R/kp_team_tables.R
In saiemgilani/kenpomR: Access Men's Basketball Play by Play Data
Defines functions
kp_team_lineups
kp_team_depth_chart
kp_team_player_stats
kp_minutes_matrix
kp_player_career
kp_team_players
kp_opptracker
kp_gameplan
kp_team_schedule
Documented in
kp_gameplan
kp_minutes_matrix
kp_opptracker
kp_player_career
kp_team_depth_chart
kp_team_lineups
kp_team_players
kp_team_player_stats
kp_team_schedule
#' **Get team schedule results**
#'
#'
#' @param team Team filter to select.
#' @param year Year of data to pull
#'
#' @return Returns a tibble of team schedules
#'
#' |col_name |types |
#' |:-----------------|:---------|
#' |team_rk |numeric |
#' |team |character |
#' |opponent_rk |numeric |
#' |opponent |character |
#' |result |character |
#' |poss |numeric |
#' |ot |numeric |
#' |pre_wp |numeric |
#' |location |character |
#' |w |numeric |
#' |l |numeric |
#' |w_conference |numeric |
#' |l_conference |numeric |
#' |conference_game |logical |
#' |postseason |character |
#' |year |numeric |
#' |day_date |character |
#' |game_date |numeric |
#' |w_proj |numeric |
#' |l_proj |numeric |
#' |w_conference_proj |numeric |
#' |l_conference_proj |numeric |
#' |date |character |
#' |game_id |numeric |
#' |tiers_of_joy |character |
#'
#' @importFrom cli cli_abort
#' @importFrom dplyr filter mutate select
#' @importFrom stringr str_trim str_extract str_remove str_replace str_detect str_pad
#' @import rvest
#' @export
#' @keywords Team Schedule
#' @family KenPom Team Functions
#'
#' @examples
#' \donttest{
#' try(kp_team_schedule(team = 'Florida St.', year = 2022))
#' }
kp_team_schedule <- function(team, year = 2022){
tryCatch(
expr = {
if (!has_kp_user_and_pw()) stop("This function requires a KenPom subscription e-mail and password combination,\n set as the system environment variables KP_USER and KP_PW.", "\n See ?kp_user_pw for details.", call. = FALSE)
browser <- login()
if (!(is.numeric(year) && nchar(year) == 4 && year >= 2001)) {
# Check if year is numeric, if not NULL
cli::cli_abort("Enter valid year as a number (YYYY), data only goes back to 2001")
}
if (!(team %in% hoopR::teams_links$Team)) {
cli::cli_abort("Incorrect team name as compared to the website, see hoopR::teams_links for team name parameter specifications.")
}
teams_links <- hoopR::teams_links[hoopR::teams_links$Year == year,]
team_name = teams_links$team.link.ref[teams_links$Team == team]
### Pull Data
url <- paste0("https://kenpom.com/team.php?",
"team=",team_name,
"&y=", year)
page <- rvest::session_jump_to(browser, url)
Sys.sleep(5)
if (year >= 2011) {
sched_header_cols <- c("Day.Date","Team.Rk","Opponent.Rk","Opponent","Result",
"Poss","OT","Location","Record","Conference", "Postseason")
} else {
sched_header_cols <- c("Day.Date", "Opponent.Rk", "Opponent", "Result",
"Poss", "OT", "Location", "Record", "Conference", "Postseason")
}
sched <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table') %>%
rvest::html_table()) %>%
as.data.frame()
## Removing the tiers of joy column, will add back to data frame subsequently
# sched <- sched[,1:(length(sched)-1)]
#
# Note: As a result of the tiers of joy column being an image (.gif) instead of text,
# there is an extra unnamed column with no text. Antecedently, I was removing this column
# and the resulting code below is in efforts to extract the GameId from the box/pregame link
# and the fanmatch link date. Additionally, we add back a text-equivalent for tiers of joy.
# I realized that since this extra column exists and the label column for
# postseason events repeats across the entire data frame row, I could use that last repeat
# as a label for regular vs conference tourney/postseason tourney games.
# One small piece of good fortune in this otherwise mundane task.
colnames(sched) <- sched_header_cols
sched <- sched %>%
dplyr::mutate(Postseason = ifelse(.data$Postseason == "", NA_character_, .data$Postseason)) %>%
tidyr::fill("Postseason", .direction = c("down"))
suppressWarnings(
sched <- sched %>%
dplyr::mutate(
WL = stringr::str_replace(stringr::str_extract(.data$Result,'W|L'),",",""),
Score = stringr::str_replace(stringr::str_extract(.data$Result,'\\d{1,3}-\\d{1,3}'),",","")) %>%
tidyr::separate("Score", into = c("WinnerScore", "LoserScore"), sep = "-") %>%
dplyr::mutate(
TeamScore = dplyr::case_when(
.data$WL == "W" & .data$Record != "" ~ as.numeric(.data$WinnerScore),
.data$WL == "L" & .data$Record != "" ~ as.numeric(.data$LoserScore),
.data$WL == "" ~ NA_real_),
OpponentScore = dplyr::case_when(
.data$WL == "L" & .data$Record != "" ~ as.numeric(.data$WinnerScore),
.data$WL == "W" & .data$Record != "" ~ as.numeric(.data$LoserScore),
.data$WL == "" ~ NA_real_)) %>%
tidyr::separate("Record", into = c("W", "L"), sep = "-") %>%
dplyr::filter(.data$Location %in% c("Home", "Away", "Neutral",
"Semi-Home","Semi-Away")) %>%
dplyr::select(
-"WinnerScore",
-"LoserScore") %>%
dplyr::mutate_at(c("Opponent.Rk", "Poss","TeamScore","OpponentScore"), as.numeric)
)
suppressWarnings(
if (year >= 2011){
sched <- sched %>%
dplyr::mutate_at(c("Team.Rk"), as.numeric)
}
)
sched <- sched %>%
dplyr::mutate(
Team = team,
Year = year,
PreWP = ifelse(stringr::str_detect(.data$OT, '%'),
as.numeric(stringr::str_extract(.data$OT, '\\d+'))/100, NA_real_),
OT = dplyr::case_when(
.data$OT == " " ~ 0,
.data$OT == "OT" ~ 1,
stringr::str_detect(.data$OT, "OT") ~ as.numeric(stringr::str_extract(.data$OT,'\\d')),
TRUE ~ NA_real_),
ConferenceGame = ifelse(.data$Conference != "", TRUE, FALSE))
suppressWarnings(
sched <- sched %>%
tidyr::separate("Conference",
into = c("W.Conference","L.Conference"), sep = "-") %>%
dplyr::mutate(
W.Conference = ifelse((.data$W.Conference == "\u00d7") | (.data$W.Conference == ""), NA_real_, .data$W.Conference)
)
)
if (year >= 2011) {
sched <- sched %>%
dplyr::select(
"Team.Rk",
"Team",
"Opponent.Rk",
"Opponent",
"Result",
"Poss",
"OT",
"PreWP",
"Location",
"W",
"L",
"W.Conference",
"L.Conference",
"ConferenceGame",
"Postseason",
"Year",
"Day.Date")
} else {
sched <- sched %>%
dplyr::select(
"Team",
"Opponent.Rk",
"Opponent",
"Result",
"Poss",
"OT",
"PreWP",
"Location",
"W",
"L",
"W.Conference",
"L.Conference",
"ConferenceGame",
"Postseason",
"Year",
"Day.Date")
}
suppressWarnings(
sched <- sched %>%
dplyr::filter(!is.na(.data$Day.Date)) %>%
dplyr::mutate_at(c("Opponent.Rk","Poss","W", "L",
"W.Conference","L.Conference"), as.numeric)
)
sched <- sched %>%
dplyr::mutate(
Date.DD = stringr::str_pad(stringr::str_extract(.data$Day.Date, '\\d+'), 2, pad = "0"),
Date.MO = NA_character_,
Date.MO = dplyr::case_when(
stringr::str_detect(.data$Day.Date, regex("Oct",ignore_case = TRUE)) ~ "10",
stringr::str_detect(.data$Day.Date, regex("Nov",ignore_case = TRUE)) ~ "11",
stringr::str_detect(.data$Day.Date, regex("Dec",ignore_case = TRUE)) ~ "12",
stringr::str_detect(.data$Day.Date, regex("Jan",ignore_case = TRUE)) ~ stringr::str_pad(1, 2, pad = "0"),
stringr::str_detect(.data$Day.Date, regex("Feb",ignore_case = TRUE)) ~ stringr::str_pad(2, 2, pad = "0"),
stringr::str_detect(.data$Day.Date, regex("Mar",ignore_case = TRUE)) ~ stringr::str_pad(3, 2, pad = "0"),
stringr::str_detect(.data$Day.Date, regex("Apr",ignore_case = TRUE)) ~ stringr::str_pad(4, 2, pad = "0")),
Date.YR = dplyr::case_when(
stringr::str_detect(.data$Day.Date, regex("Oct",ignore_case = TRUE)) ~ glue::glue("{year-1}"),
stringr::str_detect(.data$Day.Date, regex("Nov",ignore_case = TRUE)) ~ glue::glue("{year-1}"),
stringr::str_detect(.data$Day.Date, regex("Dec",ignore_case = TRUE)) ~ glue::glue("{year-1}"),
stringr::str_detect(.data$Day.Date, regex("Jan",ignore_case = TRUE)) ~ glue::glue("{year}"),
stringr::str_detect(.data$Day.Date, regex("Feb",ignore_case = TRUE)) ~ glue::glue("{year}"),
stringr::str_detect(.data$Day.Date, regex("Mar",ignore_case = TRUE)) ~ glue::glue("{year}"),
stringr::str_detect(.data$Day.Date, regex("Apr",ignore_case = TRUE)) ~ glue::glue("{year}")),
GameDate = as.numeric(paste0(.data$Date.YR, .data$Date.MO, .data$Date.DD)),
W.Proj = round(cummax(ifelse(is.na(.data$W), 0, .data$W)) +
cumsum(ifelse(is.na(.data$PreWP), 0, .data$PreWP))),
L.Proj = round(cummax(ifelse(is.na(.data$L), 0, .data$L)) +
cumsum(ifelse(is.na(.data$PreWP), 0, 1 - .data$PreWP))),
W.ConferenceProj = round(cummax(ifelse(is.na(.data$W.Conference), 0, .data$W.Conference)) +
cumsum(ifelse(.data$ConferenceGame == TRUE & !is.na(.data$PreWP), .data$PreWP, 0))),
L.ConferenceProj = round(cummax(ifelse(is.na(.data$L.Conference), 0, .data$L.Conference)) +
cumsum(ifelse(.data$ConferenceGame == TRUE & !is.na(.data$PreWP), 1 - .data$PreWP, 0)))) %>%
dplyr::select(
-"Date.DD",
-"Date.MO",
-"Date.YR")
extractor <- function(x){
data.frame(
ifelse(
is.null(rvest::html_element(x, xpath = "a")),
NA_real_,
rvest::html_element(x, xpath = "a") %>%
rvest::html_attr("href")), stringsAsFactors = FALSE)
}
img_extractor <- function(x){
data.frame(
ifelse(
is.null(rvest::html_element(x, css = "a > img")),
NA_character_,
toupper(stringr::str_trim(
stringr::str_replace(
stringr::str_extract(rvest::html_element(x, css = "a > img") %>%
xml2::xml_attr("src"), "a.gif|b.gif"),
".gif","")))),
stringsAsFactors = FALSE)
}
if (year >= 2011) {
w_links <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table') %>%
rvest::html_elements("tr.w > td:not(.label):nth-child(1)")
l_links <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table') %>%
rvest::html_elements("tr.l > td:not(.label):nth-child(1)")
un_links <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table') %>%
rvest::html_elements("tr.un > td:not(.label):nth-child(1)")
fm_links <- c(w_links,l_links,un_links)
w_box <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = "#schedule-table") %>%
rvest::html_elements("tr.w > td:not(.label):nth-child(5)")
l_box <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = "#schedule-table") %>%
rvest::html_elements("tr.l > td:not(.label):nth-child(5)")
un_box <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = "#schedule-table") %>%
rvest::html_elements("tr.un > td:not(.label):nth-child(5)")
box_links <- c(w_box, l_box, un_box)
w_tier <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table') %>%
rvest::html_elements("tr.w > td:not(.label):nth-child(11)")
l_tier <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table') %>%
rvest::html_elements("tr.l > td:not(.label):nth-child(11)")
un_tier <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table') %>%
rvest::html_elements("tr.un > td:not(.label):nth-child(11)")
tiers <- c(w_tier, l_tier, un_tier)
} else {
w_links <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table') %>%
rvest::html_elements("tr.w > td:not(.label):nth-child(1)")
l_links <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table') %>%
rvest::html_elements("tr.l > td:not(.label):nth-child(1)")
un_links <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table') %>%
rvest::html_elements("tr.un > td:not(.label):nth-child(1)")
fm_links <- c(w_links,l_links, un_links)
w_box <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = "#schedule-table") %>%
rvest::html_elements("tr.w > td:not(.label):nth-child(4)")
l_box <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = "#schedule-table") %>%
rvest::html_elements("tr.l > td:not(.label):nth-child(4)")
un_box <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = "#schedule-table") %>%
rvest::html_elements("tr.un > td:not(.label):nth-child(4)")
box_links <- c(w_box, l_box, un_box)
w_tier <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table') %>%
rvest::html_elements("tr.w > td:not(.label):nth-child(10)")
l_tier <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table') %>%
rvest::html_elements("tr.l > td:not(.label):nth-child(10)")
un_tier <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table') %>%
rvest::html_elements("tr.un > td:not(.label):nth-child(10)")
tiers <- c(w_tier, l_tier, un_tier)
}
day = dplyr::bind_rows(lapply(fm_links,
function(x){
data.frame(rvest::html_text(x),
stringsAsFactors = FALSE)}))
colnames(day) <- "Day.Date"
fm_links <- dplyr::bind_rows(lapply(fm_links, extractor))
names(fm_links)[1] <- "fanmatch.link"
tiers <- dplyr::bind_rows(lapply(tiers, img_extractor))
names(tiers)[1] <- "TiersOfJoy"
box_links <- dplyr::bind_rows(lapply(box_links, extractor))
names(box_links)[1] <- "pregame.box"
sched_links <- dplyr::bind_cols(tiers, fm_links,box_links, day)
sched_links <- sched_links %>%
dplyr::mutate(
Date = stringr::str_remove(stringr::str_extract(.data$fanmatch.link, "=(.+)"), "="),
GameId = as.numeric(stringr::str_remove(stringr::str_remove(
stringi::stri_extract_first_regex(.data$pregame.box, "=(.+)"), "="), "&(.+)"))) %>%
dplyr::select(
"Date",
"GameId",
"TiersOfJoy",
"Day.Date")
### Add Date and GameId back back to data frame
sched <- dplyr::left_join(sched, sched_links, by = "Day.Date")
### Store Data
kenpom <- sched %>%
dplyr::arrange(.data$GameDate) %>%
dplyr::mutate(Postseason = ifelse(is.na(.data$Postseason), "Regular", .data$Postseason)) %>%
janitor::clean_names()
},
error = function(e){
message(glue::glue("{Sys.Date()} - No team schedule tables available for {team} - {year}"))
},
warning = function(w){
},
finally = {
}
)
return(kenpom)
}
#' **Get KenPom's team game plan page**
#'
#'
#' @param team Team filter to select.
#' @param year Year of data to pull
#' @return Returns a named list of tibbles: gameplan, correlations, position_distributions
#'
#' **gameplan**
#'
#'
#' |col_name |types |
#' |:--------------|:---------|
#' |date |Date |
#' |opponent_rk |numeric |
#' |opponent |character |
#' |result |character |
#' |location |character |
#' |pace |numeric |
#' |off_eff |numeric |
#' |off_eff_rk |numeric |
#' |off_e_fg_pct |numeric |
#' |off_to_pct |numeric |
#' |off_or_pct |numeric |
#' |off_ftr |numeric |
#' |off_fgm_2 |numeric |
#' |off_fga_2 |numeric |
#' |off_fg_2_pct |numeric |
#' |off_fgm_3 |numeric |
#' |off_fga_3 |numeric |
#' |off_fg_3_pct |numeric |
#' |off_fg_3a_pct |numeric |
#' |def_eff |numeric |
#' |def_eff_rk |numeric |
#' |def_e_fg_pct |numeric |
#' |def_to_pct |numeric |
#' |def_or_pct |numeric |
#' |def_ftr |numeric |
#' |def_fgm_2 |numeric |
#' |def_fga_2 |numeric |
#' |def_fg_2_pct |numeric |
#' |def_fgm_3 |numeric |
#' |def_fga_3 |numeric |
#' |def_fg_3_pct |numeric |
#' |def_fg_3a_pct |numeric |
#' |wl |character |
#' |team_score |numeric |
#' |opponent_score |numeric |
#' |day_date |character |
#' |game_date |numeric |
#'
#' **correlations**
#'
#'
#' |col_name |types |
#' |:--------------------|:---------|
#' |correlations_r_x_100 |character |
#' |pace |character |
#' |off_e_fg_pct |character |
#' |off_to_pct |character |
#' |off_or_pct |character |
#' |off_ftr |character |
#' |def_e_fg_pct |character |
#' |def_to_pct |character |
#' |def_or_pct |character |
#' |def_ftr |character |
#'
#' **position_distributions**
#'
#'
#' |col_name |types |
#' |:-------------|:---------|
#' |team |character |
#' |category |character |
#' |c_pct |numeric |
#' |pf_pct |numeric |
#' |sf_pct |numeric |
#' |sg_pct |numeric |
#' |pg_pct |numeric |
#' |c_pct_rk |numeric |
#' |pf_pct_rk |numeric |
#' |sf_pct_rk |numeric |
#' |sg_pct_rk |numeric |
#' |pg_pct_rk |numeric |
#' |c_pct_d1_avg |numeric |
#' |pf_pct_d1_avg |numeric |
#' |sf_pct_d1_avg |numeric |
#' |sg_pct_d1_avg |numeric |
#' |pg_pct_d1_avg |numeric |
#'
#' @importFrom cli cli_abort
#' @importFrom dplyr filter select rename mutate case_when mutate_at bind_rows
#' @importFrom tidyr separate everything
#' @importFrom stringr str_trim str_extract str_remove str_replace str_detect
#' @import rvest
#' @export
#' @keywords Game Plan
#' @family KenPom Team Functions
#' @examples
#' \donttest{
#' try(kp_gameplan(team='Florida St.', year=2021))
#' }
kp_gameplan <- function(team, year=2021){
tryCatch(
expr = {
if (!has_kp_user_and_pw()) stop("This function requires a KenPom subscription e-mail and password combination,\n set as the system environment variables KP_USER and KP_PW.", "\n See ?kp_user_pw for details.", call. = FALSE)
browser <- login()
if (!(is.numeric(year) && nchar(year) == 4 && year >= 2001)) {
# Check if year is numeric, if not NULL
cli::cli_abort("Enter valid year as a number (YYYY), data only goes back to 2001")
}
if (!(team %in% hoopR::teams_links$Team)) {
cli::cli_abort("Incorrect team name as compared to the website, see hoopR::teams_links for team name parameter specifications.")
}
teams_links <- hoopR::teams_links[hoopR::teams_links$Year == year,]
team_name = teams_links$team.link.ref[teams_links$Team == team]
### Pull Data
url <- paste0("https://kenpom.com/gameplan.php?",
"team=", team_name,
"&y=", year)
page <- rvest::session_jump_to(browser, url)
Sys.sleep(5)
header_cols <- c("Date","Opponent.Rk", "Opponent","Result","Location","Pace",
"Off.Eff", "Off.Eff.Rk", "Off.eFG.Pct", "Off.TO.Pct", "Off.OR.Pct", "Off.FTR",
"Off.FGM_2-A", "Off.FG_2.Pct", "Off.FGM_3-A", "Off.FG_3.Pct", "Off.FG_3A.Pct",
"Def.Eff", "Def.Eff.Rk", "Def.eFG.Pct", "Def.TO.Pct", "Def.OR.Pct", "Def.FTR",
"Def.FGM_2-A", "Def.FG_2.Pct", "Def.FGM_3-A", "Def.FG_3.Pct", "Def.FG_3A.Pct")
gp <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table'))[[1]] %>%
rvest::html_table() %>%
as.data.frame()
colnames(gp) <- header_cols
gp <- gp %>%
dplyr::filter(.data$Location != "")
suppressWarnings(
gp <- gp %>%
dplyr::mutate(
WL = stringr::str_replace(stringr::str_extract(.data$Result,'W|L'),",",""),
Score = stringr::str_replace(stringr::str_extract(.data$Result,'\\d{1,3}-\\d{1,3}'),",","")) %>%
tidyr::separate("Score", into = c("WinnerScore", "LoserScore"), sep = "-") %>%
dplyr::mutate(
TeamScore = dplyr::case_when(
.data$WL == "W" ~ as.numeric(.data$WinnerScore),
.data$WL == "L" ~ as.numeric(.data$LoserScore),
.data$WL == "" ~ NA_real_),
OpponentScore = dplyr::case_when(
.data$WL == "L" ~ as.numeric(.data$WinnerScore),
.data$WL == "W" ~ as.numeric(.data$LoserScore),
.data$WL == "" ~ NA_real_),
Date.DD = stringr::str_pad(stringr::str_extract(.data$Date,'\\d+'), 2, pad = "0"),
Date.MO = NA_character_,
Date.MO = dplyr::case_when(
stringr::str_detect(.data$Date, regex("Oct", ignore_case = TRUE)) ~ "10",
stringr::str_detect(.data$Date, regex("Nov", ignore_case = TRUE)) ~ "11",
stringr::str_detect(.data$Date, regex("Dec", ignore_case = TRUE)) ~ "12",
stringr::str_detect(.data$Date, regex("Jan", ignore_case = TRUE)) ~ stringr::str_pad(1, 2, pad="0"),
stringr::str_detect(.data$Date, regex("Feb", ignore_case = TRUE)) ~ stringr::str_pad(2, 2, pad="0"),
stringr::str_detect(.data$Date, regex("Mar", ignore_case = TRUE)) ~ stringr::str_pad(3, 2, pad="0"),
stringr::str_detect(.data$Date, regex("Apr", ignore_case = TRUE)) ~ stringr::str_pad(4, 2, pad="0")
),
Date.YR = dplyr::case_when(
stringr::str_detect(.data$Date, regex("Oct", ignore_case = TRUE)) ~ glue::glue("{year-1}"),
stringr::str_detect(.data$Date, regex("Nov", ignore_case = TRUE)) ~ glue::glue("{year-1}"),
stringr::str_detect(.data$Date, regex("Dec", ignore_case = TRUE)) ~ glue::glue("{year-1}"),
stringr::str_detect(.data$Date, regex("Jan", ignore_case = TRUE)) ~ glue::glue("{year}"),
stringr::str_detect(.data$Date, regex("Feb", ignore_case = TRUE)) ~ glue::glue("{year}"),
stringr::str_detect(.data$Date, regex("Mar", ignore_case = TRUE)) ~ glue::glue("{year}"),
stringr::str_detect(.data$Date, regex("Apr", ignore_case = TRUE)) ~ glue::glue("{year}")
),
Day.Date = .data$Date,
Date = as.Date(glue::glue("{.data$Date.YR}-{.data$Date.MO}-{.data$Date.DD}")),
GameDate = as.numeric(paste0(.data$Date.YR, .data$Date.MO, .data$Date.DD))) %>%
dplyr::select(
-"Date.DD",
-"Date.MO",
-"Date.YR")
)
cor <- gp[(nrow(gp) - 2):nrow(gp),]
cor <- cor %>%
dplyr::select(
"Location",
"Pace",
"Off.eFG.Pct",
"Off.TO.Pct",
"Off.OR.Pct",
"Off.FTR",
"Def.eFG.Pct",
"Def.TO.Pct",
"Def.OR.Pct",
"Def.FTR") %>%
dplyr::rename("Correlations (R x 100)" = "Location")
cor <- cor[2:3,] %>%
janitor::clean_names()
suppressWarnings(
gp <- gp %>%
dplyr::filter(!is.na(as.numeric(.data$Off.Eff))) %>%
tidyr::separate("Off.FGM_2-A", into = c("Off.FGM_2","Off.FGA_2")) %>%
tidyr::separate("Off.FGM_3-A", into = c("Off.FGM_3","Off.FGA_3")) %>%
tidyr::separate("Def.FGM_2-A", into = c("Def.FGM_2","Def.FGA_2")) %>%
tidyr::separate("Def.FGM_3-A", into = c("Def.FGM_3","Def.FGA_3")) %>%
dplyr::mutate_at(c("Opponent.Rk", "Pace", "Off.Eff", "Off.Eff.Rk",
"Off.eFG.Pct", "Off.TO.Pct", "Off.OR.Pct", "Off.FTR",
"Off.FGM_2", "Off.FGA_2", "Off.FG_2.Pct",
"Off.FGM_3", "Off.FGA_3","Off.FG_3.Pct", "Off.FG_3A.Pct",
"Def.Eff", "Def.Eff.Rk", "Def.eFG.Pct", "Def.TO.Pct",
"Def.OR.Pct", "Def.FTR", "Def.FGM_2", "Def.FGA_2",
"Def.FG_2.Pct", "Def.FGM_3", "Def.FGA_3",
"Def.FG_3.Pct", "Def.FG_3A.Pct", "TeamScore","OpponentScore"), as.numeric)
)
### Store Data
gp <- gp %>%
dplyr::select(
-"WinnerScore",
-"LoserScore") %>%
janitor::clean_names()
z <- data.frame()
y <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '.dist-table')
if (length(y) > 0) {
for (i in 1:length(y)) {
header_cols <- c("Team","C.Pct","PF.Pct","SF.Pct","SG.Pct","PG.Pct")
d <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = '.dist-table'))[[i]] %>%
rvest::html_table() %>%
as.data.frame()
category <- colnames(d)[1]
colnames(d) <- header_cols
d$Category <- category
d$C.Pct.Rk <- NA_real_
d$PF.Pct.Rk <- NA_real_
d$SF.Pct.Rk <- NA_real_
d$SG.Pct.Rk <- NA_real_
d$PG.Pct.Rk <- NA_real_
suppressWarnings(
d <- d %>%
dplyr::mutate(
C.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$C.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
PF.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$PF.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
SF.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$SF.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
SG.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$SG.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
PG.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$PG.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
C.Pct = as.numeric(substr(sprintf("%.*f", 4, as.numeric(.data$C.Pct)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$C.Pct))) - 3)),
PF.Pct = as.numeric(substr(sprintf("%.*f", 4, as.numeric(.data$PF.Pct)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$PF.Pct))) - 3)),
SF.Pct = as.numeric(substr(sprintf("%.*f", 4, as.numeric(.data$SF.Pct)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$SF.Pct))) - 3)),
SG.Pct = as.numeric(substr(sprintf("%.*f", 4, as.numeric(.data$SG.Pct)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$SG.Pct))) - 3)),
PG.Pct = as.numeric(substr(sprintf("%.*f", 4, as.numeric(.data$PG.Pct)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$PG.Pct))) - 3)))
)
d$C.Pct.D1.Avg = as.numeric(d[3, "C.Pct"])
d$PF.Pct.D1.Avg = as.numeric(d[3, "PF.Pct"])
d$SF.Pct.D1.Avg = as.numeric(d[3, "SF.Pct"])
d$SG.Pct.D1.Avg = as.numeric(d[3, "SG.Pct"])
d$PG.Pct.D1.Avg = as.numeric(d[3, "PG.Pct"])
d <- d %>%
dplyr::filter(!is.na(.data$C.Pct.Rk)) %>%
dplyr::select(
"Team",
"Category",
tidyr::everything())
z <- dplyr::bind_rows(z, d)
}
}
z <- z %>%
janitor::clean_names()
kenpom <- c(list(gp),list(cor),list(z))
names(kenpom) <- c("gameplan", "correlations", "position_distributions")
},
error = function(e){
message(glue::glue("{Sys.Date()} - No Game Plan Points distribution tables available for {team} - {year}"))
},
warning = function(w){
},
finally = {
}
)
return(kenpom)
}
#' **Get KenPom's team opponent tracker page**
#'
#'
#' @param team Team filter to select.
