library(tidyverse)
library(jsonlite)
library(janitor)
library(corrplot)
dates <- c("10/19",
"10/21",
"10/22",
"10/24",
"10/26",
"10/28",
"10/30",
"11/3",
"11/5",
"11/7",
"11/9",
"11/11",
"11/13",
"11/22",
"11/23",
"11/25",
"11/28",
"11/30",
"12/2",
"12/4",
"12/6",
"12/8",
"12/10",
"12/14",
"12/16",
"12/18",
"12/20",
"12/23",
"12/25",
"12/27",
"12/28",
"12/30",
"1/1",
"1/2",
"1/5",
"1/6",
"1/9",
"1/11",
"1/15",
"1/17",
"1/18",
"1/24",
"1/28",
"1/31",
"2/2",
"2/4",
"2/7",
"2/9",
"2/11",
"2/13",
"2/15",
"2/23",
"2/25",
"2/26",
"2/28",
"3/3",
"3/6",
"3/8",
"3/10",
"3/12",
"3/14",
"3/16",
"3/18",
"3/19",
"3/22",
"3/25",
"3/27",
"4/4",
"4/8") %>%
as.data.frame() %>%
mutate( season = "Regular")
names(dates)[names(dates) == '.'] <- 'date'
dates2 <- c("4/16",
"4/19",
"4/21",
"4/23",
"4/25",
"4/29",
"5/1",
"5/5",
"5/7",
"5/9",
"5/11",
"5/16",
"5/18",
"5/20",
"5/22",
"6/1",
"6/4",
"6/7",
"6/9",
"6/12") %>%
as.data.frame() %>%
mutate(season = "Playoffs")
names(dates2)[names(dates2) == '.'] <- 'date'
team_passes <- c(307,
320,
333,
347,
306,
289,
310,
312,
293,
282,
264,
267,
313,
303,
396,
292,
306,
287,
333,
301,
303,
292,
273,
276,
306,
341,
334,
294,
336,
344,
302,
320,
286,
265,
304,
265,
321,
309,
308,
306,
250,
308,
293,
302,
284,
289,
311,
282,
293,
312,
289,
277,
293,
320,
304,
273,
256,
287,
281,
281,
219,
269,
287,
287,
275,
273,
313,
284,
342,
274,
279,
305,
294,
291,
240,
273,
284,
269,
276,
323,
284,
298,
279,
288,
293,
293,
250,
271,
273)
jokic_passes <- c(77,
80,
96,
78,
73,
61,
74,
77,
59,
65,
38,
50,
81,
80,
96,
61,
59,
69,
88,
78,
77,
70,
67,
66,
79,
98,
88,
76,
101,
97,
68,
80,
70,
70,
56,
71,
91,
68,
83,
84,
57,
93,
92,
99,
85,
76,
62,
73,
78,
79,
80,
76,
58,
81,
67,
83,
73,
73,
74,
71,
58,
73,
81,
85,
77,
60,
87,
58,
68,
57,
88,
88,
84,
92,
53,
88,
91,
69,
76,
92,
95,
92,
78,
108,
78,
66,
75,
79,
83)
pbp_url_jok <- "https://api.pbpstats.com/get-game-logs/nba?Season=2022-23&SeasonType=Regular%2BSeason&EntityId=203999&EntityType=Player"
pbp_jok <- read_json(pbp_url_jok)
jok_df <- pbp_jok[["multi_row_table_data"]] %>%
bind_rows() %>%
clean_names() %>%
select(
on_off_rtg,
on_def_rtg
)
pbp_url_jokP <- "https://api.pbpstats.com/get-game-logs/nba?Season=2022-23&SeasonType=Playoffs&EntityId=203999&EntityType=Player"
pbp_jokP <- read_json(pbp_url_jokP)
jokP_df <- pbp_jokP[["multi_row_table_data"]] %>%
bind_rows() %>%
clean_names() %>%
select(
on_off_rtg,
on_def_rtg
)
jok_on <- rbind(jok_df, jokP_df)
jok_passing <- rbind(dates,dates2) %>%
cbind(team_passes) %>%
cbind(jokic_passes) %>%
mutate( '%of_team_passes' = jokic_passes/team_passes) %>%
cbind(jok_on)
jok_clean <- jok_passing %>%
subset( , select = -c(season,date))
corr_J <- cor(as.matrix(jok_clean))
corrplot(corr_J, method = "circle",
title = "Jokic Passing",
mar=c(0,0,1,0))
jok_passing_playoffs <- rbind(dates,dates2) %>%
cbind(team_passes) %>%
cbind(jokic_passes) %>%
mutate( '%of_team_passes' = jokic_passes/team_passes) %>%
cbind(jok_on) %>%
filter(season == "Playoffs")
jok_cleanP <- jok_passing_playoffs %>%
subset( , select = -c(season,date))
corr_JP <- cor(as.matrix(jok_cleanP))
corrplot(corr_JP, method = "circle",
title = "Jokic Passing - Playoffs",
mar=c(0,0,1,0))
jok_passing_regular <- rbind(dates,dates2) %>%
cbind(team_passes) %>%
cbind(jokic_passes) %>%
mutate( '%of_team_passes' = jokic_passes/team_passes) %>%
cbind(jok_on) %>%
filter(season == "Regular")
jok_cleanR <- jok_passing_regular %>%
subset( , select = -c(season,date))
corr_JR <- cor(as.matrix(jok_cleanR))
corrplot(corr_JR, method = "circle",
title = "Jokic Passing - Regular",
mar=c(0,0,1,0))