Expected points was determined by multiplying a player’s season fg% for a given zone by the value of a made shot from that zone.
If a player shoots 36% from the right corner 3, than the expected point formula would be: 3 * .36
Expected Free throw points utilizes player’s career ft% instead of just this season.
library(tidyverse)
library(nbastatR)
library(plyr)
library(dplyr)
library(reactable)
library(reactablefmtr)
library(jsonlite)
library(janitor)
library(purrr)
library(rvest)
Sys.setenv("VROOM_CONNECTION_SIZE" = 131072 * 2)pbp_url_team <- "https://api.pbpstats.com/get-game-logs/nba?Season=2022-23&SeasonType=Playoffs&EntityId=1610612743&EntityType=Team"
pbp_team <- read_json(pbp_url_team)
team_df <- pbp_team[["multi_row_table_data"]] %>%
bind_rows() %>%
clean_names()
pbp_url_opp <- "https://api.pbpstats.com/get-game-logs/nba?Season=2022-23&SeasonType=Playoffs&EntityId=1610612743&EntityType=Opponent"
pbp_opp <- read_json(pbp_url_opp)
opp_df <- pbp_opp[["multi_row_table_data"]] %>%
bind_rows() %>%
clean_names()team_points <- team_df %>%
select(date,
ft_points,
points)
opp_points <- opp_df %>%
mutate( opp_points = points) %>%
select(date,
opp_points)
nugs_results <- right_join(team_points,opp_points) %>%
mutate( result = points - opp_points) %>%
select(date,
result,
ft_points)#Jeff Green
pbp_url_1 <- "https://api.pbpstats.com/get-game-logs/nba?Season=2022-23&SeasonType=Playoffs&EntityId=201145&EntityType=Player"
pbp_1 <- read_json(pbp_url_1)
df_1 <- pbp_1[["multi_row_table_data"]] %>%
bind_rows() %>%
clean_names() %>%
filter( team == "DEN") %>%
mutate( expected_ft_points = fta * .803,
'Jeff Green' = expected_ft_points) %>%
select(date,
'Jeff Green') %>%
drop_na()#DeAndre Jordan
pbp_url_2 <- "https://api.pbpstats.com/get-game-logs/nba?Season=2022-23&SeasonType=Playoffs&EntityId=201599&EntityType=Player"
pbp_2 <- read_json(pbp_url_2)
df_2 <- pbp_2[["multi_row_table_data"]] %>%
bind_rows() %>%
clean_names() %>%
filter( team == "DEN") %>%
mutate( 'DeAndre Jordan' = fta * .475) %>%
select(date,
'DeAndre Jordan') %>%
drop_na()#Kentavious Caldwell-Pope
pbp_url_5 <- "https://api.pbpstats.com/get-game-logs/nba?Season=2022-23&SeasonType=Playoffs&EntityId=203484&EntityType=Player"
pbp_5 <- read_json(pbp_url_5)
df_5 <- pbp_5[["multi_row_table_data"]] %>%
bind_rows() %>%
clean_names() %>%
filter( team == "DEN") %>%
mutate( 'Kentavious Caldwell-Pope' = fta * .814) %>%
select(date,
'Kentavious Caldwell-Pope') %>%
drop_na()#Aaron Gordon
pbp_url_6 <- "https://api.pbpstats.com/get-game-logs/nba?Season=2022-23&SeasonType=Playoffs&EntityId=203932&EntityType=Player"
pbp_6 <- read_json(pbp_url_6)
df_6 <- pbp_6[["multi_row_table_data"]] %>%
bind_rows() %>%
clean_names() %>%
filter( team == "DEN") %>%
mutate( 'Aaron Gordon' = fta * .687) %>%
select(date,
'Aaron Gordon') %>%
drop_na()#Nikola Jokic
pbp_url_7 <- "https://api.pbpstats.com/get-game-logs/nba?Season=2022-23&SeasonType=Playoffs&EntityId=203999&EntityType=Player"
pbp_7 <- read_json(pbp_url_7)
df_7 <- pbp_7[["multi_row_table_data"]] %>%
bind_rows() %>%
clean_names() %>%
filter( team == "DEN") %>%
mutate( 'Nikola Jokic' = fta * .829) %>%
select(date,
'Nikola Jokic') %>%
drop_na()#Jamal Murray
pbp_url_8 <- "https://api.pbpstats.com/get-game-logs/nba?Season=2022-23&SeasonType=Playoffs&EntityId=1627750&EntityType=Player"
pbp_8 <- read_json(pbp_url_8)
df_8 <- pbp_8[["multi_row_table_data"]] %>%
bind_rows() %>%
clean_names() %>%
filter( team == "DEN") %>%
mutate( 'Jamal Murray' = fta * .87) %>%
select(date,
'Jamal Murray') %>%
drop_na()#Bruce Brown
pbp_url_12 <- "https://api.pbpstats.com/get-game-logs/nba?Season=2022-23&SeasonType=Playoffs&EntityId=1628971&EntityType=Player"
pbp_12 <- read_json(pbp_url_12)
df_12 <- pbp_12[["multi_row_table_data"]] %>%
bind_rows() %>%
clean_names() %>%
filter( team == "DEN") %>%
mutate( 'Bruce Brown' = fta * .749) %>%
select(date,
'Bruce Brown') %>%
drop_na()#Michael Porter Jr
pbp_url_13 <- "https://api.pbpstats.com/get-game-logs/nba?Season=2022-23&SeasonType=Playoffs&EntityId=1629008&EntityType=Player"
pbp_13 <- read_json(pbp_url_13)
df_13 <- pbp_13[["multi_row_table_data"]] %>%
bind_rows() %>%
clean_names() %>%
filter( team == "DEN") %>%
