library(tidyverse)
library(nbastatR)
library(stringr)
library(corrplot)
library(reactable)
library(reactablefmtr)
library(dplyr)
Sys.setenv("VROOM_CONNECTION_SIZE" = 131072 * 2)data pull
teams <- nba_teams() %>%
filter( isNonNBATeam == 0,
yearPlayedLast == 2023,
idConference > 0)
league_id <- teams$idTeam
get_shots <- function(x) {
df <- teams_shots(
team_ids = league_id,
seasons = x,
season_types = "Regular Season"
)
return(df)
}
seasons <- 2015:2024
# Empty list to store the results
results_list <- list()
# Loop through each season and call the function
for (season in seasons) {
results_list[[as.character(season)]] <- get_shots(season)
}## Atlanta Hawks 2014-15 shot data
## Boston Celtics 2014-15 shot data
## Cleveland Cavaliers 2014-15 shot data
## New Orleans Pelicans 2014-15 shot data
## Chicago Bulls 2014-15 shot data
## Dallas Mavericks 2014-15 shot data
## Denver Nuggets 2014-15 shot data
## Golden State Warriors 2014-15 shot data
## Houston Rockets 2014-15 shot data
## Los Angeles Clippers 2014-15 shot data
## Los Angeles Lakers 2014-15 shot data
## Miami Heat 2014-15 shot data
## Milwaukee Bucks 2014-15 shot data
## Minnesota Timberwolves 2014-15 shot data
## Brooklyn Nets 2014-15 shot data
## New York Knicks 2014-15 shot data
## Orlando Magic 2014-15 shot data
## Indiana Pacers 2014-15 shot data
## Philadelphia 76ers 2014-15 shot data
## Phoenix Suns 2014-15 shot data
## Portland Trail Blazers 2014-15 shot data
## Sacramento Kings 2014-15 shot data
## San Antonio Spurs 2014-15 shot data
## Oklahoma City Thunder 2014-15 shot data
## Toronto Raptors 2014-15 shot data
## Utah Jazz 2014-15 shot data
## Memphis Grizzlies 2014-15 shot data
## Washington Wizards 2014-15 shot data
## Detroit Pistons 2014-15 shot data
## Charlotte Hornets 2014-15 shot data
## Atlanta Hawks 2015-16 shot data
## Boston Celtics 2015-16 shot data
## Cleveland Cavaliers 2015-16 shot data
## New Orleans Pelicans 2015-16 shot data
## Chicago Bulls 2015-16 shot data
## Dallas Mavericks 2015-16 shot data
## Denver Nuggets 2015-16 shot data
## Golden State Warriors 2015-16 shot data
## Houston Rockets 2015-16 shot data
## Los Angeles Clippers 2015-16 shot data
## Los Angeles Lakers 2015-16 shot data
## Miami Heat 2015-16 shot data
## Milwaukee Bucks 2015-16 shot data
## Minnesota Timberwolves 2015-16 shot data
## Brooklyn Nets 2015-16 shot data
## New York Knicks 2015-16 shot data
## Orlando Magic 2015-16 shot data
## Indiana Pacers 2015-16 shot data
## Philadelphia 76ers 2015-16 shot data
## Phoenix Suns 2015-16 shot data
## Portland Trail Blazers 2015-16 shot data
## Sacramento Kings 2015-16 shot data
## San Antonio Spurs 2015-16 shot data
## Oklahoma City Thunder 2015-16 shot data
## Toronto Raptors 2015-16 shot data
## Utah Jazz 2015-16 shot data
## Memphis Grizzlies 2015-16 shot data
## Washington Wizards 2015-16 shot data
## Detroit Pistons 2015-16 shot data
## Charlotte Hornets 2015-16 shot data
## Atlanta Hawks 2016-17 shot data
## Boston Celtics 2016-17 shot data
## Cleveland Cavaliers 