/
get_game_data.R
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/
get_game_data.R
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################################################################################
# Author: Ben Baldwin, Sebastian Carl, Jared Lee
# Purpose: Function that can pull 4th downs from a live game courtesy of ESPN
# Code Style Guide: styler::tidyverse_style()
################################################################################
#' Get 4th down plays from a game
#'
#' @description Get 4th down plays from a game.
#'
#' @param df A data frame of a game to get 4th down decisions of.
#' @details Obtains a data frame that can be used with `add_4th_probs()`. The following columns
#' must be present:
#' \itemize{
#' \item{game_id : ESPN game ID from ESPN or cfbfastR (eg '401114223')}
#' \item{home_team : Name of the home team}
#' \item{away_team : Name of the away team}
#' }
#' @return Original data frame Data frame plus the following columns added:
#' \describe{
#' \item{desc}{Play description from ESPN.}
#' \item{type_text}{Play type text from ESPN.}
#' \item{index}{Index number of play from a given game. Useful for tracking plays (e.g. for 4th down bot).}
#' \item{The rest}{All the columns needed for `add_4th_probs().`}
#' }
#' @export
#' @examples
#' \donttest{
#'
#' game <- cfbfastR::cfbd_game_info(2019, team = "Utah", week = 3)
#' plays <- cfb4th::get_4th_plays(game)
#'
#' dplyr::glimpse(plays)
#' }
get_4th_plays <- function(df) {
espn_game_id <- df$game_id
home <- df$home_team
away <- df$away_team
home_team <- df$home_team
away_team <- df$away_team
if (is.null(df$week)) {
week <- NA
} else {
week <- df$week
}
plays <- data.frame()
tryCatch(
expr = {
warn <- 0
pbp <- httr::GET(url = glue::glue("http://site.api.espn.com/apis/site/v2/sports/football/college-football/summary?event={espn_game_id}")) %>%
httr::content(as = "text", encoding = "UTF-8") %>%
jsonlite::fromJSON(flatten = TRUE)
if ("code" %in% names(pbp)) {
warning(warn <- 1)
}
# get plays out of the drives lists
# i think current drive duplicates a drive in previous drive so might be ok to cut this
if ("current" %in% names(pbp$drives) & "previous" %in% names(pbp$drives)) {
current_drive <- pbp$drives$current
current_drive <- current_drive[['plays']] %>%
dplyr::bind_rows() %>%
dplyr::as_tibble() %>%
dplyr::mutate(team.abbreviation = current_drive$team$abbreviation)
previous_drives <- pbp$drives$previous
drives <- dplyr::bind_rows(
previous_drives %>%
dplyr::select("team.abbreviation", "plays") %>%
tidyr::unnest("plays"),
current_drive
)
} else if ("current" %in% names(pbp$drives)) {
current_drive <- pbp$drives$current
drives <- current_drive[['plays']] %>%
dplyr::bind_rows() %>%
dplyr::as_tibble() %>%
dplyr::mutate(team.abbreviation = current_drive$team$abbreviation)
} else {
previous_drives <- pbp$drives$previous
drives <- previous_drives %>%
dplyr::select("team.abbreviation", "plays") %>%
tidyr::unnest("plays")
}
line <- pbp$pickcenter %>%
dplyr::mutate(provider = factor(.data$provider.name,
c(
"consensus",
"teamrankings",
"numberfire",
"Caesars",
"Caesars (Pennsylvania)",
"William Hill (New Jersey)",
"SugarHouse",
"Bovada"
))) %>%
dplyr::arrange(.data$provider) %>%
slice(1)
