-
Notifications
You must be signed in to change notification settings - Fork 0
/
NBA_Redraft.r
375 lines (337 loc) · 16.6 KB
/
NBA_Redraft.r
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
library(xml2)
library(magrittr)
library(dplyr)
library(ggplot2)
tables = lapply(c(1989:2008) ,function(yr){
df <- paste0("http://www.basketball-reference.com/draft/NBA_", yr, ".html", sep="") %>%
as.character() %>%
read_html() %>%
xml_find_all(xpath = "//*[@id='stats']/tbody/tr/td") %>%
xml_text() %>%
matrix(ncol=21, byrow=T) %>%
as.data.frame(stringsAsFactors=FALSE)
df$Year = yr
names(df) = c('Rk', 'Tm', 'Player', 'College', 'Yrs', 'G','MP_T', 'PTS_T',
'TRB_T','AST_T', 'FG','threeP', 'FT', 'MP', 'PTS', 'TRB', 'AST',
'WS', 'WS_per', 'BPM', 'VORP','Year')
df
})
df_full <- Reduce(x = tables, f = rbind)
cols = c(1, 5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22)
df_full[,cols] %<>% lapply(function(x) as.numeric(as.character(x)))
df <- select(df_full, Rk, Tm, Player, College, MP_T, VORP, Year)
#Dealing with missing values
#有些是高中畢業就進NBA，有些是非美籍球員
#1989
df$College[df$Player == "Vlade Divac"] <- "International"
df$College[df$Player == "Dino Radja"] <- "International"
#1990
df$College[df$Player == "Toni Kukoc"] <- "International"
df$College[df$Player == "Stefano Rusconi"] <- "International"
#1991
df$College[df$Player == "Zan Tabak"] <- "International"
#1992
df$College[df$Player == "Sasha Danilovic"] <- "International"
#1993
df$College[df$Player == "Gheorghe Muresan"] <- "International"
df$College[df$Player == "Marcelo Nicola"] <- "International"
#1994
df$College[df$Player == "Andrei Fetisov"] <- "International"
df$College[df$Player == "William Njoku"] <- "International"
df$College[df$Player == "Zeljko Rebraca"] <- "International"
#1995
df$College[df$Player == "Kevin Garnett"] <- "High School"
df$College[df$Player == "Dragan Tarlac"] <- "International"
df$College[df$Player == "Dejan Bodiroga"] <- "International"
df$College[df$Player == "Aurelijius Zukauskas"] <- "International"
#1996
df$College[df$Player == "Peja Stojakovic"] <- "International"
df$College[df$Player == "Zydrunas Ilgauskas"] <- "International"
df$College[df$Player == "Efthimi Rentzias"] <- "International"
df$College[df$Player == "Martin Muursepp"] <- "International"
df$College[df$Player == "Kobe Bryant"] <- "High School"
df$College[df$Player == "Jermaine O'Neal"] <- "High School"
#1997
df$College[df$Player == "Chris Anstey"] <- "International"
df$College[df$Player == "Marko Milic"] <- "International"
df$College[df$Player == "Predrag Drobnjak"] <- "International"
df$College[df$Player == "Alain Digbeu"] <- "International"
df$College[df$Player == "Ben Pepper"] <- "International"
df$College[df$Player == "Roberto Duenas"] <- "International"
df$College[df$Player == "Tracy McGrady"] <- "High School"
#1998
df$College[df$Player == "Dirk Nowitzki"] <- "International"
df$College[df$Player == "Rasho Nesterovic"] <- "International"
df$College[df$Player == "Mirsad Turkcan"] <- "International"
df$College[df$Player == "Vladimir Stepania"] <- "International"
df$College[df$Player == "Bruno Sundov"] <- "International"
df$College[df$Player == "Al Harrington"] <- "High School"
df$College[df$Player == "Rashard Lewis"] <- "High School"
df$College[df$Player == "Korleone Young"] <- "High School"
#1999
df$College[df$Player == "Frederic Weis"] <- "International"
df$College[df$Player == "Andrei Kirilenko"] <- "International"
df$College[df$Player == "Wang Zhizhi"] <- "International"
df$College[df$Player == "Gordan Giricek"] <- "International"
df$College[df$Player == "Manu Ginobili"] <- "International"