#' @param year Year of data to pull
#' @return Returns a tibble of team opponent tracker data
#'
#' |col_name |types |
#' |:----------------|:---------|
#' |date |Date |
#' |game_date |numeric |
#' |day_date |character |
#' |wl |character |
#' |team |character |
#' |team_score |numeric |
#' |opponent |character |
#' |opponent_score |numeric |
#' |result |character |
#' |adj_oe |numeric |
#' |adj_oe_rk |integer |
#' |off_e_fg_pct |numeric |
#' |off_e_fg_pct_rk |integer |
#' |off_to_pct |numeric |
#' |off_to_pct_rk |integer |
#' |off_or_pct |numeric |
#' |off_or_pct_rk |integer |
#' |off_ft_rate |numeric |
#' |off_ft_rate_rk |integer |
#' |off_fg_2_pct |numeric |
#' |off_fg_2_pct_rk |integer |
#' |off_fg_3_pct |numeric |
#' |off_fg_3_pct_rk |integer |
#' |off_blk_pct |numeric |
#' |off_blk_pct_rk |integer |
#' |off_fg_3a_pct |numeric |
#' |off_fg_3a_pct_rk |integer |
#' |off_apl |numeric |
#' |off_apl_rk |integer |
#' |adj_de |numeric |
#' |adj_de_rk |integer |
#' |def_e_fg_pct |numeric |
#' |def_e_fg_pct_rk |integer |
#' |def_to_pct |numeric |
#' |def_to_pct_rk |integer |
#' |def_or_pct |numeric |
#' |def_or_pct_rk |integer |
#' |def_ft_rate |numeric |
#' |def_ft_rate_rk |integer |
#' |def_fg_2_pct |numeric |
#' |def_fg_2_pct_rk |integer |
#' |def_fg_3_pct |numeric |
#' |def_fg_3_pct_rk |integer |
#' |def_blk_pct |numeric |
#' |def_blk_pct_rk |integer |
#' |def_fg_3a_pct |numeric |
#' |def_fg_3a_pct_rk |integer |
#' |def_apl |numeric |
#' |def_apl_rk |integer |
#'
#' @importFrom cli cli_abort
#' @importFrom dplyr filter
#' @import rvest
#' @export
#' @keywords Opponent Tracker
#' @family KenPom Team Functions
#'
#' @examples
#' \donttest{
#' try(kp_opptracker(team = 'Florida St.', year = 2021))
#' }
kp_opptracker <- function(team, year = 2021){
tryCatch(
expr = {
if (!has_kp_user_and_pw()) stop("This function requires a KenPom subscription e-mail and password combination,\n set as the system environment variables KP_USER and KP_PW.", "\n See ?kp_user_pw for details.", call. = FALSE)
browser <- login()
if (!(is.numeric(year) && nchar(year) == 4 && year >= 2001)) {
# Check if year is numeric, if not NULL
cli::cli_abort("Enter valid year as a number (YYYY), data only goes back to 2001")
}
if (!(team %in% hoopR::teams_links$Team)) {
cli::cli_abort("Incorrect team name as compared to the website, see hoopR::teams_links for team name parameter specifications.")
}
teams_links <- hoopR::teams_links[hoopR::teams_links$Year == year,]
team_name = teams_links$team.link.ref[teams_links$Team == team]
### Pull Data
url <- paste0("https://kenpom.com/opptracker.php?",
"team=", team_name,
"&y=", year,
"&t=o")
page_o <- rvest::session_jump_to(browser, url)
Sys.sleep(5)
header_cols <- c("Date","Opponent","Result","AdjOE","AdjOE.Rk",
"Off.eFG.Pct","Off.eFG.Pct.Rk","Off.TO.Pct","Off.TO.Pct.Rk",
"Off.OR.Pct","Off.OR.Pct.Rk","Off.FTRate","Off.FTRate.Rk",
"Off.FG_2.Pct","Off.FG_2.Pct.Rk","Off.FG_3.Pct","Off.FG_3.Pct.Rk",
"Off.Blk.Pct","Off.Blk.Pct.Rk","Off.FG_3A.Pct","Off.FG_3A.Pct.Rk")
if (year >= 2010) {
header_cols <- c(header_cols, "Off.APL","Off.APL.Rk")
}
opptracker_o <- (page_o %>%
xml2::read_html() %>%
rvest::html_elements(css = '#conf-table'))[[1]] %>%
rvest::html_table() %>%
as.data.frame()
colnames(opptracker_o) <- header_cols
suppressWarnings(
opptracker_o <- opptracker_o %>%
dplyr::filter(!is.na(as.numeric(.data$Off.eFG.Pct)))
)
suppressWarnings(
opptracker_o <- opptracker_o %>%
dplyr::mutate(
Team = team,
WL = stringr::str_replace(stringr::str_extract(.data$Result,'W|L'),",",""),
Score = stringr::str_replace(stringr::str_extract(.data$Result,'\\d{1,3}-\\d{1,3}'),",","")) %>%
tidyr::separate("Score", into = c("WinnerScore", "LoserScore"), sep = "-") %>%
dplyr::mutate(
TeamScore = dplyr::case_when(
.data$WL == "W" ~ as.numeric(.data$WinnerScore),
.data$WL == "L" ~ as.numeric(.data$LoserScore),
.data$WL == "" ~ NA_real_),
OpponentScore = dplyr::case_when(
.data$WL == "L" ~ as.numeric(.data$WinnerScore),
.data$WL == "W" ~ as.numeric(.data$LoserScore),
.data$WL == "" ~ NA_real_),
Date.DD = stringr::str_pad(stringr::str_extract(.data$Date,'\\d+'), 2, pad = "0"),
Date.MO = NA_character_,
Date.MO = dplyr::case_when(
stringr::str_detect(.data$Date, regex("Oct", ignore_case = TRUE)) ~ "10",
stringr::str_detect(.data$Date, regex("Nov", ignore_case = TRUE)) ~ "11",
stringr::str_detect(.data$Date, regex("Dec", ignore_case = TRUE)) ~ "12",
stringr::str_detect(.data$Date, regex("Jan", ignore_case = TRUE)) ~ stringr::str_pad(1, 2, pad="0"),
stringr::str_detect(.data$Date, regex("Feb", ignore_case = TRUE)) ~ stringr::str_pad(2, 2, pad="0"),
stringr::str_detect(.data$Date, regex("Mar", ignore_case = TRUE)) ~ stringr::str_pad(3, 2, pad="0"),
stringr::str_detect(.data$Date, regex("Apr", ignore_case = TRUE)) ~ stringr::str_pad(4, 2, pad="0")
),
Date.YR = dplyr::case_when(
stringr::str_detect(.data$Date, regex("Oct",ignore_case = TRUE)) ~ glue::glue("{year-1}"),
stringr::str_detect(.data$Date, regex("Nov",ignore_case = TRUE)) ~ glue::glue("{year-1}"),
stringr::str_detect(.data$Date, regex("Dec",ignore_case = TRUE)) ~ glue::glue("{year-1}"),
stringr::str_detect(.data$Date, regex("Jan",ignore_case = TRUE)) ~ glue::glue("{year}"),
stringr::str_detect(.data$Date, regex("Feb",ignore_case = TRUE)) ~ glue::glue("{year}"),
stringr::str_detect(.data$Date, regex("Mar",ignore_case = TRUE)) ~ glue::glue("{year}"),
stringr::str_detect(.data$Date, regex("Apr",ignore_case = TRUE)) ~ glue::glue("{year}")
),
Day.Date = .data$Date,
Date = as.Date(glue::glue("{.data$Date.YR}-{.data$Date.MO}-{.data$Date.DD}")),
GameDate = as.numeric(paste0(.data$Date.YR, .data$Date.MO, .data$Date.DD))) %>%
dplyr::select(
-"Date.DD",
-"Date.MO",
-"Date.YR",
-"WinnerScore",
-"LoserScore")
)
header_cols <- c("Date","Opponent","Result","AdjDE","AdjDE.Rk",
"Def.eFG.Pct","Def.eFG.Pct.Rk","Def.TO.Pct","Def.TO.Pct.Rk",
"Def.OR.Pct","Def.OR.Pct.Rk","Def.FTRate","Def.FTRate.Rk",
"Def.FG_2.Pct","Def.FG_2.Pct.Rk","Def.FG_3.Pct","Def.FG_3.Pct.Rk",
"Def.Blk.Pct","Def.Blk.Pct.Rk","Def.FG_3A.Pct","Def.FG_3A.Pct.Rk")
if (year >= 2010) {
header_cols <- c(header_cols, "Def.APL","Def.APL.Rk")
}
### Pull Data
url <- paste0("https://kenpom.com/opptracker.php?",
"team=", team_name,
"&y=", year,
"&t=d")
page_d <- rvest::session_jump_to(browser, url)
Sys.sleep(5)
opptracker_d <- (page_d %>%
xml2::read_html() %>%
rvest::html_elements(css = '#conf-table'))[[1]] %>%
rvest::html_table() %>%
as.data.frame()
colnames(opptracker_d) <- header_cols
suppressWarnings(
opptracker_d <- opptracker_d %>%
dplyr::filter(!is.na(as.numeric(.data$Def.eFG.Pct)))
)
opptracker <- dplyr::bind_cols(opptracker_o, opptracker_d[,4:ncol(opptracker_d)])
### Store Data
kenpom <- opptracker %>%
dplyr::select(
"Date",
"GameDate",
"Day.Date",
"WL",
"Team",
"TeamScore",
"Opponent",
"OpponentScore",
tidyr::everything()) %>%
janitor::clean_names()
},
error = function(e){
message(glue::glue("{Sys.time()} - {team} - {year} Team opponent tracker data is missing"))
},
warning = function(w){
},
finally = {
}
)
return(kenpom)
}
#' **Get KenPom's player stats from the team page**
#'
#'
#' @param team Team filter to select.
#' @param year Year of data to pull
#' @return Returns a tibble of team player data
#'
#' |col_name |types |
#' |:-------------|:---------|
#' |role |character |
#' |number |numeric |
#' |player |character |
#' |ht |character |
#' |wt |numeric |
#' |yr |character |
#' |g |numeric |
#' |s |numeric |
#' |min_pct |numeric |
#' |o_rtg |numeric |
#' |poss_pct |numeric |
#' |shots_pct |numeric |
#' |e_fg_pct |numeric |
#' |ts_pct |numeric |
#' |or_pct |numeric |
#' |dr_pct |numeric |
#' |a_rate |numeric |
#' |to_rate |numeric |
#' |blk_pct |numeric |
#' |stl_pct |numeric |
#' |f_cper40 |numeric |
#' |f_dper40 |numeric |
#' |ft_rate |numeric |
#' |ftm |numeric |
#' |fta |numeric |
#' |ft_pct |numeric |
#' |fgm_2 |numeric |
#' |fga_2 |numeric |
#' |fg_2_pct |numeric |
#' |fgm_3 |numeric |
#' |fga_3 |numeric |
#' |fg_3_pct |numeric |
#' |min_pct_rk |numeric |
#' |o_rtg_rk |numeric |
#' |poss_pct_rk |numeric |
#' |shots_pct_rk |numeric |
#' |e_fg_pct_rk |numeric |
#' |ts_pct_rk |numeric |
#' |or_pct_rk |numeric |
#' |dr_pct_rk |numeric |
#' |a_rate_rk |numeric |
#' |to_rate_rk |numeric |
#' |blk_pct_rk |numeric |
#' |stl_pct_rk |numeric |
#' |f_cper40_rk |numeric |
#' |f_dper40_rk |numeric |
#' |ft_rate_rk |numeric |
#' |ft_pct_rk |numeric |
#' |fg_2_pct_rk |numeric |
#' |fg_3_pct_rk |numeric |
#' |national_rank |character |
#' |team |character |
#' |year |numeric |
#' |player_id |numeric |
#'
#' @importFrom cli cli_abort
#' @importFrom dplyr select mutate filter case_when mutate_at bind_cols bind_rows
#' @importFrom stringr str_extract str_remove str_replace str_detect
#' @importFrom tidyr everything separate
#' @import rvest
#' @export
#' @keywords Team Player Stats
#' @family KenPom Team Functions
#'
#' @examples
#' \donttest{
#' try(kp_team_players(team = 'Florida St.', year = 2024))
#' }
#'
kp_team_players <- function(team, year = 2021){
tryCatch(
expr = {
browser <- login()
if (!(is.numeric(year) && nchar(year) == 4 && year >= 2002)) {
# Check if year is numeric, if not NULL
cli::cli_abort("Enter valid year as a number (YYYY), data only goes back to 2002")
}
if (!(team %in% hoopR::teams_links$Team)) {
cli::cli_abort("Incorrect team name as compared to the website, see hoopR::teams_links for team name parameter specifications.")
}
teams_links <- hoopR::teams_links[hoopR::teams_links$Year == year,]
team_name = teams_links$team.link.ref[teams_links$Team == team]
### Pull Data
url <- paste0("https://kenpom.com/team.php?",
"team=",team_name,
"&y=", year)
page <- rvest::session_jump_to(browser, url)
Sys.sleep(5)
player_links <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#player-table') %>%
rvest::html_elements("td:nth-child(2) > a")
pid <- dplyr::bind_rows(lapply(xml2::xml_attrs(player_links),
function(x){
if (!stringr::str_detect(x,"kpoy")) {
data.frame(as.list(x), stringsAsFactors = FALSE)
}
}))
pid <- pid %>%
dplyr::mutate(PlayerId = stringr::str_remove(stringr::str_extract(.data$href,"=(.+)"),"=")) %>%
dplyr::select("PlayerId")
if (year >= 2014) { # "S" - starts only available from 2014 onwards
players_header_cols <- c("Number", "Player", "Ht", "Wt", "Yr", "G", "S",
"Min.Pct", "ORtg", "Poss.Pct","Shots.Pct",
"eFG.Pct", "TS.Pct", "OR.Pct", "DR.Pct",
"ARate", "TORate", "Blk.Pct","Stl.Pct","FCper40","FDper40",
"FTRate", "FTM-A", "FT.Pct",
"FGM_2-A", "FG_2.Pct", "FGM_3-A", "FG_3.Pct")
} else {
players_header_cols <- c("Number", "Player", "Ht", "Wt", "Yr", "G",
"Min.Pct", "ORtg", "Poss.Pct","Shots.Pct",
"eFG.Pct", "TS.Pct", "OR.Pct", "DR.Pct",
"ARate", "TORate", "Blk.Pct","Stl.Pct","FCper40","FDper40",
"FTRate", "FTM-A", "FT.Pct",
"FGM_2-A", "FG_2.Pct", "FGM_3-A", "FG_3.Pct")
}
players <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#player-table'))[[1]]
players <- players %>%
rvest::html_table()
colnames(players) <- players_header_cols
suppressWarnings(
players <- players %>%
dplyr::filter(!is.na(as.numeric(.data$G)))
)
players$Min.Pct.Rk <- NA_real_
players$ORtg.Rk <- NA_real_
players$Poss.Pct.Rk <- NA_real_
players$Shots.Pct.Rk <- NA_real_
players$eFG.Pct.Rk <- NA_real_
players$TS.Pct.Rk <- NA_real_
players$OR.Pct.Rk <- NA_real_
players$DR.Pct.Rk <- NA_real_
players$ARate.Rk <- NA_real_
players$TORate.Rk <- NA_real_
players$Blk.Pct.Rk <- NA_real_
players$Stl.Pct.Rk <- NA_real_
players$FCper40.Rk <- NA_real_
players$FDper40.Rk <- NA_real_
players$FTRate.Rk <- NA_real_
players$FT.Pct.Rk <- NA_real_
players$FG_2.Pct.Rk <- NA_real_
players$FG_3.Pct.Rk <- NA_real_
players <- players %>%
dplyr::mutate(
Min.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$Min.Pct,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
ORtg.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$ORtg,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
Poss.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$Poss.Pct,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
Shots.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$Shots.Pct,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
eFG.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$eFG.Pct,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
TS.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$TS.Pct,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
OR.Pct.Rk = stringr::str_replace(stringr::str_extract(.data$OR.Pct,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',""),
DR.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$DR.Pct,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
ARate.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$ARate,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
TORate.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$TORate,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
Blk.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$Blk.Pct,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
Stl.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$Stl.Pct,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
FCper40.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$FCper40,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
FDper40.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$FDper40,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
FTRate.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$FTRate,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
FT.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$FT.Pct,'\\.\\d{3}(.+)'),'\\.\\d{3}',"")),
FG_2.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$FG_2.Pct,'\\.\\d{3}(.+)'),'\\.\\d{3}',"")),
FG_3.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$FG_3.Pct,'\\.\\d{3}(.+)'),'\\.\\d{3}',"")),
NationalRank = stringr::str_extract(.data$Player, "National Rank"),
Player = stringr::str_replace(.data$Player, "National Rank",""),
Min.Pct = substr(sprintf("%.*f",4, as.numeric(.data$Min.Pct)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$Min.Pct))) - 3),
ORtg = substr(sprintf("%.*f",4, as.numeric(.data$ORtg)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$ORtg))) - 3),
Poss.Pct = substr(sprintf("%.*f",4, as.numeric(.data$Poss.Pct)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$Poss.Pct))) - 3),
Shots.Pct = substr(sprintf("%.*f",4, as.numeric(.data$Shots.Pct)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$Shots.Pct))) - 3),
eFG.Pct = substr(sprintf("%.*f",4, as.numeric(.data$eFG.Pct)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$eFG.Pct))) - 3),
TS.Pct = substr(sprintf("%.*f",4, as.numeric(.data$TS.Pct)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$TS.Pct))) - 3),
OR.Pct = substr(sprintf("%.*f",4, as.numeric(.data$OR.Pct)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$OR.Pct))) - 3),
DR.Pct = substr(sprintf("%.*f",4, as.numeric(.data$ARate)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$DR.Pct))) - 3),
ARate = substr(sprintf("%.*f",4, as.numeric(.data$ARate)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$ARate))) - 3),
TORate = substr(sprintf("%.*f",4, as.numeric(.data$TORate)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$TORate))) - 3),
Blk.Pct = substr(sprintf("%.*f",4, as.numeric(.data$Blk.Pct)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$Blk.Pct))) - 3),
Stl.Pct = substr(sprintf("%.*f",4, as.numeric(.data$Stl.Pct)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$Stl.Pct))) - 3),
FCper40 = substr(sprintf("%.*f",4, as.numeric(.data$FCper40)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$FCper40))) - 3),
FDper40 = substr(sprintf("%.*f",4, as.numeric(.data$FDper40)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$FDper40))) - 3),
FTRate = substr(sprintf("%.*f",4, as.numeric(.data$FTRate)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$FTRate))) - 3),
FT.Pct = substr(sprintf("%.*f",6, as.numeric(.data$FT.Pct)), 1,
nchar(sprintf("%.*f",6, as.numeric(.data$FT.Pct))) - 3),
FG_2.Pct = substr(sprintf("%.*f",6, as.numeric(.data$FG_2.Pct)), 1,
nchar(sprintf("%.*f",6, as.numeric(.data$FG_2.Pct))) - 3),
FG_3.Pct = substr(sprintf("%.*f",6, as.numeric(.data$FG_3.Pct)), 1,
nchar(sprintf("%.*f",6, as.numeric(.data$FG_3.Pct))) - 3))
if (year >= 2014) {
suppressWarnings(
players <- players %>%
tidyr::separate("FTM-A", into = c("FTM", "FTA"), sep = "-") %>%
tidyr::separate("FGM_2-A", into = c("FGM_2", "FGA_2"), sep = "-") %>%
tidyr::separate("FGM_3-A", into = c("FGM_3", "FGA_3"), sep = "-") %>%
dplyr::mutate_at(c("Number", "Wt", "G", "S",
"Min.Pct", "ORtg", "Poss.Pct","Shots.Pct",
"eFG.Pct", "TS.Pct", "OR.Pct", "DR.Pct",
"ARate", "TORate", "Blk.Pct","Stl.Pct","FCper40","FDper40",
"FTRate", "FTM", "FTA", "FT.Pct",
"FGM_2", "FGA_2", "FG_2.Pct", "FGM_3", "FGA_3", "FG_3.Pct",
"Min.Pct.Rk", "ORtg.Rk", "Poss.Pct.Rk", "Shots.Pct.Rk",
"eFG.Pct.Rk", "TS.Pct.Rk", "OR.Pct.Rk", "DR.Pct.Rk",
"ARate.Rk", "TORate.Rk", "Blk.Pct.Rk","Stl.Pct.Rk", "FCper40.Rk", "FDper40.Rk",
"FTRate.Rk", "FT.Pct.Rk", "FG_2.Pct.Rk", "FG_3.Pct.Rk"), as.numeric)
)
} else {
suppressWarnings(
players <- players %>%
tidyr::separate("FTM-A", into = c("FTM", "FTA"), sep = "-") %>%
tidyr::separate("FGM_2-A", into = c("FGM_2", "FGA_2"), sep = "-") %>%
tidyr::separate("FGM_3-A", into = c("FGM_3", "FGA_3"), sep = "-") %>%
dplyr::mutate_at(c("Number", "Wt", "G",
"Min.Pct", "ORtg", "Poss.Pct","Shots.Pct",
"eFG.Pct", "TS.Pct", "OR.Pct", "DR.Pct",
"ARate", "TORate", "Blk.Pct","Stl.Pct","FCper40","FDper40",
"FTRate", "FTM", "FTA", "FT.Pct",
"FGM_2", "FGA_2", "FG_2.Pct", "FGM_3", "FGA_3", "FG_3.Pct",
"Min.Pct.Rk", "ORtg.Rk", "Poss.Pct.Rk", "Shots.Pct.Rk",
"eFG.Pct.Rk", "TS.Pct.Rk", "OR.Pct.Rk", "DR.Pct.Rk",
"ARate.Rk", "TORate.Rk", "Blk.Pct.Rk","Stl.Pct.Rk", "FCper40.Rk", "FDper40.Rk",
"FTRate.Rk", "FT.Pct.Rk", "FG_2.Pct.Rk", "FG_3.Pct.Rk"), as.numeric)
)
}
players <- players %>%
dplyr::mutate(Team = team,
Year = year,
Role = dplyr::case_when(.data$Min.Pct < 10.0 ~ "Benchwarmer",
.data$Poss.Pct < 12.0 ~ "Nearly Invisible",
.data$Poss.Pct >= 12.0 & .data$Poss.Pct < 16.0 ~ "Limited Role",
.data$Poss.Pct >= 16.0 & .data$Poss.Pct < 20.0 ~ "Role Player",
.data$Poss.Pct >= 20.0 & .data$Poss.Pct < 24.0 ~ "Significant Contributor",
.data$Poss.Pct >= 24.0 & .data$Poss.Pct < 28.0 ~ "Major Contributor",
.data$Poss.Pct >= 28.0 ~ "Go-to Guys")) %>%
dplyr::select(
"Role",
tidyr::everything()) %>%
dplyr::bind_cols(lapply(pid, as.numeric))
### Store Data
kenpom <- players %>%
janitor::clean_names()
},
error = function(e){
message(glue::glue("{Sys.time()} - No Player Data available for {team} in {year}"))
},
warning = function(w){
},
finally = {
}
)
return(kenpom)
}
#' **Get KenPom's player career stats from the player page**
#'
#'
#' @param player_id Player Id filter to select.
