R/players_teams.R
In abresler/nbastatR: R's interface to NBA data
Defines functions
teams_players_stats
.players_teams_season_summary
.generate_dash_url
Documented in
teams_players_stats
.dictionary_nba_queries <-
memoise(function() {
tibble(typeQuery = c("splits", "splits", "general", "general", "defense", "defense", "clutch", "clutch",
"hustle", "hustle", "shots", "shots", "shot locations", "shot locations"),
slugQuery = c("teamdashboardbygeneralsplits", "playerdashboardbygeneralsplits", "leaguedashteamstats", "leaguedashplayerstats" ,"leaguedashptdefend", "leaguedashptdefend", "leaguedashteamclutch", "leaguedashplayerclutch","leaguehustlestatsteam", "leaguehustlestatsplayer", "leaguedashteamptshot", "leaguedashplayerptshot",
"leaguedashteamshotlocations", "leaguedashplayershotlocations"),
typeSearch = c("team", "player", "team", "player", "team", "player", "team", "player", "team", "player", "team", "player", "team", "player"))
})
.generate_dash_url <-
function(query_type = "general",
type = "team",
id = "",
season = 2017,
season_type = "Regular Season",
measure = "Base",
mode = "PerGame",
defense = "Overall",
is_plus_minus = F,
is_pace_adjusted = F,
period = 0,
is_rank = F,
game_segment = NA ,
division_against = NA,
conference_against = NA,
date_from = NA,
date_to = NA,
weight = NA,
last_n_games = 0,
location = NA,
month = 0,
season_segment = NA,
opponent = NA,
outcome = NA,
playoff_round = 0,
ahead_or_behind = "Ahead or Behind",
general_range = "Overall",
dribble_range = "0 Dribbles",
touch_time_range = NA,
closest_defender_range = NA,
shot_distance_range = "By Zone",
point_diff = 5,
country = NA,
player_experience = NA, # c(NA, "Rookie", "Sophomore", "Veteran"),
player_position = NA, # c(NA, "F", "C", "G", "C-F", "F-C", "F-G", "G-F"),
college = NA,
draft_pick = NA, #c( NA, "First Round", "2nd Round", "1st Pick", "Lottery Pick", "Top 5 Pick", "Top 10 Pick", "Top 15 Pick", "Top 20 Pick", "Top 25 Pick", "Picks 11 Thru 20", "Picks 21 Thru 30", "Undrafted")
draft_year = NA,
clutch_time = "Last 5 Minutes",
game_scope = NA, #c(NA, "Yesterday", "Last 10"),
height = NA, # c(NA, "LT 6-0", "GT 6-0", "LT 6-4", "GT 6-4", "LT 6-7", "GT 6-7", "LT 6-10", "GT 6-10", "LT 7-0", "GT 7-0"),
shot_clock_range = NA, #c(NA, "24-22", "22-18 Very Early", "18-15 Early", "15-7 Average", "7-4 Late", "4-0 Very Late", "ShotClock Off")
starter_bench = NA # c(NA, "Starters", "Bench"),
) {
if (!'df_nba_team_dict' %>% exists()) {
df_nba_team_dict <- nba_teams()
assign('df_nba_team_dict', df_nba_team_dict, envir = .GlobalEnv)
}
df_query_dict <-
.dictionary_nba_queries()
query_slug <-
df_query_dict %>%
filter(typeQuery %>% str_detect(str_to_lower(query_type))) %>%
filter(typeSearch %>% str_detect(str_to_lower(type))) %>%
pull(slugQuery)
base <-
glue("https://stats.nba.com/stats/{query_slug}?") %>%
as.character()
slug_type <-
case_when(type %>% str_to_lower() == "team" ~ "TeamID",
TRUE ~ 'PlayerID')
if (season < 1996) {
stop("Sorry data only goes back to the 1996-97 Season")
}
slugSeason <-
generate_season_slug(season = season)
if (!opponent %>% is.na()) {
if (!opponent %>% str_to_lower() %in% df_nba_team_dict$nameTeam %>% str_to_lower()) {
"Opponent must be either " %>%
paste0(df_nba_team_dict$nameTeam %>% paste0(collapse = ', ')) %>%
stop()
}
opponent_stem <-
df_nba_team_dict %>%
mutate(nameTeam = nameTeam %>% str_to_lower()) %>%
dplyr::filter(nameTeam == opponent %>% str_to_lower()) %>%
.$idTeam
} else {
opponent_stem <-
0
}
if (!conference_against %>% is.na()) {
if (!conference_against %in% c("East", "West")) {
stop("Sorry conference against can only be East or West")
}
conference_against_stem <-
conference_against %>% clean_to_stem()
} else {
conference_against_stem <-
''
}
if (!date_from %>% is.na()) {
date_from_stem <-
date_from %>% clean_to_stem()
} else {
date_from_stem <-
''
}
if (!date_to %>% is.na()) {
date_to_stem <-
date_to %>% clean_to_stem()
} else {
date_to_stem <-
''
}
if (!division_against %>% is.na()) {
if (!division_against %in% c("Atlantic",
"Central",
"Northwest",
"Pacific",
"Southeast",
"Southwest")) {
stop(
"Sorry division against can only be Atlantic, Central\nNorthwest, Pacific, Southeast, orSouthwest"
)
}
division_against_stem <-
division_against[1] %>% clean_to_stem
} else {
division_against_stem <-
''
}
if (!game_segment %>% is.na()) {
GameSegment = c("First Half", "Second Half", "Overtime")
if (!game_segment %in% GameSegment) {
"Sorry game segment can only be " %>%
paste0(GameSegment %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
game_segment_stem <-
game_segment %>% clean_to_stem()
} else {
game_segment_stem <-
''
}
if (!last_n_games %>% is.na()) {
if (!last_n_games >= 0) {
stop("Last N games must be over 0")
}
last_n_games_stem <-
last_n_games
} else {
last_n_games_stem <-
0
}
if (!location %>% is.na()) {
if (!location %in% c("Home", "Road")) {
stop("Sorry location can only be Home or Road")
}
location_stem <-
location %>% clean_to_stem()
} else {
location_stem <-
''
}
if (!measure %>% is.na()) {
MeasureType = c("Base",
"Advanced",
"Defense",
"Misc",
"Scoring",
"Usage",
"Four Factors",
"Opponent")
if (!measure %in% MeasureType) {
"Sorry measure type can only be " %>%
paste0(measure %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
measure_type_stem <-
measure %>% clean_to_stem()
} else {
measure_type_stem <-
'Base'
}
if (!outcome %>% is.na()) {
Outcome = c("W", "L")
if (!outcome %in% Outcome) {
"Sorry outcome can only be " %>%
paste0(Outcome %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
outcome_stem <-
outcome %>% clean_to_stem
} else {
outcome_stem <-
''
}
if (playoff_round > 4) {
stop("Playoff round can only be zero to 4")
} else {
playoff_round_stem <-
playoff_round
}
if (is_pace_adjusted) {
pace_stem <-
"Y"
} else {
pace_stem <-
"N"
}
if (!mode %>% is.na()) {
PerMode = c(
"Totals",
"PerGame",
"MinutesPer",
"Per48",
"Per40",
"Per36",
"PerMinute",
"PerPossession",
"PerPlay",
"Per100Possessions",
"Per100Plays"
)
mode <-
mode[1] %>%
str_replace('\\ ', '')
if (!mode[1] %>% clean_to_stem() %in% PerMode) {
"Sorry per mode can only be " %>%
paste0(mode[1] %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
per_mode_type_stem <-
mode[1] %>% clean_to_stem()
} else {
per_mode_stem <-
'Totals'
}
if (month > 12) {
stop("Month can only be zero to 12")
} else {
month_stem <-
month
}
if (period > 14) {
stop("Period can only be zero to 14")
} else {
period_stem <-
period
}
if (is_plus_minus) {
plus_minus_stem <-
"Y"
} else {
plus_minus_stem <-
"N"
}
if (is_rank) {
rank_stem <-
"Y"
} else {
rank_stem <-
"N"
}
if (!season_segment %>% is.na()) {
SeasonSegment = c("Post All-Star", "Pre All-Star")
if (!season_segment[1] %in% SeasonSegment) {
"Sorry season segment can only be " %>%
paste0(SeasonSegment %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
season_segment_stem <-
season_segment %>% clean_to_stem()
} else {
season_segment_stem <-
''
}
if (!season_type %>% is.na()) {
SeasonType = c('Regular Season', 'Pre Season', 'Playoffs', 'All Star')