2016-17 shot data
## New Orleans Pelicans 2016-17 shot data
## Chicago Bulls 2016-17 shot data
## Dallas Mavericks 2016-17 shot data
## Denver Nuggets 2016-17 shot data
## Golden State Warriors 2016-17 shot data
## Houston Rockets 2016-17 shot data
## Los Angeles Clippers 2016-17 shot data
## Los Angeles Lakers 2016-17 shot data
## Miami Heat 2016-17 shot data
## Milwaukee Bucks 2016-17 shot data
## Minnesota Timberwolves 2016-17 shot data
## Brooklyn Nets 2016-17 shot data
## New York Knicks 2016-17 shot data
## Orlando Magic 2016-17 shot data
## Indiana Pacers 2016-17 shot data
## Philadelphia 76ers 2016-17 shot data
## Phoenix Suns 2016-17 shot data
## Portland Trail Blazers 2016-17 shot data
## Sacramento Kings 2016-17 shot data
## San Antonio Spurs 2016-17 shot data
## Oklahoma City Thunder 2016-17 shot data
## Toronto Raptors 2016-17 shot data
## Utah Jazz 2016-17 shot data
## Memphis Grizzlies 2016-17 shot data
## Washington Wizards 2016-17 shot data
## Detroit Pistons 2016-17 shot data
## Charlotte Hornets 2016-17 shot data
## Atlanta Hawks 2017-18 shot data
## Boston Celtics 2017-18 shot data
## Cleveland Cavaliers 2017-18 shot data
## New Orleans Pelicans 2017-18 shot data
## Chicago Bulls 2017-18 shot data
## Dallas Mavericks 2017-18 shot data
## Denver Nuggets 2017-18 shot data
## Golden State Warriors 2017-18 shot data
## Houston Rockets 2017-18 shot data
## Los Angeles Clippers 2017-18 shot data
## Los Angeles Lakers 2017-18 shot data
## Miami Heat 2017-18 shot data
## Milwaukee Bucks 2017-18 shot data
## Minnesota Timberwolves 2017-18 shot data
## Brooklyn Nets 2017-18 shot data
## New York Knicks 2017-18 shot data
## Orlando Magic 2017-18 shot data
## Indiana Pacers 2017-18 shot data
## Philadelphia 76ers 2017-18 shot data
## Phoenix Suns 2017-18 shot data
## Portland Trail Blazers 2017-18 shot data
## Sacramento Kings 2017-18 shot data
## San Antonio Spurs 2017-18 shot data
## Oklahoma City Thunder 2017-18 shot data
## Toronto Raptors 2017-18 shot data
## Utah Jazz 2017-18 shot data
## Memphis Grizzlies 2017-18 shot data
## Washington Wizards 2017-18 shot data
## Detroit Pistons 2017-18 shot data
## Charlotte Hornets 2017-18 shot data
## Atlanta Hawks 2018-19 shot data
## Boston Celtics 2018-19 shot data
## Cleveland Cavaliers 2018-19 shot data
## New Orleans Pelicans 2018-19 shot data
## Chicago Bulls 2018-19 shot data
## Dallas Mavericks 2018-19 shot data
## Denver Nuggets 2018-19 shot data
## Golden State Warriors 2018-19 shot data
## Houston Rockets 2018-19 shot data
## Los Angeles Clippers 2018-19 shot data
## Los Angeles Lakers 2018-19 shot data
## Miami Heat 2018-19 shot data
## Milwaukee Bucks 2018-19 shot data
## Minnesota Timberwolves 2018-19 shot data
## Brooklyn Nets 2018-19 shot data
## New York Knicks 2018-19 shot data
## Orlando Magic 2018-19 shot data
## Indiana Pacers 2018-19 shot data
## Philadelphia 76ers 2018-19 shot data
## Phoenix Suns 2018-19 shot data
## Portland Trail Blazers 2018-19 shot data
## Sacramento Kings 2018-19 shot data