#' @return Returns a named list of tibbles: player_stats, gamelog
#'
#' **player_stats**
#'
#'
#' |col_name |types |
#' |:-------------|:---------|
#' |year |numeric |
#' |team_rk |numeric |
#' |team |character |
#' |number |numeric |
#' |name |character |
#' |position |character |
#' |hgt |character |
#' |wgt |numeric |
#' |yr |character |
#' |g |numeric |
#' |min_pct |numeric |
#' |o_rtg |numeric |
#' |poss_pct |numeric |
#' |shots_pct |numeric |
#' |e_fg_pct |numeric |
#' |ts_pct |numeric |
#' |or_pct |numeric |
#' |dr_pct |numeric |
#' |a_rate |numeric |
#' |to_rate |numeric |
#' |blk_pct |numeric |
#' |stl_pct |numeric |
#' |f_cper40 |numeric |
#' |f_dper40 |numeric |
#' |ft_rate |numeric |
#' |ftm |numeric |
#' |fta |numeric |
#' |ft_pct |numeric |
#' |fgm_2 |numeric |
#' |fga_2 |numeric |
#' |fg_2_pct |numeric |
#' |fgm_3 |numeric |
#' |fga_3 |numeric |
#' |fg_3_pct |numeric |
#' |group_rank |character |
#' |team_finish |character |
#' |ncaa_seed |numeric |
#' |hometown |character |
#' |date_of_birth |character |
#' |age |character |
#' |comparisons |character |
#'
#' **gamelog**
#'
#'
#' |col_name |types |
#' |:--------------|:---------|
#' |year |numeric |
#' |team |character |
#' |name |character |
#' |position |character |
#' |opponent_tier |logical |
#' |date |character |
#' |opponent_rk |numeric |
#' |opponent |character |
#' |result |character |
#' |ot |character |
#' |location |character |
#' |game_type |character |
#' |mvp |character |
#' |start |character |
#' |minutes_played |numeric |
#' |o_rtg |numeric |
#' |poss_pct |numeric |
#' |pts |numeric |
#' |fgm_2 |numeric |
#' |fga_2 |numeric |
#' |fgm_3 |numeric |
#' |fga_3 |numeric |
#' |ftm |numeric |
#' |fta |numeric |
#' |or |numeric |
#' |dr |numeric |
#' |a |numeric |
#' |to |numeric |
#' |blk |numeric |
#' |stl |numeric |
#' |pf |numeric |
#'
#' @importFrom cli cli_abort
#' @importFrom dplyr select mutate filter case_when mutate_at bind_cols bind_rows
#' @importFrom stringr str_extract str_remove str_replace str_detect
#' @importFrom tidyr everything separate
#' @import rvest
#' @export
#' @keywords Player Career Stats
#' @family KenPom Team Functions
#'
#' @examples
#' \donttest{
#' try(kp_player_career(player_id = '41180'))
#' }
#'
kp_player_career <- function(player_id){
tryCatch(
expr = {
if (!has_kp_user_and_pw()) stop("This function requires a KenPom subscription e-mail and password combination,\n set as the system environment variables KP_USER and KP_PW.", "\n See ?kp_user_pw for details.", call. = FALSE)
browser <- login()
### Pull Data
url <- paste0("https://kenpom.com/player.php?",
"p=",player_id)
page <- rvest::session_jump_to(browser, url)
Sys.sleep(5)
#--- Player Info ----
player_info <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = 'span.name')) %>%
rvest::html_text() %>%
as.data.frame()
colnames(player_info) <- "Player"
player_town <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = 'span.town')) %>%
rvest::html_text() %>%
as.data.frame()
colnames(player_town) <- "Num"
player_town <- player_town %>%
tidyr::separate("Num", into = c("Number", "Town", "DateOfBirth"), sep = "\u00b7")
player_info <- dplyr::bind_cols(player_info, player_town)
#--- Player Career Average Stats ----
players_header_cols <- c("Year","Team","Hgt","Wgt","Yr","G","Min.Pct","ORtg",
"Poss.Pct","Shots.Pct","eFG.Pct","TS.Pct","OR.Pct",
"DR.Pct","ARate","TORate","Blk.Pct",
"Stl.Pct","FCper40","FDper40","FTRate",
"FTM-A","FT.Pct","FG_2M-A","FG_2.Pct","FG_3M-A",
"FG_3.Pct")
players <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#player-table'))[[1]] %>%
rvest::html_table()
colnames(players) <- players_header_cols
players <- players %>%
dplyr::mutate(
Position = gsub('[0-9]','',.data$Year),
Year = gsub('[^0-9]','',.data$Year),
GroupRank = stringr::str_extract(.data$Team,"National Rank|Conference Rank"),
Team = stringr::str_trim(stringr::str_replace(.data$Team,"National Rank|Conference Rank", "")),
Team.Finish = stringr::str_extract(.data$Team, stringr::regex('R1|R2|S16|E8|F4|2nd|CH',ignore_case = FALSE)),
Team = stringr::str_replace(.data$Team, stringr::regex(' R1| R2| S16| E8| F4| 2nd| CH',ignore_case = FALSE),""),
Team.Rk = gsub("[^0-9]", "",stringr::str_extract(.data$Team, stringr::regex('\\d{1,3}')))
)
# separating the career totals so as to not fill those columns (they're empty in the table)
players_career <- players[(nrow(players) - 2):nrow(players),]
players <- players[1:(nrow(players) - 3),]
# Now need to fill year to create a join column for the age and player comps columns
players <- players %>%
dplyr::mutate(Year = ifelse(.data$Year == "", NA_real_, .data$Year)) %>%
tidyr::fill("Year", .direction = c("down"))
player_age <- players %>%
dplyr::filter(stringr::str_detect(.data$Team,'Age:')) %>%
dplyr::select(
"Year",
"Team",
"Min.Pct") %>%
dplyr::rename(
"Age" = "Team",
"Comparisons" = "Min.Pct") %>%
dplyr::mutate(
Age = stringr::str_replace(.data$Age, "Age: ", ""),
Comparisons = stringr::str_replace(.data$Comparisons, "Similar: ", "")
)
players <- players %>%
dplyr::filter(!(stringr::str_detect(.data$Team,'Age:')),
!(stringr::str_detect(.data$Min.Pct,'Similar'))) %>%
dplyr::mutate(
NCAASeed = stringr::str_extract(.data$Team, stringr::regex(' \\d{1,2}')))
players <- dplyr::mutate(players,
"Team" = sapply(.data$Team, function(arg) {
stringr::str_trim(stringr::str_replace(stringr::str_remove(arg,'\\d+| \\*| \\*+'),'\\d+|\\*+','')) }))
players <- players %>%
dplyr::mutate(
Hgt = ifelse(.data$Hgt == "", NA_character_, .data$Hgt),
Yr = ifelse(.data$Yr == "", NA_character_, .data$Yr),
Position = ifelse(.data$Position == "", NA_character_, .data$Position),
Name = player_info$Player,
Number = player_info$Number,
Hometown = player_info$Town,
DateOfBirth = player_info$DateOfBirth) %>%
tidyr::fill("Hgt", .direction = c("down")) %>%
tidyr::fill("Wgt", .direction = c("down")) %>%
tidyr::fill("Yr", .direction = c("down")) %>%
tidyr::fill("Position", .direction = c("down")) %>%
tidyr::fill("Team.Rk", .direction = c("down")) %>%
dplyr::group_by(.data$Year) %>%
tidyr::fill("Team.Finish", .direction = c("down")) %>%
tidyr::fill("NCAASeed", .direction = c("down")) %>%
dplyr::ungroup() %>%
dplyr::bind_rows(players_career) %>%
dplyr::left_join(player_age, by = c("Year"))
suppressWarnings(
players <- players %>%
tidyr::separate("FTM-A", into = c("FTM", "FTA")) %>%
tidyr::separate("FG_2M-A", into = c("FGM_2", "FGA_2")) %>%
tidyr::separate("FG_3M-A", into = c("FGM_3", "FGA_3")) %>%
dplyr::mutate_at(c("Year", "Wgt", "G", "Min.Pct",
"ORtg", "Poss.Pct", "Shots.Pct", "eFG.Pct",
"TS.Pct", "OR.Pct", "DR.Pct", "ARate",
"TORate", "Blk.Pct", "Stl.Pct", "FCper40",
"FDper40", "FTRate","FTM", "FTA", "FT.Pct",
"FGM_2", "FGA_2", "FG_2.Pct",
"FGM_3", "FGA_3", "FG_3.Pct",
"Team.Rk", "NCAASeed", "Number"), as.numeric)
)
players_team_name <- players %>%
dplyr::filter(!(stringr::str_detect(.data$Team ,"Tier A|Conference|Career"))) %>%
dplyr::select(
"Year",
"Team",
"Name",
"Position")
img_extractor <- function(x){
data.frame(
ifelse(
is.null(rvest::html_element(x, css = "a > img")),
NA_character_,
toupper(stringr::str_trim(
stringr::str_replace(
stringr::str_extract(rvest::html_element(x, css = "a > img") %>%
xml2::xml_attr("src"), "a.gif|b.gif"),
".gif","")))),
stringsAsFactors = FALSE)
}
players <- players %>%
dplyr::select(
"Year",
"Team.Rk",
"Team",
"Number",
"Name",
"Position",
tidyr::everything()) %>%
janitor::clean_names()
s <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table'))
schedule_games <- data.frame()
for (i in 1:length(s)) {
header <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = 'div.gamelogdiv > h3'))[[i]] %>%
rvest::html_text()
sched_header_cols <- c("Opponent.Tier", "Date", "Opponent.Rk", "Opponent",
"Result","OT", "Location", "GameType",
"MVP", "Start", "MinutesPlayed", "ORtg", "Poss.Pct",
"Pts", "FG_2M-A", "FG_3M-A", "FTM-A",
"OR", "DR", "A", "TO", "Blk", "Stl", "PF")
sched <- ((page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table'))[[i]] %>%
rvest::html_table())[,1:24]
colnames(sched) <- sched_header_cols
rownames(sched) <- NULL
sched <- sched %>% dplyr::filter(.data$Date != "")
sched$GameData <- header
sched <- sched %>%
dplyr::mutate(Year = as.numeric(stringr::str_replace(.data$GameData," Game Data",""))) %>%
dplyr::select(-"GameData")
sched <- sched %>%
dplyr::left_join(players_team_name, by = "Year")
suppressWarnings(
sched <- sched %>%
tidyr::separate("FTM-A", into = c("FTM", "FTA")) %>%
tidyr::separate("FG_2M-A", into = c("FGM_2", "FGA_2")) %>%
tidyr::separate("FG_3M-A", into = c("FGM_3", "FGA_3")) %>%
dplyr::mutate_at(c("Opponent.Rk","MinutesPlayed","ORtg","Poss.Pct",
"Pts","OR","DR","A","TO",
"FTM", "FTA","FGM_2", "FGA_2",
"FGM_3", "FGA_3",
"Blk","Stl","PF"), as.numeric)
)
sched <- sched %>%
dplyr::select(
"Year",
"Team",
"Name",
"Position",
tidyr::everything())
schedule_games <- dplyr::bind_rows(schedule_games,sched)
}
schedule_games <- schedule_games %>%
janitor::clean_names()
### Store Data
kenpom <- c(list(players),list(schedule_games))
names(kenpom) <- c("player_stats", "gamelog")
},
error = function(e){
message(glue::glue("{Sys.time()} - No Player Career Data available for {player_id}"))
},
warning = function(w){
},
finally = {
}
)
return(kenpom)
}
#' **Get Minutes Matrix from Expanded Player Page**
#'
#'
#' @param team Team filter to select.
#' @param year Year of data to pull
#' @return Returns a tibble of minutes matrix data
#'
#' @importFrom cli cli_abort
#' @importFrom dplyr mutate filter
#' @import rvest
#' @export
#' @keywords Minutes Matrix
#' @family KenPom Team Functions
#'
#' @examples
#' \donttest{
#' try(kp_minutes_matrix(team = 'Florida St.', year = 2021))
#' }
#'
#'
kp_minutes_matrix <- function(team, year = 2021){
tryCatch(
expr = {
if (!has_kp_user_and_pw()) stop("This function requires a KenPom subscription e-mail and password combination,\n set as the system environment variables KP_USER and KP_PW.", "\n See ?kp_user_pw for details.", call. = FALSE)
browser <- login()
if (!(is.numeric(year) && nchar(year) == 4 && year >= 2014)) {
# Check if year is numeric, if not NULL
cli::cli_abort("Enter valid year as a number (YYYY), data only goes back to 2014")
}
if (!(team %in% hoopR::teams_links$Team)) {
cli::cli_abort("Incorrect team name as compared to the website, see hoopR::teams_links for team name parameter specifications.")
}
teams_links <- hoopR::teams_links[hoopR::teams_links$Year == year,]
team_name = teams_links$team.link.ref[teams_links$Team == team]
### Pull Data
url <- paste0("https://kenpom.com/player-expanded.php?",
"team=",team_name,
"&y=", year)
page <- rvest::session_jump_to(browser, url)
Sys.sleep(5)
header_cols <- c("Date","Opponent.Rk","Opponent","Result")
x <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#minutes-table'))[[1]] %>%
rvest::html_table() %>%
as.data.frame()
colnames(x)[1:4] <- header_cols
team_name <- gsub("\\+"," ",team)
suppressWarnings(
x <- x %>%
dplyr::filter(!is.na(as.numeric(.data$Opponent.Rk)))
)
x <- x %>%
dplyr::mutate(Team = team_name,
Year = year)
### Store Data
kenpom <- x %>%
janitor::clean_names()
},
error = function(e){
message(glue::glue("{Sys.time()} - {team} - {year} minutes matrix is missing"))
},
warning = function(w){
},
finally = {
}
)
return(kenpom)
}
#' **Get Team Player Stats**
#' @param team Team filter to select.
#' @param year Year of data to pull
#'
#' @return Returns a list of named data frames: all_games, conference_games
#'
#' **all_games**
#'
#'
#' |col_name |types |
#' |:------------|:---------|
#' |role |character |
#' |number |numeric |
#' |player |character |
#' |ht |character |
#' |wt |numeric |
#' |yr |character |
#' |g |numeric |
#' |min_pct |numeric |
#' |o_rtg |numeric |
#' |poss_pct |numeric |
#' |shots_pct |numeric |
#' |e_fg_pct |numeric |
#' |ts_pct |numeric |
#' |or_pct |numeric |
#' |dr_pct |numeric |
#' |a_rate |numeric |
#' |to_rate |numeric |
#' |blk_pct |numeric |
#' |stl_pct |numeric |
#' |f_cper40 |numeric |
#' |f_dper40 |numeric |
#' |ft_rate |numeric |
#' |ftm |numeric |
#' |fta |numeric |
#' |ft_pct |numeric |
#' |fgm_2 |numeric |
#' |fga_2 |numeric |
#' |fg_2_pct |numeric |
#' |fgm_3 |numeric |
#' |fga_3 |numeric |
#' |fg_3_pct |numeric |
#' |category |character |
#' |min_pct_rk |numeric |
#' |o_rtg_rk |numeric |
#' |poss_pct_rk |numeric |
#' |shots_pct_rk |numeric |
#' |e_fg_pct_rk |numeric |
#' |ts_pct_rk |numeric |
#' |or_pct_rk |numeric |
#' |dr_pct_rk |numeric |
#' |a_rate_rk |numeric |
#' |to_rate_rk |numeric |
#' |blk_pct_rk |numeric |
#' |stl_pct_rk |numeric |
#' |f_cper40_rk |numeric |
#' |f_dper40_rk |numeric |
#' |ft_rate_rk |numeric |
#' |ft_pct_rk |numeric |
#' |fg_2_pct_rk |numeric |
#' |fg_3_pct_rk |numeric |
#' |group_rank |character |
#' |team |character |
#' |year |numeric |
#' |player_id |numeric |
#'
#' **conference_games**
#'
#'
#' |col_name |types |
#' |:------------|:---------|
#' |role |character |
#' |number |numeric |
#' |player |character |
#' |ht |character |
#' |wt |numeric |
#' |yr |character |
#' |g |numeric |
#' |min_pct |numeric |
#' |o_rtg |numeric |
#' |poss_pct |numeric |
#' |shots_pct |numeric |
#' |e_fg_pct |numeric |
#' |ts_pct |numeric |
#' |or_pct |numeric |
#' |dr_pct |numeric |
#' |a_rate |numeric |
#' |to_rate |numeric |
#' |blk_pct |numeric |
#' |stl_pct |numeric |
#' |f_cper40 |numeric |
#' |f_dper40 |numeric |
#' |ft_rate |numeric |
#' |ftm |numeric |
#' |fta |numeric |
#' |ft_pct |numeric |
#' |fgm_2 |numeric |
#' |fga_2 |numeric |
#' |fg_2_pct |numeric |
#' |fgm_3 |numeric |
#' |fga_3 |numeric |
#' |fg_3_pct |numeric |
#' |category |character |
#' |min_pct_rk |numeric |
#' |o_rtg_rk |numeric |
#' |poss_pct_rk |numeric |
#' |shots_pct_rk |numeric |
#' |e_fg_pct_rk |numeric |
#' |ts_pct_rk |numeric |
#' |or_pct_rk |numeric |
#' |dr_pct_rk |numeric |
#' |a_rate_rk |numeric |
#' |to_rate_rk |numeric |
#' |blk_pct_rk |numeric |
#' |stl_pct_rk |numeric |
#' |f_cper40_rk |numeric |
#' |f_dper40_rk |numeric |
#' |ft_rate_rk |numeric |
#' |ft_pct_rk |numeric |
#' |fg_2_pct_rk |numeric |
#' |fg_3_pct_rk |numeric |
#' |group_rank |character |
#' |team |character |
#' |year |numeric |
#' |player_id |numeric |
#'
#' @importFrom cli cli_abort
#' @importFrom dplyr select mutate filter case_when mutate_at bind_cols bind_rows
#' @importFrom stringr str_extract str_remove str_replace str_detect
#' @importFrom tidyr everything separate
#' @import rvest
#' @export
#' @keywords Team Player Stats
#' @family KenPom Team Functions
#'
#' @examples
#' \donttest{
#' try(kp_team_player_stats(team = 'Florida St.', year = 2021))
#' }
kp_team_player_stats <- function(team, year = 2021){
tryCatch(
expr = {
if (!has_kp_user_and_pw()) stop("This function requires a KenPom subscription e-mail and password combination,\n set as the system environment variables KP_USER and KP_PW.", "\n See ?kp_user_pw for details.", call. = FALSE)
browser <- login()
if (!(is.numeric(year) && nchar(year) == 4 && year >= 2014)) {
# Check if year is numeric, if not NULL
cli::cli_abort("Enter valid year as a number (YYYY), data only goes back to 2014")
}
if (!(team %in% hoopR::teams_links$Team)) {
cli::cli_abort("Incorrect team name as compared to the website, see hoopR::teams_links for team name parameter specifications.")