mutate( 'Michael Porter Jr.' = fta * .749) %>%
select(date,
'Michael Porter Jr.') %>%
drop_na()#Christian Braun
pbp_url_16 <- "https://api.pbpstats.com/get-game-logs/nba?Season=2022-23&SeasonType=Playoffs&EntityId=1631128&EntityType=Player"
pbp_16 <- read_json(pbp_url_16)
df_16 <- pbp_16[["multi_row_table_data"]] %>%
bind_rows() %>%
clean_names() %>%
filter( team == "DEN") %>%
mutate( 'Christian Braun' = fta * .625) %>%
select(date,
'Christian Braun') %>%
drop_na()exp_ft <- left_join(nugs_results, df_1) %>%
left_join(df_2) %>%
left_join(df_5) %>%
left_join(df_6) %>%
left_join(df_7) %>%
left_join(df_8) %>%
left_join(df_12) %>%
left_join(df_13) %>%
left_join(df_16)
exp_ft[is.na(exp_ft)] <- 0
exp_ft$'Exp. Total' <- exp_ft$'Jeff Green' +
exp_ft$'DeAndre Jordan' +
exp_ft$'Kentavious Caldwell-Pope' +
exp_ft$'Aaron Gordon' +
exp_ft$'Nikola Jokic' +
exp_ft$'Jamal Murray' +
exp_ft$'Bruce Brown' +
exp_ft$'Christian Braun' +
exp_ft$'Michael Porter Jr.'
exp_ft$'Free throw luck' <- exp_ft$ft_points - exp_ft$'Exp. Total'
exp_ft <- exp_ft %>%
mutate( 'win/loss' = case_when(
result > 0 ~ "Win",
result < 0 ~ "Loss",
))
exp_ft_table <- exp_ft %>%
select(
date,
'win/loss',
'Free throw luck',
ft_points,
'Exp. Total'
) %>%
mutate_at(vars(`Free throw luck`,
`Exp. Total`), funs(round(.,2)))pbp_url_team2 <- "https://api.pbpstats.com/get-game-logs/nba?Season=2022-23&SeasonType=Playoffs&EntityId=1610612743&EntityType=Team"
pbp_team2 <- read_json(pbp_url_team2)
team_df2 <- pbp_team2[["multi_row_table_data"]] %>%
bind_rows() %>%
clean_names()
pbp_url_opp2 <- "https://api.pbpstats.com/get-game-logs/nba?Season=2022-23&SeasonType=Playoffs&EntityId=1610612743&EntityType=Opponent"
pbp_opp2 <- read_json(pbp_url_opp2)
opp_df2 <- pbp_opp2[["multi_row_table_data"]] %>%
bind_rows() %>%
clean_names()team_points2 <- team_df2 %>%
mutate( fg_points = points - ft_points) %>%
select(date,
fg_points,
points)
opp_points2 <- opp_df2 %>%
mutate( opp_fg_points = points - ft_points,
opp_points = points) %>%
select(date,
opp_fg_points,
opp_points)
nugs_results2 <- right_join(team_points2,opp_points2) %>%
mutate( result = points - opp_points) %>%
select(date,
fg_points,
result)
nugs_results2$date <- gsub("-", "", as.character(nugs_results2$date))
nugs_results2 <- nugs_results2 %>%
mutate(dateGame = date)nuggets_shots_23 <- teams_shots(
teams = "Denver Nuggets",
seasons = 2023,
season_types = "Playoffs",
return_message = FALSE
)player_1 <- nuggets_shots_23 %>%
filter(namePlayer == "Aaron Gordon")
abb3_1 <- player_1 %>%
filter( zoneBasic == "Above the Break 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot)) %>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( abb3_pct = accuracy * 100,
zone = "Above the Break 3")
lc3_1 <- player_1 %>%
filter( zoneBasic == "Left Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( lc3_pct = accuracy * 100,
zone = "Left Corner 3")
mr_1 <- player_1 %>%
filter( zoneBasic == "Mid-Range") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( mr_pct = accuracy * 100,
zone = "Mid-Range")
rc3_1 <- player_1 %>%
filter( zoneBasic == "Right Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( rc3_pct = accuracy * 100,
zone = "Right Corner 3")
ip_1 <- player_1 %>%
filter( zoneBasic == "In The Paint (Non-RA)") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ip_pct = accuracy * 100,
zone = "In the Paint (non RA)")
ra_1 <- player_1 %>%
filter( zoneBasic == "Restricted Area") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ra_1 = accuracy * 100,
zone = "Restricted Area")
player_1_exp_points <- player_1 %>%
mutate(
expected_points = case_when(
zoneBasic == "Restricted Area" ~ 2 * .734,
zoneBasic == "In The Paint (Non-RA)" ~ 2 * .377,
zoneBasic == "Mid-Range" ~ 2 * .245,
zoneBasic == "Above the Break 3" ~ 3 * .407,
zoneBasic == "Right Corner 3" ~ 3 * .307,
zoneBasic == "Left Corner 3" ~ 3 * .2,
)
) %>%
select(namePlayer,
idGame,
dateGame,
expected_points) %>%
group_by(dateGame) %>%
summarise_at(vars(expected_points), sum) %>%
replace(is.na(.), 0) %>%
mutate( 'Aaron Gordon' = expected_points) %>%
select(dateGame,
'Aaron Gordon') %>%
drop_na()player_2 <- nuggets_shots_23 %>%
filter(namePlayer == "Christian Braun")
