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library(engsoccerdata)
library(dplyr)
library(tidyr)
library(plotly)
# shape data into desired format
dat <- england %>%
gather(location, team, home, visitor) %>%
# focus on tier 1 teams that are still playing in 2015
filter(team %in% maketable_eng(england, 2015, 1)[["team"]]) %>%
mutate(
pts = ifelse(location == "home" & goaldif > 0, 3,
ifelse(location == "away" & goaldif < 0, 3, 1))
) %>%
arrange(Date) %>%
group_by(Season, team) %>%
mutate(gameno = row_number(), cumpts = cumsum(pts)) %>%
ungroup() %>%
group_by(gameno) %>%
mutate(meanP = mean(cumpts)) %>%
filter(Season > 2006)
sd <- highlight_key(dat, ~team, "Select a team")
# a 'wormchart' like fig 8 here http://www.gradaanwr.net/wp-content/uploads/2016/06/dataApr16.pdf
p <- ggplot(sd, aes(x = gameno, y = cumpts - meanP)) +
geom_line(aes(group = team), alpha = 0.5) +
facet_wrap(~ Season, ncol = 3) +
labs(
title = "English Premier League Performance",
x = "Game in season",
y = "Cumulative points (above/below) average"
)
gg <- ggplotly(p, tooltip = "team")
highlight(
gg,
dynamic = TRUE,
selectize = TRUE,
color = RColorBrewer::brewer.pal(12, "Paired")
)
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