## San Antonio Spurs 2018-19 shot data
## Oklahoma City Thunder 2018-19 shot data
## Toronto Raptors 2018-19 shot data
## Utah Jazz 2018-19 shot data
## Memphis Grizzlies 2018-19 shot data
## Washington Wizards 2018-19 shot data
## Detroit Pistons 2018-19 shot data
## Charlotte Hornets 2018-19 shot data
## Atlanta Hawks 2019-20 shot data
## Boston Celtics 2019-20 shot data
## Cleveland Cavaliers 2019-20 shot data
## New Orleans Pelicans 2019-20 shot data
## Chicago Bulls 2019-20 shot data
## Dallas Mavericks 2019-20 shot data
## Denver Nuggets 2019-20 shot data
## Golden State Warriors 2019-20 shot data
## Houston Rockets 2019-20 shot data
## Los Angeles Clippers 2019-20 shot data
## Los Angeles Lakers 2019-20 shot data
## Miami Heat 2019-20 shot data
## Milwaukee Bucks 2019-20 shot data
## Minnesota Timberwolves 2019-20 shot data
## Brooklyn Nets 2019-20 shot data
## New York Knicks 2019-20 shot data
## Orlando Magic 2019-20 shot data
## Indiana Pacers 2019-20 shot data
## Philadelphia 76ers 2019-20 shot data
## Phoenix Suns 2019-20 shot data
## Portland Trail Blazers 2019-20 shot data
## Sacramento Kings 2019-20 shot data
## San Antonio Spurs 2019-20 shot data
## Oklahoma City Thunder 2019-20 shot data
## Toronto Raptors 2019-20 shot data
## Utah Jazz 2019-20 shot data
## Memphis Grizzlies 2019-20 shot data
## Washington Wizards 2019-20 shot data
## Detroit Pistons 2019-20 shot data
## Charlotte Hornets 2019-20 shot data
## Atlanta Hawks 2020-21 shot data
## Boston Celtics 2020-21 shot data
## Cleveland Cavaliers 2020-21 shot data
## New Orleans Pelicans 2020-21 shot data
## Chicago Bulls 2020-21 shot data
## Dallas Mavericks 2020-21 shot data
## Denver Nuggets 2020-21 shot data
## Golden State Warriors 2020-21 shot data
## Houston Rockets 2020-21 shot data
## Los Angeles Clippers 2020-21 shot data
## Los Angeles Lakers 2020-21 shot data
## Miami Heat 2020-21 shot data
## Milwaukee Bucks 2020-21 shot data
## Minnesota Timberwolves 2020-21 shot data
## Brooklyn Nets 2020-21 shot data
## New York Knicks 2020-21 shot data
## Orlando Magic 2020-21 shot data
## Indiana Pacers 2020-21 shot data
## Philadelphia 76ers 2020-21 shot data
## Phoenix Suns 2020-21 shot data
## Portland Trail Blazers 2020-21 shot data
## Sacramento Kings 2020-21 shot data
## San Antonio Spurs 2020-21 shot data
## Oklahoma City Thunder 2020-21 shot data
## Toronto Raptors 2020-21 shot data
## Utah Jazz 2020-21 shot data
## Memphis Grizzlies 2020-21 shot data
## Washington Wizards 2020-21 shot data
## Detroit Pistons 2020-21 shot data
## Charlotte Hornets 2020-21 shot data
## Atlanta Hawks 2021-22 shot data
## Boston Celtics 2021-22 shot data
## Cleveland Cavaliers 2021-22 shot data
## New Orleans Pelicans 2021-22 shot data
## Chicago Bulls 2021-22 shot data
## Dallas Mavericks 2021-22 shot data
## Denver Nuggets 2021-22 shot data
## Golden State Warriors 2021-22 shot data
## Houston Rockets 2021-22 shot data
## Los Angeles Clippers 2021-22 shot data
## Los Angeles Lakers 2021-22 shot data
## Miami Heat 