df$College[df$Player == "Jonathan Bender"] <- "High School"
df$College[df$Player == "Leon Smith"] <- "High School"
#2000
df$College[df$Player == "Darius Miles"] <- "High School"
df$College[df$Player == "DeShawn Stevenson"] <- "High School"
df$College[df$Player == "Hedo Turkoglu"] <- "International"
df$College[df$Player == "Dalibor Bagaric"] <- "International"
df$College[df$Player == "Jake Tsakalidis"] <- "International"
df$College[df$Player == "Primoz Brezec"] <- "International"
df$College[df$Player == "Marko Jaric"] <- "International"
df$College[df$Player == "Soumaila Samake"] <- "International"
df$College[df$Player == "Olumide Oyedeji"] <- "International"
df$College[df$Player == "Josip Sesar"] <- "International"
df$College[df$Player == "Igor Rakocevic"] <- "International"
#2001
df$College[df$Player == "Pau Gasol"] <- "International"
df$College[df$Player == "DeSagana Diop"] <- "International"
df$College[df$Player == "Vladimir Radmanovic"] <- "International"
df$College[df$Player == "Raul Lopez"] <- "International"
df$College[df$Player == "Tony Parker"] <- "International"
df$College[df$Player == "Mehmet Okur"] <- "International"
df$College[df$Player == "Ousmane Cisse"] <- "International"
df$College[df$Player == "Antonis Fotsis"] <- "International"
df$College[df$Player == "Robertas Javtokas"] <- "International"
df$College[df$Player == "Kwame Brown"] <- "High School"
df$College[df$Player == "Tyson Chandler"] <- "High School"
df$College[df$Player == "Eddy Curry"] <- "High School"
#2002
df$College[df$Player == "Yao Ming"] <- "International"
df$College[df$Player == "Nikoloz Tskitishvili"] <- "International"
df$College[df$Player == "Nene Hilario"] <- "International"
df$College[df$Player == "Bostjan Nachbar"] <- "International"
df$College[df$Player == "Jiri Welsch"] <- "International"
df$College[df$Player == "Nenad Krstic"] <- "International"
df$College[df$Player == "Milos Vujanic"] <- "International"
df$College[df$Player == "David Andersen"] <- "International"
df$College[df$Player == "Juan Carlos Navarro"] <- "International"
df$College[df$Player == "Mario Kasun"] <- "International"
df$College[df$Player == "Peter Fehse"] <- "International"
df$College[df$Player == "Federico Kammerichs"] <- "International"
df$College[df$Player == "Mladen Sekularac"] <- "International"
df$College[df$Player == "Amar'e Stoudemire"] <- "High School"
#2003
df$College[df$Player == "Darko Milicic"] <- "International"
df$College[df$Player == "Mickael Pietrus"] <- "International"
df$College[df$Player == "Zarko Cabarkapa"] <- "International"
df$College[df$Player == "Sasha Pavlovic"] <- "International"
df$College[df$Player == "Boris Diaw"] <- "International"
df$College[df$Player == "Zoran Planinic"] <- "International"
df$College[df$Player == "Carlos Delfino"] <- "International"
df$College[df$Player == "Ndudi Ebi"] <- "International"
df$College[df$Player == "Leandro Barbosa"] <- "International"
df$College[df$Player == "Maciej Lampe"] <- "International"
df$College[df$Player == "Sofoklis Schortsanitis"] <- "International"
df$College[df$Player == "Szymon Szewczyk"] <- "International"
df$College[df$Player == "Slavko Vranes"] <- "International"
df$College[df$Player == "Zaza Pachulia"] <- "International"
df$College[df$Player == "Malick Badiane"] <- "International"
df$College[df$Player == "Sani Becirovic"] <- "International"
df$College[df$Player == "James Lang"] <- "International"
df$College[df$Player == "Paccelis Morlende"] <- "International"
df$College[df$Player == "Remon Van de Hare"] <- "International"
df$College[df$Player == "Nedzad Sinanovic"] <- "International"
