##########################################################################################
# Designed and developed by Tinniam V Ganesh
# Date : 23 Nov 2021
# Function: teamWicketsERPlotOppnAllMatches
# This function computes the wickets vs ER of team against all opposition in all matches
#
###########################################################################################
#' @title
#' Team wickets vs ER against all opposition all matches
#'
#' @description
#' This function computes wickets vs ER against all oppositions in all matches
#'
#' @usage
#' teamWicketsERPlotOppnAllMatches(matches,t1,t2,plot=1)
#'
#' @param matches
#' The matches of the team against all oppositions and all matches
#'
#' @param t1
#' The 1st team of the match
#'
#' @param t2
#' the 2nd team in the match
#'
#' @param plot
#' Plot=1 (static), Plot=2(interactive)
#'
#'
#' @references
#' \url{https://cricsheet.org/}\cr
#' \url{https://gigadom.in/}\cr
#' \url{https://github.com/tvganesh/yorkrData/}
#' @author
#' Tinniam V Ganesh
#' @note
#' Maintainer: Tinniam V Ganesh \email{tvganesh.85@gmail.com}
#'
#' @examples
#' \dontrun{
#' teamWicketsERPlotOppnAllMatches(matches,t1,t2,plot=1)
#'}
#' @seealso
#' \code{\link{teamBowlersVsBatsmenAllOppnAllMatchesMain}}\cr
#' \code{\link{teamBowlersVsBatsmenAllOppnAllMatchesPlot}}\cr
#'
#' @export
#'
teamWicketsERPlotOppnAllMatches <- function(matches,t1,t2,plot=1){
noBalls=wides=team=runs=bowler=wicketKind=wicketPlayerOut=ER=quantile=quadrant=NULL
team=bowler=ball=wides=noballs=runsConceded=overs=ggplotly=NULL
over=wickets=maidens=NULL
a <-filter(matches,team!=t1)
a1 <- unlist(strsplit(a$ball[1],"\\."))
# Create a string for substitution 1st or 2nd
a2 <- paste(a1[1],"\\.",sep="")
# only wides and noballs need to be included with runs for bowlers.
# Note: byes and legbyes should not be included
b <- a %>%
select(bowler,ball,noballs,wides,runs,wicketKind,wicketPlayerOut) %>%
#mutate(over=gsub("1st\\.","",ball)) %>%
mutate(over=gsub(a2,"",ball)) %>%
mutate(over=gsub("\\.\\d+","",over))
#Calculate the number of maiden overs
c <- summarise(group_by(b,bowler,over),sum(runs,wides,noballs))
names(c) <- c("bowler","over","runsConceded")
d <-summarize(group_by(c,bowler),maidens=sum(runsConceded==0))
#Compute total runs conceded (runs_wides+noballs)
e <- summarize(group_by(c,bowler),runs=sum(runsConceded))
# Calculate the number of overs bowled by each bwler
f <- select(c,bowler,over)
g <- summarise(group_by(f,bowler),overs=length(unique(over)))
#Compute number of wickets
h <- b %>%
select(bowler,wicketKind,wicketPlayerOut) %>%
filter(wicketPlayerOut != "nobody")
i <- summarise(group_by(h,bowler),wickets=length(wicketPlayerOut))
#Join the over & maidens
j <- full_join(g,d,by="bowler")
# Add runs
k <- full_join(j,e,by="bowler")
# Add wickets
l <- full_join(k,i,by="bowler")
# Set NAs to 0 if there are any
if(sum(is.na(l$wickets)) != 0){
l[is.na(l$wickets),]$wickets=0
}
# Arrange in descending order of wickets and runs and ascending order for maidens
l <-arrange(l,desc(wickets),desc(runs),maidens)
l$ER = l$runs/l$overs
x_lower <- quantile(l$wickets,p=0.66,na.rm = TRUE)
y_lower <- quantile(l$ER,p=0.66,na.rm = TRUE)
plot.title <- paste("Wickets-ER of ", t1, " in all matches against ", t2)
if(plot == 1){ #ggplot2
l %>%
mutate(quadrant = case_when(wickets > x_lower & ER > y_lower ~ "Q1",
wickets <= x_lower & ER > y_lower ~ "Q2",
wickets <= x_lower & ER <= y_lower ~ "Q3",
TRUE ~ "Q4")) %>%
ggplot(aes(wickets,ER,color=quadrant)) +
geom_text(aes(wickets,ER,label=bowler,color=quadrant)) + geom_point() +
xlab("Wickets") + ylab("Economy rate") +
geom_vline(xintercept = x_lower,linetype="dashed") + # plot vertical line
geom_hline(yintercept = y_lower,linetype="dashed") + # plot horizontal line
ggtitle(plot.title)
} else if(plot == 2){ #ggplotly
g <- l %>%
mutate(quadrant = case_when(wickets > x_lower & ER > y_lower ~ "Q1",
wickets <= x_lower & ER > y_lower ~ "Q2",
wickets <= x_lower & ER <= y_lower ~ "Q3",
TRUE ~ "Q4")) %>%
ggplot(aes(wickets,ER,color=quadrant)) +
geom_text(aes(wickets,ER,label=bowler,color=quadrant)) + geom_point() +
xlab("Wickets") + ylab("Economy rate") +
geom_vline(xintercept = x_lower,linetype="dashed") + # plot vertical line
geom_hline(yintercept = y_lower,linetype="dashed") + # plot horizontal line
ggtitle(plot.title)
ggplotly(g)
}
}
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