2021-22 shot data
## Milwaukee Bucks 2021-22 shot data
## Minnesota Timberwolves 2021-22 shot data
## Brooklyn Nets 2021-22 shot data
## New York Knicks 2021-22 shot data
## Orlando Magic 2021-22 shot data
## Indiana Pacers 2021-22 shot data
## Philadelphia 76ers 2021-22 shot data
## Phoenix Suns 2021-22 shot data
## Portland Trail Blazers 2021-22 shot data
## Sacramento Kings 2021-22 shot data
## San Antonio Spurs 2021-22 shot data
## Oklahoma City Thunder 2021-22 shot data
## Toronto Raptors 2021-22 shot data
## Utah Jazz 2021-22 shot data
## Memphis Grizzlies 2021-22 shot data
## Washington Wizards 2021-22 shot data
## Detroit Pistons 2021-22 shot data
## Charlotte Hornets 2021-22 shot data
## Atlanta Hawks 2022-23 shot data
## Boston Celtics 2022-23 shot data
## Cleveland Cavaliers 2022-23 shot data
## New Orleans Pelicans 2022-23 shot data
## Chicago Bulls 2022-23 shot data
## Dallas Mavericks 2022-23 shot data
## Denver Nuggets 2022-23 shot data
## Golden State Warriors 2022-23 shot data
## Houston Rockets 2022-23 shot data
## Los Angeles Clippers 2022-23 shot data
## Los Angeles Lakers 2022-23 shot data
## Miami Heat 2022-23 shot data
## Milwaukee Bucks 2022-23 shot data
## Minnesota Timberwolves 2022-23 shot data
## Brooklyn Nets 2022-23 shot data
## New York Knicks 2022-23 shot data
## Orlando Magic 2022-23 shot data
## Indiana Pacers 2022-23 shot data
## Philadelphia 76ers 2022-23 shot data
## Phoenix Suns 2022-23 shot data
## Portland Trail Blazers 2022-23 shot data
## Sacramento Kings 2022-23 shot data
## San Antonio Spurs 2022-23 shot data
## Oklahoma City Thunder 2022-23 shot data
## Toronto Raptors 2022-23 shot data
## Utah Jazz 2022-23 shot data
## Memphis Grizzlies 2022-23 shot data
## Washington Wizards 2022-23 shot data
## Detroit Pistons 2022-23 shot data
## Charlotte Hornets 2022-23 shot data
## Atlanta Hawks 2023-24 shot data
## Boston Celtics 2023-24 shot data
## Cleveland Cavaliers 2023-24 shot data
## New Orleans Pelicans 2023-24 shot data
## Chicago Bulls 2023-24 shot data
## Dallas Mavericks 2023-24 shot data
## Denver Nuggets 2023-24 shot data
## Golden State Warriors 2023-24 shot data
## Houston Rockets 2023-24 shot data
## Los Angeles Clippers 2023-24 shot data
## Los Angeles Lakers 2023-24 shot data
## Miami Heat 2023-24 shot data
## Milwaukee Bucks 2023-24 shot data
## Minnesota Timberwolves 2023-24 shot data
## Brooklyn Nets 2023-24 shot data
## New York Knicks 2023-24 shot data
## Orlando Magic 2023-24 shot data
## Indiana Pacers 2023-24 shot data
## Philadelphia 76ers 2023-24 shot data
## Phoenix Suns 2023-24 shot data
## Portland Trail Blazers 2023-24 shot data
## Sacramento Kings 2023-24 shot data
## San Antonio Spurs 2023-24 shot data
## Oklahoma City Thunder 2023-24 shot data
## Toronto Raptors 2023-24 shot data
## Utah Jazz 2023-24 shot data
## Memphis Grizzlies 2023-24 shot data
## Washington Wizards 2023-24 shot data
## Detroit Pistons 2023-24 shot data
## Charlotte Hornets 2023-24 shot data# Combine the results into a single data frame if needed
combined_df <- do.call(rbind, results_list)
