#' Get player game averages for Predicted Points Added (PPA)
#'
#' @param year (\emph{Integer} required): Year, 4 digit format (\emph{YYYY})
#' @param week (\emph{Integer} optional): Week - values range from 1-15, 1-14 for seasons pre-playoff, i.e. 2013 or earlier
#' @param team (\emph{String} optional): D-I Team
#' @param position (\emph{string} optional): Position abbreviation of the player you are searching for.\cr
#' Position Group - options include:\cr
#' * Offense: QB, RB, FB, TE, OL, G, OT, C, WR\cr
#' * Defense: DB, CB, S, LB, DE, DT, NT, DL\cr
#' * Special Teams: K, P, LS, PK\cr
#' @param athlete_id (\emph{Integer} optional): Athlete ID filter for querying a single athlete\cr
#' Can be found using the \code{\link[cfbscrapR:cfb_player_info]{cfbscrapR::cfb_player_info()}} function.
#' @param threshold (\emph{Integer} optional): Minimum threshold of plays.
#' @param excl_garbage_time (\emph{Logical} default FALSE): Select whether to exclude Garbage Time (TRUE or FALSE)
#'
#' @return A data frame with 9 variables:
#' \describe{
#' \item{\code{season}}{integer.}
#' \item{\code{week}}{integer.}
#' \item{\code{name}}{character.}
#' \item{\code{position}}{character.}
#' \item{\code{team}}{character.}
#' \item{\code{opponent}}{character.}
#' \item{\code{avg_PPA_all}}{double.}
#' \item{\code{avg_PPA_pass}}{double.}
#' \item{\code{avg_PPA_rush}}{double.}
#' }
#' @source \url{https://api.collegefootballdata.com/ppa/players/games}
#' @keywords Players Predicted Points
#' @importFrom attempt stop_if_all
#' @importFrom jsonlite fromJSON
#' @importFrom httr GET
#' @importFrom utils URLencode
#' @importFrom assertthat assert_that
#' @importFrom glue glue
#' @import dplyr
#' @import tidyr
#' @export
#' @examples
#'
#' cfb_metrics_ppa_players_games(year = 2019,week=3, team = 'TCU')
#'
cfb_metrics_ppa_players_games <- function(year = NULL,
week = NULL,
team = NULL,
position = NULL,
athlete_id = NULL,
threshold = NULL,
excl_garbage_time = FALSE){
# Position Group vector to check input arguments against
pos_groups <- c('QB', 'RB', 'FB', 'TE', 'WR', 'OL', 'OT', 'G', 'OC',
'DB', 'CB', 'S', 'LB', 'DE', 'NT','DL', 'DT',
'K', 'P','PK','LS')
if(!is.null(year)){
## check if year is numeric
assertthat::assert_that(is.numeric(year) & nchar(year)==4,
msg = 'Enter valid year as integer in 4 digit format (YYYY)')
}
if(!is.null(week)){
# Check if week is numeric, if not NULL
assertthat::assert_that(is.numeric(week) & nchar(week) <= 2,
msg = 'Enter valid week (Integer): 1-15\n(14 for seasons pre-playoff, i.e. 2014 or earlier)')
}
if(!is.null(team)){
if(team == "San Jose State"){
team = utils::URLencode(paste0("San Jos","\u00e9", " State"), reserved = TRUE)
} else{
# Encode team parameter for URL if not NULL
team = utils::URLencode(team, reserved = TRUE)
}
}
if(!is.null(position)){
## check if position in position group set
assertthat::assert_that(position %in% pos_groups,
msg = 'Enter valid position group\nOffense: QB, RB, FB, TE, WR, OL, G, OT, C\nDefense: DB, CB, S, LB, DL, DE, DT, NT\nSpecial Teams: K, P, LS, PK')
}
if(!is.null(athlete_id)){
# Check if athlete_id is numeric, if not NULL
assertthat::assert_that(is.numeric(athlete_id),
msg = 'Enter valid athlete_id value (Integer)\nCan be found using the `cfb_player_info()` function')
}
if(!is.null(threshold)){
# Check if threshold is numeric, if not NULL
assertthat::assert_that(is.numeric(threshold),
msg = 'Enter valid threshold value (Integer)')
}
if(excl_garbage_time!=FALSE){
# Check if excl_garbage_time is TRUE, if not FALSE
assertthat::assert_that(excl_garbage_time==TRUE,
msg = 'Enter valid excl_garbage_time value (Logical) - TRUE or FALSE')
}
base_url <- "https://api.collegefootballdata.com/ppa/players/games?"
full_url <- paste0(base_url,
"year=", year,
"&week=", week,
"&team=", team,
"&position=", position,
"&playerId=", athlete_id,
"&threshold=", threshold,
"&excludeGarbageTime=", excl_garbage_time)
# Check for internet
check_internet()
# Create the GET request and set response as res
res <- httr::GET(full_url)
# Check the result
check_status(res)
df <- data.frame()
tryCatch(
expr = {
# Get the content, flatten and return result as data.frame
df = jsonlite::fromJSON(full_url, flatten = TRUE)
colnames(df) = gsub("averagePPA.", "avg_PPA_", colnames(df))
message(glue::glue("{Sys.time()}: Scraping CFBData metrics PPA game-level players data..."))
},
error = function(e) {
message(glue::glue("{Sys.time()}: Invalid arguments or no CFBData metrics PPA game-level players data available!"))
},
warning = function(w) {
},
finally = {
}
)
return(df)
}
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