suppressWarnings(
plays <- drives %>%
tibble::as_tibble() %>%
dplyr::group_by(.data$id) %>%
dplyr::slice(1) %>%
dplyr::ungroup() %>%
janitor::clean_names() %>%
dplyr::rename(
"abbreviation" = "team_abbreviation",
"qtr" = "period_number",
"yardline_100" = "start_yards_to_endzone",
"yardline" = "start_possession_text",
"down" = "start_down",
"ydstogo" = "start_distance",
"desc" = "text",
"time" = "clock_display_value"
) %>%
# dplyr::left_join(team_info %>%
# select(abbreviation,pos_team = school) %>%
# mutate(abbreviation = case_when(pos_team == "Louisiana" ~ "UL",
# pos_team == "Wisconsin" ~ "WISC",
# pos_team == "Oklahoma" ~ "OU",
# pos_team == "Indiana" ~ "IU",
# pos_team == "Charlotte" ~ "CLT",
# pos_team == "UMass" ~ "MASS",
# pos_team == "Northwestern" ~ "NU",
# pos_team == "Miami" ~ "MIA",
# TRUE ~ abbreviation)),
# by = "abbreviation") %>%
dplyr::filter(.data$qtr <= 4) %>%
dplyr::mutate(
# time column is wacky so extract it from play description when possible
play_time = stringr::str_extract(.data$desc, "\\([^()]+(?=\\)\\s)"),
play_time = substr(.data$play_time, 2, nchar(.data$play_time)),
play_min = stringr::str_extract(.data$play_time, "[^()]+(?=\\:)") %>% as.integer(),
play_min = if_else(is.na(.data$play_min) & !is.na(.data$play_time), as.integer(0), .data$play_min),
play_sec = substr(.data$play_time, nchar(.data$play_time) - 1, nchar(.data$play_time)) %>% as.integer(),
mins = if_else(nchar(.data$time) == 5, substr(.data$time, 1, 2), substr(.data$time, 1, 1)) %>% as.integer(),
secs = if_else(nchar(.data$time) == 5, substr(.data$time, 4, 5), substr(.data$time, 3, 4)) %>% as.integer(),
mins = if_else(is.na(.data$play_min), .data$mins, .data$play_min),
secs = if_else(is.na(.data$play_sec), .data$secs, .data$play_sec)
) %>%
dplyr::arrange(.data$qtr, dplyr::desc(.data$mins), dplyr::desc(.data$secs), .data$id) %>%
dplyr::mutate(
home_team = home,
away_team = away,
home_team_abbrv = pbp$header$competitions$competitors[[1]]$team.abbreviation[[1]],
home_team_nick = pbp$header$competitions$competitors[[1]]$team.name[[1]],
home_team_alt = pbp$header$competitions$competitors[[1]]$team.nickname[[1]],
away_team_abbrv = pbp$header$competitions$competitors[[1]]$team.abbreviation[[2]],
away_team_nick = pbp$header$competitions$competitors[[1]]$team.name[[2]],
away_team_alt = pbp$header$competitions$competitors[[1]]$team.nickname[[2]],
pos_team = dplyr::if_else(.data$abbreviation == .data$home_team_abbrv, .data$home_team, .data$away_team),
defteam = dplyr::if_else(.data$pos_team == .data$home_team, .data$away_team, .data$home_team),
half = dplyr::if_else(.data$qtr <= 2, 1, 2),
challenge_team = stringr::str_extract(.data$desc, "[:alpha:]*\\s*[:alpha:]*\\s*[:alpha:]*[:alpha:]+(?=\\schallenged)"),
challenge_team = stringr::str_replace_all(.data$challenge_team, "[\r\n]" , ""),
challenge_team = stringr::str_trim(.data$challenge_team, side = c("both")),
desc_timeout = dplyr::if_else(stringr::str_detect(.data$desc, "Timeout "), 1, 0),
timeout_team = stringr::str_extract(.data$desc, "(?<=Timeout ).{2,20}(?=, )"),
home_timeout_used = dplyr::case_when(
.data$timeout_team == toupper(.data$home_team) ~ 1,
.data$timeout_team == toupper(.data$home_team_abbrv) ~ 1,
.data$timeout_team == toupper(.data$home_team_nick) ~ 1,
