#' Scraping and calculating data to use for fantasy football projections.
#'
#' The ffanalytics package provides three categories of important functions:
#' scrape, calculation and analysis.
#'
#' @section Scrape functions:
#' The scrape flow works like this:
#' \enumerate{
#' \item User initiates the script and specifies the data period that needs to
#' be scraped
#' \item The scripts displays available analysts to scrape and the user selects
#' which to use
#' \item The script then displays available positions and asks the user to
#' select positions to scrape.
#' \item Data scrape is executed and returns a list with a data table for each
#' position}
#' User can next specify which aggregate method to apply and execute the
#' calculation scripts on this list to get a data table with projected points,
#' confidence intervals, rankings, risk etc.
#'
#' Tiers are calculated using effect size thresholds based on Cohen's d.
#' D value thresholds for determining tiers for each position can be set by:
#' \code{tierDValues <- c(QB = 1, RB = 1, WR = 1, TE = 1, K = 1, DST = 1, DL = 1, DB = 1, LB = 1)}
#'
#' @docType package
#' @name ffanalytics
#' @import RCurl tcltk
NULL
#>
.onLoad <- function(libname, pkgname){
vorBaseline <<- ffa.vorBaseline
ffnAPI <<- "test"
vorType <<- ffa.vorType
scoreThreshold <<- ffa.scoreThreshold
tierGroups <<- ffa.tierGroups
tierDValues <<- c(QB = 1, RB = 1, WR = 1, TE = 1, K = 1, DST = 1, DL = 1, DB = 1, LB = 1)
projDir <<- Sys.getenv("HOME")
warning("Package is outdated. Please install new version from 'https://github.com/FantasyFootballAnalytics/ffanalytics'", call. = FALSE)
}
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