R/do_EPS.R

In BAwiR: Analysis of Basketball Data

#' Efficient Points Scored (EPS)
#' 
#' @aliases do_EPS
#'
#' @description 
#' A limitation of \code{\link{do_OE}} is that it doesn't rely on the quantity
#' of the player's offense production, that's to say, whether the player 
#' provides a lot of offense or not. In addition, it does not give credit 
#' for free-throws. An extension of \code{\link{do_OE}} has been defined: 
#' the Efficient Points Scored (EPS), which is the result of the product of 
#' OE and points scored. Points scored counts free-throws, two-point and 
#' three-point field goals. A factor \emph{F} is also added to put the adjusted 
#' total points on a points scored scale. With the factor \emph{F}, the sum of the 
#' EPS scores for all players in a given season is equal to the sum of the 
#' league total points scored in that season.
#' 
#' @usage 
#' do_EPS(df)
#' 
#' @param df Data frame with the games and the players info.
#' 
#' @return 
#' EPS values.
#' 
#' @references 
#' Shea, S., Baker, C., (2013). Basketball Analytics: 
#' Objective and Efficient Strategies for Understanding 
#' How Teams Win. Lake St. Louis, MO: Advanced Metrics, LLC.
#' 
#' @author 
#' Guillermo Vinue
#'
#' @seealso 
#' \code{\link{do_OE}}, \code{\link{do_add_adv_stats}}
#' 
#' @examples 
#' df <- do_join_games_bio("ACB", acb_games_1718, acb_players_1718)
#' df1 <- do_add_adv_stats(df)
#' do_EPS(df1)[1]
#'
#' @export

do_EPS <- function(df){
  oe_num <- do_OE(df) 
  den <- oe_num * df$PTS 
  
  F <- sum(df$PTS) / sum(den)
  eps_num <- round(F * den, 1)
  
  return(eps_num)
}