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cricket-insights.R
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cricket-insights.R
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#
# This is a Shiny web application. You can run the application by clicking
# the 'Run App' button above.
#
# Find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com/
#
library(shiny)
library(shinythemes)
library(readr)
library(magrittr)
library(tidyverse)
library(extrafont)
library(ggplot2)
library(ggsoccer)
library(tidyr)
library(cowplot)
library(paletteer)
library(RColorBrewer)
library(reactable)
library(reactablefmtr)
library(lubridate)
# Load datasets
cric<-read.csv("ipl_big.csv")
ipl_res<-cric%>%filter(innings%in%c(1))%>%
group_by(batting_team,innings,start_date,match_id)%>%
summarise(runs=sum(runs_off_bat)+sum(extras),balls=n_distinct(ball),
wickets=n_distinct(player_dismissed)-1)%>%
arrange(start_date,match_id)%>%
full_join(cric%>%filter(innings%in%c(2))%>%
group_by(batting_team,innings,start_date,match_id)%>%
summarise(runs=sum(runs_off_bat)+sum(extras),balls=n_distinct(ball),
wickets=n_distinct(player_dismissed)-1)%>%
arrange(start_date,match_id),
by = c('match_id','start_date'))%>%
as.data.frame()%>%
arrange(match_id)%>%
mutate(Winner=ifelse(runs.x>runs.y,batting_team.x,
ifelse(runs.x<runs.y,batting_team.y,"Tie")))
knocksdf<-cric%>%filter(is.na(wides))%>%
group_by(striker,batting_team,match_id,innings,bowling_team)%>%
summarise(runs=sum(runs_off_bat),
balls=n_distinct(ball),
boundaries=sum(runs_off_bat%in%c(4,6)),
dots=sum(runs_off_bat==0))%>%
arrange(desc(runs))%>%
mutate(perc_46=boundaries/balls,
perc_dot=dots/balls,
strike_rate=round(runs*100/balls,1))%>%
#filter(runs>=40)%>%
as.data.frame()
knocks_full<-knocksdf%>%
left_join(ipl_res%>%select(match_id,start_date,Winner),by = 'match_id')%>%
mutate(res=ifelse(batting_team==Winner,"W",
ifelse(Winner=="Tie","T","L")))%>%
filter(innings%in%c(1,2),runs>=40,res%in%c("W","L"))%>%
mutate(year=lubridate::year(start_date))
knocks_full<-knocks_full%>%
mutate(desc=paste0(runs," (",balls,") - ",striker," - IPL ",year))
# Write functions
wormplot <- function(desc1,desc2) {
a = knocks_full$desc==desc1
b = knocks_full$desc==desc2
sd1 = knocks_full$start_date[a]
str1 = knocks_full$striker[a]
score1 = knocks_full$runs[a]
sd2 <- knocks_full$start_date[b]
str2 <- knocks_full$striker[b]
score2 <- knocks_full$runs[b]
batsman1 <- cric%>%
filter(start_date==sd1,
striker==str1,
is.na(wides))%>%
group_by(striker,ball,innings,match_id)%>%
summarise(runs=cumsum(runs_off_bat))%>%
ungroup()%>%
mutate(cum_runs=cumsum(runs),
inns_balls_faced=seq(from=1,to=length(striker),length.out=length(striker)))%>%
arrange(innings,ball)%>%
as.data.frame()
batsman2 <- cric%>%
filter(start_date==sd2,
striker==str2,
is.na(wides))%>%
group_by(striker,ball,innings,match_id)%>%
summarise(runs=cumsum(runs_off_bat))%>%
ungroup()%>%
mutate(cum_runs=cumsum(runs),
inns_balls_faced=seq(from=1,to=length(striker),length.out=length(striker)))%>%
arrange(innings,ball)%>%
as.data.frame()
batsmen <- rbind(batsman1,batsman2)
batsmen<-batsmen%>%
left_join(batsmen%>%
group_by(striker,match_id)%>%
summarise(runx=sum(runs))%>%
mutate(uid=paste0(striker," (",runx,")")),
by=c('striker','match_id'))
det <- paste0(str1,"'s ",score1," vs ",str2,"'s ",score2)
cricket <- ggplot(data = batsmen)+
geom_line(aes(x=inns_balls_faced,y=cum_runs,colour=uid),
size=1)+
geom_hline(yintercept = 100,
colour="white",
linetype=3)+
scale_color_manual(values = c("#A6AAB0","#FB4447"))+
labs(title = "Innings Progression",
subtitle = det)+
xlab("Innings Balls Faced")+
ylab("Innings Runs")+
theme(text = element_text(family = "Helvetica"),
plot.background = element_rect(fill = "#2A374A"),
panel.background = element_rect(fill = "#2A374A"),
panel.grid = element_blank(),
axis.text = element_text(colour = "white"),
panel.border = element_rect(colour = "white",fill = NA),
plot.title = element_text(colour = "white",size = 20,face = "bold"),
plot.subtitle = element_text(colour = "#A6AAB0",size = 10),
axis.title = element_text(colour = "white",size = 15),