if (!season_type %in% SeasonType) {
"Sorry season type can only be " %>%
paste0(SeasonType %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
season_type_stem <-
season_type %>% clean_to_stem()
} else {
season_type_stem <-
'Regular+Season'
}
if (!shot_clock_range %>% is.na()) {
ShotClockRange = c(
"24-22",
"22-18 Very Early",
"18-15 Early",
"15-7 Average",
"7-4 Late",
"4-0 Very Late",
"ShotClock Off"
)
if (!shot_clock_range %in% ShotClockRange) {
"Sorry shot clock range can only be " %>%
paste0(ShotClockRange %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
shot_clock_range_stem <-
shot_clock_range %>% clean_to_stem()
} else {
shot_clock_range_stem <-
''
}
if (!draft_pick %>% is.na()) {
DraftPick = c(
"First Round",
"2nd Round",
"1st Pick",
"Lottery Pick",
"Top 5 Pick",
"Top 10 Pick",
"Top 15 Pick",
"Top 20 Pick",
"Top 25 Pick",
"Picks 11 Thru 20",
"Picks 21 Thru 30",
"Undrafted"
)
if (!draft_pick %in% DraftPick) {
"Sorry draft pick can only be " %>%
paste0(DraftPick %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
draft_pick_stem <-
draft_pick %>% clean_to_stem()
} else {
draft_pick_stem <-
''
}
if (!draft_year %>% is.na()) {
if (!draft_year > 1947) {
stop("Draft year must be after 1947")
}
draft_year_stem <-
draft_year
} else {
draft_year_stem <-
''
}
if (!game_scope %>% is.na()) {
GameScope = c("Yesterday", "Last 10")
if (!game_scope %in% GameScope) {
"Sorry game scope can only be " %>%
paste0(GameScope %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
game_scope_stem <-
game_scope %>% clean_to_stem()
} else {
game_scope_stem <-
''
}
if (!player_position %>% is.na()) {
PlayerPosition = c("F", "C", "G", "C-F", "F-C", "F-G", "G-F")
if (!player_position %in% PlayerPosition) {
"Sorry player position can only be " %>%
paste0(PlayerPosition %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
player_position_stem <-
player_position[1] %>% clean_to_stem()
} else {
player_position_stem <-
''
}
if (!height %>% is.na) {
Height = c(
"LT 6-0",
"GT 6-0",
"LT 6-4",
"GT 6-4",
"LT 6-7",
"GT 6-7",
"LT 6-10",
"GT 6-10",
"LT 7-0",
"GT 7-0"
)
if (!height %in% Height) {
"Sorry height can only be " %>%
paste0(Height %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
height_stem <-
height %>% clean_to_stem()
} else {
height_stem <-
''
}
if (!college %>% is.na()) {
college_stem <-
college[1] %>% clean_to_stem()
} else {
college_stem <-
''
}
if (!country %>% is.na()) {
country_stem <-
country %>% clean_to_stem
} else {
country_stem <-
''
}
if (!starter_bench %>% is.na()) {
StarterBench = c("Starters", "Bench")
if (!starter_bench %in% StarterBench) {
"Sorry starter/bench can only be " %>%
paste0(StarterBench %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
starter_bench_stem <-
starter_bench[1] %>% clean_to_stem()
} else {
starter_bench_range_stem <-
''
}
if (!weight %>% is.na) {
Weight = c(
"LT 200",
"GT 200",
"LT 225",
"GT 225",
"LT 250",
"GT 250",
"LT 275",
"GT 275",
"LT 300",
"GT 300"
)
if (!weight %in% Weight) {
"Sorry starter/bench can only be " %>%
paste0(Weight %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
weight_stem <-
weight[1] %>% clean_to_stem()
} else {
weight_stem <-
''
}
clutch_stem <-
clutch_time %>% str_replace_all("\\ ", "+")
ahead_behind_stem <-
ahead_or_behind %>% str_replace_all("\\ ", "+")
defense_stem <-
defense %>%
str_replace_all("\\ ", "+")
general_range_stem <-
general_range %>% str_replace_all("\\ ", "+")
dribble_range_stem <-
dribble_range %>%
str_replace_all("\\ ", "+")
shot_distance_range_stem <-
shot_distance_range %>%
str_replace_all("\\ ", "+")
touch_time_range_stem <-
case_when(touch_time_range %>% is.na() ~ "",
TRUE ~ str_replace_all(touch_time_range, "\\ ", "\\+"))
closest_defender_range_stem <-
case_when(closest_defender_range %>% is.na() ~ "",
TRUE ~ str_replace_all(closest_defender_range, "\\ ", "\\+"))
if (!player_experience %>% is.na()) {
PlayerExperience = c("Rookie", "Sophomore", "Veteran")
if (!player_experience %in% PlayerExperience) {
"Sorry player experience can only be " %>%
paste0(PlayerExperience %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
player_experience_stem <-
player_experience %>% clean_to_stem()
} else {
player_experience_stem <-
''
}
url <-
glue("{base}&DateFrom={date_from_stem}&DateTo={date_to_stem}&GameSegment={game_segment_stem}&LastNGames={last_n_games_stem}&LeagueID=00&Location={location_stem}&MeasureType={measure_type_stem}&LastNGames={last_n_games_stem}&Month={month_stem}&OpponentTeamID={opponent_stem}&Outcome={outcome_stem}&PORound={playoff_round_stem}&PaceAdjust={pace_stem}&PerMode={per_mode_type_stem}&Period={period_stem}&PlusMinus={plus_minus_stem}&Rank={rank_stem}&Season={slugSeason}&SeasonSegment={season_segment_stem}&SeasonType={season_type_stem}&ShotClockRange={shot_clock_range_stem}&{slug_type}={id}&VsConference={conference_against_stem}&VsDivision={division_against_stem}&DraftYear={draft_year_stem}&GameScope={game_scope_stem}&PlayerPosition={player_position_stem}&height={height_stem}&Country={country_stem}&College={college_stem}&DraftPick={draft_pick_stem}&Weight={weight_stem}&StarterBench={starter_bench_range_stem}&PlayerExperience={player_experience_stem}&clutchTime={clutch_stem}&aheadBehind={ahead_behind_stem}&defenseCategory={defense_stem}&pointDiff={point_diff}&closeDefDistRange={closest_defender_range_stem}&touchTimeRange={touch_time_range_stem}&generalRange={general_range_stem}&dribbleRange={dribble_range_stem}&distanceRange={shot_distance_range_stem}") %>%
as.character()
url
}
.players_teams_season_summary <-
function(season = 2017,
type = "player",
table = "general",
season_type = "Regular Season",
measure = "Base",
mode = "PerGame",
defense = "Overall",
is_plus_minus = F,
is_pace_adjusted = F,
period = 0,
is_rank = F,
game_segment = NA ,
division_against = NA,
conference_against = NA,
date_from = NA,
date_to = NA,
last_n_games = 0,
location = NA,
month = 0,
season_segment = NA,
opponent = NA,
outcome = NA,
playoff_round = 0,
player_experience = NA,
player_position = NA,
college = NA,
draft_pick = NA,
draft_year = NA,
game_scope = NA,
country = NA,
weight = NA,
height = NA,
clutch_time = "Last 5 minutes",
ahead_or_behind = "Ahead or Behind",
point_diff = 5,
general_range = "Overall",
dribble_range = "0 Dribbles",
shot_distance_range = "By Zone",
touch_time_range = NA,
closest_defender_range = NA,
shot_clock_range = NA,
starter_bench = NA,
return_message = TRUE) {
if (!'df_nba_team_dict' %>% exists()) {
df_nba_team_dict <- nba_teams()
assign('df_nba_team_dict', df_nba_team_dict, envir = .GlobalEnv)
}
slugSeason <-
generate_season_slug(season = season)
if (return_message) {
glue("Acquiring all {type} {mode} {table} {measure} split tables for the {slugSeason} season") %>% cat(fill = T)
}
url_json <-
.generate_dash_url(
type =type,
query_type = table,
id = "",
season = season,
defense = defense,
season_type = season_type,
measure = measure,
mode = mode,
is_plus_minus = is_plus_minus,
is_pace_adjusted = is_pace_adjusted,
period = period,
is_rank = is_rank,
game_segment = game_segment,