}
teams_links <- hoopR::teams_links[hoopR::teams_links$Year == year,]
team_name = teams_links$team.link.ref[teams_links$Team == team]
### Pull Data
url <- paste0("https://kenpom.com/player-expanded.php?",
"team=",team_name,
"&y=", year)
page <- rvest::session_jump_to(browser, url)
Sys.sleep(5)
players <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#player-table'))
y <- list()
for (i in 1:length(players)) {
player_links <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#player-table'))[[i]] %>%
rvest::html_elements("td:nth-child(2) > a")
pid <- dplyr::bind_rows(lapply(xml2::xml_attrs(player_links),
function(x){
if (!stringr::str_detect(x,"kpoy")) {
data.frame(as.list(x), stringsAsFactors = FALSE)
}
}))
# pid <- dplyr::bind_rows(lapply(player_links, extractor))
pid <- pid %>%
dplyr::mutate(PlayerId = stringr::str_remove(stringr::str_extract(.data$href,"=(.+)"),"=")) %>%
dplyr::select("PlayerId")
players_header_cols <- c("Number", "Player", "Ht", "Wt", "Yr", "G",
"Min.Pct", "ORtg", "Poss.Pct","Shots.Pct",
"eFG.Pct", "TS.Pct", "OR.Pct", "DR.Pct",
"ARate", "TORate", "Blk.Pct","Stl.Pct","FCper40","FDper40",
"FTRate", "FTM-A", "FT.Pct",
"FGM_2-A", "FG_2.Pct", "FGM_3-A", "FG_3.Pct")
players <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#player-table'))[[i]]
players <- players %>%
rvest::html_table()
colnames(players) <- players_header_cols
suppressWarnings(
players <- players %>%
dplyr::filter(!is.na(as.numeric(.data$G)))
)
if (i == 1) {
players$Category <- "All Games"
} else {
players$Category <- "Conference Games"
}
players$Min.Pct.Rk <- NA_real_
players$ORtg.Rk <- NA_real_
players$Poss.Pct.Rk <- NA_real_
players$Shots.Pct.Rk <- NA_real_
players$eFG.Pct.Rk <- NA_real_
players$TS.Pct.Rk <- NA_real_
players$OR.Pct.Rk <- NA_real_
players$DR.Pct.Rk <- NA_real_
players$ARate.Rk <- NA_real_
players$TORate.Rk <- NA_real_
players$Blk.Pct.Rk <- NA_real_
players$Stl.Pct.Rk <- NA_real_
players$FCper40.Rk <- NA_real_
players$FDper40.Rk <- NA_real_
players$FTRate.Rk <- NA_real_
players$FT.Pct.Rk <- NA_real_
players$FG_2.Pct.Rk <- NA_real_
players$FG_3.Pct.Rk <- NA_real_
players <- players %>%
dplyr::mutate(
Min.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$Min.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
ORtg.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$ORtg, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
Poss.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$Poss.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
Shots.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$Shots.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
eFG.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$eFG.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
TS.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$TS.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
OR.Pct.Rk = stringr::str_replace(stringr::str_extract(.data$OR.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', ""),
DR.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$DR.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
ARate.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$ARate, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
TORate.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$TORate, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
Blk.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$Blk.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
Stl.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$Stl.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
FCper40.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$FCper40, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
FDper40.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$FDper40, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
FTRate.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$FTRate, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
FT.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$FT.Pct, '\\.\\d{3}(.+)'), '\\.\\d{3}', "")),
FG_2.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$FG_2.Pct, '\\.\\d{3}(.+)'), '\\.\\d{3}', "")),
FG_3.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$FG_3.Pct, '\\.\\d{3}(.+)'), '\\.\\d{3}', "")),
GroupRank = stringr::str_extract(.data$Player, "National Rank|Conference Rank"),
Player = stringr::str_replace(.data$Player, "National Rank|Conference Rank",""),
Min.Pct = substr(sprintf("%.*f", 4, as.numeric(.data$Min.Pct)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$Min.Pct))) - 3),
ORtg = substr(sprintf("%.*f", 4, as.numeric(.data$ORtg)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$ORtg))) - 3),
Poss.Pct = substr(sprintf("%.*f", 4, as.numeric(.data$Poss.Pct)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$Poss.Pct))) - 3),
Shots.Pct = substr(sprintf("%.*f",4, as.numeric(.data$Shots.Pct)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$Shots.Pct))) - 3),
eFG.Pct = substr(sprintf("%.*f",4, as.numeric(.data$eFG.Pct)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$eFG.Pct))) - 3),
TS.Pct = substr(sprintf("%.*f", 4, as.numeric(.data$TS.Pct)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$TS.Pct))) - 3),
OR.Pct = substr(sprintf("%.*f", 4, as.numeric(.data$OR.Pct)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$OR.Pct))) - 3),
DR.Pct = substr(sprintf("%.*f", 4, as.numeric(.data$ARate)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$DR.Pct))) - 3),
ARate = substr(sprintf("%.*f", 4, as.numeric(.data$ARate)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$ARate))) - 3),
TORate = substr(sprintf("%.*f", 4, as.numeric(.data$TORate)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$TORate))) - 3),
Blk.Pct = substr(sprintf("%.*f", 4, as.numeric(.data$Blk.Pct)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$Blk.Pct))) - 3),
Stl.Pct = substr(sprintf("%.*f", 4, as.numeric(.data$Stl.Pct)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$Stl.Pct))) - 3),
FCper40 = substr(sprintf("%.*f",4, as.numeric(.data$FCper40)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$FCper40))) - 3),
FDper40 = substr(sprintf("%.*f", 4, as.numeric(.data$FDper40)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$FDper40))) - 3),
FTRate = substr(sprintf("%.*f", 4, as.numeric(.data$FTRate)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$FTRate))) - 3),
FT.Pct = substr(sprintf("%.*f", 6, as.numeric(.data$FT.Pct)), 1,
nchar(sprintf("%.*f", 6, as.numeric(.data$FT.Pct))) - 3),
FG_2.Pct = substr(sprintf("%.*f", 6, as.numeric(.data$FG_2.Pct)), 1,
nchar(sprintf("%.*f", 6, as.numeric(.data$FG_2.Pct))) - 3),
FG_3.Pct = substr(sprintf("%.*f", 6, as.numeric(.data$FG_3.Pct)), 1,
nchar(sprintf("%.*f", 6, as.numeric(.data$FG_3.Pct))) - 3))
suppressWarnings(
players <- players %>%
tidyr::separate("FTM-A", into = c("FTM", "FTA"), sep = "-") %>%
tidyr::separate("FGM_2-A", into = c("FGM_2", "FGA_2"), sep = "-") %>%
tidyr::separate("FGM_3-A", into = c("FGM_3", "FGA_3"), sep = "-") %>%
dplyr::mutate_at(c("Number", "Wt", "G",
"Min.Pct", "ORtg", "Poss.Pct","Shots.Pct",
"eFG.Pct", "TS.Pct", "OR.Pct", "DR.Pct",
"ARate", "TORate", "Blk.Pct","Stl.Pct","FCper40","FDper40",
"FTRate", "FTM", "FTA", "FT.Pct",
"FGM_2", "FGA_2", "FG_2.Pct", "FGM_3", "FGA_3", "FG_3.Pct",
"Min.Pct.Rk", "ORtg.Rk", "Poss.Pct.Rk", "Shots.Pct.Rk",
"eFG.Pct.Rk", "TS.Pct.Rk", "OR.Pct.Rk", "DR.Pct.Rk",
"ARate.Rk", "TORate.Rk", "Blk.Pct.Rk","Stl.Pct.Rk", "FCper40.Rk", "FDper40.Rk",
"FTRate.Rk", "FT.Pct.Rk", "FG_2.Pct.Rk", "FG_3.Pct.Rk"), as.numeric)
)
players <- players %>%
dplyr::mutate(Team = team,
Year = year,
Role = dplyr::case_when(.data$Min.Pct < 10.0 ~ "Benchwarmer",
.data$Poss.Pct < 12.0 ~ "Nearly Invisible",
.data$Poss.Pct >= 12.0 & .data$Poss.Pct < 16.0 ~ "Limited Role",
.data$Poss.Pct >= 16.0 & .data$Poss.Pct < 20.0 ~ "Role Player",
.data$Poss.Pct >= 20.0 & .data$Poss.Pct < 24.0 ~ "Significant Contributor",
.data$Poss.Pct >= 24.0 & .data$Poss.Pct < 28.0 ~ "Major Contributor",
.data$Poss.Pct >= 28.0 ~ "Go-to Guys")) %>%
dplyr::select("Role", tidyr::everything()) %>%
dplyr::bind_cols(lapply(pid, as.numeric)) %>%
janitor::clean_names()
y <- c(y, list(players))
}
### Store Data
kenpom <- y
names(kenpom) <- c("all_games", "conference_games")
},
error = function(e){
message(glue::glue("{Sys.time()} - {team} - {year} team player stats are missing"))
},
warning = function(w){
},
finally = {
}
)
return(kenpom)
}
#' **Get Depth Chart Last 5 Games from Team Page**
#'
#'
#' @param team Team filter to select.
#' @param year Year of data to pull
#' @return A data frame with the following columns:
#'
#' |col_name |types |
#' |:--------------------|:---------|
#' |pg_number |numeric |
#' |pg_player_first_name |character |
#' |pg_player_last_name |character |
#' |pg_hgt |character |
#' |pg_wgt |numeric |
#' |pg_yr |character |
#' |pg_min_pct |numeric |
#' |sg_number |numeric |
#' |sg_player_first_name |character |
#' |sg_player_last_name |character |
#' |sg_hgt |character |
#' |sg_wgt |numeric |
#' |sg_yr |character |
#' |sg_min_pct |numeric |
#' |sf_number |numeric |
#' |sf_player_first_name |character |
#' |sf_player_last_name |character |
#' |sf_hgt |character |
#' |sf_wgt |numeric |
#' |sf_yr |character |
#' |sf_min_pct |numeric |
#' |pf_number |numeric |
#' |pf_player_first_name |character |
#' |pf_player_last_name |character |
#' |pf_hgt |character |
#' |pf_wgt |numeric |
#' |pf_yr |character |
#' |pf_min_pct |numeric |
#' |c_number |numeric |
#' |c_player_first_name |character |
#' |c_player_last_name |character |
#' |c_hgt |character |
#' |c_wgt |numeric |
#' |c_yr |character |
#' |c_min_pct |numeric |
#' |team |character |
#' |year |numeric |
#'
#' @importFrom cli cli_abort
#' @importFrom dplyr select mutate filter bind_cols bind_rows
#' @importFrom stringr str_extract str_remove str_replace str_detect str_trim
#' @importFrom tidyr separate
#' @importFrom glue glue
#' @import rvest
#' @export
#' @keywords Depth Chart
#' @family KenPom Team Functions
#'
#' @examples
#' \donttest{
#' try(kp_team_depth_chart(team = 'Florida St.', year= 2021))
#' }
#'
#'
kp_team_depth_chart <- function(team, year= 2021){
tryCatch(
expr = {
if (!has_kp_user_and_pw()) stop("This function requires a KenPom subscription e-mail and password combination,\n set as the system environment variables KP_USER and KP_PW.", "\n See ?kp_user_pw for details.", call. = FALSE)
browser <- login()
if (!(is.numeric(year) && nchar(year) == 4 && year >= 2014)) {
# Check if year is numeric, if not NULL
cli::cli_abort("Enter valid year as a number (YYYY), data only goes back to 2014")
}
if (!(team %in% hoopR::teams_links$Team)) {
cli::cli_abort("Incorrect team name as compared to the website, see hoopR::teams_links for team name parameter specifications.")
}
teams_links <- hoopR::teams_links[hoopR::teams_links$Year == year,]
team_name = teams_links$team.link.ref[teams_links$Team == team]
### Pull Data
url <- paste0("https://kenpom.com/team.php?",
"team=",team_name,
"&y=", year)
page <- rvest::session_jump_to(browser, url)
Sys.sleep(5)
depth1_header_cols <- c("PG", "PG.Min.Pct", "SG", "SG.Min.Pct", "SF", "SF.Min.Pct",
"PF", "PF.Min.Pct", "C", "C.Min.Pct")
depth1 <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#dc-table'))[[1]] %>%
rvest::html_table() %>%
as.data.frame()
colnames(depth1) <- depth1_header_cols
suppressWarnings(
depth1 <- depth1 %>%
dplyr::filter(.data$PG != "PG")
)
depth1 <- depth1 %>%
dplyr::mutate(
PG.Yr = substr(.data$PG, nchar(.data$PG) - 2, nchar(.data$PG)),
PG = substr(.data$PG, 1, nchar(.data$PG) - 3),
PG.Wgt = stringr::str_extract(.data$PG, '\\d{3}'),
PG = stringr::str_trim(stringr::str_remove(.data$PG, '\\d{3}')),
PG.Hgt = stringr::str_extract(.data$PG, '\\d{1}-\\d{0,2}'),
PG = stringr::str_remove(.data$PG, '\\d{1}-\\d{0,2}'),
SG.Yr = substr(.data$SG, nchar(.data$SG) - 2, nchar(.data$SG)),
SG = substr(.data$SG, 1, nchar(.data$SG) - 3),
SG.Wgt = stringr::str_extract(.data$SG, '\\d{3}'),
SG = stringr::str_trim(stringr::str_remove(.data$SG, '\\d{3}')),
SG.Hgt = stringr::str_extract(.data$SG, '\\d{1}-\\d{0,2}'),
SG = stringr::str_remove(.data$SG, '\\d{1}-\\d{0,2}'),
SF.Yr = substr(.data$SF, nchar(.data$SF) - 2, nchar(.data$SF)),
SF = substr(.data$SF, 1, nchar(.data$SF) - 3),
SF.Wgt = stringr::str_extract(.data$SF, '\\d{3}'),
SF = stringr::str_trim(stringr::str_remove(.data$SF, '\\d{3}')),
SF.Hgt = stringr::str_extract(.data$SF, '\\d{1}-\\d{0,2}'),
SF = stringr::str_remove(.data$SF, '\\d{1}-\\d{0,2}'),
PF.Yr = substr(.data$PF, nchar(.data$PF) - 2, nchar(.data$PF)),
PF = substr(.data$PF, 1, nchar(.data$PF) - 3),
PF.Wgt = stringr::str_extract(.data$PF,'\\d{3}'),
PF = stringr::str_trim(stringr::str_remove(.data$PF,'\\d{3}')),
PF.Hgt = stringr::str_extract(.data$PF, '\\d{1}-\\d{0,2}'),
PF = stringr::str_remove(.data$PF, '\\d{1}-\\d{0,2}'),
C.Yr = substr(.data$C, nchar(.data$C) - 2, nchar(.data$C)),
C = substr(.data$C, 1, nchar(.data$C) - 3),
C.Wgt = stringr::str_extract(.data$C, '\\d{3}'),
C = stringr::str_trim(stringr::str_remove(.data$C, '\\d{3}')),
C.Hgt = stringr::str_extract(.data$C, '\\d{1}-\\d{0,2}'),
C = stringr::str_remove(.data$C, '\\d{1}-\\d{0,2}')
)
suppressWarnings(
depth1 <- depth1 %>%
tidyr::separate("PG", into = c("PG.Number", "PG.PlayerFirstName", "PG.PlayerLastName"), sep = "[^\\w']") %>%
tidyr::separate("SG", into = c("SG.Number", "SG.PlayerFirstName", "SG.PlayerLastName"), sep = "[^\\w']") %>%
tidyr::separate("SF", into = c("SF.Number", "SF.PlayerFirstName", "SF.PlayerLastName"), sep = "[^\\w']") %>%
tidyr::separate("PF", into = c("PF.Number", "PF.PlayerFirstName", "PF.PlayerLastName"), sep = "[^\\w']") %>%
tidyr::separate("C", into = c("C.Number", "C.PlayerFirstName", "C.PlayerLastName"), sep = "[^\\w']")
)
suppressWarnings(
depth1 <- depth1 %>%
dplyr::mutate(
Team = team,
Year = year,
PG.Min.Pct = as.numeric(stringr::str_replace(.data$PG.Min.Pct, '%', ''))/100,
SG.Min.Pct = as.numeric(stringr::str_replace(.data$SG.Min.Pct, '%', ''))/100,
SF.Min.Pct = as.numeric(stringr::str_replace(.data$SF.Min.Pct, '%', ''))/100,
PF.Min.Pct = as.numeric(stringr::str_replace(.data$PF.Min.Pct, '%', ''))/100,
C.Min.Pct = as.numeric(stringr::str_replace(.data$C.Min.Pct, '%', ''))/100,
PG.Number = as.numeric(.data$PG.Number),
SG.Number = as.numeric(.data$SG.Number),
SF.Number = as.numeric(.data$SF.Number),
PF.Number = as.numeric(.data$PF.Number),
C.Number = as.numeric(.data$C.Number),
PG.Wgt = as.numeric(.data$PG.Wgt),
SG.Wgt = as.numeric(.data$SG.Wgt),
SF.Wgt = as.numeric(.data$SF.Wgt),
PF.Wgt = as.numeric(.data$PF.Wgt),
C.Wgt = as.numeric(.data$C.Wgt))
)
depth1 <- depth1 %>%
dplyr::select(
"PG.Number",
"PG.PlayerFirstName",
"PG.PlayerLastName",
"PG.Hgt",
"PG.Wgt",
"PG.Yr",
"PG.Min.Pct",
"SG.Number",
"SG.PlayerFirstName",
"SG.PlayerLastName",
"SG.Hgt",
"SG.Wgt",
"SG.Yr",
"SG.Min.Pct",
"SF.Number",
"SF.PlayerFirstName",
"SF.PlayerLastName",
"SF.Hgt",
"SF.Wgt",
"SF.Yr",
"SF.Min.Pct",
"PF.Number",
"PF.PlayerFirstName",
"PF.PlayerLastName",
"PF.Hgt",
"PF.Wgt",
"PF.Yr",
"PF.Min.Pct",
"C.Number",
"C.PlayerFirstName",
"C.PlayerLastName",
"C.Hgt",
"C.Wgt",
"C.Yr",
"C.Min.Pct",
"Team",
"Year")
### Store Data
kenpom <- depth1 %>%
janitor::clean_names()
},
error = function(e){
message(glue::glue("{Sys.time()} - {team} - {year} Team Depth Chart is missing"))
},
warning = function(w){
},
finally = {
}
)
return(kenpom)
}
#' **Get Lineups Last 5 Games from Team Page**
#'
#'
#' @param team Team filter to select.
#' @param year Year of data to pull
#' @return A data frame with the following columns:
#'
#' |col_name |types |
#' |:--------------------|:---------|
#' |year |numeric |
#' |team |character |
#' |min_pct |numeric |
#' |pg_number |numeric |
#' |pg_player_first_name |character |
#' |pg_player_last_name |character |
#' |pg_hgt |character |
#' |pg_wgt |numeric |
#' |pg_yr |character |
#' |sg_number |numeric |
#' |sg_player_first_name |character |
#' |sg_player_last_name |character |
#' |sg_hgt |character |
#' |sg_wgt |numeric |
#' |sg_yr |character |
#' |sf_number |numeric |
#' |sf_player_first_name |character |
#' |sf_player_last_name |character |
#' |sf_hgt |character |
#' |sf_wgt |numeric |
#' |sf_yr |character |
#' |pf_number |numeric |
#' |pf_player_first_name |character |
#' |pf_player_last_name |character |
#' |pf_hgt |character |
#' |pf_wgt |numeric |
#' |pf_yr |character |
#' |c_number |numeric |
#' |c_player_first_name |character |
#' |c_player_last_name |character |
#' |c_hgt |character |
#' |c_wgt |numeric |
#' |c_yr |character |
#'
#' @importFrom cli cli_abort
#' @importFrom dplyr select mutate filter
#' @importFrom glue glue
#' @importFrom stringr str_remove str_replace str_extract
#' @import rvest
#' @export
#' @keywords Depth Chart
#' @family KenPom Team Functions
#'
#' @examples
#' \donttest{
#' try(kp_team_lineups(team = 'Florida St.', year = 2021))
#' }
#'
kp_team_lineups <- function(team, year=2021){
tryCatch(
expr = {
if (!has_kp_user_and_pw()) stop("This function requires a KenPom subscription e-mail and password combination,\n set as the system environment variables KP_USER and KP_PW.", "\n See ?kp_user_pw for details.", call. = FALSE)
browser <- login()
if (!(is.numeric(year) && nchar(year) == 4 && year >= 2010)) {
# Check if year is numeric, if not NULL
cli::cli_abort("Enter valid year as a number (YYYY), data only goes back to 2010")
}
if (!(team %in% hoopR::teams_links$Team)) {
cli::cli_abort("Incorrect team name as compared to the website, see hoopR::teams_links for team name parameter specifications.")
}
teams_links <- hoopR::teams_links[hoopR::teams_links$Year == year,]
team_name = teams_links$team.link.ref[teams_links$Team == team]
### Pull Data
url <- paste0("https://kenpom.com/team.php?",
"team=",team_name,
"&y=", year)
page <- rvest::session_jump_to(browser, url)
Sys.sleep(5)
depth2_header_cols <- c("Rk","PG", "SG", "SF",
"PF", "C", "Min.Pct")
depth2 <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#dc-table2'))[[1]] %>%
rvest::html_table() %>%
as.data.frame()
colnames(depth2) <- depth2_header_cols
suppressWarnings(
depth2 <- depth2 %>%
dplyr::filter(!is.na(as.numeric(.data$Min.Pct)))
)
depth2 <- depth2 %>%
dplyr::mutate(
PG.Yr = substr(.data$PG, nchar(.data$PG) - 2, nchar(.data$PG)),
PG = substr(.data$PG, 1, nchar(.data$PG) - 3),
PG.Wgt = stringr::str_extract(.data$PG, '\\d{3}'),
PG = stringr::str_trim(stringr::str_remove(.data$PG, '\\d{3}')),
PG.Hgt = stringr::str_extract(.data$PG, '\\d{1}-\\d{0,2}'),
PG = stringr::str_remove(.data$PG, '\\d{1}-\\d{0,2}'),
SG.Yr = substr(.data$SG, nchar(.data$SG) - 2, nchar(.data$SG)),
SG = substr(.data$SG, 1, nchar(.data$SG) - 3),
SG.Wgt = stringr::str_extract(.data$SG, '\\d{3}'),
SG = stringr::str_trim(stringr::str_remove(.data$SG, '\\d{3}')),
SG.Hgt = stringr::str_extract(.data$SG, '\\d{1}-\\d{0,2}'),
SG = stringr::str_remove(.data$SG, '\\d{1}-\\d{0,2}'),
SF.Yr = substr(.data$SF, nchar(.data$SF) - 2, nchar(.data$SF)),
SF = substr(.data$SF, 1, nchar(.data$SF) - 3),
SF.Wgt = stringr::str_extract(.data$SF, '\\d{3}'),
SF = stringr::str_trim(stringr::str_remove(.data$SF, '\\d{3}')),
SF.Hgt = stringr::str_extract(.data$SF, '\\d{1}-\\d{0,2}'),
SF = stringr::str_remove(.data$SF, '\\d{1}-\\d{0,2}'),
PF.Yr = substr(.data$PF, nchar(.data$PF) - 2, nchar(.data$PF)),
PF = substr(.data$PF, 1, nchar(.data$PF) - 3),
PF.Wgt = stringr::str_extract(.data$PF, '\\d{3}'),
PF = stringr::str_trim(stringr::str_remove(.data$PF, '\\d{3}')),
PF.Hgt = stringr::str_extract(.data$PF, '\\d{1}-\\d{0,2}'),
PF = stringr::str_remove(.data$PF, '\\d{1}-\\d{0,2}'),
C.Yr = substr(.data$C, nchar(.data$C) - 2, nchar(.data$C)),
C = substr(.data$C, 1, nchar(.data$C) - 3),
C.Wgt = stringr::str_extract(.data$C, '\\d{3}'),
C = stringr::str_trim(stringr::str_remove(.data$C, '\\d{3}')),
C.Hgt = stringr::str_extract(.data$C, '\\d{1}-\\d{0,2}'),
C = stringr::str_remove(.data$C, '\\d{1}-\\d{0,2}')
)
suppressWarnings(
depth2 <- depth2 %>%
tidyr::separate("PG", into = c("PG.Number", "PG.PlayerFirstName", "PG.PlayerLastName"), sep = "[^\\w']") %>%
tidyr::separate("SG", into = c("SG.Number", "SG.PlayerFirstName", "SG.PlayerLastName"), sep = "[^\\w']") %>%
tidyr::separate("SF", into = c("SF.Number", "SF.PlayerFirstName", "SF.PlayerLastName"), sep = "[^\\w']") %>%
tidyr::separate("PF", into = c("PF.Number", "PF.PlayerFirstName", "PF.PlayerLastName"), sep = "[^\\w']") %>%
tidyr::separate("C", into = c("C.Number", "C.PlayerFirstName", "C.PlayerLastName"), sep = "[^\\w']")
)
suppressWarnings(
depth2 <- depth2 %>%
dplyr::mutate(
Min.Pct = as.numeric(stringr::str_replace(.data$Min.Pct, '%', ''))/100,
PG.Number = as.numeric(.data$PG.Number),
SG.Number = as.numeric(.data$SG.Number),
SF.Number = as.numeric(.data$SF.Number),
PF.Number = as.numeric(.data$PF.Number),
C.Number = as.numeric(.data$C.Number),
PG.Wgt = as.numeric(.data$PG.Wgt),
SG.Wgt = as.numeric(.data$SG.Wgt),
SF.Wgt = as.numeric(.data$SF.Wgt),
PF.Wgt = as.numeric(.data$PF.Wgt),
C.Wgt = as.numeric(.data$C.Wgt))
)
depth2 <- depth2 %>%
dplyr::mutate(Team = team,
Year = year) %>%
dplyr::select(
"Year",
"Team",
"Min.Pct",
"PG.Number",
"PG.PlayerFirstName",
"PG.PlayerLastName",
"PG.Hgt",
"PG.Wgt",
"PG.Yr",
"SG.Number",
"SG.PlayerFirstName",
"SG.PlayerLastName",
"SG.Hgt",
"SG.Wgt",
"SG.Yr",
"SF.Number",
"SF.PlayerFirstName",
"SF.PlayerLastName",
"SF.Hgt",
"SF.Wgt",
"SF.Yr",
"PF.Number",
"PF.PlayerFirstName",
"PF.PlayerLastName",
"PF.Hgt",
"PF.Wgt",
"PF.Yr",
"C.Number",
"C.PlayerFirstName",
"C.PlayerLastName",
"C.Hgt",
"C.Wgt",
"C.Yr")
### Store Data
depth2[nrow(depth2),"PG.PlayerFirstName"] <- "UNKNOWN"
depth2[nrow(depth2),"C.Number"] <- NA_real_
depth2[nrow(depth2),"C.Yr"] <- NA_real_
kenpom <- depth2 %>%
janitor::clean_names()
},
error = function(e){
message(glue::glue("{Sys.time()} - {team} - {year} Team Lineups are missing"))
},
warning = function(w){
},
finally = {
}
)
return(kenpom)
}
saiemgilani/kenpomR documentation built on Dec. 10, 2023, 3:34 a.m.
