R/rankT20Bowlers.R

In tvganesh/yorkr: Analyze Cricket Performances Based on Data from Cricsheet

##########################################################################################
# Designed and developed by Tinniam V Ganesh
# Date : 28 Jan 2021
# Function: rankT20Bowlers
# This function ranks the t20 bowlers
#
###########################################################################################
#' @title
#' Ranks the T20 bowlers
#'
#' @description
#' This function creates a single datframe of all T20 bowlers and then ranks them
#'
#' @usage
#' rankT20Bowlers(dir=".",minMatches, dateRange, wicketsVsER,type)
#'
#'
#' @param dir
#' The directory
#'
#' @param minMatches
#' Minimum matches played
#'
#' @param dateRange
#' Date interval to consider
#'
#' @param wicketsVsER
#' Wickets  or economy rate
#'
#' @param type
#' T20 format
#'
#' @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{
#' rankT20Bowlers(dir=".",minMatches, dateRange, wicketsVsER,type)
#' }
#'
#' @seealso
#' \code{\link{rankODIBowlers}}\cr
#' \code{\link{rankODIBatsmen}}\cr
#' \code{\link{rankT20Batsmen}}\cr
#' \code{\link{rankT20Bowlers}}\cr
#' @export
#'
rankT20Bowlers <- function(dir=".",minMatches, dateRange, wicketsVsER,type) {
    bowlingDetails=bowler=wickets=economyRate=matches=meanWickets=meanER=totalWickets=year=NULL
    wicketPlayerOut=opposition=venue=NULL
    currDir= getwd()

    #Change dir
    setwd(dir)
    bowlingDF<-NULL

    print("*******")
    print(type)
    bowlingDetails <- paste(type,"-BowlingDetails.RData",sep="")
    print(bowlingDetails)
    load(bowlingDetails)
    print(dim(bowlingDF))

    # Note: If the date Range is NULL setback to root directory
    tryCatch({

        df=bowlingDF %>% filter(date >= dateRange[1]  & date <= dateRange[2])

    },
    warning=function(war)
    {
        print(paste("NULL values: ", war))
    },
    error=function(err)
    {
        # Change to root directory on error
        setwd(currDir)
        cat("Back to root",getwd(),"\n")
    })


    # Compute number of matches played
    a=df %>% select(bowler,date) %>% unique()
    b=summarise(group_by(a,bowler),matches=n())

    # Compute wickets
    c <- filter(df,wicketPlayerOut != "nobody")
    d <- select(c,bowler,wicketPlayerOut,economyRate,date,opposition,venue)
    e <- summarise(group_by(d,bowler,date,economyRate),wickets=length(unique(wicketPlayerOut)))
    f=summarise(group_by(e,bowler), totalWickets=sum(wickets),meanER=mean(economyRate))

    # Join
    g=merge(b,f,by="bowler",all.x = TRUE)
    g[is.na(g)] <- 0
    h <- filter(g,matches >= minMatches)
    # Reset to currDir
    setwd(currDir)
    if(wicketsVsER == "Wickets over Economy rate"){
          T20BowlersRank <- arrange(h,desc(totalWickets),desc(meanER))
    } else if(wicketsVsER == "Economy rate over Wickets"){

        T20BowlersRank <- arrange(h,meanER,desc(totalWickets))
    }
    T20BowlersRank <- distinct(T20BowlersRank)
    T20BowlersRank

}