division_against = division_against,
conference_against = conference_against,
date_from = date_from,
date_to = date_to,
last_n_games = last_n_games,
location = location,
month = month,
season_segment = season_segment,
opponent = opponent,
outcome = outcome,
clutch_time = clutch_time,
playoff_round = playoff_round,
player_experience = player_experience,
player_position = player_position,
college = college,
country = country,
weight = weight,
draft_pick = draft_pick,
draft_year = draft_year,
game_scope = game_scope,
height = height,
shot_clock_range = shot_clock_range,
starter_bench = starter_bench,
ahead_or_behind = ahead_or_behind,
point_diff = point_diff,
general_range = general_range,
shot_distance_range = shot_distance_range,
dribble_range = dribble_range,
touch_time_range = touch_time_range,
closest_defender_range = closest_defender_range
)
json <-
url_json %>%
.curl_chinazi()
table_length <-
json$resultSets$rowSet %>% length()
if (table %>% str_to_lower() == "shot locations") {
table_length <- 1
}
data <-
1:table_length %>%
future_map_dfr(function(table_id) {
table_name <-
json$resultSets$name[table_id]
df_parameters <- json$parameters %>% flatten_df()
df_parameters <-
df_parameters %>%
set_names(names(df_parameters) %>% resolve_nba_names())
df_parameters <-
df_parameters %>%
mutate_at(
df_parameters %>% dplyr::select(dplyr::matches("is[A-Z]")) %>% names(),
funs(ifelse(. == "Y", 1, 0) %>% as.logical())
) %>%
mutate(numberTable = table_id) %>%
select(numberTable, everything())
if (table_name == "ShotLocations") {
if (type %>% str_to_lower() == "player") {
df_table <-
json$resultSets$rowSet %>%
data.frame(stringsAsFactors = F) %>%
as_tibble()
actual_names <-
c(
"idPlayer",
"namePlayer",
"idTeam",
"slugTeam",
"agePlayer",
"fgmRestrictedArea",
"fgaRestrictedArea",
"pctFGRestrictedArea",
"fgmInThePaintNonRA",
"fgaInThePaintNonRA",
"pctFGInThePaintNonRA",
"fgmMidRange",
"fgaMidRange",
"pctFGMidRange",
"fgmLeftCorner3",
"fgaLeftCorner3",
"pctFGLeftCorner3",
"fgmRightCorner3",
"fgaRightCorner3",
"pctFGRightCorner3",
"fgmAbovetheBreak3",
"fgaAbovetheBreak3",
"pctFGAbovetheBreak3",
"fgmBackcourt",
"fgaBackcourt",
"pctFGBackcourt"
)
df_table <-
df_table %>%
set_names(actual_names) %>%
munge_nba_data() %>%
mutate(numberTable = table_id) %>%
select(numberTable, everything())
} else {
df_table <-
json$resultSets$rowSet %>%
data.frame(stringsAsFactors = F) %>%
as_tibble()
actual_names <-
c(
"idTeam",
"nameTeam",
"fgmRestrictedArea",
"fgaRestrictedArea",
"pctFGRestrictedArea",
"fgmInThePaintNonRA",
"fgaInThePaintNonRA",
"pctFGInThePaintNonRA",
"fgmMidRange",
"fgaMidRange",
"pctFGMidRange",
"fgmLeftCorner3",
"fgaLeftCorner3",
"pctFGLeftCorner3",
"fgmRightCorner3",
"fgaRightCorner3",
"pctFGRightCorner3",
"fgmAbovetheBreak3",
"fgaAbovetheBreak3",
"pctFGAbovetheBreak3",
"fgmBackcourt",
"fgaBackcourt",
"pctFGBackcourt"
)
df_table <-
df_table %>%
set_names(actual_names) %>%
munge_nba_data() %>%
mutate(numberTable = table_id) %>%
select(numberTable, everything())
}
} else {
df_table <-
json %>%
nba_json_to_df(table_id = table_id) %>%
mutate(numberTable = table_id) %>%
select(numberTable, everything())
}
df_table <-
df_table %>%
left_join(df_parameters %>% select(-one_of(c("idTeam")))) %>%
dplyr::select(one_of(names(df_parameters)), everything()) %>%
suppressMessages() %>%
select(-one_of(c("numberTable"))) %>%
suppressWarnings()
df_table <-
df_table %>%
mutate(nameTable = table_name,
modeSearch = mode,
slugSeason,
yearSeason = season) %>%
select(nameTable, modeSearch, everything())
df_table <-
df_table %>%
dplyr::select(-one_of("idLeague")) %>%
dplyr::select(-dplyr::matches("Group")) %>%
nest(-c(nameTable, slugSeason, yearSeason, modeSearch, typeSeason),
.key = 'dataTable')
return(df_table)
}) %>%
mutate(nameTable = table,
typeResult = type) %>%
dplyr::select(nameTable, typeResult, everything())
data
}
#' NBA teams and player statistics
#'
#' Gets NBA summary statistics tables
#' @param types type of data options include \itemize{
#' \item player
#' \item team
#' }
#' @param tables type of table options include \itemize{
#' \item clutch
#' \item defense
#' \item general
#' \item hustle
#' \item shot locations
#' \item shots
#' \item splits
#' }
#' @param seasons vector of seasons
#' @param season_types vector of season types options \itemize{
#' \item Pre Season
#' \item Regular Season
#' \item Playoffs
#' \item All Star
#' }
#' @param measures vector of measures options \itemize{
#' \item Base
#' \item Advanced
#' \item Defense
#' \item Four Factors
#' \item Misc
#' \item Opponent
#' \item Scoring
#' \item Usage
#' }
#' @param modes vector of modes options \itemize{
#' \item Totals
#' \item MinutesPer
#' \item PerGame
#' \item Per48
#' \item Per40
#' \item Per36
#' \item PerMinute
#' \item PerPossession
#' \item PerPlay
#' \item Per100Possessions
#' \item Per100Plays
#' }
#' @param is_plus_minus if `TRUE` uses plus minus
#' @param is_pace_adjusted if `TRUE` is pace adjusted
#' @param periods vector of periods
#' @param is_rank if `TRUE` returns rank
#' @param game_segments vector of game segments options \itemize{
#' \item NA - All
#' \item First Half
#' \item Second Half
#' \item Overtime
#' }
#' @param divisions_against vector of seasons options \itemize{
#' \item NA - ALL
#' \item Atlantic
#' \item Central
#' \item Northwest
#' \item Pacific
#' \item Southeast
#' \item Southwest
#' \item East
#' \item West
#' }
#' @param conferences_against vector of conferences against options \itemize{
#' \item NA - ALL
#' \item East
#' \item West
#' }
#' @param date_from dates from
#' @param date_to dates to
#' @param last_n_games vector games
#' @param locations vector of locations
#' @param months vector of months 0:12
#' @param season_segments vector of seasons segments options \itemize{
#' \item NA
#' \item Pre All-Star
#' \item Post All-Star
#' }
#' @param opponents vector of opponent ids
#' @param outcomes vector of outcomes options \itemize{
#' \item NA - all
#' \item W
#' \item L
#' }
#' @param playoff_rounds vector of playoff rounds options \code{0:4}
#' @param players_experience vector of experience options \itemize{
#' \item NA
#' \item Rookie
#' \item Sophomore
#' \item Veteran
#' }
#' @param colleges vector of colleges
#' @param draft_picks vector of draft picks options \itemize{
#' \item NA
#' \item 1st Round
#' \item 2nd Round
#' \item 1st Pick
#' \item Lottery Pick
#' \item Top 5 Pick
#' \item Top 10 Pick
#' \item Top 15 Pick
#' \item Top 20 Pick
#' \item Top 25 Pick
#' \item Picks 11 Thru 20
#' \item Picks 21 Thru 30
#' \item Undrafted
#' }
#' @param draft_years numeric vector vector of draft years
#' @param game_scopes vector game scopes options \itemize{
#' \item NA
#' \item Last 10
#' \item Yesterday
#' }
#' @param heights vector of heights options \itemize{
#' \item NA
#' \item LT 6-0
#' \item GT 6-0
#' \item LT 6-4
#' \item GT 6-4
#' \item LT 6-7
#' \item GT 6-7
#' \item LT 6-10
#' \item GT 6-10
#' \item LT 7-0
#' \item GT 7-0
#' }
#' @param shot_clock_ranges character vector of shot clock ranges options \itemize{