R Package Documentation
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Defines functions kp_team_lineups kp_team_depth_chart kp_team_player_stats kp_minutes_matrix kp_player_career kp_team_players kp_opptracker kp_gameplan kp_team_schedule
Documented in kp_gameplan kp_minutes_matrix kp_opptracker kp_player_career kp_team_depth_chart kp_team_lineups kp_team_players kp_team_player_stats kp_team_schedule
#' **Get team schedule results**
#'
#'
#' @param team Team filter to select.
#' @param year Year of data to pull
#'
#' @return Returns a tibble of team schedules
#'
#' |col_name |types |
#' |:-----------------|:---------|
#' |team_rk |numeric |
#' |team |character |
#' |opponent_rk |numeric |
#' |opponent |character |
#' |result |character |
#' |poss |numeric |
#' |ot |numeric |
#' |pre_wp |numeric |
#' |location |character |
#' |w |numeric |
#' |l |numeric |
#' |w_conference |numeric |
#' |l_conference |numeric |
#' |conference_game |logical |
#' |postseason |character |
#' |year |numeric |
#' |day_date |character |
#' |game_date |numeric |
#' |w_proj |numeric |
#' |l_proj |numeric |
#' |w_conference_proj |numeric |
#' |l_conference_proj |numeric |
#' |date |character |
#' |game_id |numeric |
#' |tiers_of_joy |character |
#'
#' @importFrom cli cli_abort
#' @importFrom dplyr filter mutate select
#' @importFrom stringr str_trim str_extract str_remove str_replace str_detect str_pad
#' @import rvest
#' @export
#' @keywords Team Schedule
#' @family KenPom Team Functions
#'
#' @examples
#' \donttest{
#' try(kp_team_schedule(team = 'Florida St.', year = 2022))
#' }
kp_team_schedule <- function(team, year = 2022){
tryCatch(
expr = {
if (!has_kp_user_and_pw()) stop("This function requires a KenPom subscription e-mail and password combination,\n set as the system environment variables KP_USER and KP_PW.", "\n See ?kp_user_pw for details.", call. = FALSE)
browser <- login()
if (!(is.numeric(year) && nchar(year) == 4 && year >= 2001)) {
# Check if year is numeric, if not NULL
cli::cli_abort("Enter valid year as a number (YYYY), data only goes back to 2001")
}
if (!(team %in% hoopR::teams_links$Team)) {
cli::cli_abort("Incorrect team name as compared to the website, see hoopR::teams_links for team name parameter specifications.")
}
teams_links <- hoopR::teams_links[hoopR::teams_links$Year == year,]
team_name = teams_links$team.link.ref[teams_links$Team == team]
### Pull Data
url <- paste0("https://kenpom.com/team.php?",
"team=",team_name,
"&y=", year)
page <- rvest::session_jump_to(browser, url)
Sys.sleep(5)
if (year >= 2011) {
sched_header_cols <- c("Day.Date","Team.Rk","Opponent.Rk","Opponent","Result",
"Poss","OT","Location","Record","Conference", "Postseason")
} else {
sched_header_cols <- c("Day.Date", "Opponent.Rk", "Opponent", "Result",
"Poss", "OT", "Location", "Record", "Conference", "Postseason")
}
sched <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table') %>%
rvest::html_table()) %>%
as.data.frame()
## Removing the tiers of joy column, will add back to data frame subsequently
# sched <- sched[,1:(length(sched)-1)]
#
# Note: As a result of the tiers of joy column being an image (.gif) instead of text,
# there is an extra unnamed column with no text. Antecedently, I was removing this column
# and the resulting code below is in efforts to extract the GameId from the box/pregame link
# and the fanmatch link date. Additionally, we add back a text-equivalent for tiers of joy.
# I realized that since this extra column exists and the label column for
# postseason events repeats across the entire data frame row, I could use that last repeat
# as a label for regular vs conference tourney/postseason tourney games.
# One small piece of good fortune in this otherwise mundane task.
colnames(sched) <- sched_header_cols
sched <- sched %>%
dplyr::mutate(Postseason = ifelse(.data$Postseason == "", NA_character_, .data$Postseason)) %>%
tidyr::fill("Postseason", .direction = c("down"))
suppressWarnings(
sched <- sched %>%
dplyr::mutate(
WL = stringr::str_replace(stringr::str_extract(.data$Result,'W|L'),",",""),
Score = stringr::str_replace(stringr::str_extract(.data$Result,'\\d{1,3}-\\d{1,3}'),",","")) %>%
tidyr::separate("Score", into = c("WinnerScore", "LoserScore"), sep = "-") %>%
dplyr::mutate(
TeamScore = dplyr::case_when(
.data$WL == "W" & .data$Record != "" ~ as.numeric(.data$WinnerScore),
.data$WL == "L" & .data$Record != "" ~ as.numeric(.data$LoserScore),
.data$WL == "" ~ NA_real_),
OpponentScore = dplyr::case_when(
.data$WL == "L" & .data$Record != "" ~ as.numeric(.data$WinnerScore),
.data$WL == "W" & .data$Record != "" ~ as.numeric(.data$LoserScore),
.data$WL == "" ~ NA_real_)) %>%
tidyr::separate("Record", into = c("W", "L"), sep = "-") %>%
dplyr::filter(.data$Location %in% c("Home", "Away", "Neutral",
"Semi-Home","Semi-Away")) %>%
dplyr::select(
-"WinnerScore",
-"LoserScore") %>%
dplyr::mutate_at(c("Opponent.Rk", "Poss","TeamScore","OpponentScore"), as.numeric)
)
suppressWarnings(
if (year >= 2011){
sched <- sched %>%
dplyr::mutate_at(c("Team.Rk"), as.numeric)
}
)
sched <- sched %>%
dplyr::mutate(
Team = team,
Year = year,
PreWP = ifelse(stringr::str_detect(.data$OT, '%'),
as.numeric(stringr::str_extract(.data$OT, '\\d+'))/100, NA_real_),
OT = dplyr::case_when(
.data$OT == " " ~ 0,
.data$OT == "OT" ~ 1,
stringr::str_detect(.data$OT, "OT") ~ as.numeric(stringr::str_extract(.data$OT,'\\d')),
TRUE ~ NA_real_),
ConferenceGame = ifelse(.data$Conference != "", TRUE, FALSE))
suppressWarnings(
sched <- sched %>%
tidyr::separate("Conference",
into = c("W.Conference","L.Conference"), sep = "-") %>%
dplyr::mutate(
W.Conference = ifelse((.data$W.Conference == "\u00d7") | (.data$W.Conference == ""), NA_real_, .data$W.Conference)
)
)
if (year >= 2011) {
sched <- sched %>%
dplyr::select(
"Team.Rk",
"Team",
"Opponent.Rk",
"Opponent",
"Result",
"Poss",
"OT",
"PreWP",
"Location",
"W",
"L",
"W.Conference",
"L.Conference",
"ConferenceGame",
"Postseason",
"Year",
"Day.Date")
} else {
sched <- sched %>%
dplyr::select(
"Team",
"Opponent.Rk",
"Opponent",
"Result",
"Poss",
"OT",
"PreWP",
"Location",
"W",
"L",
"W.Conference",
"L.Conference",
"ConferenceGame",
"Postseason",
"Year",
"Day.Date")
}
suppressWarnings(
sched <- sched %>%
dplyr::filter(!is.na(.data$Day.Date)) %>%
dplyr::mutate_at(c("Opponent.Rk","Poss","W", "L",
"W.Conference","L.Conference"), as.numeric)
)
sched <- sched %>%
dplyr::mutate(
Date.DD = stringr::str_pad(stringr::str_extract(.data$Day.Date, '\\d+'), 2, pad = "0"),
Date.MO = NA_character_,
Date.MO = dplyr::case_when(
stringr::str_detect(.data$Day.Date, regex("Oct",ignore_case = TRUE)) ~ "10",
stringr::str_detect(.data$Day.Date, regex("Nov",ignore_case = TRUE)) ~ "11",
stringr::str_detect(.data$Day.Date, regex("Dec",ignore_case = TRUE)) ~ "12",
stringr::str_detect(.data$Day.Date, regex("Jan",ignore_case = TRUE)) ~ stringr::str_pad(1, 2, pad = "0"),
stringr::str_detect(.data$Day.Date, regex("Feb",ignore_case = TRUE)) ~ stringr::str_pad(2, 2, pad = "0"),
stringr::str_detect(.data$Day.Date, regex("Mar",ignore_case = TRUE)) ~ stringr::str_pad(3, 2, pad = "0"),
stringr::str_detect(.data$Day.Date, regex("Apr",ignore_case = TRUE)) ~ stringr::str_pad(4, 2, pad = "0")),
Date.YR = dplyr::case_when(
stringr::str_detect(.data$Day.Date, regex("Oct",ignore_case = TRUE)) ~ glue::glue("{year-1}"),
stringr::str_detect(.data$Day.Date, regex("Nov",ignore_case = TRUE)) ~ glue::glue("{year-1}"),
stringr::str_detect(.data$Day.Date, regex("Dec",ignore_case = TRUE)) ~ glue::glue("{year-1}"),
stringr::str_detect(.data$Day.Date, regex("Jan",ignore_case = TRUE)) ~ glue::glue("{year}"),
stringr::str_detect(.data$Day.Date, regex("Feb",ignore_case = TRUE)) ~ glue::glue("{year}"),
stringr::str_detect(.data$Day.Date, regex("Mar",ignore_case = TRUE)) ~ glue::glue("{year}"),
stringr::str_detect(.data$Day.Date, regex("Apr",ignore_case = TRUE)) ~ glue::glue("{year}")),
GameDate = as.numeric(paste0(.data$Date.YR, .data$Date.MO, .data$Date.DD)),
W.Proj = round(cummax(ifelse(is.na(.data$W), 0, .data$W)) +
cumsum(ifelse(is.na(.data$PreWP), 0, .data$PreWP))),
L.Proj = round(cummax(ifelse(is.na(.data$L), 0, .data$L)) +
cumsum(ifelse(is.na(.data$PreWP), 0, 1 - .data$PreWP))),
W.ConferenceProj = round(cummax(ifelse(is.na(.data$W.Conference), 0, .data$W.Conference)) +
cumsum(ifelse(.data$ConferenceGame == TRUE & !is.na(.data$PreWP), .data$PreWP, 0))),
L.ConferenceProj = round(cummax(ifelse(is.na(.data$L.Conference), 0, .data$L.Conference)) +
cumsum(ifelse(.data$ConferenceGame == TRUE & !is.na(.data$PreWP), 1 - .data$PreWP, 0)))) %>%
dplyr::select(
-"Date.DD",
-"Date.MO",
-"Date.YR")
extractor <- function(x){
data.frame(
ifelse(
is.null(rvest::html_element(x, xpath = "a")),
NA_real_,
rvest::html_element(x, xpath = "a") %>%
rvest::html_attr("href")), stringsAsFactors = FALSE)
}
img_extractor <- function(x){
data.frame(
ifelse(
is.null(rvest::html_element(x, css = "a > img")),
NA_character_,
toupper(stringr::str_trim(
stringr::str_replace(
stringr::str_extract(rvest::html_element(x, css = "a > img") %>%
xml2::xml_attr("src"), "a.gif|b.gif"),
".gif","")))),
stringsAsFactors = FALSE)
}
if (year >= 2011) {
w_links <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table') %>%
rvest::html_elements("tr.w > td:not(.label):nth-child(1)")
l_links <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table') %>%
rvest::html_elements("tr.l > td:not(.label):nth-child(1)")
un_links <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table') %>%
rvest::html_elements("tr.un > td:not(.label):nth-child(1)")
fm_links <- c(w_links,l_links,un_links)
w_box <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = "#schedule-table") %>%
rvest::html_elements("tr.w > td:not(.label):nth-child(5)")
l_box <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = "#schedule-table") %>%
rvest::html_elements("tr.l > td:not(.label):nth-child(5)")
un_box <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = "#schedule-table") %>%
rvest::html_elements("tr.un > td:not(.label):nth-child(5)")
box_links <- c(w_box, l_box, un_box)
w_tier <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table') %>%
rvest::html_elements("tr.w > td:not(.label):nth-child(11)")
l_tier <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table') %>%
rvest::html_elements("tr.l > td:not(.label):nth-child(11)")
un_tier <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table') %>%
rvest::html_elements("tr.un > td:not(.label):nth-child(11)")
tiers <- c(w_tier, l_tier, un_tier)
} else {
w_links <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table') %>%
rvest::html_elements("tr.w > td:not(.label):nth-child(1)")
l_links <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table') %>%
rvest::html_elements("tr.l > td:not(.label):nth-child(1)")
un_links <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table') %>%
rvest::html_elements("tr.un > td:not(.label):nth-child(1)")
fm_links <- c(w_links,l_links, un_links)
w_box <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = "#schedule-table") %>%
rvest::html_elements("tr.w > td:not(.label):nth-child(4)")
l_box <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = "#schedule-table") %>%
rvest::html_elements("tr.l > td:not(.label):nth-child(4)")
un_box <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = "#schedule-table") %>%
rvest::html_elements("tr.un > td:not(.label):nth-child(4)")
box_links <- c(w_box, l_box, un_box)
w_tier <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table') %>%
rvest::html_elements("tr.w > td:not(.label):nth-child(10)")
l_tier <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table') %>%
rvest::html_elements("tr.l > td:not(.label):nth-child(10)")
un_tier <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table') %>%
rvest::html_elements("tr.un > td:not(.label):nth-child(10)")
tiers <- c(w_tier, l_tier, un_tier)
}
day = dplyr::bind_rows(lapply(fm_links,
function(x){
data.frame(rvest::html_text(x),
stringsAsFactors = FALSE)}))
colnames(day) <- "Day.Date"
fm_links <- dplyr::bind_rows(lapply(fm_links, extractor))
names(fm_links)[1] <- "fanmatch.link"
tiers <- dplyr::bind_rows(lapply(tiers, img_extractor))
names(tiers)[1] <- "TiersOfJoy"
box_links <- dplyr::bind_rows(lapply(box_links, extractor))
names(box_links)[1] <- "pregame.box"
sched_links <- dplyr::bind_cols(tiers, fm_links,box_links, day)
sched_links <- sched_links %>%
dplyr::mutate(
Date = stringr::str_remove(stringr::str_extract(.data$fanmatch.link, "=(.+)"), "="),
GameId = as.numeric(stringr::str_remove(stringr::str_remove(
stringi::stri_extract_first_regex(.data$pregame.box, "=(.+)"), "="), "&(.+)"))) %>%
dplyr::select(
"Date",
"GameId",
"TiersOfJoy",
"Day.Date")
### Add Date and GameId back back to data frame
sched <- dplyr::left_join(sched, sched_links, by = "Day.Date")
### Store Data
kenpom <- sched %>%
dplyr::arrange(.data$GameDate) %>%
dplyr::mutate(Postseason = ifelse(is.na(.data$Postseason), "Regular", .data$Postseason)) %>%
janitor::clean_names()
},
error = function(e){
message(glue::glue("{Sys.Date()} - No team schedule tables available for {team} - {year}"))
},
warning = function(w){
},
finally = {
}
)
return(kenpom)
}
#' **Get KenPom's team game plan page**
#'
#'
#' @param team Team filter to select.
#' @param year Year of data to pull
#' @return Returns a named list of tibbles: gameplan, correlations, position_distributions
#'
#' **gameplan**
#'
#'
#' |col_name |types |
#' |:--------------|:---------|
#' |date |Date |
#' |opponent_rk |numeric |
#' |opponent |character |
#' |result |character |
#' |location |character |
#' |pace |numeric |
#' |off_eff |numeric |
#' |off_eff_rk |numeric |
#' |off_e_fg_pct |numeric |
#' |off_to_pct |numeric |
#' |off_or_pct |numeric |
#' |off_ftr |numeric |
#' |off_fgm_2 |numeric |
#' |off_fga_2 |numeric |
#' |off_fg_2_pct |numeric |
#' |off_fgm_3 |numeric |
#' |off_fga_3 |numeric |
#' |off_fg_3_pct |numeric |
#' |off_fg_3a_pct |numeric |
#' |def_eff |numeric |
#' |def_eff_rk |numeric |
#' |def_e_fg_pct |numeric |
#' |def_to_pct |numeric |
#' |def_or_pct |numeric |
#' |def_ftr |numeric |
#' |def_fgm_2 |numeric |
#' |def_fga_2 |numeric |
#' |def_fg_2_pct |numeric |
#' |def_fgm_3 |numeric |
#' |def_fga_3 |numeric |
#' |def_fg_3_pct |numeric |
#' |def_fg_3a_pct |numeric |
#' |wl |character |
#' |team_score |numeric |
#' |opponent_score |numeric |
#' |day_date |character |
#' |game_date |numeric |
#'
#' **correlations**
#'
#'
#' |col_name |types |
#' |:--------------------|:---------|
#' |correlations_r_x_100 |character |
#' |pace |character |
#' |off_e_fg_pct |character |
#' |off_to_pct |character |
#' |off_or_pct |character |
#' |off_ftr |character |
#' |def_e_fg_pct |character |
#' |def_to_pct |character |
#' |def_or_pct |character |
#' |def_ftr |character |
#'
#' **position_distributions**
#'
#'
#' |col_name |types |
#' |:-------------|:---------|
#' |team |character |
#' |category |character |
#' |c_pct |numeric |
#' |pf_pct |numeric |
#' |sf_pct |numeric |
#' |sg_pct |numeric |
#' |pg_pct |numeric |
#' |c_pct_rk |numeric |
#' |pf_pct_rk |numeric |
#' |sf_pct_rk |numeric |
#' |sg_pct_rk |numeric |
#' |pg_pct_rk |numeric |
#' |c_pct_d1_avg |numeric |
#' |pf_pct_d1_avg |numeric |
#' |sf_pct_d1_avg |numeric |
#' |sg_pct_d1_avg |numeric |
#' |pg_pct_d1_avg |numeric |
#'
#' @importFrom cli cli_abort
#' @importFrom dplyr filter select rename mutate case_when mutate_at bind_rows
#' @importFrom tidyr separate everything
#' @importFrom stringr str_trim str_extract str_remove str_replace str_detect
#' @import rvest
#' @export
#' @keywords Game Plan
#' @family KenPom Team Functions
#' @examples
#' \donttest{
#' try(kp_gameplan(team='Florida St.', year=2021))
#' }
kp_gameplan <- function(team, year=2021){
tryCatch(
expr = {
if (!has_kp_user_and_pw()) stop("This function requires a KenPom subscription e-mail and password combination,\n set as the system environment variables KP_USER and KP_PW.", "\n See ?kp_user_pw for details.", call. = FALSE)
browser <- login()
if (!(is.numeric(year) && nchar(year) == 4 && year >= 2001)) {
# Check if year is numeric, if not NULL
cli::cli_abort("Enter valid year as a number (YYYY), data only goes back to 2001")
}
if (!(team %in% hoopR::teams_links$Team)) {
cli::cli_abort("Incorrect team name as compared to the website, see hoopR::teams_links for team name parameter specifications.")
}
teams_links <- hoopR::teams_links[hoopR::teams_links$Year == year,]
team_name = teams_links$team.link.ref[teams_links$Team == team]
### Pull Data
url <- paste0("https://kenpom.com/gameplan.php?",
"team=", team_name,
"&y=", year)
page <- rvest::session_jump_to(browser, url)
Sys.sleep(5)
header_cols <- c("Date","Opponent.Rk", "Opponent","Result","Location","Pace",
"Off.Eff", "Off.Eff.Rk", "Off.eFG.Pct", "Off.TO.Pct", "Off.OR.Pct", "Off.FTR",
"Off.FGM_2-A", "Off.FG_2.Pct", "Off.FGM_3-A", "Off.FG_3.Pct", "Off.FG_3A.Pct",
"Def.Eff", "Def.Eff.Rk", "Def.eFG.Pct", "Def.TO.Pct", "Def.OR.Pct", "Def.FTR",
"Def.FGM_2-A", "Def.FG_2.Pct", "Def.FGM_3-A", "Def.FG_3.Pct", "Def.FG_3A.Pct")
gp <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table'))[[1]] %>%
rvest::html_table() %>%
as.data.frame()
colnames(gp) <- header_cols
gp <- gp %>%
dplyr::filter(.data$Location != "")
suppressWarnings(
gp <- gp %>%
dplyr::mutate(
WL = stringr::str_replace(stringr::str_extract(.data$Result,'W|L'),",",""),
Score = stringr::str_replace(stringr::str_extract(.data$Result,'\\d{1,3}-\\d{1,3}'),",","")) %>%
tidyr::separate("Score", into = c("WinnerScore", "LoserScore"), sep = "-") %>%
dplyr::mutate(
TeamScore = dplyr::case_when(
.data$WL == "W" ~ as.numeric(.data$WinnerScore),
.data$WL == "L" ~ as.numeric(.data$LoserScore),
.data$WL == "" ~ NA_real_),
OpponentScore = dplyr::case_when(
.data$WL == "L" ~ as.numeric(.data$WinnerScore),
.data$WL == "W" ~ as.numeric(.data$LoserScore),
.data$WL == "" ~ NA_real_),
Date.DD = stringr::str_pad(stringr::str_extract(.data$Date,'\\d+'), 2, pad = "0"),
Date.MO = NA_character_,
Date.MO = dplyr::case_when(
stringr::str_detect(.data$Date, regex("Oct", ignore_case = TRUE)) ~ "10",
stringr::str_detect(.data$Date, regex("Nov", ignore_case = TRUE)) ~ "11",
stringr::str_detect(.data$Date, regex("Dec", ignore_case = TRUE)) ~ "12",
stringr::str_detect(.data$Date, regex("Jan", ignore_case = TRUE)) ~ stringr::str_pad(1, 2, pad="0"),
stringr::str_detect(.data$Date, regex("Feb", ignore_case = TRUE)) ~ stringr::str_pad(2, 2, pad="0"),
stringr::str_detect(.data$Date, regex("Mar", ignore_case = TRUE)) ~ stringr::str_pad(3, 2, pad="0"),
stringr::str_detect(.data$Date, regex("Apr", ignore_case = TRUE)) ~ stringr::str_pad(4, 2, pad="0")
),
Date.YR = dplyr::case_when(
stringr::str_detect(.data$Date, regex("Oct", ignore_case = TRUE)) ~ glue::glue("{year-1}"),
stringr::str_detect(.data$Date, regex("Nov", ignore_case = TRUE)) ~ glue::glue("{year-1}"),
stringr::str_detect(.data$Date, regex("Dec", ignore_case = TRUE)) ~ glue::glue("{year-1}"),
stringr::str_detect(.data$Date, regex("Jan", ignore_case = TRUE)) ~ glue::glue("{year}"),
stringr::str_detect(.data$Date, regex("Feb", ignore_case = TRUE)) ~ glue::glue("{year}"),
stringr::str_detect(.data$Date, regex("Mar", ignore_case = TRUE)) ~ glue::glue("{year}"),
stringr::str_detect(.data$Date, regex("Apr", ignore_case = TRUE)) ~ glue::glue("{year}")
),
Day.Date = .data$Date,
Date = as.Date(glue::glue("{.data$Date.YR}-{.data$Date.MO}-{.data$Date.DD}")),
GameDate = as.numeric(paste0(.data$Date.YR, .data$Date.MO, .data$Date.DD))) %>%
dplyr::select(
-"Date.DD",
-"Date.MO",
-"Date.YR")
)
cor <- gp[(nrow(gp) - 2):nrow(gp),]
cor <- cor %>%
dplyr::select(
"Location",
"Pace",
"Off.eFG.Pct",
"Off.TO.Pct",
"Off.OR.Pct",
"Off.FTR",
"Def.eFG.Pct",
"Def.TO.Pct",
"Def.OR.Pct",
"Def.FTR") %>%
dplyr::rename("Correlations (R x 100)" = "Location")
cor <- cor[2:3,] %>%
janitor::clean_names()
suppressWarnings(
gp <- gp %>%
dplyr::filter(!is.na(as.numeric(.data$Off.Eff))) %>%
tidyr::separate("Off.FGM_2-A", into = c("Off.FGM_2","Off.FGA_2")) %>%
tidyr::separate("Off.FGM_3-A", into = c("Off.FGM_3","Off.FGA_3")) %>%
tidyr::separate("Def.FGM_2-A", into = c("Def.FGM_2","Def.FGA_2")) %>%
tidyr::separate("Def.FGM_3-A", into = c("Def.FGM_3","Def.FGA_3")) %>%
dplyr::mutate_at(c("Opponent.Rk", "Pace", "Off.Eff", "Off.Eff.Rk",
"Off.eFG.Pct", "Off.TO.Pct", "Off.OR.Pct", "Off.FTR",
"Off.FGM_2", "Off.FGA_2", "Off.FG_2.Pct",
"Off.FGM_3", "Off.FGA_3","Off.FG_3.Pct", "Off.FG_3A.Pct",
"Def.Eff", "Def.Eff.Rk", "Def.eFG.Pct", "Def.TO.Pct",
"Def.OR.Pct", "Def.FTR", "Def.FGM_2", "Def.FGA_2",
"Def.FG_2.Pct", "Def.FGM_3", "Def.FGA_3",
"Def.FG_3.Pct", "Def.FG_3A.Pct", "TeamScore","OpponentScore"), as.numeric)
)
### Store Data
gp <- gp %>%
dplyr::select(
-"WinnerScore",
-"LoserScore") %>%
janitor::clean_names()
z <- data.frame()
y <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '.dist-table')
if (length(y) > 0) {
for (i in 1:length(y)) {
header_cols <- c("Team","C.Pct","PF.Pct","SF.Pct","SG.Pct","PG.Pct")
d <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = '.dist-table'))[[i]] %>%
rvest::html_table() %>%
as.data.frame()
category <- colnames(d)[1]
colnames(d) <- header_cols
d$Category <- category
d$C.Pct.Rk <- NA_real_
d$PF.Pct.Rk <- NA_real_
d$SF.Pct.Rk <- NA_real_
d$SG.Pct.Rk <- NA_real_
d$PG.Pct.Rk <- NA_real_
suppressWarnings(
d <- d %>%
dplyr::mutate(
C.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$C.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
PF.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$PF.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
SF.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$SF.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
SG.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$SG.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
PG.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$PG.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
C.Pct = as.numeric(substr(sprintf("%.*f", 4, as.numeric(.data$C.Pct)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$C.Pct))) - 3)),
PF.Pct = as.numeric(substr(sprintf("%.*f", 4, as.numeric(.data$PF.Pct)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$PF.Pct))) - 3)),
SF.Pct = as.numeric(substr(sprintf("%.*f", 4, as.numeric(.data$SF.Pct)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$SF.Pct))) - 3)),
SG.Pct = as.numeric(substr(sprintf("%.*f", 4, as.numeric(.data$SG.Pct)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$SG.Pct))) - 3)),
PG.Pct = as.numeric(substr(sprintf("%.*f", 4, as.numeric(.data$PG.Pct)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$PG.Pct))) - 3)))
)
d$C.Pct.D1.Avg = as.numeric(d[3, "C.Pct"])
d$PF.Pct.D1.Avg = as.numeric(d[3, "PF.Pct"])
d$SF.Pct.D1.Avg = as.numeric(d[3, "SF.Pct"])
d$SG.Pct.D1.Avg = as.numeric(d[3, "SG.Pct"])
d$PG.Pct.D1.Avg = as.numeric(d[3, "PG.Pct"])
d <- d %>%
dplyr::filter(!is.na(.data$C.Pct.Rk)) %>%
dplyr::select(
"Team",
"Category",
tidyr::everything())
z <- dplyr::bind_rows(z, d)
}
}
z <- z %>%
janitor::clean_names()
kenpom <- c(list(gp),list(cor),list(z))
names(kenpom) <- c("gameplan", "correlations", "position_distributions")
},
error = function(e){
message(glue::glue("{Sys.Date()} - No Game Plan Points distribution tables available for {team} - {year}"))
},
warning = function(w){
},
finally = {
}
)
return(kenpom)
}
#' **Get KenPom's team opponent tracker page**
#'
#'
#' @param team Team filter to select.