.data$timeout_team == toupper(.data$home_team_alt) ~ 1,
.data$timeout_team != .data$home_team ~ 0,
is.na(.data$timeout_team) ~ 0
),
away_timeout_used = dplyr::case_when(
.data$timeout_team == toupper(.data$away_team) ~ 1,
.data$timeout_team == toupper(.data$away_team_abbrv) ~ 1,
.data$timeout_team == toupper(.data$away_team_nick) ~ 1,
.data$timeout_team == toupper(.data$away_team_alt) ~ 1,
.data$timeout_team != .data$away_team ~ 0,
is.na(.data$timeout_team) ~ 0
),
home_timeouts_remaining = 3,
away_timeouts_remaining = 3
) %>%
dplyr::group_by(.data$half) %>%
dplyr::arrange(.data$qtr, dplyr::desc(.data$mins), dplyr::desc(.data$secs), .data$id) %>%
dplyr::mutate(
total_home_timeouts_used = dplyr::if_else(cumsum(.data$home_timeout_used) > 3, 3, cumsum(.data$home_timeout_used)),
total_away_timeouts_used = dplyr::if_else(cumsum(.data$away_timeout_used) > 3, 3, cumsum(.data$away_timeout_used))
) %>%
dplyr::ungroup() %>%
dplyr::mutate(
home_timeouts_remaining = .data$home_timeouts_remaining - .data$total_home_timeouts_used,
away_timeouts_remaining = .data$away_timeouts_remaining - .data$total_away_timeouts_used,
pos_team_timeouts_remaining = dplyr::if_else(
.data$pos_team == .data$home_team,
.data$home_timeouts_remaining,
.data$away_timeouts_remaining
),
defteam_timeouts_remaining = dplyr::if_else(
.data$defteam == .data$home_team,
.data$home_timeouts_remaining,
.data$away_timeouts_remaining
),
time = 60 * as.integer(.data$mins) + as.integer(.data$secs),
home_score = dplyr::lag(.data$home_score),
away_score = dplyr::lag(.data$away_score),
score_differential = dplyr::if_else(.data$pos_team == .data$home_team, .data$home_score - .data$away_score, .data$away_score - .data$home_score),
runoff = 0,
yr = 2021,
home_opening_kickoff = dplyr::if_else(dplyr::first(stats::na.omit(.data$pos_team)) == .data$home_team, 1, 0),
week = week,
type = dplyr::if_else(.data$week <= 17, "reg", "post")
) %>%
dplyr::filter(
.data$down == 4,
!stringr::str_detect(.data$desc,"kickoff"),
!stringr::str_detect(.data$desc,"on-side"),
!(.data$time < 30 & .data$qtr %in% c(4)),
!stringr::str_detect(.data$desc,"Timeout"),
is.na(.data$timeout_team),
.data$type_text != "Two-minute warning",
.data$type_text != "End Period"
) %>%
dplyr::group_by(.data$qtr, .data$time, .data$ydstogo) %>%
dplyr::slice(1) %>%
dplyr::ungroup() %>%
dplyr::arrange(.data$qtr, dplyr::desc(.data$time), .data$ydstogo) %>%
dplyr::mutate(
season = pbp$header$season$year,
week = pbp$header$week,
game_id = df$game_id,
yardline_side = purrr::map_chr(
stringr::str_split(.data$yardline, " "),
function(x) x[1]
),
yardline_side = dplyr::case_when(
.data$yardline_side == "WSH" ~ "WAS",
.data$yardline_side == "LAR" ~ "LA",
TRUE ~ .data$yardline_side
),
yardline_number = as.numeric(purrr::map_chr(
stringr::str_split(.data$yardline, " "),
function(x) x[2]
)),
temp_yardline = dplyr::if_else(
.data$yardline_side == .data$abbreviation | .data$yardline_100 == 50,
100 - .data$yardline_number,
.data$yardline_number
),
yardline_100 = dplyr::if_else(
!is.na(.data$temp_yardline), as.integer(.data$temp_yardline), .data$yardline_100
),
TimeSecsRem = .data$time + ifelse(.data$qtr == 1 | .data$qtr == 3, 900, 0),
half = ifelse(.data$qtr < 3, 1, 2),