legend.background = element_rect(fill = "#2A374A"),
legend.key = element_rect(fill = "#2A374A"),
legend.title = element_blank(),
legend.text = element_text(colour = "white"),
#legend.position = c(0.1,0.95),
legend.position = "top",
legend.direction = "vertical",
legend.justification = c(1,0),
legend.margin = margin(0,2,0,1),
legend.box.margin = margin(0,0,0,0),
plot.margin = margin(20,40,20,20),
aspect.ratio = 1)
return(cricket)
}
reactruns<-function(seasons,batsman){
a=cric%>%
filter(season%in%seasons,
striker==batsman)%>%
group_by(striker,bowling_style)%>%
summarise(total_balls=n())%>%
left_join(cric%>%
filter(season%in%seasons,
striker==batsman)%>%
group_by(striker,bowling_style)%>%
summarise(runs=sum(runs_off_bat)),
by = c('striker','bowling_style'))%>%
mutate(runs_per_over=round(runs*6/total_balls,1))
c<-reactable(a[,c(2,4,3,5)],
defaultSortOrder = "desc",
defaultSorted = "runs",
columns = list(
bowling_style=colDef(name = "Bowling Style"),
total_balls=colDef(name = "Balls Faced"),
runs=colDef(name = "Runs Scored",
filterable = F,maxWidth = 100),
runs_per_over=colDef(name = "Average Runs per Over")
),
filterable = F,
minRows = 6,
defaultPageSize = 6,
outlined = T,
borderless = F,
highlight = T,
theme = reactableTheme(
headerStyle = list(borderColor = "#555"
),
color = "white",
borderColor = "hsl(233, 9%, 22%)",
backgroundColor = "#2A374A",
stripedColor = "white",
highlightColor = "hsl(233, 12%, 24%)",
cellPadding = "8px 12px",
style = list(fontFamily = "Helvetica"),
searchInputStyle = list(width = "100%")
))%>%
add_title("Runs vs. Bowling Styles",
align = "center",
font_color = "#A6AAB0",
font_family = "Helvetica",
font_size = 25,
font_style = "normal",
font_weight = "bold",
text_decoration = NULL,
background_color = "#2A374A",
margin = 0
)%>%
add_subtitle(batsman,align = "center",
font_color = "#A6AAB0",
font_family = "Helvetica",
font_size = 15,
font_style = "normal",
font_weight = "normal",
text_decoration = NULL,
background_color = "#2A374A",
margin = 0
)
return(c)
}
reactwickets<-function(seasons,batsman){
a=cric%>%
filter(season%in%c(seasons),
player_dismissed==batsman)%>%
group_by(player_dismissed,bowling_style)%>%
summarise(dism=sum(player_dismissed==batsman))%>%
#filter(player_dismissed!="")%>%
arrange(desc(dism))%>%
left_join(cric%>%
filter(season%in%c(seasons),
striker==batsman)%>%
group_by(striker,bowling_style)%>%
summarise(total_balls=n()),
by = 'bowling_style')%>%
mutate(balls_per_dismissal=round(total_balls/dism,0))
c<-reactable(a[,c(2,3,5,6)],
defaultSortOrder = "desc",
defaultSorted = "dism",
columns = list(
bowling_style=colDef(name = "Bowling Style"),
dism=colDef(name = "Times Dismissed"),
total_balls=colDef(name = "Balls Faced"),
balls_per_dismissal=colDef(name = "Balls Faced per Dismissal")
),
filterable = F,
minRows = 6,
defaultPageSize = 6,
outlined = T,
borderless = F,
highlight = T,
theme = reactableTheme(
headerStyle = list(borderColor = "#555"
),
color = "white",
borderColor = "hsl(233, 9%, 22%)",
backgroundColor = "#2A374A",
stripedColor = "white",
highlightColor = "hsl(233, 12%, 24%)",
cellPadding = "8px 12px",
style = list(fontFamily = "Helvetica"),
searchInputStyle = list(width = "100%")
))%>%
add_title("Dismissals vs. Bowling Styles",
align = "center",
font_color = "#A6AAB0",
font_family = "Helvetica",
font_size = 25,
font_style = "normal",
font_weight = "bold",
text_decoration = NULL,
background_color = "#2A374A",
margin = 0
)%>%
add_subtitle(batsman,align = "center",
font_color = "#A6AAB0",
font_family = "Helvetica",
font_size = 15,
font_style = "normal",
font_weight = "normal",
text_decoration = NULL,
background_color = "#2A374A",
margin = 0
)
return(c)
}
# Define UI for application
ui <- fluidPage(
tags$head(tags$style(HTML('* {font-family: "Helvetica"};'))),
theme = shinytheme("sandstone"),
navbarPage(
title = strong("cricket INSIGHTS"),
id = "main",
collapsible = T,
position = "static-top",
tabPanel(
title = strong(tags$p("Home")),
fluidRow(
column(6,
imageOutput("landing",hr(),hr(),
width = "100%",
height = "100%",
click = "landing_cl")
),
column(6,
h1(tags$strong("cricket INSIGHTS")),
br(),