combined_df$dateGame <- as.Date(combined_df$dateGame, format = "%Y%m%d")
combined_3pt <- combined_df %>%
filter(typeShot == "3PT Field Goal",
typeAction != "Tip Shot",
zoneBasic != "Mid-Range",
zoneBasic != "In The Paint (Non-RA)",
zoneBasic != "Restricted Area",
zoneBasic != "Backcourt")data manipulation
clean_df <- combined_3pt %>%
mutate(Type =
case_when(
str_detect(typeAction, "Jump Shot") ~ "Set",
str_detect(typeAction, "Jump Bank Shot") ~ "Set",
str_detect(typeAction, "Hook Shot") ~ "Set",
str_detect(typeAction, "Putback Layup Shot") ~ "Set",
str_detect(typeAction, "Fadeaway Jump Shot") ~ "Fadeaway",
str_detect(typeAction, "Turnaround Fadeaway shot") ~ "Fadeaway",
str_detect(typeAction, "Turnaround Fadeaway Bank Jump Shot") ~ "Fadeaway",
str_detect(typeAction, "Turnaround Bank shot") ~ "Fadeaway",
str_detect(typeAction, "Turnaround Bank Hook shot") ~ "Fadeaway",
str_detect(typeAction, "Fadeaway Bank shot") ~ "Fadeaway",
str_detect(typeAction, "Turnaround Jump Shot") ~ "Fadeaway",
str_detect(typeAction, "Turnaround Hook Shot") ~ "Fadeaway",
str_detect(typeAction, "Running Bank shot") ~ "Movement",
str_detect(typeAction, "Running Jump Shot") ~ "Movement",
str_detect(typeAction, "Floating Jump shot") ~ "Movement",
str_detect(typeAction, "Driving Layup Shot") ~ "Movement",
str_detect(typeAction, "Driving Bank Shot") ~ "Movement",
str_detect(typeAction, "Driving Bank shot") ~ "Movement",
str_detect(typeAction, "Driving Bank Hook Shot") ~ "Movement",
str_detect(typeAction, "Driving Hook Shot") ~ "Movement",
str_detect(typeAction, "Driving Floating Jump Shot") ~ "Movement",
str_detect(typeAction, "Driving Floating Bank Jump Shot") ~ "Movement",
str_detect(typeAction, "Layup Shot") ~ "Movement",
str_detect(typeAction, "Tip Shot") ~ "Movement",
str_detect(typeAction, "Running Hook Shot") ~ "Movement",
str_detect(typeAction, "Driving Jump shot") ~ "Fadeaway",
str_detect(typeAction, "Pullup Jump shot") ~ "Pullup",
str_detect(typeAction, "Running Pull-up Jump Shot") ~ "Pullup",
str_detect(typeAction, "Pullup Bank shot") ~ "Pullup",
str_detect(typeAction, "Step Back Jump shot") ~ "Step Back",
str_detect(typeAction, "Step Back Bank Jump shot") ~ "Step Back",
TRUE ~ "other"
)) %>%
mutate(Result = case_when(
str_detect(typeEvent, "Made Shot") ~ 1,
str_detect(typeEvent, "Missed Shot") ~ 0,
TRUE ~ NA_real_
))game_logs <- clean_df %>%
group_by(idPlayer, namePlayer, idGame, zoneBasic, Type, dateGame) %>%
summarize(
makes = sum(Result),
attempts = n()
) %>%
ungroup()
cor_date <- clean_df %>%
group_by(dateGame, zoneBasic, Type) %>%
summarize(
makes = sum(Result),
attempts = n()
) %>%
ungroup()
percents <- game_logs %>%
filter(dateGame > '2022-10-01') %>%
group_by(zoneBasic, Type) %>%
summarize(
total_makes = sum(makes),
total_attempts = sum(attempts)
) %>%
mutate(
percent = total_makes / total_attempts
) %>%
ungroup() %>%
filter(total_attempts > 50)percents_player <- game_logs %>%
filter(dateGame > '2022-10-01') %>%