#' \item NA
#' \item 24-22
#' \item 22-18 Very Early
#' \item 18-15 Early
#' \item 15-7 Average
#' \item 7-4 Late
#' \item 4-0 Very Late
#' \item ShotClock Off
#' }
#' @param starters_bench vector of starter type options \itemize{
#' \item NA
#' \item Bench
#' \item Starters
#' }
#' @param assign_to_environment if `TRUE` assigns tables to environment
#' @param weights vector of weights options \itemize{
#' \item NA
#' \item LT 200
#' \item GT 200
#' \item LT 225
#' \item GT 225
#' \item LT 250
#' \item GT 250
#' \item LT 275
#' \item GT 275
#' \item LT 300
#' \item GT 300
#' }
#' @param countries vector of countries
#' @param add_mode_names if `TRUE` adds mode names
#' @param players_positions vector of player positions options \itemize{
#' \item NA
#' \item C
#' \item F
#' \item G
#' }
#' @param clutch_times clutch options options \itemize{
#' \item NA
#' \item Last 5 Minutes
#' \item Last 4 Minutes
#' \item Last 3 Minutes
#' \item Last 2 Minutes
#' \item Last 1 Minute
#' \item Last 30 Seconds
#' \item Last 10 Seconds
#' }
#' @param ahead_or_behind ahead of behind type options \itemize{
#' \item Ahead or Behind
#' \item Behind or Tied
#' \item Ahead or Tied
#' }
#' @param defenses defense options include \itemize{
#' \item Overall
#' \item 3 Pointers
#' \item 2 Pointers
#' \item Less Than 6Ft
#' \item Less Than 10Ft
#' \item Greater Than 15Ft
#' }
#' @param general_ranges general shop type ranges options include \itemize{
#' \item Overall
#' \item Catch and Shoot
#' \item Less Than 10 ft
#' \item Pullups
#' }
#' @param dribble_ranges range of dribbles options include \itemize{
#' \item 0 Dribbles
#' \item 1 Dribble
#' \item 2 Dribbles
#' \item 3-6 Dribbles
#' \item 7+ Dribbles
#' }
#' @param shot_distance_ranges shot distance
#' @param touch_time_ranges touch time range options include \itemize{
#' \item Touch < 2 Seconds
#' \item Touch 2-6 Seconds
#' \item Touch 6+ Seconds
#'
#' }
#' @param closest_defender_ranges closest defender range options include \itemize{
#' \item NA
#' \item 0-2 Feet - Very Tight
#' \item 2-4 Feet - Tight
#' \item 4-6 Feet - Open
#' \item 6+ Feet - Wide Open
#' }
#' @param point_diffs numeric vector between \code{1:5}
#' @param return_message if `TRUE` returns a message
#' @family players
#' @family teams
#' @family summary statistics
#' @return a `tibble`
#' @export
#'
#' @examples
#' teams_players_stats(seasons = 2018, types = c("player", "team"),
#' modes = c("PerGame", "Totals"),
#' tables = c("general", "defense", "clutch", "hustle", "shots", "shot locations"))
#' )
teams_players_stats <-
function(seasons = 2018,
types = c("player", "team"),
tables = c("defense"),
season_types = "Regular Season",
measures = "Base",
modes = "PerGame",
defenses = "Overall",
is_plus_minus = F,
is_pace_adjusted = F,
periods = 0,
is_rank = F,
game_segments = NA ,
divisions_against = NA,
conferences_against = NA,
date_from = NA,
date_to = NA,
last_n_games = 0,
locations = NA,
months = 0,
season_segments = NA,
opponents = NA,
countries = NA,
weights = NA,
outcomes = NA,
playoff_rounds = 0,
players_experience = NA,
players_positions = NA,
colleges = NA,
draft_picks = NA,
draft_years = NA,
game_scopes = NA,
heights = NA,
shot_clock_ranges = NA,
clutch_times = "Last 5 Minutes",
ahead_or_behind = "Ahead or Behind",
general_ranges = "Overall",
dribble_ranges = "0 Dribbles",
shot_distance_ranges = "By Zone",
touch_time_ranges = NA,
closest_defender_ranges = NA,
point_diffs = 5,
starters_bench = NA,
assign_to_environment = TRUE,
add_mode_names = T,
return_message = TRUE) {
if (types %>% str_to_lower() %in% c("player", "team") %>% sum(na.rm = T) == 0) {
stop("Result type can only be player and/or team")
}
input_df <-
expand.grid(season = seasons,
type = types,
table = tables,
season_type = season_types,
measure = measures,
defense = defenses,
mode = modes,
general_range =general_ranges,
dribble_range = dribble_ranges,
touch_time_range = touch_time_ranges,
closest_defender_range = closest_defender_ranges,
is_plus_minus = is_plus_minus,
is_pace_adjusted = is_pace_adjusted,
period = periods,
is_rank = is_rank,
game_segment =game_segments,
division_against = divisions_against,
conference_against = conferences_against,
date_from = date_from,
shot_distance_range = shot_distance_ranges,
date_to = date_to,
last_n_games = last_n_games,
location = locations,
month = months,
clutch_time = clutch_times,
ahead_or_behind = ahead_or_behind,
point_diff = point_diffs,
country = countries,
weight = weights,
season_segment = season_segments,
opponent = opponents,
outcome = outcomes,
playoff_round = playoff_rounds,
player_experience = players_experience,
player_position = players_positions,
college = colleges,
draft_pick = draft_picks,
draft_year = draft_years,
game_scope = game_scopes,
height = heights,
shot_clock_range = shot_clock_ranges,
starter_bench = starters_bench
,stringsAsFactors = F) %>%
dplyr::as_tibble()
players_teams_season_summary_safe <-
possibly(.players_teams_season_summary, tibble())
all_data <-
1:nrow(input_df) %>%
future_map_dfr(function(x) {
df_row <-
input_df %>% slice(x)
df_row %$%
players_teams_season_summary_safe(
season = season,
table = table,
type = type,
season_type = season_type,
measure = measure,
mode = mode,
is_plus_minus = is_plus_minus,
is_pace_adjusted = is_pace_adjusted,
period = period,
is_rank = is_rank,
game_segment = game_segment,
division_against = division_against,
conference_against = conference_against,
date_from = date_from,
date_to = date_to,
last_n_games = last_n_games,
location = location,
month = month,
season_segment = season_segment,
opponent = opponent,
outcome = outcome,
playoff_round = playoff_round,
player_experience = player_experience,
player_position = player_position,
college = college,
draft_pick = draft_pick,
draft_year = draft_year,
game_scope = game_scope,
height = height,
shot_clock_range = shot_clock_range,
starter_bench = starter_bench,
defense = defense,
country = country,
clutch_time = clutch_time,
weight = weight,
ahead_or_behind = ahead_or_behind,
point_diff = point_diff,
general_range = general_range,
dribble_range = dribble_range,
touch_time_range = touch_time_range,
closest_defender_range = closest_defender_range,
shot_distance_range = shot_distance_range,
return_message = return_message
)
})
if (assign_to_environment) {
types <- all_data$typeResult %>% unique()
types %>%
walk(function(type){
result_type <-
glue("{type}s") %>%
str_to_title()
df_table <-
all_data %>%
filter(typeResult == type) %>%
select(-typeResult)
tables <-
df_table$nameTable %>% unique()
tables %>%
walk(function(table){
tn <- table %>%
str_split("\\ ") %>%
flatten_chr() %>%
str_to_title() %>%
str_c(collapse = "")
table_name <-
glue("data{tn}{result_type}") %>%
as.character()
data <-
df_table %>%
filter(nameTable == table) %>%
select(-nameTable) %>%
unnest() %>%
remove_zero_sum_cols()
assign(table_name, data, envir = .GlobalEnv)
})
})
}
all_data
}
abresler/nbastatR documentation built on Nov. 9, 2023, 2:33 p.m.