#' @param year Year of data to pull
#' @return Returns a tibble of team opponent tracker data
#'
#' |col_name |types |
#' |:----------------|:---------|
#' |date |Date |
#' |game_date |numeric |
#' |day_date |character |
#' |wl |character |
#' |team |character |
#' |team_score |numeric |
#' |opponent |character |
#' |opponent_score |numeric |
#' |result |character |
#' |adj_oe |numeric |
#' |adj_oe_rk |integer |
#' |off_e_fg_pct |numeric |
#' |off_e_fg_pct_rk |integer |
#' |off_to_pct |numeric |
#' |off_to_pct_rk |integer |
#' |off_or_pct |numeric |
#' |off_or_pct_rk |integer |
#' |off_ft_rate |numeric |
#' |off_ft_rate_rk |integer |
#' |off_fg_2_pct |numeric |
#' |off_fg_2_pct_rk |integer |
#' |off_fg_3_pct |numeric |
#' |off_fg_3_pct_rk |integer |
#' |off_blk_pct |numeric |
#' |off_blk_pct_rk |integer |
#' |off_fg_3a_pct |numeric |
#' |off_fg_3a_pct_rk |integer |
#' |off_apl |numeric |
#' |off_apl_rk |integer |
#' |adj_de |numeric |
#' |adj_de_rk |integer |
#' |def_e_fg_pct |numeric |
#' |def_e_fg_pct_rk |integer |
#' |def_to_pct |numeric |
#' |def_to_pct_rk |integer |
#' |def_or_pct |numeric |
#' |def_or_pct_rk |integer |
#' |def_ft_rate |numeric |
#' |def_ft_rate_rk |integer |
#' |def_fg_2_pct |numeric |
#' |def_fg_2_pct_rk |integer |
#' |def_fg_3_pct |numeric |
#' |def_fg_3_pct_rk |integer |
#' |def_blk_pct |numeric |
#' |def_blk_pct_rk |integer |
#' |def_fg_3a_pct |numeric |
#' |def_fg_3a_pct_rk |integer |
#' |def_apl |numeric |
#' |def_apl_rk |integer |
#'
#' @importFrom cli cli_abort
#' @importFrom dplyr filter
#' @import rvest
#' @export
#' @keywords Opponent Tracker
#' @family KenPom Team Functions
#'
#' @examples
#' \donttest{
#' try(kp_opptracker(team = 'Florida St.', year = 2021))
#' }
kp_opptracker <- function(team, year = 2021){
tryCatch(
expr = {
if (!has_kp_user_and_pw()) stop("This function requires a KenPom subscription e-mail and password combination,\n set as the system environment variables KP_USER and KP_PW.", "\n See ?kp_user_pw for details.", call. = FALSE)
browser <- login()
if (!(is.numeric(year) && nchar(year) == 4 && year >= 2001)) {
# Check if year is numeric, if not NULL
cli::cli_abort("Enter valid year as a number (YYYY), data only goes back to 2001")
}
if (!(team %in% hoopR::teams_links$Team)) {
cli::cli_abort("Incorrect team name as compared to the website, see hoopR::teams_links for team name parameter specifications.")
}
teams_links <- hoopR::teams_links[hoopR::teams_links$Year == year,]
team_name = teams_links$team.link.ref[teams_links$Team == team]
### Pull Data
url <- paste0("https://kenpom.com/opptracker.php?",
"team=", team_name,
"&y=", year,
"&t=o")
page_o <- rvest::session_jump_to(browser, url)
Sys.sleep(5)
header_cols <- c("Date","Opponent","Result","AdjOE","AdjOE.Rk",
"Off.eFG.Pct","Off.eFG.Pct.Rk","Off.TO.Pct","Off.TO.Pct.Rk",
"Off.OR.Pct","Off.OR.Pct.Rk","Off.FTRate","Off.FTRate.Rk",
"Off.FG_2.Pct","Off.FG_2.Pct.Rk","Off.FG_3.Pct","Off.FG_3.Pct.Rk",
"Off.Blk.Pct","Off.Blk.Pct.Rk","Off.FG_3A.Pct","Off.FG_3A.Pct.Rk")
if (year >= 2010) {
header_cols <- c(header_cols, "Off.APL","Off.APL.Rk")
}
opptracker_o <- (page_o %>%
xml2::read_html() %>%
rvest::html_elements(css = '#conf-table'))[[1]] %>%
rvest::html_table() %>%
as.data.frame()
colnames(opptracker_o) <- header_cols
suppressWarnings(
opptracker_o <- opptracker_o %>%
dplyr::filter(!is.na(as.numeric(.data$Off.eFG.Pct)))
)
suppressWarnings(
opptracker_o <- opptracker_o %>%
dplyr::mutate(
Team = team,
WL = stringr::str_replace(stringr::str_extract(.data$Result,'W|L'),",",""),
Score = stringr::str_replace(stringr::str_extract(.data$Result,'\\d{1,3}-\\d{1,3}'),",","")) %>%
tidyr::separate("Score", into = c("WinnerScore", "LoserScore"), sep = "-") %>%
dplyr::mutate(
TeamScore = dplyr::case_when(
.data$WL == "W" ~ as.numeric(.data$WinnerScore),
.data$WL == "L" ~ as.numeric(.data$LoserScore),
.data$WL == "" ~ NA_real_),
OpponentScore = dplyr::case_when(
.data$WL == "L" ~ as.numeric(.data$WinnerScore),
.data$WL == "W" ~ as.numeric(.data$LoserScore),
.data$WL == "" ~ NA_real_),
Date.DD = stringr::str_pad(stringr::str_extract(.data$Date,'\\d+'), 2, pad = "0"),
Date.MO = NA_character_,
Date.MO = dplyr::case_when(
stringr::str_detect(.data$Date, regex("Oct", ignore_case = TRUE)) ~ "10",
stringr::str_detect(.data$Date, regex("Nov", ignore_case = TRUE)) ~ "11",
stringr::str_detect(.data$Date, regex("Dec", ignore_case = TRUE)) ~ "12",
stringr::str_detect(.data$Date, regex("Jan", ignore_case = TRUE)) ~ stringr::str_pad(1, 2, pad="0"),
stringr::str_detect(.data$Date, regex("Feb", ignore_case = TRUE)) ~ stringr::str_pad(2, 2, pad="0"),
stringr::str_detect(.data$Date, regex("Mar", ignore_case = TRUE)) ~ stringr::str_pad(3, 2, pad="0"),
stringr::str_detect(.data$Date, regex("Apr", ignore_case = TRUE)) ~ stringr::str_pad(4, 2, pad="0")
),
Date.YR = dplyr::case_when(
stringr::str_detect(.data$Date, regex("Oct",ignore_case = TRUE)) ~ glue::glue("{year-1}"),
stringr::str_detect(.data$Date, regex("Nov",ignore_case = TRUE)) ~ glue::glue("{year-1}"),
stringr::str_detect(.data$Date, regex("Dec",ignore_case = TRUE)) ~ glue::glue("{year-1}"),
stringr::str_detect(.data$Date, regex("Jan",ignore_case = TRUE)) ~ glue::glue("{year}"),
stringr::str_detect(.data$Date, regex("Feb",ignore_case = TRUE)) ~ glue::glue("{year}"),
stringr::str_detect(.data$Date, regex("Mar",ignore_case = TRUE)) ~ glue::glue("{year}"),
stringr::str_detect(.data$Date, regex("Apr",ignore_case = TRUE)) ~ glue::glue("{year}")
),
Day.Date = .data$Date,
Date = as.Date(glue::glue("{.data$Date.YR}-{.data$Date.MO}-{.data$Date.DD}")),
GameDate = as.numeric(paste0(.data$Date.YR, .data$Date.MO, .data$Date.DD))) %>%
dplyr::select(
-"Date.DD",
-"Date.MO",
-"Date.YR",
-"WinnerScore",
-"LoserScore")
)
header_cols <- c("Date","Opponent","Result","AdjDE","AdjDE.Rk",
"Def.eFG.Pct","Def.eFG.Pct.Rk","Def.TO.Pct","Def.TO.Pct.Rk",
"Def.OR.Pct","Def.OR.Pct.Rk","Def.FTRate","Def.FTRate.Rk",
"Def.FG_2.Pct","Def.FG_2.Pct.Rk","Def.FG_3.Pct","Def.FG_3.Pct.Rk",
"Def.Blk.Pct","Def.Blk.Pct.Rk","Def.FG_3A.Pct","Def.FG_3A.Pct.Rk")
if (year >= 2010) {
header_cols <- c(header_cols, "Def.APL","Def.APL.Rk")
}
### Pull Data
url <- paste0("https://kenpom.com/opptracker.php?",
"team=", team_name,
"&y=", year,
"&t=d")
page_d <- rvest::session_jump_to(browser, url)
Sys.sleep(5)
opptracker_d <- (page_d %>%
xml2::read_html() %>%
rvest::html_elements(css = '#conf-table'))[[1]] %>%
rvest::html_table() %>%
as.data.frame()
colnames(opptracker_d) <- header_cols
suppressWarnings(
opptracker_d <- opptracker_d %>%
dplyr::filter(!is.na(as.numeric(.data$Def.eFG.Pct)))
)
opptracker <- dplyr::bind_cols(opptracker_o, opptracker_d[,4:ncol(opptracker_d)])
### Store Data
kenpom <- opptracker %>%
dplyr::select(
"Date",
"GameDate",
"Day.Date",
"WL",
"Team",
"TeamScore",
"Opponent",
"OpponentScore",
tidyr::everything()) %>%
janitor::clean_names()
},
error = function(e){
message(glue::glue("{Sys.time()} - {team} - {year} Team opponent tracker data is missing"))
},
warning = function(w){
},
finally = {
}
)
return(kenpom)
}
#' **Get KenPom's player stats from the team page**
#'
#'
#' @param team Team filter to select.
#' @param year Year of data to pull
#' @return Returns a tibble of team player data
#'
#' |col_name |types |
#' |:-------------|:---------|
#' |role |character |
#' |number |numeric |
#' |player |character |
#' |ht |character |
#' |wt |numeric |
#' |yr |character |
#' |g |numeric |
#' |s |numeric |
#' |min_pct |numeric |
#' |o_rtg |numeric |
#' |poss_pct |numeric |
#' |shots_pct |numeric |
#' |e_fg_pct |numeric |
#' |ts_pct |numeric |
#' |or_pct |numeric |
#' |dr_pct |numeric |
#' |a_rate |numeric |
#' |to_rate |numeric |
#' |blk_pct |numeric |
#' |stl_pct |numeric |
#' |f_cper40 |numeric |
#' |f_dper40 |numeric |
#' |ft_rate |numeric |
#' |ftm |numeric |
#' |fta |numeric |
#' |ft_pct |numeric |
#' |fgm_2 |numeric |
#' |fga_2 |numeric |
#' |fg_2_pct |numeric |
#' |fgm_3 |numeric |
#' |fga_3 |numeric |
#' |fg_3_pct |numeric |
#' |min_pct_rk |numeric |
#' |o_rtg_rk |numeric |
#' |poss_pct_rk |numeric |
#' |shots_pct_rk |numeric |
#' |e_fg_pct_rk |numeric |
#' |ts_pct_rk |numeric |
#' |or_pct_rk |numeric |
#' |dr_pct_rk |numeric |
#' |a_rate_rk |numeric |
#' |to_rate_rk |numeric |
#' |blk_pct_rk |numeric |
#' |stl_pct_rk |numeric |
#' |f_cper40_rk |numeric |
#' |f_dper40_rk |numeric |
#' |ft_rate_rk |numeric |
#' |ft_pct_rk |numeric |
#' |fg_2_pct_rk |numeric |
#' |fg_3_pct_rk |numeric |
#' |national_rank |character |
#' |team |character |
#' |year |numeric |
#' |player_id |numeric |
#'
#' @importFrom cli cli_abort
#' @importFrom dplyr select mutate filter case_when mutate_at bind_cols bind_rows
#' @importFrom stringr str_extract str_remove str_replace str_detect
#' @importFrom tidyr everything separate
#' @import rvest
#' @export
#' @keywords Team Player Stats
#' @family KenPom Team Functions
#'
#' @examples
#' \donttest{
#' try(kp_team_players(team = 'Florida St.', year = 2024))
#' }
#'
kp_team_players <- function(team, year = 2021){
tryCatch(
expr = {
browser <- login()
if (!(is.numeric(year) && nchar(year) == 4 && year >= 2002)) {
# Check if year is numeric, if not NULL
cli::cli_abort("Enter valid year as a number (YYYY), data only goes back to 2002")
}
if (!(team %in% hoopR::teams_links$Team)) {
cli::cli_abort("Incorrect team name as compared to the website, see hoopR::teams_links for team name parameter specifications.")
}
teams_links <- hoopR::teams_links[hoopR::teams_links$Year == year,]
team_name = teams_links$team.link.ref[teams_links$Team == team]
### Pull Data
url <- paste0("https://kenpom.com/team.php?",
"team=",team_name,
"&y=", year)
page <- rvest::session_jump_to(browser, url)
Sys.sleep(5)
player_links <- page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#player-table') %>%
rvest::html_elements("td:nth-child(2) > a")
pid <- dplyr::bind_rows(lapply(xml2::xml_attrs(player_links),
function(x){
if (!stringr::str_detect(x,"kpoy")) {
data.frame(as.list(x), stringsAsFactors = FALSE)
}
}))
pid <- pid %>%
dplyr::mutate(PlayerId = stringr::str_remove(stringr::str_extract(.data$href,"=(.+)"),"=")) %>%
dplyr::select("PlayerId")
if (year >= 2014) { # "S" - starts only available from 2014 onwards
players_header_cols <- c("Number", "Player", "Ht", "Wt", "Yr", "G", "S",
"Min.Pct", "ORtg", "Poss.Pct","Shots.Pct",
"eFG.Pct", "TS.Pct", "OR.Pct", "DR.Pct",
"ARate", "TORate", "Blk.Pct","Stl.Pct","FCper40","FDper40",
"FTRate", "FTM-A", "FT.Pct",
"FGM_2-A", "FG_2.Pct", "FGM_3-A", "FG_3.Pct")
} else {
players_header_cols <- c("Number", "Player", "Ht", "Wt", "Yr", "G",
"Min.Pct", "ORtg", "Poss.Pct","Shots.Pct",
"eFG.Pct", "TS.Pct", "OR.Pct", "DR.Pct",
"ARate", "TORate", "Blk.Pct","Stl.Pct","FCper40","FDper40",
"FTRate", "FTM-A", "FT.Pct",
"FGM_2-A", "FG_2.Pct", "FGM_3-A", "FG_3.Pct")
}
players <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#player-table'))[[1]]
players <- players %>%
rvest::html_table()
colnames(players) <- players_header_cols
suppressWarnings(
players <- players %>%
dplyr::filter(!is.na(as.numeric(.data$G)))
)
players$Min.Pct.Rk <- NA_real_
players$ORtg.Rk <- NA_real_
players$Poss.Pct.Rk <- NA_real_
players$Shots.Pct.Rk <- NA_real_
players$eFG.Pct.Rk <- NA_real_
players$TS.Pct.Rk <- NA_real_
players$OR.Pct.Rk <- NA_real_
players$DR.Pct.Rk <- NA_real_
players$ARate.Rk <- NA_real_
players$TORate.Rk <- NA_real_
players$Blk.Pct.Rk <- NA_real_
players$Stl.Pct.Rk <- NA_real_
players$FCper40.Rk <- NA_real_
players$FDper40.Rk <- NA_real_
players$FTRate.Rk <- NA_real_
players$FT.Pct.Rk <- NA_real_
players$FG_2.Pct.Rk <- NA_real_
players$FG_3.Pct.Rk <- NA_real_
players <- players %>%
dplyr::mutate(
Min.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$Min.Pct,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
ORtg.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$ORtg,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
Poss.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$Poss.Pct,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
Shots.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$Shots.Pct,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
eFG.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$eFG.Pct,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
TS.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$TS.Pct,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
OR.Pct.Rk = stringr::str_replace(stringr::str_extract(.data$OR.Pct,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',""),
DR.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$DR.Pct,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
ARate.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$ARate,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
TORate.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$TORate,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
Blk.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$Blk.Pct,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
Stl.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$Stl.Pct,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
FCper40.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$FCper40,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
FDper40.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$FDper40,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
FTRate.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$FTRate,'\\d{1,3}\\.\\d(.+)'),'(.+)\\.\\d',"")),
FT.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$FT.Pct,'\\.\\d{3}(.+)'),'\\.\\d{3}',"")),
FG_2.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$FG_2.Pct,'\\.\\d{3}(.+)'),'\\.\\d{3}',"")),
FG_3.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$FG_3.Pct,'\\.\\d{3}(.+)'),'\\.\\d{3}',"")),
NationalRank = stringr::str_extract(.data$Player, "National Rank"),
Player = stringr::str_replace(.data$Player, "National Rank",""),
Min.Pct = substr(sprintf("%.*f",4, as.numeric(.data$Min.Pct)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$Min.Pct))) - 3),
ORtg = substr(sprintf("%.*f",4, as.numeric(.data$ORtg)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$ORtg))) - 3),
Poss.Pct = substr(sprintf("%.*f",4, as.numeric(.data$Poss.Pct)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$Poss.Pct))) - 3),
Shots.Pct = substr(sprintf("%.*f",4, as.numeric(.data$Shots.Pct)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$Shots.Pct))) - 3),
eFG.Pct = substr(sprintf("%.*f",4, as.numeric(.data$eFG.Pct)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$eFG.Pct))) - 3),
TS.Pct = substr(sprintf("%.*f",4, as.numeric(.data$TS.Pct)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$TS.Pct))) - 3),
OR.Pct = substr(sprintf("%.*f",4, as.numeric(.data$OR.Pct)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$OR.Pct))) - 3),
DR.Pct = substr(sprintf("%.*f",4, as.numeric(.data$ARate)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$DR.Pct))) - 3),
ARate = substr(sprintf("%.*f",4, as.numeric(.data$ARate)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$ARate))) - 3),
TORate = substr(sprintf("%.*f",4, as.numeric(.data$TORate)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$TORate))) - 3),
Blk.Pct = substr(sprintf("%.*f",4, as.numeric(.data$Blk.Pct)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$Blk.Pct))) - 3),
Stl.Pct = substr(sprintf("%.*f",4, as.numeric(.data$Stl.Pct)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$Stl.Pct))) - 3),
FCper40 = substr(sprintf("%.*f",4, as.numeric(.data$FCper40)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$FCper40))) - 3),
FDper40 = substr(sprintf("%.*f",4, as.numeric(.data$FDper40)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$FDper40))) - 3),
FTRate = substr(sprintf("%.*f",4, as.numeric(.data$FTRate)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$FTRate))) - 3),
FT.Pct = substr(sprintf("%.*f",6, as.numeric(.data$FT.Pct)), 1,
nchar(sprintf("%.*f",6, as.numeric(.data$FT.Pct))) - 3),
FG_2.Pct = substr(sprintf("%.*f",6, as.numeric(.data$FG_2.Pct)), 1,
nchar(sprintf("%.*f",6, as.numeric(.data$FG_2.Pct))) - 3),
FG_3.Pct = substr(sprintf("%.*f",6, as.numeric(.data$FG_3.Pct)), 1,
nchar(sprintf("%.*f",6, as.numeric(.data$FG_3.Pct))) - 3))
if (year >= 2014) {
suppressWarnings(
players <- players %>%
tidyr::separate("FTM-A", into = c("FTM", "FTA"), sep = "-") %>%
tidyr::separate("FGM_2-A", into = c("FGM_2", "FGA_2"), sep = "-") %>%
tidyr::separate("FGM_3-A", into = c("FGM_3", "FGA_3"), sep = "-") %>%
dplyr::mutate_at(c("Number", "Wt", "G", "S",
"Min.Pct", "ORtg", "Poss.Pct","Shots.Pct",
"eFG.Pct", "TS.Pct", "OR.Pct", "DR.Pct",
"ARate", "TORate", "Blk.Pct","Stl.Pct","FCper40","FDper40",
"FTRate", "FTM", "FTA", "FT.Pct",
"FGM_2", "FGA_2", "FG_2.Pct", "FGM_3", "FGA_3", "FG_3.Pct",
"Min.Pct.Rk", "ORtg.Rk", "Poss.Pct.Rk", "Shots.Pct.Rk",
"eFG.Pct.Rk", "TS.Pct.Rk", "OR.Pct.Rk", "DR.Pct.Rk",
"ARate.Rk", "TORate.Rk", "Blk.Pct.Rk","Stl.Pct.Rk", "FCper40.Rk", "FDper40.Rk",
"FTRate.Rk", "FT.Pct.Rk", "FG_2.Pct.Rk", "FG_3.Pct.Rk"), as.numeric)
)
} else {
suppressWarnings(
players <- players %>%
tidyr::separate("FTM-A", into = c("FTM", "FTA"), sep = "-") %>%
tidyr::separate("FGM_2-A", into = c("FGM_2", "FGA_2"), sep = "-") %>%
tidyr::separate("FGM_3-A", into = c("FGM_3", "FGA_3"), sep = "-") %>%
dplyr::mutate_at(c("Number", "Wt", "G",
"Min.Pct", "ORtg", "Poss.Pct","Shots.Pct",
"eFG.Pct", "TS.Pct", "OR.Pct", "DR.Pct",
"ARate", "TORate", "Blk.Pct","Stl.Pct","FCper40","FDper40",
"FTRate", "FTM", "FTA", "FT.Pct",
"FGM_2", "FGA_2", "FG_2.Pct", "FGM_3", "FGA_3", "FG_3.Pct",
"Min.Pct.Rk", "ORtg.Rk", "Poss.Pct.Rk", "Shots.Pct.Rk",
"eFG.Pct.Rk", "TS.Pct.Rk", "OR.Pct.Rk", "DR.Pct.Rk",
"ARate.Rk", "TORate.Rk", "Blk.Pct.Rk","Stl.Pct.Rk", "FCper40.Rk", "FDper40.Rk",
"FTRate.Rk", "FT.Pct.Rk", "FG_2.Pct.Rk", "FG_3.Pct.Rk"), as.numeric)
)
}
players <- players %>%
dplyr::mutate(Team = team,
Year = year,
Role = dplyr::case_when(.data$Min.Pct < 10.0 ~ "Benchwarmer",
.data$Poss.Pct < 12.0 ~ "Nearly Invisible",
.data$Poss.Pct >= 12.0 & .data$Poss.Pct < 16.0 ~ "Limited Role",
.data$Poss.Pct >= 16.0 & .data$Poss.Pct < 20.0 ~ "Role Player",
.data$Poss.Pct >= 20.0 & .data$Poss.Pct < 24.0 ~ "Significant Contributor",
.data$Poss.Pct >= 24.0 & .data$Poss.Pct < 28.0 ~ "Major Contributor",
.data$Poss.Pct >= 28.0 ~ "Go-to Guys")) %>%
dplyr::select(
"Role",
tidyr::everything()) %>%
dplyr::bind_cols(lapply(pid, as.numeric))
### Store Data
kenpom <- players %>%
janitor::clean_names()
},
error = function(e){
message(glue::glue("{Sys.time()} - No Player Data available for {team} in {year}"))
},
warning = function(w){
},
finally = {
}
)
return(kenpom)
}
#' **Get KenPom's player career stats from the player page**
#'
#'
#' @param player_id Player Id filter to select.