group_by(zoneBasic, Type, idPlayer, namePlayer) %>%
summarize(
total_makes = sum(makes),
total_attempts = sum(attempts)
) %>%
mutate(
percent = total_makes / total_attempts
) %>%
ungroup() %>%
filter(total_attempts > 10) %>%
filter(zoneBasic == "Above the Break 3")
percents_player$total_attempts <- as.numeric(percents_player$total_attempts)
corners <- game_logs %>%
filter(dateGame > '2022-10-01') %>%
group_by(zoneBasic, idPlayer, namePlayer) %>%
summarize(
total_makes = sum(makes),
total_attempts = sum(attempts)
) %>%
mutate(
percent = total_makes / total_attempts
) %>%
ungroup() %>%
filter(zoneBasic != "Above the Break 3")
corner_league <- game_logs %>%
filter(dateGame > '2022-10-01') %>%
group_by(zoneBasic) %>%
summarize(
total_makes = sum(makes),
total_attempts = sum(attempts)
) %>%
mutate(
percent = total_makes / total_attempts
) %>%
ungroup() %>%
filter(zoneBasic != "Above the Break 3")
corners$total_attempts <- as.numeric(corners$total_attempts)correlation
game_logs2 <- game_logs %>%
separate(dateGame, into = c("year", "month", "day"), sep = '-', remove = FALSE)
percents_player2 <- game_logs2 %>%
group_by(zoneBasic, Type, month, year) %>%
summarize(
total_makes = sum(makes),
total_attempts = sum(attempts)
) %>%
mutate(
percent = total_makes / total_attempts
) %>%
ungroup() %>%
select(zoneBasic, Type, percent, month, year) %>%
pivot_wider(
names_from = c(zoneBasic, Type),
values_from = percent
)
replace_with_mean <- function(x) {
mean_val <- mean(x, na.rm = TRUE) # Compute the mean of the column
x[is.na(x)] <- mean_val # Replace NA values with the mean
return(x)
}
# Replace NA values with the mean of each column
data_cleaned <- percents_player2 %>%
mutate_at(vars(starts_with("Right Corner 3_")), replace_with_mean) %>%
mutate_at(vars(starts_with("Left Corner 3_")), replace_with_mean) %>%
select(-c(month, year))
corr_J <- cor(as.matrix(data_cleaned))anchor function - regular season
above_break_pull_up <- percents[[3, 5]]
above_break_stepback <- percents[[5, 5]]
above_break_set <- percents[[4, 5]]
corner_left <- corner_league[[1, 4]]
corner_right <- corner_league[[2,4]]
# function for anchored shooting but does not adjust by other 3pt shots
shooting <- function(x) {
df <- percents_player %>%
filter(namePlayer == x)
df <- df %>%
mutate( anchored = case_when(
str_detect(Type, "Pullup") ~ ((total_makes + (100 * above_break_pull_up))/ (100 + total_attempts)),
str_detect(Type, "Step Back") ~ ((total_makes + (100 * above_break_stepback))/ (100 + total_attempts)),
str_detect(Type, "Set") ~ ((total_makes + (100 * above_break_set))/ (100 + total_attempts))
))
df$zoneBasic <- paste(df$zoneBasic, df$Type)
df <- df %>%
select(zoneBasic,
idPlayer,
namePlayer,
total_makes,
total_attempts,
percent,
anchored)
df_2 <- corners %>%
filter(namePlayer == x)
df_2 <- df_2 %>%
mutate(anchored = case_when(
str_detect(zoneBasic, "Left Corner 3") ~ ((total_makes + (100 * corner_left))/ (100 + total_attempts)),
str_detect(zoneBasic, "Right Corner 3") ~ ((total_makes + (100 * corner_right))/ (100 + total_attempts))