R Package Documentation
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Defines functions teams_players_stats .players_teams_season_summary .generate_dash_url
Documented in teams_players_stats
.dictionary_nba_queries <-
memoise(function() {
tibble(typeQuery = c("splits", "splits", "general", "general", "defense", "defense", "clutch", "clutch",
"hustle", "hustle", "shots", "shots", "shot locations", "shot locations"),
slugQuery = c("teamdashboardbygeneralsplits", "playerdashboardbygeneralsplits", "leaguedashteamstats", "leaguedashplayerstats" ,"leaguedashptdefend", "leaguedashptdefend", "leaguedashteamclutch", "leaguedashplayerclutch","leaguehustlestatsteam", "leaguehustlestatsplayer", "leaguedashteamptshot", "leaguedashplayerptshot",
"leaguedashteamshotlocations", "leaguedashplayershotlocations"),
typeSearch = c("team", "player", "team", "player", "team", "player", "team", "player", "team", "player", "team", "player", "team", "player"))
})
.generate_dash_url <-
function(query_type = "general",
type = "team",
id = "",
season = 2017,
season_type = "Regular Season",
measure = "Base",
mode = "PerGame",
defense = "Overall",
is_plus_minus = F,
is_pace_adjusted = F,
period = 0,
is_rank = F,
game_segment = NA ,
division_against = NA,
conference_against = NA,
date_from = NA,
date_to = NA,
weight = NA,
last_n_games = 0,
location = NA,
month = 0,
season_segment = NA,
opponent = NA,
outcome = NA,
playoff_round = 0,
ahead_or_behind = "Ahead or Behind",
general_range = "Overall",
dribble_range = "0 Dribbles",
touch_time_range = NA,
closest_defender_range = NA,
shot_distance_range = "By Zone",
point_diff = 5,
country = NA,
player_experience = NA, # c(NA, "Rookie", "Sophomore", "Veteran"),
player_position = NA, # c(NA, "F", "C", "G", "C-F", "F-C", "F-G", "G-F"),
college = NA,
draft_pick = NA, #c( NA, "First Round", "2nd Round", "1st Pick", "Lottery Pick", "Top 5 Pick", "Top 10 Pick", "Top 15 Pick", "Top 20 Pick", "Top 25 Pick", "Picks 11 Thru 20", "Picks 21 Thru 30", "Undrafted")
draft_year = NA,
clutch_time = "Last 5 Minutes",
game_scope = NA, #c(NA, "Yesterday", "Last 10"),
height = NA, # c(NA, "LT 6-0", "GT 6-0", "LT 6-4", "GT 6-4", "LT 6-7", "GT 6-7", "LT 6-10", "GT 6-10", "LT 7-0", "GT 7-0"),
shot_clock_range = NA, #c(NA, "24-22", "22-18 Very Early", "18-15 Early", "15-7 Average", "7-4 Late", "4-0 Very Late", "ShotClock Off")
starter_bench = NA # c(NA, "Starters", "Bench"),
) {
if (!'df_nba_team_dict' %>% exists()) {
df_nba_team_dict <- nba_teams()
assign('df_nba_team_dict', df_nba_team_dict, envir = .GlobalEnv)
}
df_query_dict <-
.dictionary_nba_queries()
query_slug <-
df_query_dict %>%
filter(typeQuery %>% str_detect(str_to_lower(query_type))) %>%
filter(typeSearch %>% str_detect(str_to_lower(type))) %>%
pull(slugQuery)
base <-
glue("https://stats.nba.com/stats/{query_slug}?") %>%
as.character()
slug_type <-
case_when(type %>% str_to_lower() == "team" ~ "TeamID",
TRUE ~ 'PlayerID')
if (season < 1996) {
stop("Sorry data only goes back to the 1996-97 Season")
}
slugSeason <-
generate_season_slug(season = season)
if (!opponent %>% is.na()) {
if (!opponent %>% str_to_lower() %in% df_nba_team_dict$nameTeam %>% str_to_lower()) {
"Opponent must be either " %>%
paste0(df_nba_team_dict$nameTeam %>% paste0(collapse = ', ')) %>%
stop()
}
opponent_stem <-
df_nba_team_dict %>%
mutate(nameTeam = nameTeam %>% str_to_lower()) %>%
dplyr::filter(nameTeam == opponent %>% str_to_lower()) %>%
.$idTeam
} else {
opponent_stem <-
0
}
if (!conference_against %>% is.na()) {
if (!conference_against %in% c("East", "West")) {
stop("Sorry conference against can only be East or West")
}
conference_against_stem <-
conference_against %>% clean_to_stem()
} else {
conference_against_stem <-
''
}
if (!date_from %>% is.na()) {
date_from_stem <-
date_from %>% clean_to_stem()
} else {
date_from_stem <-
''
}
if (!date_to %>% is.na()) {
date_to_stem <-
date_to %>% clean_to_stem()
} else {
date_to_stem <-
''
}
if (!division_against %>% is.na()) {
if (!division_against %in% c("Atlantic",
"Central",
"Northwest",
"Pacific",
"Southeast",
"Southwest")) {
stop(
"Sorry division against can only be Atlantic, Central\nNorthwest, Pacific, Southeast, orSouthwest"
)
}
division_against_stem <-
division_against[1] %>% clean_to_stem
} else {
division_against_stem <-
''
}
if (!game_segment %>% is.na()) {
GameSegment = c("First Half", "Second Half", "Overtime")
if (!game_segment %in% GameSegment) {
"Sorry game segment can only be " %>%
paste0(GameSegment %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
game_segment_stem <-
game_segment %>% clean_to_stem()
} else {
game_segment_stem <-
''
}
if (!last_n_games %>% is.na()) {
if (!last_n_games >= 0) {
stop("Last N games must be over 0")
}
last_n_games_stem <-
last_n_games
} else {
last_n_games_stem <-
0
}
if (!location %>% is.na()) {
if (!location %in% c("Home", "Road")) {
stop("Sorry location can only be Home or Road")
}
location_stem <-
location %>% clean_to_stem()
} else {
location_stem <-
''
}
if (!measure %>% is.na()) {
MeasureType = c("Base",
"Advanced",
"Defense",
"Misc",
"Scoring",
"Usage",
"Four Factors",
"Opponent")
if (!measure %in% MeasureType) {
"Sorry measure type can only be " %>%
paste0(measure %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
measure_type_stem <-
measure %>% clean_to_stem()
} else {
measure_type_stem <-
'Base'
}
if (!outcome %>% is.na()) {
Outcome = c("W", "L")
if (!outcome %in% Outcome) {
"Sorry outcome can only be " %>%
paste0(Outcome %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
outcome_stem <-
outcome %>% clean_to_stem
} else {
outcome_stem <-
''
}
if (playoff_round > 4) {
stop("Playoff round can only be zero to 4")
} else {
playoff_round_stem <-
playoff_round
}
if (is_pace_adjusted) {
pace_stem <-
"Y"
} else {
pace_stem <-
"N"
}
if (!mode %>% is.na()) {
PerMode = c(
"Totals",
"PerGame",
"MinutesPer",
"Per48",
"Per40",
"Per36",
"PerMinute",
"PerPossession",
"PerPlay",
"Per100Possessions",
"Per100Plays"
)
mode <-
mode[1] %>%
str_replace('\\ ', '')
if (!mode[1] %>% clean_to_stem() %in% PerMode) {
"Sorry per mode can only be " %>%
paste0(mode[1] %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
per_mode_type_stem <-
mode[1] %>% clean_to_stem()
} else {
per_mode_stem <-
'Totals'
}
if (month > 12) {
stop("Month can only be zero to 12")
} else {
month_stem <-
month
}
if (period > 14) {
stop("Period can only be zero to 14")
} else {
period_stem <-
period
}
if (is_plus_minus) {
plus_minus_stem <-
"Y"
} else {
plus_minus_stem <-
"N"
}
if (is_rank) {
rank_stem <-
"Y"
} else {
rank_stem <-
"N"
}
if (!season_segment %>% is.na()) {
SeasonSegment = c("Post All-Star", "Pre All-Star")
if (!season_segment[1] %in% SeasonSegment) {
"Sorry season segment can only be " %>%
paste0(SeasonSegment %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
season_segment_stem <-
season_segment %>% clean_to_stem()
} else {
season_segment_stem <-
''
}
if (!season_type %>% is.na()) {
SeasonType = c('Regular Season', 'Pre Season', 'Playoffs', 'All Star')