df$College[df$Player == "Xue Yuyang"] <- "International"
df$College[df$Player == "Andreas Glyniadakis"] <- "International"
df$College[df$Player == "LeBron James"] <- "High School"
df$College[df$Player == "Travis Outlaw"] <- "High School"
df$College[df$Player == "Kendrick Perkins"] <- "High School"
#2004
df$College[df$Player == "Andris Biedrins"] <- "International"
df$College[df$Player == "Pavel Podkolzin"] <- "International"
df$College[df$Player == "Viktor Khryapa"] <- "International"
df$College[df$Player == "Sergei Monia"] <- "International"
df$College[df$Player == "Sasha Vujacic"] <- "International"
df$College[df$Player == "Beno Udrih"] <- "International"
df$College[df$Player == "Anderson Varejao"] <- "International"
df$College[df$Player == "Peter John Ramos"] <- "International"
df$College[df$Player == "Albert Miralles"] <- "International"
df$College[df$Player == "Viktor Sanikidze"] <- "International"
df$College[df$Player == "Ha Seung-Jin"] <- "International"
df$College[df$Player == "Sergei Lishouk"] <- "International"
df$College[df$Player == "Vassilis Spanoulis"] <- "International"
df$College[df$Player == "Sergei Karaulov"] <- "International"
df$College[df$Player == "Dwight Howard"] <- "High School"
df$College[df$Player == "Shaun Livingston"] <- "High School"
df$College[df$Player == "Robert Swift"] <- "High School"
df$College[df$Player == "Sebastian Telfair"] <- "High School"
df$College[df$Player == "Al Jefferson"] <- "High School"
df$College[df$Player == "Josh Smith"] <- "High School"
df$College[df$Player == "J.R. Smith"] <- "High School"
df$College[df$Player == "Dorell Wright"] <- "High School"
#2005
df$College[df$Player == "Fran Vazquez"] <- "International"
df$College[df$Player == "Yaroslav Korolev"] <- "International"
df$College[df$Player == "Johan Petro"] <- "International"
df$College[df$Player == "Ian Mahinmi"] <- "International"
df$College[df$Player == "Ricky Sanchez"] <- "International"
df$College[df$Player == "Ersan Ilyasova"] <- "International"
df$College[df$Player == "Roko Ukic"] <- "International"
df$College[df$Player == "Mile Ilic"] <- "International"
df$College[df$Player == "Martynas Andriuskevicius"] <- "International"
df$College[df$Player == "Erazem Lorbek"] <- "International"
df$College[df$Player == "Mickael Gelabale"] <- "International"
df$College[df$Player == "Axel Hervelle"] <- "International"
df$College[df$Player == "Marcin Gortat"] <- "International"
df$College[df$Player == "Uros Slokar"] <- "International"
df$College[df$Player == "Cenk Akyol"] <- "International"
df$College[df$Player == "Martell Webster"] <- "High School"
df$College[df$Player == "Andrew Bynum"] <- "High School"
df$College[df$Player == "Gerald Green"] <- "High School"
df$College[df$Player == "C.J. Miles"] <- "High School"
df$College[df$Player == "Monta Ellis"] <- "High School"
df$College[df$Player == "Louis Williams"] <- "High School"
df$College[df$Player == "Andray Blatche"] <- "High School"
df$College[df$Player == "Amir Johnson"] <- "High School"
#2006
df$College[df$Player == "Andrea Bargnani"] <- "International"
df$College[df$Player == "Mouhamed Sene"] <- "International"
df$College[df$Player == "Thabo Sefolosha"] <- "International"
df$College[df$Player == "Oleksiy Pecherov"] <- "International"
df$College[df$Player == "Sergio Rodriguez"] <- "International"
df$College[df$Player == "Joel Freeland"] <- "International"
df$College[df$Player == "Kosta Perovic"] <- "International"
df$College[df$Player == "Marcus Vinicius"] <- "International"
df$College[df$Player == "Lior Eliyahu"] <- "International"
df$College[df$Player == "Vladimir Veremeenko"] <- "International"