abb3_2 <- player_2 %>%
filter( zoneBasic == "Above the Break 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot)) %>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( abb3_pct = accuracy * 100,
zone = "Above the Break 3")
lc3_2 <- player_2 %>%
filter( zoneBasic == "Left Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( lc3_pct = accuracy * 100,
zone = "Left Corner 3")
mr_2 <- player_2 %>%
filter( zoneBasic == "Mid-Range") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( mr_pct = accuracy * 100,
zone = "Mid-Range")
rc3_2 <- player_2 %>%
filter( zoneBasic == "Right Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( rc3_pct = accuracy * 100,
zone = "Right Corner 3")
ip_2 <- player_2 %>%
filter( zoneBasic == "In The Paint (Non-RA)") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ip_pct = accuracy * 100,
zone = "In the Paint (non RA)")
ra_2 <- player_2 %>%
filter( zoneBasic == "Restricted Area") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ra_1 = accuracy * 100,
zone = "Restricted Area")
player_2_exp_points <- player_2 %>%
mutate(
expected_points = case_when(
zoneBasic == "Restricted Area" ~ 2 * .682,
zoneBasic == "In The Paint (Non-RA)" ~ 2 * .348,
zoneBasic == "Mid-Range" ~ 2 * .2,
zoneBasic == "Above the Break 3" ~ 3 * .321,
zoneBasic == "Right Corner 3" ~ 3 * .286,
zoneBasic == "Left Corner 3" ~ 3 * .462,
)
) %>%
select(namePlayer,
idGame,
dateGame,
expected_points) %>%
group_by(dateGame) %>%
summarise_at(vars(expected_points), sum) %>%
replace(is.na(.), 0) %>%
mutate( 'Christian Braun' = expected_points) %>%
select(dateGame,
'Christian Braun') %>%
drop_na()player_3 <- nuggets_shots_23 %>%
filter(namePlayer == "Bruce Brown")
abb3_3 <- player_3 %>%
filter( zoneBasic == "Above the Break 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot)) %>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( abb3_pct = accuracy * 100,
zone = "Above the Break 3")
lc3_3 <- player_3 %>%
filter( zoneBasic == "Left Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( lc3_pct = accuracy * 100,
zone = "Left Corner 3")
mr_3 <- player_3 %>%
filter( zoneBasic == "Mid-Range") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( mr_pct = accuracy * 100,
zone = "Mid-Range")
rc3_3 <- player_3 %>%
filter( zoneBasic == "Right Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( rc3_pct = accuracy * 100,
zone = "Right Corner 3")
ip_3 <- player_3 %>%
filter( zoneBasic == "In The Paint (Non-RA)") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ip_pct = accuracy * 100,
zone = "In the Paint (non RA)")
ra_3 <- player_3 %>%
filter( zoneBasic == "Restricted Area") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ra_1 = accuracy * 100,
zone = "Restricted Area")
player_3_exp_points <- player_3 %>%
mutate(
expected_points = case_when(
zoneBasic == "Restricted Area" ~ 2 * .734,
zoneBasic == "In The Paint (Non-RA)" ~ 2 * .717,
zoneBasic == "Mid-Range" ~ 2 * .269,
zoneBasic == "Above the Break 3" ~ 3 * .351,
zoneBasic == "Right Corner 3" ~ 3 * .516,
zoneBasic == "Left Corner 3" ~ 3 * .132,
)
) %>%
select(namePlayer,
idGame,
dateGame,
expected_points) %>%
group_by(dateGame) %>%
replace(is.na(.), 0) %>%
summarise_at(vars(expected_points), sum) %>%
mutate( 'Bruce Brown' = expected_points) %>%
select(dateGame,
'Bruce Brown') %>%
drop_na()player_5 <- nuggets_shots_23 %>%
filter(namePlayer == "Kentavious Caldwell-Pope")
abb3_5 <- player_5 %>%
filter( zoneBasic == "Above the Break 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot)) %>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( abb3_pct = accuracy * 100,
zone = "Above the Break 3")
lc3_5 <- player_5 %>%
filter( zoneBasic == "Left Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( lc3_pct = accuracy * 100,
zone = "Left Corner 3")
mr_5 <- player_5 %>%
filter( zoneBasic == "Mid-Range") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( mr_pct = accuracy * 100,
zone = "Mid-Range")
rc3_5 <- player_5 %>%
filter( zoneBasic == "Right Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( rc3_pct = accuracy * 100,
zone = "Right Corner 3")
ip_5 <- player_5 %>%
filter( zoneBasic == "In The Paint (Non-RA)") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ip_pct = accuracy * 100,