if (!season_type %in% SeasonType) {
"Sorry season type can only be " %>%
paste0(SeasonType %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
season_type_stem <-
season_type %>% clean_to_stem()
} else {
season_type_stem <-
'Regular+Season'
}
if (!shot_clock_range %>% is.na()) {
ShotClockRange = c(
"24-22",
"22-18 Very Early",
"18-15 Early",
"15-7 Average",
"7-4 Late",
"4-0 Very Late",
"ShotClock Off"
)
if (!shot_clock_range %in% ShotClockRange) {
"Sorry shot clock range can only be " %>%
paste0(ShotClockRange %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
shot_clock_range_stem <-
shot_clock_range %>% clean_to_stem()
} else {
shot_clock_range_stem <-
''
}
if (!draft_pick %>% is.na()) {
DraftPick = c(
"First Round",
"2nd Round",
"1st Pick",
"Lottery Pick",
"Top 5 Pick",
"Top 10 Pick",
"Top 15 Pick",
"Top 20 Pick",
"Top 25 Pick",
"Picks 11 Thru 20",
"Picks 21 Thru 30",
"Undrafted"
)
if (!draft_pick %in% DraftPick) {
"Sorry draft pick can only be " %>%
paste0(DraftPick %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
draft_pick_stem <-
draft_pick %>% clean_to_stem()
} else {
draft_pick_stem <-
''
}
if (!draft_year %>% is.na()) {
if (!draft_year > 1947) {
stop("Draft year must be after 1947")
}
draft_year_stem <-
draft_year
} else {
draft_year_stem <-
''
}
if (!game_scope %>% is.na()) {
GameScope = c("Yesterday", "Last 10")
if (!game_scope %in% GameScope) {
"Sorry game scope can only be " %>%
paste0(GameScope %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
game_scope_stem <-
game_scope %>% clean_to_stem()
} else {
game_scope_stem <-
''
}
if (!player_position %>% is.na()) {
PlayerPosition = c("F", "C", "G", "C-F", "F-C", "F-G", "G-F")
if (!player_position %in% PlayerPosition) {
"Sorry player position can only be " %>%
paste0(PlayerPosition %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
player_position_stem <-
player_position[1] %>% clean_to_stem()
} else {
player_position_stem <-
''
}
if (!height %>% is.na) {
Height = c(
"LT 6-0",
"GT 6-0",
"LT 6-4",
"GT 6-4",
"LT 6-7",
"GT 6-7",
"LT 6-10",
"GT 6-10",
"LT 7-0",
"GT 7-0"
)
if (!height %in% Height) {
"Sorry height can only be " %>%
paste0(Height %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
height_stem <-
height %>% clean_to_stem()
} else {
height_stem <-
''
}
if (!college %>% is.na()) {
college_stem <-
college[1] %>% clean_to_stem()
} else {
college_stem <-
''
}
if (!country %>% is.na()) {
country_stem <-
country %>% clean_to_stem
} else {
country_stem <-
''
}
if (!starter_bench %>% is.na()) {
StarterBench = c("Starters", "Bench")
if (!starter_bench %in% StarterBench) {
"Sorry starter/bench can only be " %>%
paste0(StarterBench %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
starter_bench_stem <-
starter_bench[1] %>% clean_to_stem()
} else {
starter_bench_range_stem <-
''
}
if (!weight %>% is.na) {
Weight = c(
"LT 200",
"GT 200",
"LT 225",
"GT 225",
"LT 250",
"GT 250",
"LT 275",
"GT 275",
"LT 300",
"GT 300"
)
if (!weight %in% Weight) {
"Sorry starter/bench can only be " %>%
paste0(Weight %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
weight_stem <-
weight[1] %>% clean_to_stem()
} else {
weight_stem <-
''
}
clutch_stem <-
clutch_time %>% str_replace_all("\\ ", "+")
ahead_behind_stem <-
ahead_or_behind %>% str_replace_all("\\ ", "+")
defense_stem <-
defense %>%
str_replace_all("\\ ", "+")
general_range_stem <-
general_range %>% str_replace_all("\\ ", "+")
dribble_range_stem <-
dribble_range %>%
str_replace_all("\\ ", "+")
shot_distance_range_stem <-
shot_distance_range %>%
str_replace_all("\\ ", "+")
touch_time_range_stem <-
case_when(touch_time_range %>% is.na() ~ "",
TRUE ~ str_replace_all(touch_time_range, "\\ ", "\\+"))
closest_defender_range_stem <-
case_when(closest_defender_range %>% is.na() ~ "",
TRUE ~ str_replace_all(closest_defender_range, "\\ ", "\\+"))
if (!player_experience %>% is.na()) {
PlayerExperience = c("Rookie", "Sophomore", "Veteran")
if (!player_experience %in% PlayerExperience) {
"Sorry player experience can only be " %>%
paste0(PlayerExperience %>% paste0(collapse = ', ')) %>%
stop(call. = F)
}
player_experience_stem <-
player_experience %>% clean_to_stem()
} else {
player_experience_stem <-
''
}
url <-
glue("{base}&DateFrom={date_from_stem}&DateTo={date_to_stem}&GameSegment={game_segment_stem}&LastNGames={last_n_games_stem}&LeagueID=00&Location={location_stem}&MeasureType={measure_type_stem}&LastNGames={last_n_games_stem}&Month={month_stem}&OpponentTeamID={opponent_stem}&Outcome={outcome_stem}&PORound={playoff_round_stem}&PaceAdjust={pace_stem}&PerMode={per_mode_type_stem}&Period={period_stem}&PlusMinus={plus_minus_stem}&Rank={rank_stem}&Season={slugSeason}&SeasonSegment={season_segment_stem}&SeasonType={season_type_stem}&ShotClockRange={shot_clock_range_stem}&{slug_type}={id}&VsConference={conference_against_stem}&VsDivision={division_against_stem}&DraftYear={draft_year_stem}&GameScope={game_scope_stem}&PlayerPosition={player_position_stem}&height={height_stem}&Country={country_stem}&College={college_stem}&DraftPick={draft_pick_stem}&Weight={weight_stem}&StarterBench={starter_bench_range_stem}&PlayerExperience={player_experience_stem}&clutchTime={clutch_stem}&aheadBehind={ahead_behind_stem}&defenseCategory={defense_stem}&pointDiff={point_diff}&closeDefDistRange={closest_defender_range_stem}&touchTimeRange={touch_time_range_stem}&generalRange={general_range_stem}&dribbleRange={dribble_range_stem}&distanceRange={shot_distance_range_stem}") %>%
as.character()
url
}
.players_teams_season_summary <-
function(season = 2017,
type = "player",
table = "general",
season_type = "Regular Season",
measure = "Base",
mode = "PerGame",
defense = "Overall",
is_plus_minus = F,
is_pace_adjusted = F,
period = 0,
is_rank = F,
game_segment = NA ,
division_against = NA,
conference_against = NA,
date_from = NA,
date_to = NA,
last_n_games = 0,
location = NA,
month = 0,
season_segment = NA,
opponent = NA,
outcome = NA,
playoff_round = 0,
player_experience = NA,
player_position = NA,
college = NA,
draft_pick = NA,
draft_year = NA,
game_scope = NA,
country = NA,
weight = NA,
height = NA,
clutch_time = "Last 5 minutes",
ahead_or_behind = "Ahead or Behind",
point_diff = 5,
general_range = "Overall",
dribble_range = "0 Dribbles",
shot_distance_range = "By Zone",
touch_time_range = NA,
closest_defender_range = NA,
shot_clock_range = NA,
starter_bench = NA,
return_message = TRUE) {
if (!'df_nba_team_dict' %>% exists()) {
df_nba_team_dict <- nba_teams()
assign('df_nba_team_dict', df_nba_team_dict, envir = .GlobalEnv)
}
slugSeason <-
generate_season_slug(season = season)
if (return_message) {
glue("Acquiring all {type} {mode} {table} {measure} split tables for the {slugSeason} season") %>% cat(fill = T)
}
url_json <-
.generate_dash_url(
type =type,
query_type = table,
id = "",
season = season,
defense = defense,
season_type = season_type,
measure = measure,
mode = mode,
is_plus_minus = is_plus_minus,
is_pace_adjusted = is_pace_adjusted,
period = period,
is_rank = is_rank,
game_segment = game_segment,