pos_score = ifelse(.data$pos_team == .data$home_team, .data$home_score, .data$away_score),
def_pos_score = ifelse(.data$pos_team == .data$home_team, .data$away_score, .data$home_score),
score_differential = .data$pos_score - .data$def_pos_score,
period = .data$qtr,
total_line = line$overUnder,
spread_line = line$spread,
home_total = (.data$spread_line + .data$total_line) / 2,
away_total = (.data$total_line - .data$spread_line) / 2,
pos_team_total = dplyr::if_else(.data$pos_team == .data$home_team, .data$home_total, .data$away_total),
pos_team_spread = dplyr::if_else(.data$pos_team == .data$home_team, .data$spread_line, -1 * .data$spread_line),
play_text = .data$desc,
play_type = .data$type_text
) %>%
dplyr::select(
"game_id",
"play_id" = "id",
"yr",
"desc",
"play_text",
"type",
"qtr",
"period",
"half",
"TimeSecsRem",
"time",
"pos_team",
"def_pos_team" = "defteam",
"abbreviation",
# yardline_side,
"away_team",
"home_team",
"away" = "away_team",
"home" = "home_team",
"yards_to_goal" = "yardline_100",
"down",
"yardline",
"distance" = "ydstogo",
"pos_team_timeouts_rem_before" = "pos_team_timeouts_remaining",
"def_pos_team_timeouts_rem_before" = "defteam_timeouts_remaining",
"home_opening_kickoff",
"score_differential",
"pos_team_total",
"pos_team_spread",
"spread" = "spread_line",
"over_under" = "total_line",
"runoff",
"home_score",
"away_score",
"pos_team_score" = "pos_score",
"def_pos_team_score" = "def_pos_score",
"type_text",
"play_type",
"yr"
) %>%
dplyr::mutate(
Under_two = .data$TimeSecsRem < 120,
distance = ifelse(.data$distance == 0, 1, .data$distance),
period = .data$qtr,
adj_TimeSecsRem = ifelse(.data$period < 3, .data$TimeSecsRem + 1800, .data$TimeSecsRem),
log_ydstogo = log(.data$yards_to_goal),
Goal_To_Go = .data$distance == .data$yards_to_goal,
pos_score_diff_start = .data$pos_team_score - .data$def_pos_team_score,
pos_team_receives_2H_kickoff = dplyr::case_when(
# 1st half, home team opened game with kickoff, away team has ball
.data$period <= 2 & .data$home_opening_kickoff == 1 & .data$pos_team == .data$away ~ 1,
# 1st half, away team opened game with kickoff, home team has ball
.data$period <= 2 & .data$home_opening_kickoff == 0 & .data$pos_team == .data$home ~ 1,
TRUE ~ 0
),
) %>%
# put in end of game conditions
dplyr::mutate(
# if there's a conversion with fewer than 5 minutes left and a lead, run off 40 seconds
runoff = ifelse(between(.data$time, 167, 300) & .data$score_differential > 0 & .data$qtr == 4, 40, .data$runoff),
# if there's a conversion right before 2 minute warning, run down to 2 minute warning
runoff = ifelse(between(.data$time, 127, 166) & .data$score_differential > 0 & .data$qtr == 4, .data$time - 120 - 6, .data$runoff),
# if conversion after 2 minute warning, run down 40 seconds
runoff = ifelse(.data$time <= 120 & .data$score_differential > 0 & .data$qtr == 4, 40, .data$runoff)
)
)
if (nrow(plays) > 0) {
plays <- plays %>%
dplyr::mutate(
index = 1:dplyr::n()
)
} else {
plays$index <- NA_real_
}
},
error = function(e) {
message("The following error has occured:")
message(e)
},
warning = function(w) {
if (warn == 1) {
message(glue::glue("Warning: The requested GameID {espn_game_id} ({df$game_id}) is invalid!"))
}
},
finally = {
}
)
return(plays)
}