#' @return Returns a named list of tibbles: player_stats, gamelog
#'
#' **player_stats**
#'
#'
#' |col_name |types |
#' |:-------------|:---------|
#' |year |numeric |
#' |team_rk |numeric |
#' |team |character |
#' |number |numeric |
#' |name |character |
#' |position |character |
#' |hgt |character |
#' |wgt |numeric |
#' |yr |character |
#' |g |numeric |
#' |min_pct |numeric |
#' |o_rtg |numeric |
#' |poss_pct |numeric |
#' |shots_pct |numeric |
#' |e_fg_pct |numeric |
#' |ts_pct |numeric |
#' |or_pct |numeric |
#' |dr_pct |numeric |
#' |a_rate |numeric |
#' |to_rate |numeric |
#' |blk_pct |numeric |
#' |stl_pct |numeric |
#' |f_cper40 |numeric |
#' |f_dper40 |numeric |
#' |ft_rate |numeric |
#' |ftm |numeric |
#' |fta |numeric |
#' |ft_pct |numeric |
#' |fgm_2 |numeric |
#' |fga_2 |numeric |
#' |fg_2_pct |numeric |
#' |fgm_3 |numeric |
#' |fga_3 |numeric |
#' |fg_3_pct |numeric |
#' |group_rank |character |
#' |team_finish |character |
#' |ncaa_seed |numeric |
#' |hometown |character |
#' |date_of_birth |character |
#' |age |character |
#' |comparisons |character |
#'
#' **gamelog**
#'
#'
#' |col_name |types |
#' |:--------------|:---------|
#' |year |numeric |
#' |team |character |
#' |name |character |
#' |position |character |
#' |opponent_tier |logical |
#' |date |character |
#' |opponent_rk |numeric |
#' |opponent |character |
#' |result |character |
#' |ot |character |
#' |location |character |
#' |game_type |character |
#' |mvp |character |
#' |start |character |
#' |minutes_played |numeric |
#' |o_rtg |numeric |
#' |poss_pct |numeric |
#' |pts |numeric |
#' |fgm_2 |numeric |
#' |fga_2 |numeric |
#' |fgm_3 |numeric |
#' |fga_3 |numeric |
#' |ftm |numeric |
#' |fta |numeric |
#' |or |numeric |
#' |dr |numeric |
#' |a |numeric |
#' |to |numeric |
#' |blk |numeric |
#' |stl |numeric |
#' |pf |numeric |
#'
#' @importFrom cli cli_abort
#' @importFrom dplyr select mutate filter case_when mutate_at bind_cols bind_rows
#' @importFrom stringr str_extract str_remove str_replace str_detect
#' @importFrom tidyr everything separate
#' @import rvest
#' @export
#' @keywords Player Career Stats
#' @family KenPom Team Functions
#'
#' @examples
#' \donttest{
#' try(kp_player_career(player_id = '41180'))
#' }
#'
kp_player_career <- function(player_id){
tryCatch(
expr = {
if (!has_kp_user_and_pw()) stop("This function requires a KenPom subscription e-mail and password combination,\n set as the system environment variables KP_USER and KP_PW.", "\n See ?kp_user_pw for details.", call. = FALSE)
browser <- login()
### Pull Data
url <- paste0("https://kenpom.com/player.php?",
"p=",player_id)
page <- rvest::session_jump_to(browser, url)
Sys.sleep(5)
#--- Player Info ----
player_info <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = 'span.name')) %>%
rvest::html_text() %>%
as.data.frame()
colnames(player_info) <- "Player"
player_town <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = 'span.town')) %>%
rvest::html_text() %>%
as.data.frame()
colnames(player_town) <- "Num"
player_town <- player_town %>%
tidyr::separate("Num", into = c("Number", "Town", "DateOfBirth"), sep = "\u00b7")
player_info <- dplyr::bind_cols(player_info, player_town)
#--- Player Career Average Stats ----
players_header_cols <- c("Year","Team","Hgt","Wgt","Yr","G","Min.Pct","ORtg",
"Poss.Pct","Shots.Pct","eFG.Pct","TS.Pct","OR.Pct",
"DR.Pct","ARate","TORate","Blk.Pct",
"Stl.Pct","FCper40","FDper40","FTRate",
"FTM-A","FT.Pct","FG_2M-A","FG_2.Pct","FG_3M-A",
"FG_3.Pct")
players <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#player-table'))[[1]] %>%
rvest::html_table()
colnames(players) <- players_header_cols
players <- players %>%
dplyr::mutate(
Position = gsub('[0-9]','',.data$Year),
Year = gsub('[^0-9]','',.data$Year),
GroupRank = stringr::str_extract(.data$Team,"National Rank|Conference Rank"),
Team = stringr::str_trim(stringr::str_replace(.data$Team,"National Rank|Conference Rank", "")),
Team.Finish = stringr::str_extract(.data$Team, stringr::regex('R1|R2|S16|E8|F4|2nd|CH',ignore_case = FALSE)),
Team = stringr::str_replace(.data$Team, stringr::regex(' R1| R2| S16| E8| F4| 2nd| CH',ignore_case = FALSE),""),
Team.Rk = gsub("[^0-9]", "",stringr::str_extract(.data$Team, stringr::regex('\\d{1,3}')))
)
# separating the career totals so as to not fill those columns (they're empty in the table)
players_career <- players[(nrow(players) - 2):nrow(players),]
players <- players[1:(nrow(players) - 3),]
# Now need to fill year to create a join column for the age and player comps columns
players <- players %>%
dplyr::mutate(Year = ifelse(.data$Year == "", NA_real_, .data$Year)) %>%
tidyr::fill("Year", .direction = c("down"))
player_age <- players %>%
dplyr::filter(stringr::str_detect(.data$Team,'Age:')) %>%
dplyr::select(
"Year",
"Team",
"Min.Pct") %>%
dplyr::rename(
"Age" = "Team",
"Comparisons" = "Min.Pct") %>%
dplyr::mutate(
Age = stringr::str_replace(.data$Age, "Age: ", ""),
Comparisons = stringr::str_replace(.data$Comparisons, "Similar: ", "")
)
players <- players %>%
dplyr::filter(!(stringr::str_detect(.data$Team,'Age:')),
!(stringr::str_detect(.data$Min.Pct,'Similar'))) %>%
dplyr::mutate(
NCAASeed = stringr::str_extract(.data$Team, stringr::regex(' \\d{1,2}')))
players <- dplyr::mutate(players,
"Team" = sapply(.data$Team, function(arg) {
stringr::str_trim(stringr::str_replace(stringr::str_remove(arg,'\\d+| \\*| \\*+'),'\\d+|\\*+','')) }))
players <- players %>%
dplyr::mutate(
Hgt = ifelse(.data$Hgt == "", NA_character_, .data$Hgt),
Yr = ifelse(.data$Yr == "", NA_character_, .data$Yr),
Position = ifelse(.data$Position == "", NA_character_, .data$Position),
Name = player_info$Player,
Number = player_info$Number,
Hometown = player_info$Town,
DateOfBirth = player_info$DateOfBirth) %>%
tidyr::fill("Hgt", .direction = c("down")) %>%
tidyr::fill("Wgt", .direction = c("down")) %>%
tidyr::fill("Yr", .direction = c("down")) %>%
tidyr::fill("Position", .direction = c("down")) %>%
tidyr::fill("Team.Rk", .direction = c("down")) %>%
dplyr::group_by(.data$Year) %>%
tidyr::fill("Team.Finish", .direction = c("down")) %>%
tidyr::fill("NCAASeed", .direction = c("down")) %>%
dplyr::ungroup() %>%
dplyr::bind_rows(players_career) %>%
dplyr::left_join(player_age, by = c("Year"))
suppressWarnings(
players <- players %>%
tidyr::separate("FTM-A", into = c("FTM", "FTA")) %>%
tidyr::separate("FG_2M-A", into = c("FGM_2", "FGA_2")) %>%
tidyr::separate("FG_3M-A", into = c("FGM_3", "FGA_3")) %>%
dplyr::mutate_at(c("Year", "Wgt", "G", "Min.Pct",
"ORtg", "Poss.Pct", "Shots.Pct", "eFG.Pct",
"TS.Pct", "OR.Pct", "DR.Pct", "ARate",
"TORate", "Blk.Pct", "Stl.Pct", "FCper40",
"FDper40", "FTRate","FTM", "FTA", "FT.Pct",
"FGM_2", "FGA_2", "FG_2.Pct",
"FGM_3", "FGA_3", "FG_3.Pct",
"Team.Rk", "NCAASeed", "Number"), as.numeric)
)
players_team_name <- players %>%
dplyr::filter(!(stringr::str_detect(.data$Team ,"Tier A|Conference|Career"))) %>%
dplyr::select(
"Year",
"Team",
"Name",
"Position")
img_extractor <- function(x){
data.frame(
ifelse(
is.null(rvest::html_element(x, css = "a > img")),
NA_character_,
toupper(stringr::str_trim(
stringr::str_replace(
stringr::str_extract(rvest::html_element(x, css = "a > img") %>%
xml2::xml_attr("src"), "a.gif|b.gif"),
".gif","")))),
stringsAsFactors = FALSE)
}
players <- players %>%
dplyr::select(
"Year",
"Team.Rk",
"Team",
"Number",
"Name",
"Position",
tidyr::everything()) %>%
janitor::clean_names()
s <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table'))
schedule_games <- data.frame()
for (i in 1:length(s)) {
header <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = 'div.gamelogdiv > h3'))[[i]] %>%
rvest::html_text()
sched_header_cols <- c("Opponent.Tier", "Date", "Opponent.Rk", "Opponent",
"Result","OT", "Location", "GameType",
"MVP", "Start", "MinutesPlayed", "ORtg", "Poss.Pct",
"Pts", "FG_2M-A", "FG_3M-A", "FTM-A",
"OR", "DR", "A", "TO", "Blk", "Stl", "PF")
sched <- ((page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#schedule-table'))[[i]] %>%
rvest::html_table())[,1:24]
colnames(sched) <- sched_header_cols
rownames(sched) <- NULL
sched <- sched %>% dplyr::filter(.data$Date != "")
sched$GameData <- header
sched <- sched %>%
dplyr::mutate(Year = as.numeric(stringr::str_replace(.data$GameData," Game Data",""))) %>%
dplyr::select(-"GameData")
sched <- sched %>%
dplyr::left_join(players_team_name, by = "Year")
suppressWarnings(
sched <- sched %>%
tidyr::separate("FTM-A", into = c("FTM", "FTA")) %>%
tidyr::separate("FG_2M-A", into = c("FGM_2", "FGA_2")) %>%
tidyr::separate("FG_3M-A", into = c("FGM_3", "FGA_3")) %>%
dplyr::mutate_at(c("Opponent.Rk","MinutesPlayed","ORtg","Poss.Pct",
"Pts","OR","DR","A","TO",
"FTM", "FTA","FGM_2", "FGA_2",
"FGM_3", "FGA_3",
"Blk","Stl","PF"), as.numeric)
)
sched <- sched %>%
dplyr::select(
"Year",
"Team",
"Name",
"Position",
tidyr::everything())
schedule_games <- dplyr::bind_rows(schedule_games,sched)
}
schedule_games <- schedule_games %>%
janitor::clean_names()
### Store Data
kenpom <- c(list(players),list(schedule_games))
names(kenpom) <- c("player_stats", "gamelog")
},
error = function(e){
message(glue::glue("{Sys.time()} - No Player Career Data available for {player_id}"))
},
warning = function(w){
},
finally = {
}
)
return(kenpom)
}
#' **Get Minutes Matrix from Expanded Player Page**
#'
#'
#' @param team Team filter to select.
#' @param year Year of data to pull
#' @return Returns a tibble of minutes matrix data
#'
#' @importFrom cli cli_abort
#' @importFrom dplyr mutate filter
#' @import rvest
#' @export
#' @keywords Minutes Matrix
#' @family KenPom Team Functions
#'
#' @examples
#' \donttest{
#' try(kp_minutes_matrix(team = 'Florida St.', year = 2021))
#' }
#'
#'
kp_minutes_matrix <- function(team, year = 2021){
tryCatch(
expr = {
if (!has_kp_user_and_pw()) stop("This function requires a KenPom subscription e-mail and password combination,\n set as the system environment variables KP_USER and KP_PW.", "\n See ?kp_user_pw for details.", call. = FALSE)
browser <- login()
if (!(is.numeric(year) && nchar(year) == 4 && year >= 2014)) {
# Check if year is numeric, if not NULL
cli::cli_abort("Enter valid year as a number (YYYY), data only goes back to 2014")
}
if (!(team %in% hoopR::teams_links$Team)) {
cli::cli_abort("Incorrect team name as compared to the website, see hoopR::teams_links for team name parameter specifications.")
}
teams_links <- hoopR::teams_links[hoopR::teams_links$Year == year,]
team_name = teams_links$team.link.ref[teams_links$Team == team]
### Pull Data
url <- paste0("https://kenpom.com/player-expanded.php?",
"team=",team_name,
"&y=", year)
page <- rvest::session_jump_to(browser, url)
Sys.sleep(5)
header_cols <- c("Date","Opponent.Rk","Opponent","Result")
x <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#minutes-table'))[[1]] %>%
rvest::html_table() %>%
as.data.frame()
colnames(x)[1:4] <- header_cols
team_name <- gsub("\\+"," ",team)
suppressWarnings(
x <- x %>%
dplyr::filter(!is.na(as.numeric(.data$Opponent.Rk)))
)
x <- x %>%
dplyr::mutate(Team = team_name,
Year = year)
### Store Data
kenpom <- x %>%
janitor::clean_names()
},
error = function(e){
message(glue::glue("{Sys.time()} - {team} - {year} minutes matrix is missing"))
},
warning = function(w){
},
finally = {
}
)
return(kenpom)
}
#' **Get Team Player Stats**
#' @param team Team filter to select.
#' @param year Year of data to pull
#'
#' @return Returns a list of named data frames: all_games, conference_games
#'
#' **all_games**
#'
#'
#' |col_name |types |
#' |:------------|:---------|
#' |role |character |
#' |number |numeric |
#' |player |character |
#' |ht |character |
#' |wt |numeric |
#' |yr |character |
#' |g |numeric |
#' |min_pct |numeric |
#' |o_rtg |numeric |
#' |poss_pct |numeric |
#' |shots_pct |numeric |
#' |e_fg_pct |numeric |
#' |ts_pct |numeric |
#' |or_pct |numeric |
#' |dr_pct |numeric |
#' |a_rate |numeric |
#' |to_rate |numeric |
#' |blk_pct |numeric |
#' |stl_pct |numeric |
#' |f_cper40 |numeric |
#' |f_dper40 |numeric |
#' |ft_rate |numeric |
#' |ftm |numeric |
#' |fta |numeric |
#' |ft_pct |numeric |
#' |fgm_2 |numeric |
#' |fga_2 |numeric |
#' |fg_2_pct |numeric |
#' |fgm_3 |numeric |
#' |fga_3 |numeric |
#' |fg_3_pct |numeric |
#' |category |character |
#' |min_pct_rk |numeric |
#' |o_rtg_rk |numeric |
#' |poss_pct_rk |numeric |
#' |shots_pct_rk |numeric |
#' |e_fg_pct_rk |numeric |
#' |ts_pct_rk |numeric |
#' |or_pct_rk |numeric |
#' |dr_pct_rk |numeric |
#' |a_rate_rk |numeric |
#' |to_rate_rk |numeric |
#' |blk_pct_rk |numeric |
#' |stl_pct_rk |numeric |
#' |f_cper40_rk |numeric |
#' |f_dper40_rk |numeric |
#' |ft_rate_rk |numeric |
#' |ft_pct_rk |numeric |
#' |fg_2_pct_rk |numeric |
#' |fg_3_pct_rk |numeric |
#' |group_rank |character |
#' |team |character |
#' |year |numeric |
#' |player_id |numeric |
#'
#' **conference_games**
#'
#'
#' |col_name |types |
#' |:------------|:---------|
#' |role |character |
#' |number |numeric |
#' |player |character |
#' |ht |character |
#' |wt |numeric |
#' |yr |character |
#' |g |numeric |
#' |min_pct |numeric |
#' |o_rtg |numeric |
#' |poss_pct |numeric |
#' |shots_pct |numeric |
#' |e_fg_pct |numeric |
#' |ts_pct |numeric |
#' |or_pct |numeric |
#' |dr_pct |numeric |
#' |a_rate |numeric |
#' |to_rate |numeric |
#' |blk_pct |numeric |
#' |stl_pct |numeric |
#' |f_cper40 |numeric |
#' |f_dper40 |numeric |
#' |ft_rate |numeric |
#' |ftm |numeric |
#' |fta |numeric |
#' |ft_pct |numeric |
#' |fgm_2 |numeric |
#' |fga_2 |numeric |
#' |fg_2_pct |numeric |
#' |fgm_3 |numeric |
#' |fga_3 |numeric |
#' |fg_3_pct |numeric |
#' |category |character |
#' |min_pct_rk |numeric |
#' |o_rtg_rk |numeric |
#' |poss_pct_rk |numeric |
#' |shots_pct_rk |numeric |
#' |e_fg_pct_rk |numeric |
#' |ts_pct_rk |numeric |
#' |or_pct_rk |numeric |
#' |dr_pct_rk |numeric |
#' |a_rate_rk |numeric |
#' |to_rate_rk |numeric |
#' |blk_pct_rk |numeric |
#' |stl_pct_rk |numeric |
#' |f_cper40_rk |numeric |
#' |f_dper40_rk |numeric |
#' |ft_rate_rk |numeric |
#' |ft_pct_rk |numeric |
#' |fg_2_pct_rk |numeric |
#' |fg_3_pct_rk |numeric |
#' |group_rank |character |
#' |team |character |
#' |year |numeric |
#' |player_id |numeric |
#'
#' @importFrom cli cli_abort
#' @importFrom dplyr select mutate filter case_when mutate_at bind_cols bind_rows
#' @importFrom stringr str_extract str_remove str_replace str_detect
#' @importFrom tidyr everything separate
#' @import rvest
#' @export
#' @keywords Team Player Stats
#' @family KenPom Team Functions
#'
#' @examples
#' \donttest{
#' try(kp_team_player_stats(team = 'Florida St.', year = 2021))
#' }
kp_team_player_stats <- function(team, year = 2021){
tryCatch(
expr = {
if (!has_kp_user_and_pw()) stop("This function requires a KenPom subscription e-mail and password combination,\n set as the system environment variables KP_USER and KP_PW.", "\n See ?kp_user_pw for details.", call. = FALSE)
browser <- login()
if (!(is.numeric(year) && nchar(year) == 4 && year >= 2014)) {
# Check if year is numeric, if not NULL
cli::cli_abort("Enter valid year as a number (YYYY), data only goes back to 2014")
}
if (!(team %in% hoopR::teams_links$Team)) {
cli::cli_abort("Incorrect team name as compared to the website, see hoopR::teams_links for team name parameter specifications.")