division_against = division_against,
conference_against = conference_against,
date_from = date_from,
date_to = date_to,
last_n_games = last_n_games,
location = location,
month = month,
season_segment = season_segment,
opponent = opponent,
outcome = outcome,
clutch_time = clutch_time,
playoff_round = playoff_round,
player_experience = player_experience,
player_position = player_position,
college = college,
country = country,
weight = weight,
draft_pick = draft_pick,
draft_year = draft_year,
game_scope = game_scope,
height = height,
shot_clock_range = shot_clock_range,
starter_bench = starter_bench,
ahead_or_behind = ahead_or_behind,
point_diff = point_diff,
general_range = general_range,
shot_distance_range = shot_distance_range,
dribble_range = dribble_range,
touch_time_range = touch_time_range,
closest_defender_range = closest_defender_range
)
json <-
url_json %>%
.curl_chinazi()
table_length <-
json$resultSets$rowSet %>% length()
if (table %>% str_to_lower() == "shot locations") {
table_length <- 1
}
data <-
1:table_length %>%
future_map_dfr(function(table_id) {
table_name <-
json$resultSets$name[table_id]
df_parameters <- json$parameters %>% flatten_df()
df_parameters <-
df_parameters %>%
set_names(names(df_parameters) %>% resolve_nba_names())
df_parameters <-
df_parameters %>%
mutate_at(
df_parameters %>% dplyr::select(dplyr::matches("is[A-Z]")) %>% names(),
funs(ifelse(. == "Y", 1, 0) %>% as.logical())
) %>%
mutate(numberTable = table_id) %>%
select(numberTable, everything())
if (table_name == "ShotLocations") {
if (type %>% str_to_lower() == "player") {
df_table <-
json$resultSets$rowSet %>%
data.frame(stringsAsFactors = F) %>%
as_tibble()
actual_names <-
c(
"idPlayer",
"namePlayer",
"idTeam",
"slugTeam",
"agePlayer",
"fgmRestrictedArea",
"fgaRestrictedArea",
"pctFGRestrictedArea",
"fgmInThePaintNonRA",
"fgaInThePaintNonRA",
"pctFGInThePaintNonRA",
"fgmMidRange",
"fgaMidRange",
"pctFGMidRange",
"fgmLeftCorner3",
"fgaLeftCorner3",
"pctFGLeftCorner3",
"fgmRightCorner3",
"fgaRightCorner3",
"pctFGRightCorner3",
"fgmAbovetheBreak3",
"fgaAbovetheBreak3",
"pctFGAbovetheBreak3",
"fgmBackcourt",
"fgaBackcourt",
"pctFGBackcourt"
)
df_table <-
df_table %>%
set_names(actual_names) %>%
munge_nba_data() %>%
mutate(numberTable = table_id) %>%
select(numberTable, everything())
} else {
df_table <-
json$resultSets$rowSet %>%
data.frame(stringsAsFactors = F) %>%
as_tibble()
actual_names <-
c(
"idTeam",
"nameTeam",
"fgmRestrictedArea",
"fgaRestrictedArea",
"pctFGRestrictedArea",
"fgmInThePaintNonRA",
"fgaInThePaintNonRA",
"pctFGInThePaintNonRA",
"fgmMidRange",
"fgaMidRange",
"pctFGMidRange",
"fgmLeftCorner3",
"fgaLeftCorner3",
"pctFGLeftCorner3",
"fgmRightCorner3",
"fgaRightCorner3",
"pctFGRightCorner3",
"fgmAbovetheBreak3",
"fgaAbovetheBreak3",
"pctFGAbovetheBreak3",
"fgmBackcourt",
"fgaBackcourt",
"pctFGBackcourt"
)
df_table <-
df_table %>%
set_names(actual_names) %>%
munge_nba_data() %>%
mutate(numberTable = table_id) %>%
select(numberTable, everything())
}
} else {
df_table <-
json %>%
nba_json_to_df(table_id = table_id) %>%
mutate(numberTable = table_id) %>%
select(numberTable, everything())
}
df_table <-
df_table %>%
left_join(df_parameters %>% select(-one_of(c("idTeam")))) %>%
dplyr::select(one_of(names(df_parameters)), everything()) %>%
suppressMessages() %>%
select(-one_of(c("numberTable"))) %>%
suppressWarnings()
df_table <-
df_table %>%
mutate(nameTable = table_name,
modeSearch = mode,
slugSeason,
yearSeason = season) %>%
select(nameTable, modeSearch, everything())
df_table <-
df_table %>%
dplyr::select(-one_of("idLeague")) %>%
dplyr::select(-dplyr::matches("Group")) %>%
nest(-c(nameTable, slugSeason, yearSeason, modeSearch, typeSeason),
.key = 'dataTable')
return(df_table)
}) %>%
mutate(nameTable = table,
typeResult = type) %>%
dplyr::select(nameTable, typeResult, everything())
data
}
#' NBA teams and player statistics
#'
#' Gets NBA summary statistics tables
#' @param types type of data options include \itemize{
#' \item player
#' \item team
#' }
#' @param tables type of table options include \itemize{
#' \item clutch
#' \item defense
#' \item general
#' \item hustle
#' \item shot locations
#' \item shots
#' \item splits
#' }
#' @param seasons vector of seasons
#' @param season_types vector of season types options \itemize{
#' \item Pre Season
#' \item Regular Season
#' \item Playoffs
#' \item All Star
#' }
#' @param measures vector of measures options \itemize{
#' \item Base
#' \item Advanced
#' \item Defense
#' \item Four Factors
#' \item Misc
#' \item Opponent
#' \item Scoring
#' \item Usage
#' }
#' @param modes vector of modes options \itemize{
#' \item Totals
#' \item MinutesPer
#' \item PerGame
#' \item Per48
#' \item Per40
#' \item Per36
#' \item PerMinute
#' \item PerPossession
#' \item PerPlay
#' \item Per100Possessions
#' \item Per100Plays
#' }
#' @param is_plus_minus if `TRUE` uses plus minus
#' @param is_pace_adjusted if `TRUE` is pace adjusted
#' @param periods vector of periods
#' @param is_rank if `TRUE` returns rank
#' @param game_segments vector of game segments options \itemize{
#' \item NA - All
#' \item First Half
#' \item Second Half
#' \item Overtime
#' }
#' @param divisions_against vector of seasons options \itemize{
#' \item NA - ALL
#' \item Atlantic
#' \item Central
#' \item Northwest
#' \item Pacific
#' \item Southeast
#' \item Southwest
#' \item East
#' \item West
#' }
#' @param conferences_against vector of conferences against options \itemize{
#' \item NA - ALL
#' \item East
#' \item West
#' }
#' @param date_from dates from
#' @param date_to dates to
#' @param last_n_games vector games
#' @param locations vector of locations
#' @param months vector of months 0:12
#' @param season_segments vector of seasons segments options \itemize{
#' \item NA
#' \item Pre All-Star
#' \item Post All-Star
#' }
#' @param opponents vector of opponent ids
#' @param outcomes vector of outcomes options \itemize{
#' \item NA - all
#' \item W
#' \item L
#' }
#' @param playoff_rounds vector of playoff rounds options \code{0:4}
#' @param players_experience vector of experience options \itemize{
#' \item NA
#' \item Rookie
#' \item Sophomore
#' \item Veteran
#' }
#' @param colleges vector of colleges
#' @param draft_picks vector of draft picks options \itemize{
#' \item NA
#' \item 1st Round
#' \item 2nd Round
#' \item 1st Pick
#' \item Lottery Pick
#' \item Top 5 Pick
#' \item Top 10 Pick
#' \item Top 15 Pick
#' \item Top 20 Pick
#' \item Top 25 Pick
#' \item Picks 11 Thru 20
#' \item Picks 21 Thru 30
#' \item Undrafted
#' }
#' @param draft_years numeric vector vector of draft years
#' @param game_scopes vector game scopes options \itemize{
#' \item NA
#' \item Last 10
#' \item Yesterday
#' }
#' @param heights vector of heights options \itemize{
#' \item NA
#' \item LT 6-0
#' \item GT 6-0
#' \item LT 6-4
#' \item GT 6-4
#' \item LT 6-7
#' \item GT 6-7
#' \item LT 6-10
#' \item GT 6-10
#' \item LT 7-0
#' \item GT 7-0
#' }
