top tier point differences

gistfile1.txt

library(engsoccerdata)
library(tidyverse)

england %>% 
  filter(tier==1) %>%
  split(.$Season) %>%
  map(function(x) maketable_eng(x, Season = x$Season[1], tier=1, penalties=T) ) %>%
  map(~summarise(., diff = Pts[Pos==1] - Pts[Pos==2])) %>%
  bind_rows %>%
  ggplot(aes(x=diff))+geom_histogram(color='black', fill="gray62", binwidth = 1) + scale_x_continuous(breaks = seq(0,20,2)) +
  theme_bw() + ylab("Frequency") + xlab("Points difference") +
  ggtitle("Final Points Difference Between 1st and 2nd in English Top Tier 1888-2018",subtitle = "Assumes 3 points for a win")



### which highest
england %>% 
  filter(tier==1) %>%
  split(.$Season) %>%
  map(function(x) maketable_eng(x, Season = x$Season[1], tier=1, penalties=T) ) %>%
  map(~summarise(., diff = Pts[Pos==1] - Pts[Pos==2])) -> d

do.call('rbind', Map(cbind, d, Season = names(d))) %>%
  arrange(-diff)