The FA Women’s Super League, is the first division women’s soccer league in England. This is map contains the stadium location of all 11 teams participating in the 2018-2019 season.
I got the list of teams from the internet, and then googled the coordinates of their respective stadiums.
clubs<-c('Arsenal',
'Birmingham City',
'Brighton & Hove Albion',
"Bristol City",
'Chelsea',
'Everton',
'Liverpool',
'Manchester City',
'Reading',
'West Ham United',
'Yeovil Town'
)
place<-c('Meadow Park Borehamwood, Hertfordshire',
'Damson Park, Solihull',
'Broadfield Stadium, Crawley',
'Stoke Gifford Stadium, Filton',
'Kingsmeadow, Kingston upon Thames',
'Haig Avenue, Southport',
'Prenton Park, Birkenhead',
'Academy Stadium, Manchester',
'Adams Park, High Wycombe',
'Rush Green Stadium, London',
'The Avenue Stadium, Dorchester')
lat<-c(51.661944,52.438886, 51.099706, 51.512622, 51.405083,
53.638089, 53.373611, 53.481111, 51.630556, 51.565,
50.700667)
lon<-c(-0.272222, -1.757242, -0.194767,-2.55688 , -0.281944,
-2.978856, -3.0325, -2.192778, -0.800278, 0.161944,
-2.445556)
wsl<-as.data.frame(cbind(clubs,place,lat,lon))
wsl$lat<-as.numeric(lat)
wsl$lon<-as.numeric(lon)
str(wsl)## 'data.frame': 11 obs. of 4 variables:
## $ clubs: Factor w/ 11 levels "Arsenal","Birmingham City",..: 1 2 3 4 5 6 7 8 9 10 ...
## $ place: Factor w/ 11 levels "Academy Stadium, Manchester",..: 7 4 3 10 6 5 8 1 2 9 ...
## $ lat : num 51.7 52.4 51.1 51.5 51.4 ...
## $ lon : num -0.272 -1.757 -0.195 -2.557 -0.282 ...library("leaflet")
library("dplyr")##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionFor a more descriptive popup marker, we used the paste0 function to label each popup marker with its respective club and stadium.
wsl %>% leaflet() %>% addTiles() %>% addMarkers(popup = paste0(wsl$clubs,": ",wsl$place))## Assuming "lon" and "lat" are longitude and latitude, respectively