zone = "In the Paint (non RA)")
ra_5 <- player_5 %>%
filter( zoneBasic == "Restricted Area") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ra_1 = accuracy * 100,
zone = "Restricted Area")
player_5_exp_points <- player_5 %>%
mutate(
expected_points = case_when(
zoneBasic == "Restricted Area" ~ 2 * .628,
zoneBasic == "In The Paint (Non-RA)" ~ 2 * .439,
zoneBasic == "Mid-Range" ~ 2 * .416,
zoneBasic == "Above the Break 3" ~ 3 * .437,
zoneBasic == "Right Corner 3" ~ 3 * .411,
zoneBasic == "Left Corner 3" ~ 3 * .405,
)
) %>%
select(namePlayer,
idGame,
dateGame,
expected_points) %>%
group_by(dateGame) %>%
summarise_at(vars(expected_points), sum) %>%
mutate( 'Kentavious Caldwell-Pope' = expected_points) %>%
select(dateGame,
'Kentavious Caldwell-Pope') %>%
drop_na()player_6 <- nuggets_shots_23 %>%
filter(namePlayer == "Vlatko Cancar")
abb3_6 <- player_6 %>%
filter( zoneBasic == "Above the Break 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot)) %>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( abb3_pct = accuracy * 100,
zone = "Above the Break 3")
lc3_6 <- player_6 %>%
filter( zoneBasic == "Left Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( lc3_pct = accuracy * 100,
zone = "Left Corner 3")
mr_6 <- player_6 %>%
filter( zoneBasic == "Mid-Range") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( mr_pct = accuracy * 100,
zone = "Mid-Range")
rc3_6 <- player_6 %>%
filter( zoneBasic == "Right Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( rc3_pct = accuracy * 100,
zone = "Right Corner 3")
ip_6 <- player_6 %>%
filter( zoneBasic == "In The Paint (Non-RA)") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ip_pct = accuracy * 100,
zone = "In the Paint (non RA)")
ra_6 <- player_6 %>%
filter( zoneBasic == "Restricted Area") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ra_1 = accuracy * 100,
zone = "Restricted Area")
player_6_exp_points <- player_6 %>%
mutate(
expected_points = case_when(
zoneBasic == "Restricted Area" ~ 2 * .696,
zoneBasic == "In The Paint (Non-RA)" ~ 2 * .352,
zoneBasic == "Mid-Range" ~ 2 * .556,
zoneBasic == "Above the Break 3" ~ 3 * .347,
zoneBasic == "Right Corner 3" ~ 3 * .444,
zoneBasic == "Left Corner 3" ~ 3 * .433,
)
) %>%
select(namePlayer,
idGame,
dateGame,
expected_points) %>%
group_by(dateGame) %>%
summarise_at(vars(expected_points), sum) %>%
mutate( 'Vlatko Cancar' = expected_points) %>%
select(dateGame,
'Vlatko Cancar') %>%
drop_na()player_8 <- nuggets_shots_23 %>%
filter(namePlayer == "Reggie Jackson")
abb3_8 <- player_8 %>%
filter( zoneBasic == "Above the Break 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot)) %>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( abb3_pct = accuracy * 100,
zone = "Above the Break 3")
lc3_8 <- player_8 %>%
filter( zoneBasic == "Left Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( lc3_pct = accuracy * 100,
zone = "Left Corner 3")
mr_8 <- player_8 %>%
filter( zoneBasic == "Mid-Range") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( mr_pct = accuracy * 100,
zone = "Mid-Range")
rc3_8 <- player_8 %>%
filter( zoneBasic == "Right Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( rc3_pct = accuracy * 100,
zone = "Right Corner 3")
ip_8 <- player_8 %>%
filter( zoneBasic == "In The Paint (Non-RA)") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ip_pct = accuracy * 100,
zone = "In the Paint (non RA)")
ra_8 <- player_8 %>%
filter( zoneBasic == "Restricted Area") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ra_1 = accuracy * 100,
zone = "Restricted Area")
player_8_exp_points <- player_8 %>%
mutate(
expected_points = case_when(
zoneBasic == "Restricted Area" ~ 2 * .615,
zoneBasic == "In The Paint (Non-RA)" ~ 2 * .536,
zoneBasic == "Mid-Range" ~ 2 * .368,
zoneBasic == "Above the Break 3" ~ 3 * .256,
zoneBasic == "Right Corner 3" ~ 3 * .437,
zoneBasic == "Left Corner 3" ~ 3 * 0,
)
) %>%
select(namePlayer,
idGame,
dateGame,
expected_points) %>%
group_by(dateGame) %>%
summarise_at(vars(expected_points), sum) %>%
mutate( 'Reggie Jackson' = expected_points) %>%
select(dateGame,
'Reggie Jackson') %>%
drop_na()player_7 <- nuggets_shots_23 %>%
