-
Notifications
You must be signed in to change notification settings - Fork 27
/
README.Rmd
250 lines (193 loc) · 7.47 KB
/
README.Rmd
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
---
output:
github_document:
html_preview: false
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, echo = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "man/figures/README-"
)
```
# ggsoccer <img src="man/figures/logo.png" width="160px" align="right" />
<!-- badges: start -->
[](https://cran.r-project.org/package=ggsoccer)
[](https://cran.r-project.org/package=ggsoccer)
[](https://lifecycle.r-lib.org/articles/stages.html#stable)
[](https://github.com/Torvaney/ggsoccer/actions)
<!-- badges: end -->
## Overview
ggsoccer provides a functions for plotting soccer event data in R/ggplot2.
## Installation
ggsoccer is available via CRAN:
```{r, eval = FALSE}
install.packages("ggsoccer")
```
Alternatively, you can download the development version from github like so:
```{r, eval = FALSE}
# install.packages("remotes")
remotes::install_github("torvaney/ggsoccer")
```
## Usage
```{r example_blank, message = FALSE}
library(ggplot2)
library(ggsoccer)
ggplot() +
annotate_pitch() +
theme_pitch()
```
The following example uses ggsoccer to solve a realistic problem: plotting a set
of passes onto a soccer pitch.
```{r example_passes}
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, plots can be customised with
standard ggplot functions and layers.
Here is a different example, plotting shots on a **green** pitch.
By default, ggsoccer will display the whole pitch. To display a
subsection of the pitch, set the plot limits as you would with any other
ggplot2 plot. Here, we use the `xlim` and `ylim` arguments to `coord_flip`.
`coord_flip` reverses the orientation of the points, so we must also reverse the y-axis
to ensure that the orientation remains correct (that is, shots from the left
hand side appear on the left, and right-sided shots appear on the right).
You can do this with either `scale_y_reverse` or by reversing the
order of the limits in `coord_flip`'s `ylim` argument.
If you don't correct (i.e. reverse) the y axis orientation, the penalty box arcs will appear
inside the box!
```{r example_shots}
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 = y),
colour = "yellow",
size = 4) +
theme_pitch() +
theme(panel.background = element_rect(fill = "springgreen4")) +
coord_flip(xlim = c(49, 101)) +
scale_y_reverse() +
ggtitle("Simple shotmap",
"ggsoccer example")
```
### Data providers
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:
* StatsPerform/Opta (`pitch_statsperform`, default)
* Statsbomb (`pitch_statsbomb`)
* Wyscout (`pitch_wyscout`)
* Tracab (`make_pitch_tracab()`)
ggsoccer also provides an interface for any custom coordinate system.
#### Statsbomb
```{r example_passes_sb}
# 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")
```
#### Custom data
To plot data for a dataset not provided, ggsoccer requires a pitch specification.
This is a list containing the required pitch dimensions like so:
```{r example_custom}
pitch_custom <- list(
length = 150,
width = 100,
penalty_box_length = 25,
penalty_box_width = 60,
six_yard_box_length = 8,
six_yard_box_width = 26,
penalty_spot_distance = 16,
goal_width = 12,
origin_x = -50,
origin_y = -75
)
ggplot() +
annotate_pitch(dimensions = pitch_custom) +
theme_pitch()
```
### Goals
ggsoccer allows you to customise your goals markings by supplying a function to
the `goals` argument of `annotate_pitch`:
```{r example_goals_line}
ggplot() +
annotate_pitch(fill = "steelblue4", colour = "white", goals = goals_line) +
theme_pitch() +
theme(panel.background = element_rect(fill = "steelblue4"))
```
```{r example_goals_strip}
ggplot() +
annotate_pitch(goals = goals_strip, fill = "lightgray") +
theme_pitch()
```
This argument takes a function (or one-sided formula). You can use the supplied functions,
or create your own goal markings function. The `goals` argument also supports using
one-sided formulas as lambda functions
(see [`rlang::as_function`](https://rlang.r-lib.org/reference/as_function.html)).
Custom goals functions must accept the arguments used by `annotate_pitch`: `colour`, `fill`,
`dimensions`, `linewidth`, `alpha`, and `linetype`. Additional arguments can also be added.
```{r example_goals_custom}
goals_custom <- function(colour, fill, dimensions, ...) {
goals_strip(colour, fill, dimensions, lineend = "square", linewidth = 3.5)
}
ggplot() +
annotate_pitch(
goals = goals_custom,
fill = "lightgray"
) +
theme_pitch()
```
See `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](https://github.com/FCrSTATS/fc.rstats) package.
### Further customisation
You can also alter the style of pitch markings with `linewidth`, `alpha`, and `linetype`:
```{r example_further_customisation}
ggplot() +
annotate_pitch(
colour = "white",
linewidth = 1.5,
linetype = "12",
alpha = 0.2,
goals = goals_line
) +
theme_pitch() +
theme(panel.background = element_rect(fill = "steelblue"))
```
## Other options
There are other packages that offer alternative pitch plotting options.
Depending on your use case, you may want to check these out too:
* [soccermatics](https://github.com/JoGall/soccermatics)
* [SBpitch](https://github.com/FCrSTATS/SBpitch)
* [fc.rstats](https://github.com/FCrSTATS/fc.rstats)
* [sportyR](https://github.com/sportsdataverse/sportyR)
### Python
There are a couple of pitch plotting options for matplotlib, too:
* [mplsoccer](https://github.com/andrewRowlinson/mplsoccer)
* [matplotsoccer](https://github.com/TomDecroos/matplotsoccer)