#' @param shot_clock_ranges character vector of shot clock ranges options \itemize{
#' \item NA
#' \item 24-22
#' \item 22-18 Very Early
#' \item 18-15 Early
#' \item 15-7 Average
#' \item 7-4 Late
#' \item 4-0 Very Late
#' \item ShotClock Off
#' }
#' @param starters_bench vector of starter type options \itemize{
#' \item NA
#' \item Bench
#' \item Starters
#' }
#' @param assign_to_environment if `TRUE` assigns tables to environment
#' @param weights vector of weights options \itemize{
#' \item NA
#' \item LT 200
#' \item GT 200
#' \item LT 225
#' \item GT 225
#' \item LT 250
#' \item GT 250
#' \item LT 275
#' \item GT 275
#' \item LT 300
#' \item GT 300
#' }
#' @param countries vector of countries
#' @param add_mode_names if `TRUE` adds mode names
#' @param players_positions vector of player positions options \itemize{
#' \item NA
#' \item C
#' \item F
#' \item G
#' }
#' @param clutch_times clutch options options \itemize{
#' \item NA
#' \item Last 5 Minutes
#' \item Last 4 Minutes
#' \item Last 3 Minutes
#' \item Last 2 Minutes
#' \item Last 1 Minute
#' \item Last 30 Seconds
#' \item Last 10 Seconds
#' }
#' @param ahead_or_behind ahead of behind type options \itemize{
#' \item Ahead or Behind
#' \item Behind or Tied
#' \item Ahead or Tied
#' }
#' @param defenses defense options include \itemize{
#' \item Overall
#' \item 3 Pointers
#' \item 2 Pointers
#' \item Less Than 6Ft
#' \item Less Than 10Ft
#' \item Greater Than 15Ft
#' }
#' @param general_ranges general shop type ranges options include \itemize{
#' \item Overall
#' \item Catch and Shoot
#' \item Less Than 10 ft
#' \item Pullups
#' }
#' @param dribble_ranges range of dribbles options include \itemize{
#' \item 0 Dribbles
#' \item 1 Dribble
#' \item 2 Dribbles
#' \item 3-6 Dribbles
#' \item 7+ Dribbles
#' }
#' @param shot_distance_ranges shot distance
#' @param touch_time_ranges touch time range options include \itemize{
#' \item Touch < 2 Seconds
#' \item Touch 2-6 Seconds
#' \item Touch 6+ Seconds
#'
#' }
#' @param closest_defender_ranges closest defender range options include \itemize{
#' \item NA
#' \item 0-2 Feet - Very Tight
#' \item 2-4 Feet - Tight
#' \item 4-6 Feet - Open
#' \item 6+ Feet - Wide Open
#' }
#' @param point_diffs numeric vector between \code{1:5}
#' @param return_message if `TRUE` returns a message
#' @family players
#' @family teams
#' @family summary statistics
#' @return a `tibble`
#' @export
#'
#' @examples
#' teams_players_stats(seasons = 2018, types = c("player", "team"),
#' modes = c("PerGame", "Totals"),
#' tables = c("general", "defense", "clutch", "hustle", "shots", "shot locations"))
#' )
teams_players_stats <-
function(seasons = 2018,
types = c("player", "team"),
tables = c("defense"),
season_types = "Regular Season",
measures = "Base",
modes = "PerGame",
defenses = "Overall",
is_plus_minus = F,
is_pace_adjusted = F,
periods = 0,
is_rank = F,
game_segments = NA ,
divisions_against = NA,
conferences_against = NA,
date_from = NA,
date_to = NA,
last_n_games = 0,
locations = NA,
months = 0,
season_segments = NA,
opponents = NA,
countries = NA,
weights = NA,
outcomes = NA,
playoff_rounds = 0,
players_experience = NA,
players_positions = NA,
colleges = NA,
draft_picks = NA,
draft_years = NA,
game_scopes = NA,
heights = NA,
shot_clock_ranges = NA,
clutch_times = "Last 5 Minutes",
ahead_or_behind = "Ahead or Behind",
general_ranges = "Overall",
dribble_ranges = "0 Dribbles",
shot_distance_ranges = "By Zone",
touch_time_ranges = NA,
closest_defender_ranges = NA,
point_diffs = 5,
starters_bench = NA,
assign_to_environment = TRUE,
add_mode_names = T,
return_message = TRUE) {
if (types %>% str_to_lower() %in% c("player", "team") %>% sum(na.rm = T) == 0) {
stop("Result type can only be player and/or team")
}
input_df <-
expand.grid(season = seasons,
type = types,
table = tables,
season_type = season_types,
measure = measures,
defense = defenses,
mode = modes,
general_range =general_ranges,
dribble_range = dribble_ranges,
touch_time_range = touch_time_ranges,
closest_defender_range = closest_defender_ranges,
is_plus_minus = is_plus_minus,
is_pace_adjusted = is_pace_adjusted,
period = periods,
is_rank = is_rank,
game_segment =game_segments,
division_against = divisions_against,
conference_against = conferences_against,
date_from = date_from,
shot_distance_range = shot_distance_ranges,
date_to = date_to,
last_n_games = last_n_games,
location = locations,
month = months,
clutch_time = clutch_times,
ahead_or_behind = ahead_or_behind,
point_diff = point_diffs,
country = countries,
weight = weights,
season_segment = season_segments,
opponent = opponents,
outcome = outcomes,
playoff_round = playoff_rounds,
player_experience = players_experience,
player_position = players_positions,
college = colleges,
draft_pick = draft_picks,
draft_year = draft_years,
game_scope = game_scopes,
height = heights,
shot_clock_range = shot_clock_ranges,
starter_bench = starters_bench
,stringsAsFactors = F) %>%
dplyr::as_tibble()
players_teams_season_summary_safe <-
possibly(.players_teams_season_summary, tibble())
all_data <-
1:nrow(input_df) %>%
future_map_dfr(function(x) {
df_row <-
input_df %>% slice(x)
df_row %$%
players_teams_season_summary_safe(
season = season,
table = table,
type = type,
season_type = season_type,
measure = measure,
mode = mode,
is_plus_minus = is_plus_minus,
is_pace_adjusted = is_pace_adjusted,
period = period,
is_rank = is_rank,
game_segment = game_segment,
division_against = division_against,
conference_against = conference_against,
date_from = date_from,
date_to = date_to,
last_n_games = last_n_games,
location = location,
month = month,
season_segment = season_segment,
opponent = opponent,
outcome = outcome,
playoff_round = playoff_round,
player_experience = player_experience,
player_position = player_position,
college = college,
draft_pick = draft_pick,
draft_year = draft_year,
game_scope = game_scope,
height = height,
shot_clock_range = shot_clock_range,
starter_bench = starter_bench,
defense = defense,
country = country,
clutch_time = clutch_time,
weight = weight,
ahead_or_behind = ahead_or_behind,
point_diff = point_diff,
general_range = general_range,
dribble_range = dribble_range,
touch_time_range = touch_time_range,
closest_defender_range = closest_defender_range,
shot_distance_range = shot_distance_range,
return_message = return_message
)
})
if (assign_to_environment) {
types <- all_data$typeResult %>% unique()
types %>%
walk(function(type){
result_type <-
glue("{type}s") %>%
str_to_title()
df_table <-
all_data %>%
filter(typeResult == type) %>%
select(-typeResult)
tables <-
df_table$nameTable %>% unique()
tables %>%
walk(function(table){
tn <- table %>%
str_split("\\ ") %>%
flatten_chr() %>%
str_to_title() %>%
str_c(collapse = "")
table_name <-
glue("data{tn}{result_type}") %>%
as.character()
data <-
df_table %>%
filter(nameTable == table) %>%
select(-nameTable) %>%
unnest() %>%
remove_zero_sum_cols()
assign(table_name, data, envir = .GlobalEnv)
})
})
}
all_data
}
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