filter(namePlayer == "Jeff Green")
abb3_7 <- player_7 %>%
filter( zoneBasic == "Above the Break 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot)) %>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( abb3_pct = accuracy * 100,
zone = "Above the Break 3")
lc3_7 <- player_7 %>%
filter( zoneBasic == "Left Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( lc3_pct = accuracy * 100,
zone = "Left Corner 3")
mr_7 <- player_7 %>%
filter( zoneBasic == "Mid-Range") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( mr_pct = accuracy * 100,
zone = "Mid-Range")
rc3_7 <- player_7 %>%
filter( zoneBasic == "Right Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( rc3_pct = accuracy * 100,
zone = "Right Corner 3")
ip_7 <- player_7 %>%
filter( zoneBasic == "In The Paint (Non-RA)") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ip_pct = accuracy * 100,
zone = "In the Paint (non RA)")
ra_7 <- player_7 %>%
filter( zoneBasic == "Restricted Area") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ra_1 = accuracy * 100,
zone = "Restricted Area")
player_7_exp_points <- player_7 %>%
mutate(
expected_points = case_when(
zoneBasic == "Restricted Area" ~ 2 * .677,
zoneBasic == "In The Paint (Non-RA)" ~ 2 * .5,
zoneBasic == "Mid-Range" ~ 2 * .321,
zoneBasic == "Above the Break 3" ~ 3 * .219,
zoneBasic == "Right Corner 3" ~ 3 * .45,
zoneBasic == "Left Corner 3" ~ 3 * .389,
)
) %>%
select(namePlayer,
idGame,
dateGame,
expected_points) %>%
group_by(dateGame) %>%
summarise_at(vars(expected_points), sum) %>%
mutate( 'Jeff Green' = expected_points) %>%
select(dateGame,
'Jeff Green') %>%
drop_na()player_9 <- nuggets_shots_23 %>%
filter(namePlayer == "Nikola Jokic")
abb3_9 <- player_9 %>%
filter( zoneBasic == "Above the Break 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot)) %>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( abb3_pct = accuracy * 100,
zone = "Above the Break 3")
lc3_9 <- player_9 %>%
filter( zoneBasic == "Left Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( lc3_pct = accuracy * 100,
zone = "Left Corner 3")
mr_9 <- player_9 %>%
filter( zoneBasic == "Mid-Range") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( mr_pct = accuracy * 100,
zone = "Mid-Range")
rc3_9 <- player_9 %>%
filter( zoneBasic == "Right Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( rc3_pct = accuracy * 100,
zone = "Right Corner 3")
ip_9 <- player_9 %>%
filter( zoneBasic == "In The Paint (Non-RA)") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ip_pct = accuracy * 100,
zone = "In the Paint (non RA)")
ra_9 <- player_9 %>%
filter( zoneBasic == "Restricted Area") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ra_1 = accuracy * 100,
zone = "Restricted Area")
player_9_exp_points <- player_9 %>%
mutate(
expected_points = case_when(
zoneBasic == "Restricted Area" ~ 2 * .745,
zoneBasic == "In The Paint (Non-RA)" ~ 2 * .627,
zoneBasic == "Mid-Range" ~ 2 * .523,
zoneBasic == "Above the Break 3" ~ 3 * .397,
zoneBasic == "Right Corner 3" ~ 3 * .25,
zoneBasic == "Left Corner 3" ~ 3 * 0,
)
) %>%
select(namePlayer,
idGame,
dateGame,
expected_points) %>%
group_by(dateGame) %>%
summarise_at(vars(expected_points), sum) %>%
mutate( 'Nikola Jokic' = expected_points) %>%
select(dateGame,
'Nikola Jokic') %>%
drop_na()player_10 <- nuggets_shots_23 %>%
filter(namePlayer == "DeAndre Jordan")
abb3_10 <- player_10 %>%
filter( zoneBasic == "Above the Break 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot)) %>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( abb3_pct = accuracy * 100,
zone = "Above the Break 3")
lc3_10 <- player_10 %>%
filter( zoneBasic == "Left Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( lc3_pct = accuracy * 100,
zone = "Left Corner 3")
mr_10 <- player_10 %>%
filter( zoneBasic == "Mid-Range") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( mr_pct = accuracy * 100,
zone = "Mid-Range")
rc3_10 <- player_10 %>%
filter( zoneBasic == "Right Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( rc3_pct = accuracy * 100,
zone = "Right Corner 3")
ip_10 <- player_10 %>%
filter( zoneBasic == "In The Paint (Non-RA)") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ip_pct = accuracy * 100,