h5(("This application highlights certain nuances of cricket using data science techniques.")),
br(),
h5("Two use cases have been developed to analyse ball-by-ball data and generate insights."),
br(),
h5(tags$b(tags$ol(
tags$li("Innings Build Up"),
br(),
tags$li("Player Match Up")
))),
br(),
h5("Enter tabs on top left of page to explore the use cases."),
br(),
h4(tags$b("Acknowledgements, sources, etc.")),
br(),
h5("Data from the Indian Premier League (IPL) is used for this study."),
br(),
h5(tags$div(tags$a(href="www.cricsheet.org", "Cricsheet"),"for ball-by-ball data of all IPL matches in history.")),
br(),
h5(tags$div(tags$a(href="www.espncricinfo.com", "ESPN Cricinfo"),"for extracting metadata of players (batting styles, bowling styles, etc.).")),
br(),
h5(tags$div("Design elements of the wormplot visualisation used in this tool are inspired by the work of",tags$a(href="https://www.statsperform.com/resource/modelling-cricket-innings-composition/","Stats Perform."))),
br(),
h4(tags$b("App author")),
br(),
h5(tags$div("Abhijit Bharali - ",tags$a(href="https://www.abhijitbharali.com", "abhijitbharali.com"),tags$a(href="https://twitter.com/abhibharali", "- Twitter"))),
br(),
)
)
),
tabPanel(
title = strong(tags$p("Innings Build Up")),
sidebarLayout(
sidebarPanel(
width = 3,
selectInput(inputId = "inn1",
choices = unique(knocks_full$desc),
label = "Pick an innings:"),
br(),
selectInput(inputId = "inn2",
choices = unique(knocks_full$desc),
label = "Pick another one:"),
br(),
actionButton("compare","Compare!",
style='font-size:100%;
font-weight: bold;
font-family: Helvetica;
text-align: center;
color: white'),
br(),
br(),
h5("Compare the progression of any two 40+ knocks in IPL history."),
br(),
br(),
h5("Visualise how they stack up against each other, in terms of how the two batters paced their innings."),
br(),
br(),
h5(tags$div("Every data point for this analysis has been sourced from",tags$a(href="www.cricsheet.org", "Cricsheet."))),
),
mainPanel(
width = 9,
div(style = "margin:0 ;text-align: left; ",
plotOutput(outputId = "wormplot")),
)
)
),
tabPanel(
title = strong(tags$p("Match Ups")),
sidebarLayout(
sidebarPanel(width = 3,
selectizeInput(inputId = "batter",
choices = unique(cric$striker),
label = "Winning cause or losing cause"),
br(),
uiOutput("secondselection"),
br(),
actionButton("insight","View insights!",
style='font-size:100%;
font-weight: bold;
font-family: Helvetica;
text-align: center;
color: white'),
br(),
br(),
h5("To gain better insight into batsman vs. bowler match ups, we can identify trends from the following tables. Runs scored and dismissal frequency of a batter against particular bowling styles inform match up advantage."),
br(),
h5(tags$div("Derived metrics like scoring rate and dismissal rate are also included in the visual analysis here. Data sourced and scraped from ",tags$a(href="www.cricsheet.org", "Cricsheet"), "and",tags$a(href="www.espncricinfo.com", "ESPN Cricinfo.")))
),
mainPanel(
width = 9,
div("Runs vs. Bowling Styles", style = "text-align: center;
background-color: #2A374A; color:#A6AAB0; font-size:200%;
font-weight: bold"),
reactableOutput(outputId = "runs"),
hr(),
div("Dismissals vs. Bowling Styles", style = "text-align: center;
background-color: #2A374A; color:#A6AAB0; font-size:200%;
font-weight: bold"),
reactableOutput(outputId = "dismissals"),
)
)
)
)
)
# Define server logic required
server <- function(input, output, session) {
x<-eventReactive(input$insight,{
reactruns(input$season,input$batter)
})
y <- eventReactive(input$insight,{
reactwickets(input$season,input$batter)
})
z <- eventReactive(input$compare,{
wormplot(input$inn1,input$inn2)
}
)
output$secondselection<-renderUI({
checkboxGroupInput("season",
"Select seasons:",
unique((cric%>%filter(striker==input$batter))$season))
})
output$landing <- renderImage(
list(src = "www/cricapp.jpeg", width = "100%"),
deleteFile = F)
output$wormplot <- renderPlot({
z()
},width = 1000,height = 750,res=96)
output$runs<-renderReactable({
x()
})
output$dismissals<-renderReactable({
y()
})
}
# Run the application
shinyApp(ui = ui, server = server)