsoccer is implemented as ggplot layers, it makes customising a plot very easy. Here is a different example, plotting shots on a green pitch.
Note that by default, ggsoccer will display the whole pitch. To display a subsection of the pitch, simply set the plot limits as you would with any other ggplot2 plot. Here, we use the
ylim arguments to
Because of the way coordinates get flipped, we must also reverse the y-axis to ensure that the orientation remains correct.
NOTE: Ordinarily, we would just do this with
scale_y_reverse. However, due to a bug in ggplot2, this results in certain elements of the pitch (centre circle and penalty box arcs) failing to render. Instead, we can flip the y coordinates manually (
100 - y in this case).
shots <- data.frame(x = c(90, 85, 82, 78, 83, 74, 94, 91), y = c(43, 40, 52, 56, 44, 71, 60, 54)) ggplot(shots) + annotate_pitch(colour = "white", fill = "springgreen4", limits = FALSE) + geom_point(aes(x = x, y = 100 - y), fill = "yellow", shape = 21, size = 4) + theme_pitch() + theme(panel.background = element_rect(fill = "springgreen4")) + coord_flip(xlim = c(49, 101), ylim = c(-12, 112)) + ggtitle("Simple shotmap", "ggsoccer example")
ggsoccer defaults to Opta’s 100x100 coordinate system. However, different data providers may use alternative coordinates.
ggsoccer provides support for a few data providers out of the box, as well as an interface for any custom coordinate system:
# ggsoccer enables you to rescale coordinates from one data provider to another, too to_statsbomb <- rescale_coordinates(from = pitch_opta, to = pitch_statsbomb) passes_rescaled <- data.frame(x = to_statsbomb$x(pass_data$x), y = to_statsbomb$y(pass_data$y), x2 = to_statsbomb$x(pass_data$x2), y2 = to_statsbomb$y(pass_data$y2)) ggplot(passes_rescaled) + annotate_pitch(dimensions = pitch_statsbomb) + geom_segment(aes(x = x, y = y, xend = x2, yend = y2), colour = "coral", arrow = arrow(length = unit(0.25, "cm"), type = "closed")) + theme_pitch() + direction_label(x_label = 60) + ggtitle("Simple passmap", "Statsbomb co-ordinates")
To plot data for a dataset not provided, ggsoccer just requires a pitch specification. This is a list containing the required pitch dimensions like so:
pitch_custom <- list( length = 150, width = 100, penalty_box_length = 25, penalty_box_width = 50, six_yard_box_length = 8, six_yard_box_width = 26, penalty_spot_distance = 16, goal_width = 12, origin_x = 0, origin_y = 0 ) ggplot() + annotate_pitch(dimensions = pitch_custom) + theme_pitch()
The standard “box” goals may not be perfectly suited to your use-case. ggsoccer allows you to customise your goals markings by supplying a function to the
goals argument of
ggplot() + annotate_pitch(fill = "steelblue4", colour = "white", goals = goals_line) + theme_pitch() + theme(panel.background = element_rect(fill = "steelblue4"))
Since this argument just requires a function (or a one-sided formula), you can modify the supplied functions, or create your own goal markings function. Additionally, the
goals argument supports using one-sided formulas as lambda functions (see
ggplot() + annotate_pitch( goals = ~ goals_strip(..., lineend = "square", size = 3.5), fill = "lightgray" ) + theme_pitch()
help(goals_box) for the full list of available functions.
The idea for having multiple goal markings was taken and adapted from the fc.rstats package.