zone = "In the Paint (non RA)")
ra_10 <- player_10 %>%
filter( zoneBasic == "Restricted Area") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ra_1 = accuracy * 100,
zone = "Restricted Area")
player_10_exp_points <- player_10 %>%
mutate(
expected_points = case_when(
zoneBasic == "Restricted Area" ~ 2 * .816,
zoneBasic == "In The Paint (Non-RA)" ~ 2 * .222,
zoneBasic == "Mid-Range" ~ 2 * .5,
zoneBasic == "Above the Break 3" ~ 3 * 1,
zoneBasic == "Right Corner 3" ~ 3 * 0,
zoneBasic == "Left Corner 3" ~ 3 * 0,
)
) %>%
select(namePlayer,
idGame,
dateGame,
expected_points) %>%
group_by(dateGame) %>%
replace(is.na(.), 0) %>%
summarise_at(vars(expected_points), sum) %>%
mutate( 'DeAndre Jordan' = expected_points) %>%
select(dateGame,
'DeAndre Jordan') %>%
drop_na()player_11 <- nuggets_shots_23 %>%
filter(namePlayer == "Jamal Murray")
abb3_11 <- player_11 %>%
filter( zoneBasic == "Above the Break 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot)) %>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( abb3_pct = accuracy * 100,
zone = "Above the Break 3")
lc3_11 <- player_11 %>%
filter( zoneBasic == "Left Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( lc3_pct = accuracy * 100,
zone = "Left Corner 3")
mr_11 <- player_11 %>%
filter( zoneBasic == "Mid-Range") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( mr_pct = accuracy * 100,
zone = "Mid-Range")
rc3_11 <- player_11 %>%
filter( zoneBasic == "Right Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( rc3_pct = accuracy * 100,
zone = "Right Corner 3")
ip_11 <- player_11 %>%
filter( zoneBasic == "In The Paint (Non-RA)") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ip_pct = accuracy * 100,
zone = "In the Paint (non RA)")
ra_11 <- player_11 %>%
filter( zoneBasic == "Restricted Area") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ra_1 = accuracy * 100,
zone = "Restricted Area")
player_11_exp_points <- player_11 %>%
mutate(
expected_points = case_when(
zoneBasic == "Restricted Area" ~ 2 * .654,
zoneBasic == "In The Paint (Non-RA)" ~ 2 * .412,
zoneBasic == "Mid-Range" ~ 2 * .411,
zoneBasic == "Above the Break 3" ~ 3 * .39,
zoneBasic == "Right Corner 3" ~ 3 * .5,
zoneBasic == "Left Corner 3" ~ 3 * .515,
)
) %>%
select(namePlayer,
idGame,
dateGame,
expected_points) %>%
group_by(dateGame) %>%
summarise_at(vars(expected_points), sum) %>%
mutate( 'Jamal Murray' = expected_points) %>%
select(dateGame,
'Jamal Murray') %>%
drop_na()player_12 <- nuggets_shots_23 %>%
filter(namePlayer == "Zeke Nnaji")
abb3_12 <- player_12 %>%
filter( zoneBasic == "Above the Break 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot)) %>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( abb3_pct = accuracy * 100,
zone = "Above the Break 3")
lc3_12 <- player_12 %>%
filter( zoneBasic == "Left Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( lc3_pct = accuracy * 100,
zone = "Left Corner 3")
mr_12 <- player_12 %>%
filter( zoneBasic == "Mid-Range") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( mr_pct = accuracy * 100,
zone = "Mid-Range")
rc3_12 <- player_12 %>%
filter( zoneBasic == "Right Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( rc3_pct = accuracy * 100,
zone = "Right Corner 3")
ip_12 <- player_12 %>%
filter( zoneBasic == "In The Paint (Non-RA)") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ip_pct = accuracy * 100,
zone = "In the Paint (non RA)")
ra_12 <- player_12 %>%
filter( zoneBasic == "Restricted Area") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ra_1 = accuracy * 100,
zone = "Restricted Area")
player_12_exp_points <- player_12 %>%
mutate(
expected_points = case_when(
zoneBasic == "Restricted Area" ~ 2 * .742,
zoneBasic == "In The Paint (Non-RA)" ~ 2 * .333,
zoneBasic == "Mid-Range" ~ 2 * .5,
zoneBasic == "Above the Break 3" ~ 3 * .282,
zoneBasic == "Right Corner 3" ~ 3 * .286,
zoneBasic == "Left Corner 3" ~ 3 * .2,
)
) %>%
select(namePlayer,
idGame,
dateGame,
expected_points) %>%
group_by(dateGame) %>%
summarise_at(vars(expected_points), sum) %>%
mutate( 'Zeke Nnaji' = expected_points) %>%
select(dateGame,
'Zeke Nnaji') %>%
drop_na()player_13 <- nuggets_shots_23 %>%
filter(namePlayer == "Michael Porter Jr.")