))
df_3 <- rbind(df, df_2)
return(df_3)
}
shooting("LeBron James")## # A tibble: 5 × 7
## zoneBasic idPlayer namePlayer total_makes total_attempts percent anchored
## <chr> <dbl> <chr> <dbl> <dbl> <dbl> <dbl>
## 1 Above the Bre… 2544 LeBron Ja… 56 151 0.371 0.358
## 2 Above the Bre… 2544 LeBron Ja… 169 443 0.381 0.378
## 3 Above the Bre… 2544 LeBron Ja… 13 66 0.197 0.292
## 4 Left Corner 3 2544 LeBron Ja… 10 34 0.294 0.362
## 5 Right Corner 3 2544 LeBron Ja… 20 42 0.476 0.415function for adjusted anchors
shooting_adj <- function(x) {
df <- percents_player %>%
filter(namePlayer == x)
df <- df %>%
mutate( anchored = case_when(
str_detect(Type, "Pullup") ~ ((total_makes + (100 * above_break_pull_up))/ (100 + total_attempts)),
str_detect(Type, "Step Back") ~ ((total_makes + (100 * above_break_stepback))/ (100 + total_attempts)),
str_detect(Type, "Set") ~ ((total_makes + (100 * above_break_set))/ (100 + total_attempts))
))
df$zoneBasic <- paste(df$zoneBasic, df$Type)
df <- df %>%
select(zoneBasic,
idPlayer,
namePlayer,
total_makes,
total_attempts,
percent,
anchored)
df_2 <- corners %>%
filter(namePlayer == x)
df_2 <- df_2 %>%
mutate(anchored = case_when(
str_detect(zoneBasic, "Left Corner 3") ~ ((total_makes + (100 * corner_left))/ (100 + total_attempts)),
str_detect(zoneBasic, "Right Corner 3") ~ ((total_makes + (100 * corner_right))/ (100 + total_attempts))
))
df_3 <- rbind(df, df_2)
df_3 <- df_3 %>%
mutate(adjusted =
ifelse(zoneBasic == "Above the Break 3 Pullup",
( (anchored * 100) + (50 * df_3$anchored[df_3$zoneBasic == "Above the Break 3 Step Back"]) + (50 * df_3$anchored[df_3$zoneBasic == "Above the Break 3 Set"]) ) / 200,
ifelse(zoneBasic == "Above the Break 3 Step Back",
( (anchored * 100) + (50 * df_3$anchored[df_3$zoneBasic == "Above the Break 3 Pullup"]) + (50 * df_3$anchored[df_3$zoneBasic == "Above the Break 3 Set"]) ) / 200,
ifelse(zoneBasic == "Above the Break 3 Set",
( (anchored * 140) + (30 * df_3$anchored[df_3$zoneBasic == "Above the Break 3 Step Back"]) + (30 * df_3$anchored[df_3$zoneBasic == "Above the Break 3 Pullup"]) ) / 200,
ifelse(zoneBasic == "Right Corner 3",
( (anchored * 100) + (65 * df_3$anchored[df_3$zoneBasic == "Left Corner 3"]) + (35 * df_3$anchored[df_3$zoneBasic == "Above the Break 3 Set"]) ) / 200,
( (anchored * 100) + (65 * df_3$anchored[df_3$zoneBasic == "Right Corner 3"]) + (35 * df_3$anchored[df_3$zoneBasic == "Above the Break 3 Set"]) ) / 200
)))))
df_3 <- df_3 %>%
select(namePlayer,
zoneBasic,
total_makes,
total_attempts,
percent,
anchored,
adjusted) %>%
mutate_at(vars(c(percent, anchored, adjusted)), round, digits = 4)
return(df_3)
}
shooting_adj("Nikola Jokic")## # A tibble: 5 × 7
## namePlayer zoneBasic total_makes total_attempts percent anchored adjusted
## <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Nikola Jokic Above the B… 14 28 0.5 0.374 0.372
## 2 Nikola Jokic Above the B… 113 306 0.369 0.368 0.369
## 3 Nikola Jokic Above the B… 9 20 0.45 0.371 0.371
## 4 Nikola Jokic Left Corner… 2 7 0.286 0.379 0.375
## 5 Nikola Jokic Right Corne… 1 7 0.143 0.374 0.374playoff adjusted anchors
above_break_pull_up_p <- .3317
