Rise and Fall of Liverpool

Load library

library(engsoccerdata)
library(dplyr)
library(lubridate)
library(ggplot2)

Extract Liverpool data from england legue data

england$Date <- ymd(england$Date)
Liverpool.home <- england %>% filter(Date > '1970-08-01', home == 'Liverpool')
Liverpool.away <- england %>% filter(Date > '1970-08-01', visitor == 'Liverpool')

Make Variable

Make Variable Points

Liverpool.home <- Liverpool.home %>% 
  mutate(points = case_when(.$result == 'H' ~ 3,
                            .$result == 'D' ~ 1,
                            TRUE ~ 0))


Liverpool.away <- Liverpool.away %>% 
  mutate(points = case_when(.$result == 'A' ~ 3,
                            .$result == 'D' ~ 1,
                            TRUE ~ 0))

Make Variable rounds

Before 95-65 season, The first division of English league has 22 teams which have match 42 for each team(except 88,89,90), but for the balancing I delete the rounds between 38 to 42.

Liverpool <- rbind(Liverpool.home, Liverpool.away) %>% arrange(Date)
season_round <- Liverpool %>% count(Season)
season_round <- season_round$n
rounds <- c()

for(i in 1:length(season_round)){
  rounds = append(rounds, 1:season_round[i])
}

Liverpool$rounds = rounds
Liverpool <- Liverpool %>% filter(rounds <= 38)

Make Variable Cumulative points

Liverpool <- Liverpool %>% group_by(Season) %>% mutate(cumpoints = cumsum(points))

Make Variable Season as factor

Liverpool$Season <- as.factor(Liverpool$Season)

Make Variable EPL

Liverpool <- Liverpool %>% mutate(EPL = if_else(Date > ymd('2001-08-01'), true = T, false = F))

Mean Timeline before EPL, and after EPL

Liverpool.meanbfE <- Liverpool %>% filter(EPL == F) %>% group_by(rounds) %>% summarise(points = mean(points)) %>% mutate(EPL = F)
Liverpool.meanafE <- Liverpool %>% filter(EPL == T) %>% group_by(rounds) %>% summarise(points = mean(points)) %>% mutate(EPL = T)
Liverpool.mean <- rbind(Liverpool.meanbfE,Liverpool.meanafE)

Liverpool.mean <- Liverpool.mean %>% group_by(EPL) %>% mutate(cumpoints = cumsum(points))
Liverpool.mean <-  ungroup(Liverpool.mean)
Liverpool.mean <- Liverpool.mean %>% mutate(Season = case_when(Liverpool.mean$EPL == T ~ "After 98",Liverpool.mean$EPL == F ~ "Before 98"))

Launch Plot

g <- ggplot(Liverpool) + geom_line (aes( rounds , cumpoints , color = EPL, fill = Season),alpha = 0.3)+ geom_line(data = Liverpool.mean, aes(rounds, cumpoints, color = EPL, fill = Season), alpha = 0.8, size = 3)+scale_x_continuous(breaks = seq(1, 38, 2))+scale_y_continuous(breaks = seq(0,90,5))+ ggthemes::theme_fivethirtyeight() + theme(legend.position = "right", legend.direction = "vertical") +labs(subtitle = "Rise and Fall of Liverpool")

g

Red : Before EPL

Blue : After EPL

Thick lines are mean points of Before EPL and After EPL