abb3_13 <- player_13 %>%
filter( zoneBasic == "Above the Break 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot)) %>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( abb3_pct = accuracy * 100,
zone = "Above the Break 3")
lc3_13 <- player_13 %>%
filter( zoneBasic == "Left Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( lc3_pct = accuracy * 100,
zone = "Left Corner 3")
mr_13 <- player_13 %>%
filter( zoneBasic == "Mid-Range") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( mr_pct = accuracy * 100,
zone = "Mid-Range")
rc3_13 <- player_13 %>%
filter( zoneBasic == "Right Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( rc3_pct = accuracy * 100,
zone = "Right Corner 3")
ip_13 <- player_13 %>%
filter( zoneBasic == "In The Paint (Non-RA)") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ip_pct = accuracy * 100,
zone = "In the Paint (non RA)")
ra_13 <- player_13 %>%
filter( zoneBasic == "Restricted Area") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ra_1 = accuracy * 100,
zone = "Restricted Area")
player_13_exp_points <- player_13 %>%
mutate(
expected_points = case_when(
zoneBasic == "Restricted Area" ~ 2 * .757,
zoneBasic == "In The Paint (Non-RA)" ~ 2 * .414,
zoneBasic == "Mid-Range" ~ 2 * .424,
zoneBasic == "Above the Break 3" ~ 3 * .387,
zoneBasic == "Right Corner 3" ~ 3 * .601,
zoneBasic == "Left Corner 3" ~ 3 * .5,
)
) %>%
select(namePlayer,
idGame,
dateGame,
expected_points) %>%
group_by(dateGame) %>%
summarise_at(vars(expected_points), sum) %>%
mutate( 'Michael Porter Jr.' = expected_points) %>%
select(dateGame,
'Michael Porter Jr.') %>%
drop_na()player_14 <- nuggets_shots_23 %>%
filter(namePlayer == "Ish Smith")
abb3_14 <- player_14 %>%
filter( zoneBasic == "Above the Break 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot)) %>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( abb3_pct = accuracy * 100,
zone = "Above the Break 3")
lc3_14 <- player_14 %>%
filter( zoneBasic == "Left Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( lc3_pct = accuracy * 100,
zone = "Left Corner 3")
mr_14 <- player_14 %>%
filter( zoneBasic == "Mid-Range") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( mr_pct = accuracy * 100,
zone = "Mid-Range")
rc3_14 <- player_14 %>%
filter( zoneBasic == "Right Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( rc3_pct = accuracy * 100,
zone = "Right Corner 3")
ip_14 <- player_14 %>%
filter( zoneBasic == "In The Paint (Non-RA)") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ip_pct = accuracy * 100,
zone = "In the Paint (non RA)")
ra_14 <- player_14 %>%
filter( zoneBasic == "Restricted Area") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ra_1 = accuracy * 100,
zone = "Restricted Area")
player_14_exp_points <- player_14 %>%
mutate(
expected_points = case_when(
zoneBasic == "Restricted Area" ~ 2 * .565,
zoneBasic == "In The Paint (Non-RA)" ~ 2 * .444,
zoneBasic == "Mid-Range" ~ 2 * .371,
zoneBasic == "Above the Break 3" ~ 3 * .111,
zoneBasic == "Right Corner 3" ~ 3 * 0,
zoneBasic == "Left Corner 3" ~ 3 * 0,
)
) %>%
select(namePlayer,
idGame,
dateGame,
expected_points) %>%
group_by(dateGame) %>%
summarise_at(vars(expected_points), sum) %>%
mutate( 'Ish Smith' = expected_points) %>%
select(dateGame,
'Ish Smith') %>%
drop_na()player_15 <- nuggets_shots_23 %>%
filter(namePlayer == "Peyton Watson")
abb3_15 <- player_15 %>%
filter( zoneBasic == "Above the Break 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot)) %>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( abb3_pct = accuracy * 100,
zone = "Above the Break 3")
lc3_15 <- player_15 %>%
filter( zoneBasic == "Left Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( lc3_pct = accuracy * 100,
zone = "Left Corner 3")
mr_15 <- player_15 %>%
filter( zoneBasic == "Mid-Range") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( mr_pct = accuracy * 100,
zone = "Mid-Range")
rc3_15 <- player_15 %>%
