Premier League Match Data

To cite Federica’s work, please use: Gazzelloni F., 2023 Data Visualization Premier League Match Data Correlation

library(tidyverse)
tuesdata <- tidytuesdayR::tt_load(2023, week = 14)

df <- tuesdata$`soccer21-22`
df%>%head

df%>%
  mutate(Date=as.Date(Date,"%d/%m/%Y"),
         year=zoo::as.yearmon(Date),.after=Date)%>%
  count(year)

df_corr <- df[,11:22]
df_corr%>%head()

df_named <- df[,11:22] %>%
  rename("HomeShots"=HS,
         "AwayShots"=AS,
         "HomeShots-on-Target"=HST,
         "AwayShots-on-Target"=AST,
         "HomeFouls"=HF,
         "AwayFouls"=AF,
         "HomeCorners"=HC,
         "AwayCorners"=AC,
         "HomeYellowCards"=HY,
         "AwayYellowCards"=AY,
         "HomeRedCards"=HR,
         "AwayRedCards"=AR)

df_named%>%head

# Quick display of two cabapilities of GGally, to assess the distribution and correlation of variables 
library(GGally)

 
# Nice visualization of correlations
ggcorr(df_named, #df[,11:22], 
       method = c("pairwise"),
       geom="circle",
       max_size = 15,
       min_size = 5,
       family="Roboto Condensed",
       nbreaks = 6,
       angle = 0,
       palette = "Paired",
       hjust = 1, 
       size = 4, 
       color = "grey50",
       #low = "green",
       #mid = "#EEEEEE",
       #high = "#F21A00",
       layout.exp = 1,
       name = expression(rho))+
  geom_point(size = 10, aes(color = coefficient > 0, 
                            alpha = abs(coefficient) > 0.5)) +
  scale_alpha_manual(values = c("TRUE" = 0.25, "FALSE" = 0)) +
  guides(alpha = FALSE)+
  labs(caption="Correlation for home and away side such as fouls, shots, cards\nDataSource: #TidyTuesday 2023 w14 Premier League Match Data\n#30daychartchallenge day20 Correlation | DataViz: Federica Gazzelloni") +
  annotate(geom = "text",
           family="Roboto Condensed",
           fontface="bold",
           label="Premier League\nMatch\n2021-2022",
           size=14,
           color="#a8bd3a",
           hjust=0,
           x = 0 ,y =c(10) )+
  theme(text=element_text(family="Roboto Condensed"),
        plot.caption = element_text(size=12,vjust = 1),
        plot.margin = margin(0,0,0,0, "pt"))

ggsave("corr.png",width = 9,height = 6)