}
teams_links <- hoopR::teams_links[hoopR::teams_links$Year == year,]
team_name = teams_links$team.link.ref[teams_links$Team == team]
### Pull Data
url <- paste0("https://kenpom.com/player-expanded.php?",
"team=",team_name,
"&y=", year)
page <- rvest::session_jump_to(browser, url)
Sys.sleep(5)
players <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#player-table'))
y <- list()
for (i in 1:length(players)) {
player_links <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#player-table'))[[i]] %>%
rvest::html_elements("td:nth-child(2) > a")
pid <- dplyr::bind_rows(lapply(xml2::xml_attrs(player_links),
function(x){
if (!stringr::str_detect(x,"kpoy")) {
data.frame(as.list(x), stringsAsFactors = FALSE)
}
}))
# pid <- dplyr::bind_rows(lapply(player_links, extractor))
pid <- pid %>%
dplyr::mutate(PlayerId = stringr::str_remove(stringr::str_extract(.data$href,"=(.+)"),"=")) %>%
dplyr::select("PlayerId")
players_header_cols <- c("Number", "Player", "Ht", "Wt", "Yr", "G",
"Min.Pct", "ORtg", "Poss.Pct","Shots.Pct",
"eFG.Pct", "TS.Pct", "OR.Pct", "DR.Pct",
"ARate", "TORate", "Blk.Pct","Stl.Pct","FCper40","FDper40",
"FTRate", "FTM-A", "FT.Pct",
"FGM_2-A", "FG_2.Pct", "FGM_3-A", "FG_3.Pct")
players <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#player-table'))[[i]]
players <- players %>%
rvest::html_table()
colnames(players) <- players_header_cols
suppressWarnings(
players <- players %>%
dplyr::filter(!is.na(as.numeric(.data$G)))
)
if (i == 1) {
players$Category <- "All Games"
} else {
players$Category <- "Conference Games"
}
players$Min.Pct.Rk <- NA_real_
players$ORtg.Rk <- NA_real_
players$Poss.Pct.Rk <- NA_real_
players$Shots.Pct.Rk <- NA_real_
players$eFG.Pct.Rk <- NA_real_
players$TS.Pct.Rk <- NA_real_
players$OR.Pct.Rk <- NA_real_
players$DR.Pct.Rk <- NA_real_
players$ARate.Rk <- NA_real_
players$TORate.Rk <- NA_real_
players$Blk.Pct.Rk <- NA_real_
players$Stl.Pct.Rk <- NA_real_
players$FCper40.Rk <- NA_real_
players$FDper40.Rk <- NA_real_
players$FTRate.Rk <- NA_real_
players$FT.Pct.Rk <- NA_real_
players$FG_2.Pct.Rk <- NA_real_
players$FG_3.Pct.Rk <- NA_real_
players <- players %>%
dplyr::mutate(
Min.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$Min.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
ORtg.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$ORtg, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
Poss.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$Poss.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
Shots.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$Shots.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
eFG.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$eFG.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
TS.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$TS.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
OR.Pct.Rk = stringr::str_replace(stringr::str_extract(.data$OR.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', ""),
DR.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$DR.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
ARate.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$ARate, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
TORate.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$TORate, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
Blk.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$Blk.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
Stl.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$Stl.Pct, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
FCper40.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$FCper40, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
FDper40.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$FDper40, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
FTRate.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$FTRate, '\\d{1,3}\\.\\d(.+)'), '(.+)\\.\\d', "")),
FT.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$FT.Pct, '\\.\\d{3}(.+)'), '\\.\\d{3}', "")),
FG_2.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$FG_2.Pct, '\\.\\d{3}(.+)'), '\\.\\d{3}', "")),
FG_3.Pct.Rk = as.numeric(stringr::str_replace(stringr::str_extract(.data$FG_3.Pct, '\\.\\d{3}(.+)'), '\\.\\d{3}', "")),
GroupRank = stringr::str_extract(.data$Player, "National Rank|Conference Rank"),
Player = stringr::str_replace(.data$Player, "National Rank|Conference Rank",""),
Min.Pct = substr(sprintf("%.*f", 4, as.numeric(.data$Min.Pct)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$Min.Pct))) - 3),
ORtg = substr(sprintf("%.*f", 4, as.numeric(.data$ORtg)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$ORtg))) - 3),
Poss.Pct = substr(sprintf("%.*f", 4, as.numeric(.data$Poss.Pct)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$Poss.Pct))) - 3),
Shots.Pct = substr(sprintf("%.*f",4, as.numeric(.data$Shots.Pct)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$Shots.Pct))) - 3),
eFG.Pct = substr(sprintf("%.*f",4, as.numeric(.data$eFG.Pct)), 1,
nchar(sprintf("%.*f",4, as.numeric(.data$eFG.Pct))) - 3),
TS.Pct = substr(sprintf("%.*f", 4, as.numeric(.data$TS.Pct)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$TS.Pct))) - 3),
OR.Pct = substr(sprintf("%.*f", 4, as.numeric(.data$OR.Pct)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$OR.Pct))) - 3),
DR.Pct = substr(sprintf("%.*f", 4, as.numeric(.data$ARate)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$DR.Pct))) - 3),
ARate = substr(sprintf("%.*f", 4, as.numeric(.data$ARate)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$ARate))) - 3),
TORate = substr(sprintf("%.*f", 4, as.numeric(.data$TORate)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$TORate))) - 3),
Blk.Pct = substr(sprintf("%.*f", 4, as.numeric(.data$Blk.Pct)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$Blk.Pct))) - 3),
Stl.Pct = substr(sprintf("%.*f", 4, as.numeric(.data$Stl.Pct)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$Stl.Pct))) - 3),
FCper40 = substr(sprintf("%.*f",4, as.numeric(.data$FCper40)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$FCper40))) - 3),
FDper40 = substr(sprintf("%.*f", 4, as.numeric(.data$FDper40)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$FDper40))) - 3),
FTRate = substr(sprintf("%.*f", 4, as.numeric(.data$FTRate)), 1,
nchar(sprintf("%.*f", 4, as.numeric(.data$FTRate))) - 3),
FT.Pct = substr(sprintf("%.*f", 6, as.numeric(.data$FT.Pct)), 1,
nchar(sprintf("%.*f", 6, as.numeric(.data$FT.Pct))) - 3),
FG_2.Pct = substr(sprintf("%.*f", 6, as.numeric(.data$FG_2.Pct)), 1,
nchar(sprintf("%.*f", 6, as.numeric(.data$FG_2.Pct))) - 3),
FG_3.Pct = substr(sprintf("%.*f", 6, as.numeric(.data$FG_3.Pct)), 1,
nchar(sprintf("%.*f", 6, as.numeric(.data$FG_3.Pct))) - 3))
suppressWarnings(
players <- players %>%
tidyr::separate("FTM-A", into = c("FTM", "FTA"), sep = "-") %>%
tidyr::separate("FGM_2-A", into = c("FGM_2", "FGA_2"), sep = "-") %>%
tidyr::separate("FGM_3-A", into = c("FGM_3", "FGA_3"), sep = "-") %>%
dplyr::mutate_at(c("Number", "Wt", "G",
"Min.Pct", "ORtg", "Poss.Pct","Shots.Pct",
"eFG.Pct", "TS.Pct", "OR.Pct", "DR.Pct",
"ARate", "TORate", "Blk.Pct","Stl.Pct","FCper40","FDper40",
"FTRate", "FTM", "FTA", "FT.Pct",
"FGM_2", "FGA_2", "FG_2.Pct", "FGM_3", "FGA_3", "FG_3.Pct",
"Min.Pct.Rk", "ORtg.Rk", "Poss.Pct.Rk", "Shots.Pct.Rk",
"eFG.Pct.Rk", "TS.Pct.Rk", "OR.Pct.Rk", "DR.Pct.Rk",
"ARate.Rk", "TORate.Rk", "Blk.Pct.Rk","Stl.Pct.Rk", "FCper40.Rk", "FDper40.Rk",
"FTRate.Rk", "FT.Pct.Rk", "FG_2.Pct.Rk", "FG_3.Pct.Rk"), as.numeric)
)
players <- players %>%
dplyr::mutate(Team = team,
Year = year,
Role = dplyr::case_when(.data$Min.Pct < 10.0 ~ "Benchwarmer",
.data$Poss.Pct < 12.0 ~ "Nearly Invisible",
.data$Poss.Pct >= 12.0 & .data$Poss.Pct < 16.0 ~ "Limited Role",
.data$Poss.Pct >= 16.0 & .data$Poss.Pct < 20.0 ~ "Role Player",
.data$Poss.Pct >= 20.0 & .data$Poss.Pct < 24.0 ~ "Significant Contributor",
.data$Poss.Pct >= 24.0 & .data$Poss.Pct < 28.0 ~ "Major Contributor",
.data$Poss.Pct >= 28.0 ~ "Go-to Guys")) %>%
dplyr::select("Role", tidyr::everything()) %>%
dplyr::bind_cols(lapply(pid, as.numeric)) %>%
janitor::clean_names()
y <- c(y, list(players))
}
### Store Data
kenpom <- y
names(kenpom) <- c("all_games", "conference_games")
},
error = function(e){
message(glue::glue("{Sys.time()} - {team} - {year} team player stats are missing"))
},
warning = function(w){
},
finally = {
}
)
return(kenpom)
}
#' **Get Depth Chart Last 5 Games from Team Page**
#'
#'
#' @param team Team filter to select.
#' @param year Year of data to pull
#' @return A data frame with the following columns:
#'
#' |col_name |types |
#' |:--------------------|:---------|
#' |pg_number |numeric |
#' |pg_player_first_name |character |
#' |pg_player_last_name |character |
#' |pg_hgt |character |
#' |pg_wgt |numeric |
#' |pg_yr |character |
#' |pg_min_pct |numeric |
#' |sg_number |numeric |
#' |sg_player_first_name |character |
#' |sg_player_last_name |character |
#' |sg_hgt |character |
#' |sg_wgt |numeric |
#' |sg_yr |character |
#' |sg_min_pct |numeric |
#' |sf_number |numeric |
#' |sf_player_first_name |character |
#' |sf_player_last_name |character |
#' |sf_hgt |character |
#' |sf_wgt |numeric |
#' |sf_yr |character |
#' |sf_min_pct |numeric |
#' |pf_number |numeric |
#' |pf_player_first_name |character |
#' |pf_player_last_name |character |
#' |pf_hgt |character |
#' |pf_wgt |numeric |
#' |pf_yr |character |
#' |pf_min_pct |numeric |
#' |c_number |numeric |
#' |c_player_first_name |character |
#' |c_player_last_name |character |
#' |c_hgt |character |
#' |c_wgt |numeric |
#' |c_yr |character |
#' |c_min_pct |numeric |
#' |team |character |
#' |year |numeric |
#'
#' @importFrom cli cli_abort
#' @importFrom dplyr select mutate filter bind_cols bind_rows
#' @importFrom stringr str_extract str_remove str_replace str_detect str_trim
#' @importFrom tidyr separate
#' @importFrom glue glue
#' @import rvest
#' @export
#' @keywords Depth Chart
#' @family KenPom Team Functions
#'
#' @examples
#' \donttest{
#' try(kp_team_depth_chart(team = 'Florida St.', year= 2021))
#' }
#'
#'
kp_team_depth_chart <- function(team, year= 2021){
tryCatch(
expr = {
if (!has_kp_user_and_pw()) stop("This function requires a KenPom subscription e-mail and password combination,\n set as the system environment variables KP_USER and KP_PW.", "\n See ?kp_user_pw for details.", call. = FALSE)
browser <- login()
if (!(is.numeric(year) && nchar(year) == 4 && year >= 2014)) {
# Check if year is numeric, if not NULL
cli::cli_abort("Enter valid year as a number (YYYY), data only goes back to 2014")
}
if (!(team %in% hoopR::teams_links$Team)) {
cli::cli_abort("Incorrect team name as compared to the website, see hoopR::teams_links for team name parameter specifications.")
}
teams_links <- hoopR::teams_links[hoopR::teams_links$Year == year,]
team_name = teams_links$team.link.ref[teams_links$Team == team]
### Pull Data
url <- paste0("https://kenpom.com/team.php?",
"team=",team_name,
"&y=", year)
page <- rvest::session_jump_to(browser, url)
Sys.sleep(5)
depth1_header_cols <- c("PG", "PG.Min.Pct", "SG", "SG.Min.Pct", "SF", "SF.Min.Pct",
"PF", "PF.Min.Pct", "C", "C.Min.Pct")
depth1 <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#dc-table'))[[1]] %>%
rvest::html_table() %>%
as.data.frame()
colnames(depth1) <- depth1_header_cols
suppressWarnings(
depth1 <- depth1 %>%
dplyr::filter(.data$PG != "PG")
)
depth1 <- depth1 %>%
dplyr::mutate(
PG.Yr = substr(.data$PG, nchar(.data$PG) - 2, nchar(.data$PG)),
PG = substr(.data$PG, 1, nchar(.data$PG) - 3),
PG.Wgt = stringr::str_extract(.data$PG, '\\d{3}'),
PG = stringr::str_trim(stringr::str_remove(.data$PG, '\\d{3}')),
PG.Hgt = stringr::str_extract(.data$PG, '\\d{1}-\\d{0,2}'),
PG = stringr::str_remove(.data$PG, '\\d{1}-\\d{0,2}'),
SG.Yr = substr(.data$SG, nchar(.data$SG) - 2, nchar(.data$SG)),
SG = substr(.data$SG, 1, nchar(.data$SG) - 3),
SG.Wgt = stringr::str_extract(.data$SG, '\\d{3}'),
SG = stringr::str_trim(stringr::str_remove(.data$SG, '\\d{3}')),
SG.Hgt = stringr::str_extract(.data$SG, '\\d{1}-\\d{0,2}'),
SG = stringr::str_remove(.data$SG, '\\d{1}-\\d{0,2}'),
SF.Yr = substr(.data$SF, nchar(.data$SF) - 2, nchar(.data$SF)),
SF = substr(.data$SF, 1, nchar(.data$SF) - 3),
SF.Wgt = stringr::str_extract(.data$SF, '\\d{3}'),
SF = stringr::str_trim(stringr::str_remove(.data$SF, '\\d{3}')),
SF.Hgt = stringr::str_extract(.data$SF, '\\d{1}-\\d{0,2}'),
SF = stringr::str_remove(.data$SF, '\\d{1}-\\d{0,2}'),
PF.Yr = substr(.data$PF, nchar(.data$PF) - 2, nchar(.data$PF)),
PF = substr(.data$PF, 1, nchar(.data$PF) - 3),
PF.Wgt = stringr::str_extract(.data$PF,'\\d{3}'),
PF = stringr::str_trim(stringr::str_remove(.data$PF,'\\d{3}')),
PF.Hgt = stringr::str_extract(.data$PF, '\\d{1}-\\d{0,2}'),
PF = stringr::str_remove(.data$PF, '\\d{1}-\\d{0,2}'),
C.Yr = substr(.data$C, nchar(.data$C) - 2, nchar(.data$C)),
C = substr(.data$C, 1, nchar(.data$C) - 3),
C.Wgt = stringr::str_extract(.data$C, '\\d{3}'),
C = stringr::str_trim(stringr::str_remove(.data$C, '\\d{3}')),
C.Hgt = stringr::str_extract(.data$C, '\\d{1}-\\d{0,2}'),
C = stringr::str_remove(.data$C, '\\d{1}-\\d{0,2}')
)
suppressWarnings(
depth1 <- depth1 %>%
tidyr::separate("PG", into = c("PG.Number", "PG.PlayerFirstName", "PG.PlayerLastName"), sep = "[^\\w']") %>%
tidyr::separate("SG", into = c("SG.Number", "SG.PlayerFirstName", "SG.PlayerLastName"), sep = "[^\\w']") %>%
tidyr::separate("SF", into = c("SF.Number", "SF.PlayerFirstName", "SF.PlayerLastName"), sep = "[^\\w']") %>%
tidyr::separate("PF", into = c("PF.Number", "PF.PlayerFirstName", "PF.PlayerLastName"), sep = "[^\\w']") %>%
tidyr::separate("C", into = c("C.Number", "C.PlayerFirstName", "C.PlayerLastName"), sep = "[^\\w']")
)
suppressWarnings(
depth1 <- depth1 %>%
dplyr::mutate(
Team = team,
Year = year,
PG.Min.Pct = as.numeric(stringr::str_replace(.data$PG.Min.Pct, '%', ''))/100,
SG.Min.Pct = as.numeric(stringr::str_replace(.data$SG.Min.Pct, '%', ''))/100,
SF.Min.Pct = as.numeric(stringr::str_replace(.data$SF.Min.Pct, '%', ''))/100,
PF.Min.Pct = as.numeric(stringr::str_replace(.data$PF.Min.Pct, '%', ''))/100,
C.Min.Pct = as.numeric(stringr::str_replace(.data$C.Min.Pct, '%', ''))/100,
PG.Number = as.numeric(.data$PG.Number),
SG.Number = as.numeric(.data$SG.Number),
SF.Number = as.numeric(.data$SF.Number),
PF.Number = as.numeric(.data$PF.Number),
C.Number = as.numeric(.data$C.Number),
PG.Wgt = as.numeric(.data$PG.Wgt),
SG.Wgt = as.numeric(.data$SG.Wgt),
SF.Wgt = as.numeric(.data$SF.Wgt),
PF.Wgt = as.numeric(.data$PF.Wgt),
C.Wgt = as.numeric(.data$C.Wgt))
)
depth1 <- depth1 %>%
dplyr::select(
"PG.Number",
"PG.PlayerFirstName",
"PG.PlayerLastName",
"PG.Hgt",
"PG.Wgt",
"PG.Yr",
"PG.Min.Pct",
"SG.Number",
"SG.PlayerFirstName",
"SG.PlayerLastName",
"SG.Hgt",
"SG.Wgt",
"SG.Yr",
"SG.Min.Pct",
"SF.Number",
"SF.PlayerFirstName",
"SF.PlayerLastName",
"SF.Hgt",
"SF.Wgt",
"SF.Yr",
"SF.Min.Pct",
"PF.Number",
"PF.PlayerFirstName",
"PF.PlayerLastName",
"PF.Hgt",
"PF.Wgt",
"PF.Yr",
"PF.Min.Pct",
"C.Number",
"C.PlayerFirstName",
"C.PlayerLastName",
"C.Hgt",
"C.Wgt",
"C.Yr",
"C.Min.Pct",
"Team",
"Year")
### Store Data
kenpom <- depth1 %>%
janitor::clean_names()
},
error = function(e){
message(glue::glue("{Sys.time()} - {team} - {year} Team Depth Chart is missing"))
},
warning = function(w){
},
finally = {
}
)
return(kenpom)
}
#' **Get Lineups Last 5 Games from Team Page**
#'
#'
#' @param team Team filter to select.
#' @param year Year of data to pull
#' @return A data frame with the following columns:
#'
#' |col_name |types |
#' |:--------------------|:---------|
#' |year |numeric |
#' |team |character |
#' |min_pct |numeric |
#' |pg_number |numeric |
#' |pg_player_first_name |character |
#' |pg_player_last_name |character |
#' |pg_hgt |character |
#' |pg_wgt |numeric |
#' |pg_yr |character |
#' |sg_number |numeric |
#' |sg_player_first_name |character |
#' |sg_player_last_name |character |
#' |sg_hgt |character |
#' |sg_wgt |numeric |
#' |sg_yr |character |
#' |sf_number |numeric |
#' |sf_player_first_name |character |
#' |sf_player_last_name |character |
#' |sf_hgt |character |
#' |sf_wgt |numeric |
#' |sf_yr |character |
#' |pf_number |numeric |
#' |pf_player_first_name |character |
#' |pf_player_last_name |character |
#' |pf_hgt |character |
#' |pf_wgt |numeric |
#' |pf_yr |character |
#' |c_number |numeric |
#' |c_player_first_name |character |
#' |c_player_last_name |character |
#' |c_hgt |character |
#' |c_wgt |numeric |
#' |c_yr |character |
#'
#' @importFrom cli cli_abort
#' @importFrom dplyr select mutate filter
#' @importFrom glue glue
#' @importFrom stringr str_remove str_replace str_extract
#' @import rvest
#' @export
#' @keywords Depth Chart
#' @family KenPom Team Functions
#'
#' @examples
#' \donttest{
#' try(kp_team_lineups(team = 'Florida St.', year = 2021))
#' }
#'
kp_team_lineups <- function(team, year=2021){
tryCatch(
expr = {
if (!has_kp_user_and_pw()) stop("This function requires a KenPom subscription e-mail and password combination,\n set as the system environment variables KP_USER and KP_PW.", "\n See ?kp_user_pw for details.", call. = FALSE)
browser <- login()
if (!(is.numeric(year) && nchar(year) == 4 && year >= 2010)) {
# Check if year is numeric, if not NULL
cli::cli_abort("Enter valid year as a number (YYYY), data only goes back to 2010")
}
if (!(team %in% hoopR::teams_links$Team)) {
cli::cli_abort("Incorrect team name as compared to the website, see hoopR::teams_links for team name parameter specifications.")
}
teams_links <- hoopR::teams_links[hoopR::teams_links$Year == year,]
team_name = teams_links$team.link.ref[teams_links$Team == team]
### Pull Data
url <- paste0("https://kenpom.com/team.php?",
"team=",team_name,
"&y=", year)
page <- rvest::session_jump_to(browser, url)
Sys.sleep(5)
depth2_header_cols <- c("Rk","PG", "SG", "SF",
"PF", "C", "Min.Pct")
depth2 <- (page %>%
xml2::read_html() %>%
rvest::html_elements(css = '#dc-table2'))[[1]] %>%
rvest::html_table() %>%
as.data.frame()
colnames(depth2) <- depth2_header_cols
suppressWarnings(
depth2 <- depth2 %>%
dplyr::filter(!is.na(as.numeric(.data$Min.Pct)))
)
depth2 <- depth2 %>%
dplyr::mutate(
PG.Yr = substr(.data$PG, nchar(.data$PG) - 2, nchar(.data$PG)),
PG = substr(.data$PG, 1, nchar(.data$PG) - 3),
PG.Wgt = stringr::str_extract(.data$PG, '\\d{3}'),
PG = stringr::str_trim(stringr::str_remove(.data$PG, '\\d{3}')),
PG.Hgt = stringr::str_extract(.data$PG, '\\d{1}-\\d{0,2}'),
PG = stringr::str_remove(.data$PG, '\\d{1}-\\d{0,2}'),
SG.Yr = substr(.data$SG, nchar(.data$SG) - 2, nchar(.data$SG)),
SG = substr(.data$SG, 1, nchar(.data$SG) - 3),
SG.Wgt = stringr::str_extract(.data$SG, '\\d{3}'),
SG = stringr::str_trim(stringr::str_remove(.data$SG, '\\d{3}')),
SG.Hgt = stringr::str_extract(.data$SG, '\\d{1}-\\d{0,2}'),
SG = stringr::str_remove(.data$SG, '\\d{1}-\\d{0,2}'),
SF.Yr = substr(.data$SF, nchar(.data$SF) - 2, nchar(.data$SF)),
SF = substr(.data$SF, 1, nchar(.data$SF) - 3),
SF.Wgt = stringr::str_extract(.data$SF, '\\d{3}'),
SF = stringr::str_trim(stringr::str_remove(.data$SF, '\\d{3}')),
SF.Hgt = stringr::str_extract(.data$SF, '\\d{1}-\\d{0,2}'),
SF = stringr::str_remove(.data$SF, '\\d{1}-\\d{0,2}'),
PF.Yr = substr(.data$PF, nchar(.data$PF) - 2, nchar(.data$PF)),
PF = substr(.data$PF, 1, nchar(.data$PF) - 3),
PF.Wgt = stringr::str_extract(.data$PF, '\\d{3}'),
PF = stringr::str_trim(stringr::str_remove(.data$PF, '\\d{3}')),
PF.Hgt = stringr::str_extract(.data$PF, '\\d{1}-\\d{0,2}'),
PF = stringr::str_remove(.data$PF, '\\d{1}-\\d{0,2}'),
C.Yr = substr(.data$C, nchar(.data$C) - 2, nchar(.data$C)),
C = substr(.data$C, 1, nchar(.data$C) - 3),
C.Wgt = stringr::str_extract(.data$C, '\\d{3}'),
C = stringr::str_trim(stringr::str_remove(.data$C, '\\d{3}')),
C.Hgt = stringr::str_extract(.data$C, '\\d{1}-\\d{0,2}'),
C = stringr::str_remove(.data$C, '\\d{1}-\\d{0,2}')
)
suppressWarnings(
depth2 <- depth2 %>%
tidyr::separate("PG", into = c("PG.Number", "PG.PlayerFirstName", "PG.PlayerLastName"), sep = "[^\\w']") %>%
tidyr::separate("SG", into = c("SG.Number", "SG.PlayerFirstName", "SG.PlayerLastName"), sep = "[^\\w']") %>%
tidyr::separate("SF", into = c("SF.Number", "SF.PlayerFirstName", "SF.PlayerLastName"), sep = "[^\\w']") %>%
tidyr::separate("PF", into = c("PF.Number", "PF.PlayerFirstName", "PF.PlayerLastName"), sep = "[^\\w']") %>%
tidyr::separate("C", into = c("C.Number", "C.PlayerFirstName", "C.PlayerLastName"), sep = "[^\\w']")
)
suppressWarnings(
depth2 <- depth2 %>%
dplyr::mutate(
Min.Pct = as.numeric(stringr::str_replace(.data$Min.Pct, '%', ''))/100,
PG.Number = as.numeric(.data$PG.Number),
SG.Number = as.numeric(.data$SG.Number),
SF.Number = as.numeric(.data$SF.Number),
PF.Number = as.numeric(.data$PF.Number),
C.Number = as.numeric(.data$C.Number),
PG.Wgt = as.numeric(.data$PG.Wgt),
SG.Wgt = as.numeric(.data$SG.Wgt),
SF.Wgt = as.numeric(.data$SF.Wgt),
PF.Wgt = as.numeric(.data$PF.Wgt),
C.Wgt = as.numeric(.data$C.Wgt))
)
depth2 <- depth2 %>%
dplyr::mutate(Team = team,
Year = year) %>%
dplyr::select(
"Year",
"Team",
"Min.Pct",
"PG.Number",
"PG.PlayerFirstName",
"PG.PlayerLastName",
"PG.Hgt",
"PG.Wgt",
"PG.Yr",
"SG.Number",
"SG.PlayerFirstName",
"SG.PlayerLastName",
"SG.Hgt",
"SG.Wgt",
"SG.Yr",
"SF.Number",
"SF.PlayerFirstName",
"SF.PlayerLastName",
"SF.Hgt",
"SF.Wgt",
"SF.Yr",
"PF.Number",
"PF.PlayerFirstName",
"PF.PlayerLastName",
"PF.Hgt",
"PF.Wgt",
"PF.Yr",
"C.Number",
"C.PlayerFirstName",
"C.PlayerLastName",
"C.Hgt",
"C.Wgt",
"C.Yr")
### Store Data
depth2[nrow(depth2),"PG.PlayerFirstName"] <- "UNKNOWN"
depth2[nrow(depth2),"C.Number"] <- NA_real_
depth2[nrow(depth2),"C.Yr"] <- NA_real_
kenpom <- depth2 %>%
janitor::clean_names()
},
error = function(e){
message(glue::glue("{Sys.time()} - {team} - {year} Team Lineups are missing"))
},
warning = function(w){
},
finally = {
}
)
return(kenpom)
}
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