above_break_stepback_p <- .3213
above_break_set_p <- .3577
corner_left_p <- .3788
corner_right_p <- .3766
shooting_adj_pf <- function(x) {
df <- percents_player %>%
filter(namePlayer == x)
df <- df %>%
mutate( anchored = case_when(
str_detect(Type, "Pullup") ~ ((total_makes + (100 * above_break_pull_up_p))/ (100 + total_attempts)),
str_detect(Type, "Step Back") ~ ((total_makes + (100 * above_break_stepback_p))/ (100 + total_attempts)),
str_detect(Type, "Set") ~ ((total_makes + (100 * above_break_set_p))/ (100 + total_attempts))
))
df$zoneBasic <- paste(df$zoneBasic, df$Type)
df <- df %>%
select(zoneBasic,
idPlayer,
namePlayer,
total_makes,
total_attempts,
percent,
anchored)
df_2 <- corners %>%
filter(namePlayer == x)
df_2 <- df_2 %>%
mutate(anchored = case_when(
str_detect(zoneBasic, "Left Corner 3") ~ ((total_makes + (100 * corner_left_p))/ (100 + total_attempts)),
str_detect(zoneBasic, "Right Corner 3") ~ ((total_makes + (100 * corner_right_p))/ (100 + total_attempts))
))
df_3 <- rbind(df, df_2)
df_3 <- df_3 %>%
mutate(adjusted =
ifelse(zoneBasic == "Above the Break 3 Pullup",
( (anchored * 100) + (50 * df_3$anchored[df_3$zoneBasic == "Above the Break 3 Step Back"]) + (50 * df_3$anchored[df_3$zoneBasic == "Above the Break 3 Set"]) ) / 200,
ifelse(zoneBasic == "Above the Break 3 Step Back",
( (anchored * 100) + (50 * df_3$anchored[df_3$zoneBasic == "Above the Break 3 Pullup"]) + (50 * df_3$anchored[df_3$zoneBasic == "Above the Break 3 Set"]) ) / 200,
ifelse(zoneBasic == "Above the Break 3 Set",
( (anchored * 140) + (30 * df_3$anchored[df_3$zoneBasic == "Above the Break 3 Step Back"]) + (30 * df_3$anchored[df_3$zoneBasic == "Above the Break 3 Pullup"]) ) / 200,
ifelse(zoneBasic == "Right Corner 3",
( (anchored * 100) + (65 * df_3$anchored[df_3$zoneBasic == "Left Corner 3"]) + (35 * df_3$anchored[df_3$zoneBasic == "Above the Break 3 Set"]) ) / 200,
( (anchored * 100) + (65 * df_3$anchored[df_3$zoneBasic == "Right Corner 3"]) + (35 * df_3$anchored[df_3$zoneBasic == "Above the Break 3 Set"]) ) / 200
)))))
df_3 <- df_3 %>%
select(namePlayer,
zoneBasic,
total_makes,
total_attempts,
percent,
anchored,
adjusted) %>%
mutate_at(vars(c(percent, anchored, adjusted)), round, digits = 4)
return(df_3)
}
shooting_adj_pf("Nikola Jokic")## # A tibble: 5 × 7
## namePlayer zoneBasic total_makes total_attempts percent anchored adjusted
## <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
## 1 Nikola Jokic Above the B… 14 28 0.5 0.368 0.362
## 2 Nikola Jokic Above the B… 113 306 0.369 0.366 0.363
## 3 Nikola Jokic Above the B… 9 20 0.45 0.343 0.355
## 4 Nikola Jokic Left Corner… 2 7 0.286 0.373 0.368
## 5 Nikola Jokic Right Corne… 1 7 0.143 0.361 0.366shooting_adj("LeBron James") %>%
reactable(theme = espn()) %>%
add_title("LeBron James adjusted 3pt shooting - Regular Season")shooting_adj_pf("LeBron James") %>%
reactable(theme = espn()) %>%
add_title("LeBron James adjusted 3pt shooting - Playoffs")