filter( zoneBasic == "Right Corner 3") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( rc3_pct = accuracy * 100,
zone = "Right Corner 3")
ip_15 <- player_15 %>%
filter( zoneBasic == "In The Paint (Non-RA)") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ip_pct = accuracy * 100,
zone = "In the Paint (non RA)")
ra_15 <- player_15 %>%
filter( zoneBasic == "Restricted Area") %>%
summarise( accuracy = mean(isShotMade),
shots = sum(isShotAttempted),
makes = sum(isShotMade),
avg_distance = mean(distanceShot))%>%
mutate_at(vars(accuracy, avg_distance), funs(round(.,4))) %>%
mutate( ra_1 = accuracy * 100,
zone = "Restricted Area")
player_15_exp_points <- player_15 %>%
mutate(
expected_points = case_when(
zoneBasic == "Restricted Area" ~ 2 * .571,
zoneBasic == "In The Paint (Non-RA)" ~ 2 * .5,
zoneBasic == "Mid-Range" ~ 2 * .2,
zoneBasic == "Above the Break 3" ~ 3 * .375,
zoneBasic == "Right Corner 3" ~ 3 * 0,
zoneBasic == "Left Corner 3" ~ 3 * .6,
)
) %>%
select(namePlayer,
idGame,
dateGame,
expected_points) %>%
group_by(dateGame) %>%
summarise_at(vars(expected_points), sum) %>%
replace(is.na(.), 0) %>%
mutate( 'Peyton Watson' = expected_points) %>%
select(dateGame,
'Peyton Watson') %>%
drop_na()exp_points <- left_join(nugs_results2, player_1_exp_points) %>%
left_join(player_2_exp_points) %>%
left_join(player_3_exp_points) %>%
left_join(player_5_exp_points) %>%
left_join(player_6_exp_points) %>%
left_join(player_7_exp_points) %>%
left_join(player_8_exp_points) %>%
left_join(player_9_exp_points) %>%
left_join(player_10_exp_points) %>%
left_join(player_11_exp_points) %>%
left_join(player_12_exp_points) %>%
left_join(player_13_exp_points) %>%
left_join(player_14_exp_points) %>%
left_join(player_15_exp_points)
exp_points[is.na(exp_points)] <- 0
exp_points$'Exp. Total' <- exp_points$`Aaron Gordon`+
exp_points$`Christian Braun` +
exp_points$`Bruce Brown` +
exp_points$`Kentavious Caldwell-Pope` +
exp_points$`Vlatko Cancar` +
exp_points$`Jeff Green` +
exp_points$`Reggie Jackson` +
exp_points$`Nikola Jokic` +
exp_points$`DeAndre Jordan` +
exp_points$`Jamal Murray` +
exp_points$`Zeke Nnaji` +
exp_points$`Michael Porter Jr.` +
exp_points$`Ish Smith` +
exp_points$`Peyton Watson`
exp_points$'Field Goal luck' <- exp_points$fg_points - exp_points$'Exp. Total'
exp_points <- exp_points %>%
mutate( 'win/loss' = case_when(
result > 0 ~ "Win",
result < 0 ~ "Loss",
))
exp_table <- exp_points %>%
select(date,
fg_points,
'Exp. Total',
'Field Goal luck',
'win/loss') exp_table2 <- exp_table %>%
mutate('Exp. FG total' = `Exp. Total`,
date2 = date) %>%
select(date2,
`Exp. FG total`,
fg_points,
`Field Goal luck`,
'win/loss')
exp_ft_table2 <- exp_ft_table %>%
mutate('Exp. FT total' = `Exp. Total`) %>%
select(date,
`Exp. FT total`,
ft_points,
`Free throw luck`)
table3 <- cbind(exp_table2,exp_ft_table2)
table3$'Total points' <- table3$fg_points + table3$ft_points
table3$'Total Exp. points' <- table3$`Exp. FG total` + table3$`Exp. FT total`
table3 %>%
select(date,
`win/loss`,
`Total points`,
`Total Exp. points`,
`Field Goal luck`,
`Free throw luck`) %>%
mutate_at(vars(`Field Goal luck`), funs(round(.,2))) %>%
reactable( theme = espn())exp_table %>%
mutate_at(vars(`Field Goal luck`,
`Exp. Total`), funs(round(.,2))) %>%
reactable(theme = espn())exp_points %>%
select(date,
fg_points,
`Exp. Total`,
'Nikola Jokic',
'Jamal Murray',
'Aaron Gordon',
'Michael Porter Jr.',
'Kentavious Caldwell-Pope',
'Bruce Brown',
'Jeff Green',
'Christian Braun',
'DeAndre Jordan',
'Vlatko Cancar',
'Reggie Jackson',
'Zeke Nnaji',
'Ish Smith',
'Peyton Watson') %>%
reactable(theme = espn()) %>%
add_title("Expected FG points by player")exp_ft_table %>%
reactable(theme = espn())exp_ft %>%
select(
date,
'win/loss',
ft_points,
'Exp. Total',
'Nikola Jokic',
'Jamal Murray',
'Aaron Gordon',
'Michael Porter Jr.',
'Kentavious Caldwell-Pope',
'Bruce Brown',
'Jeff Green',
'Christian Braun',
'DeAndre Jordan'
) %>%
reactable( theme = espn()) %>%
add_title("Expected FT points by player")