R/lineups_stats_per_possesion.R

In AdvancedBasketballStats: Advanced Basketball Statistics

#' @title Lineups stats per possesion
#' @description The function do the calculation of statistics per p possesion for the differents lineups
#' @param df1 Should be a Data Frame. This parameter has to be in the format provided by the lineups_advance_stats() function.
#' @param df2 Should be a Data Frame that represents the team's statistics. The parameter has to be in the format provided by the team_stats() function.
#' @param df3 Should be a Data Frame that represents the rival's statistics. The parameter has to be in the format provided by the team_stats() function.
#' @param p Should be a number. This parameter has to be the number of possessions to which you want to project the statistics.
#' @param m should be a number. This parameter has to be the duration of a single game.
#' @details \itemize{
#'                 \item The function only works with the basic statistics of the lineups.
#'                 \item The statistical projection is made from the estimation of the possessions that the team plays when the lineups is on the court.
#'         }
#' @author Fco Javier Cantero \email{fco.cantero@@edu.uah.es}
#' @author Juan José Cuadrado \email{jjcg@@uah.es}
#' @author Universidad de Alcalá de Henares
#' @return Data frame whit statistics per p possesion
#' @examples
#'
#' df1 <- data.frame("PG" = c("James","Rondo"),"SG" = c("Green","Caruso"),
#' "SF" = c("Caldwell","Kuzma"), "PF" = c("Davis","Davis"),
#' "C" = c("Howard ","Howard"),"MP" = c(7,1), "FG " = c(4,0),
#' "FGA " = c(7,0),"Percentage FG" = c(0.571,0),
#' "X3P  " = c(0,0),"X3PA  " = c(2,0),"Percentage 3P" = c(0,0),
#' "X2P " = c(4,0), "X2PA " = c(5,0), "Percentage 2P" = c(0.8,0),
#' "FT " = c(1,0), "FTA " = c(3,0), "Percentage FT" = c(0.333,0),
#' "ORB " = c(2,0), "DRB " = c(5,0),"TRB " = c(7,0), "AST " = c(2,0),
#' "STL " = c(1,0), "BLK " = c(0,0),"TOV " = c(7,2), "PF" = c(1,0),
#' "PLUS" = c(9,0),"MINUS" = c(17,3),"P/M" = c(-8,-3))
#'
#' df2 <- data.frame("G" = c(71), "MP" = c(17090), "FG" = c(3006),
#' "FGA" = c(6269),"Percentage FG" = c(0.48),"3P" = c(782),"3PA" = c(2242),
#' "Percentage 3P" = c(0.349),"2P" = c(2224), "2PA" = c(4027),
#' "Percentage 2P" = c(0.552),"FT" = c(1260),"FTA FG" = c(1728),
#' "Percentage FT" = c(0.729), "ORB" = c(757),  "DRB" = c(2490),
#' "TRB" = c(3247), "AST" = c(1803),  "STL" = c(612),"BLK" = c(468),
#' "TOV" = c(1077),"PF" = c(1471),  "PTS" = c(8054),  "+/-" = c(0))
#'
#' df3 <- data.frame("G" = c(71), "MP" = c(17090), "FG" = c(2773),
#' "FGA" = c(6187),"Percentage FG" = c(0.448), "3P" = c(827),
#' "3PA" = c(2373), "Percentage 3P" = c(0.349),  "2P" = c(1946),
#' "2PA" = c(3814), "Percentage 2P" = c(0.510), "FT" = c(1270),
#' "FTA FG" = c(1626),  "Percentage FT" = c(0.781), "ORB" = c(668),
#' "DRB" = c(2333),"TRB" = c(3001),  "AST" = c(1662),"STL" = c(585),
#' "BLK" = c(263),   "TOV" = c(1130),  "PF" = c(1544),
#' "PTS" = c(7643),  "+/-" = c(0))
#'
#'
#' p <- 100
#'
#' m <- 48
#'
#' lineups_stats_per_possesion(df1,df2,df3,p,m)
#'
#' @export
#'

lineups_stats_per_possesion <- function(df1,df2,df3,p,m){
  minutes <- (df2[1,2]/df2[1,1])/5
  minutes <- trunc(minutes)
  tm_poss  <- df2[1,4] - df2[1,15] / (df2[1,15] + df3[1,16]) * (df2[1,4] - df2[1,3]) * 1.07 + df2[1,21] + 0.4 * df2[1,13]
  opp_poss <- df3[1,4] - df3[1,15] / (df3[1,15] + df2[1,16]) * (df3[1,4] - df3[1,3]) * 1.07 + df3[1,21] + 0.4 * df3[1,13]
  pace     <- m * ((tm_poss + opp_poss) / (2 * (df2[1,2] / 5)))
  if(ncol(df1)==29){
    lyneup_poss <- (pace/m) * df1[6]
    for(i in 7:ncol(df1)){
      if(i==9||i==12||i==15||i==18){
        df1[i]<- round(df1[i],3)
      }
      else{
        df1[i] <- round((df1[i]/lyneup_poss) * p,2)
      }
    }
    names(df1) = c("PG","SG","SF","PF","C","MP","FG","FGA","FG%","3P","3PA","3P%","2P","2PA","2P%","FT","FTA","FT%",
                   "ORB","DRB","TRB","AST","STL","BLK","TOV","PF","+","-","+/-")
  }else if(ncol(df1)==27){
    lyneup_poss <- (pace/m) * df1[4]
    for(i in 7:ncol(df1)){
      if(i==7||i==10||i==13||i==16){
        df1[i]<- round(df1[i],3)
      }
      else{
        df1[i] <- round((df1[i]/lyneup_poss) * p,2)
      }
    }
    names(df1) = c("PG","SG","SF","MP","FG","FGA","FG%","3P","3PA","3P%","2P","2PA","2P%","FT","FTA","FT%",
                   "ORB","DRB","TRB","AST","STL","BLK","TOV","PF","+","-","+/-")
  }else if(ncol(df1)==26){
    lyneup_poss <- (pace/m) * df1[3]
    for(i in 7:ncol(df1)){
      if(i==6||i==9||i==12||i==15){
        df1[i]<- round(df1[i],3)
      }
      else{
        df1[i] <- round((df1[i]/lyneup_poss) * p,2)
      }
    }
    names(df1) = c("PF","C","MP","FG","FGA","FG%","3P","3PA","3P%","2P","2PA","2P%","FT","FTA","FT%",
                   "ORB","DRB","TRB","AST","STL","BLK","TOV","PF","+","-","+/-")
  }
  else if (ncol(df1)==25){
    lyneup_poss <- (pace/m) * df1[2]
    for(i in 7:ncol(df1)){
      if(i==5||i==8||i==11||i==14){
        df1[i]<- round(df1[i],3)
      }
      else{
        df1[i] <- round((df1[i]/lyneup_poss) * p,2)
      }
    }
  }
  df1[is.na(df1)] <- 0

  return(df1)
}