df$College[df$Player == "Cheikh Samb"] <- "International"
df$College[df$Player == "Yotam Halperin"] <- "International"
df$College[df$Player == "Ejike Ugboaja"] <- "International"
df$College[df$Player == "Edin Bavcic"] <- "International"
df$College[df$Player == "Loukas Mavrokefalidis"] <- "International"
df$College[df$Player == "Damir Markota"] <- "International"
#2007
df$College[df$Player == "Yi Jianlian"] <- "International"
df$College[df$Player == "Marco Belinelli"] <- "International"
df$College[df$Player == "Rudy Fernandez"] <- "International"
df$College[df$Player == "Tiago Splitter"] <- "International"
df$College[df$Player == "Petteri Koponen"] <- "International"
df$College[df$Player == "Kyrylo Fesenko"] <- "International"
df$College[df$Player == "Stanko Barac"] <- "International"
df$College[df$Player == "Sun Yue"] <- "International"
df$College[df$Player == "Marc Gasol"] <- "International"
df$College[df$Player == "Renaldas Seibutis"] <- "International"
df$College[df$Player == "Brad Newley"] <- "International"
df$College[df$Player == "Giorgos Printezis"] <- "International"
df$College[df$Player == "Milovan Rakovic"] <- "International"
#2008
df$College[df$Player == "Danilo Gallinari"] <- "International"
df$College[df$Player == "Alexis Ajinca"] <- "International"
df$College[df$Player == "Serge Ibaka"] <- "International"
df$College[df$Player == "Nicolas Batum"] <- "International"
df$College[df$Player == "Nikola Pekovic"] <- "International"
df$College[df$Player == "Omer Asik"] <- "International"
df$College[df$Player == "Nathan Jawai"] <- "International"
df$College[df$Player == "Ante Tomic"] <- "International"
df$College[df$Player == "Goran Dragic"] <- "International"
df$College[df$Player == "Tadija Dragicevic"] <- "International"
df$College[df$Player == "Semih Erden"] <- "International"
#做出Redraft欄位，依年份、Redraft順位排序
tables_test1 = lapply(c(1989:2008) ,function(yr){
df_2 <- subset(df, Year == yr)
df_2 <- df_2[order(-df_2$VORP), ]
df_Redraft = data.frame(VORP = df_2$VORP, Redraft=c(1:length(df_2$VORP)), Player = df_2$Player)
df_Redraft = df_Redraft[c("Player", "Redraft")]
df_2 <- left_join(df_2 , df_Redraft) %>%
arrange(Redraft) %>%
as.data.frame(stringsAsFactors=FALSE)
df_2
})
df_redraft2 <- Reduce(x = tables_test1, f = rbind)
#Rank - Redraft
p2 <- ggplot(data = df_redraft2, aes(Redraft, Rk)) +
scale_y_continuous(name="Rk", limits=c(0,60)) +
scale_x_continuous(name="Redraft", limits=c(0,60)) +
geom_abline(data=df_redraft2, mapping=aes(slope = 1, intercept = 0)) +
geom_point()
p2
#斜線上方是表現比預期好的球員，斜線下方是表現比預期差的球員。
#omit NA
df_redraft3 <- na.omit(df_redraft2)
p3 <- ggplot(data = df_redraft3, aes(Rk, Redraft)) +
scale_x_continuous(name="Rk", limits=c(0,60)) +
scale_y_continuous(name="Redraft", limits=c(0,60)) +
geom_abline(data=df_redraft3, mapping=aes(slope = 1, intercept = 0)) +
geom_point() +
coord_flip()
p3
#上場時間少於1000分鐘的不列入。MP_T > 1000
df_redraft4 <- subset(df_redraft2, MP_T > 1000)
p4 <- ggplot(data = df_redraft4, aes(Redraft, Rk)) +
scale_y_continuous(name="Rk", limits=c(0,60)) +
scale_x_continuous(name="Redraft", limits=c(0,60)) +
geom_abline(data=df_redraft4, mapping=aes(slope = 1, intercept = 0)) +
geom_point()
p4
#Player's Bust/Steal Value
tables_test3 = lapply(c(1989:2008) ,function(yr){
df_yr <- subset(df_redraft2, Year == yr)
df_1 <- subset(df_redraft2, Year == yr)
df_1 <- data.frame(cbind(df_1[, 1], df_1[, 6]))
colnames(df_1) <- c("Rk", "VORP_a")
df_1 <- df_1[order(df_1$Rk), ]
df_2 <- subset(df_redraft2, Year == yr)
df_2 <- data.frame(cbind(df_2[, 8], df_2[, 6]))
colnames(df_2) <- c("Redraft", "VORP_re")
df_test <- cbind(df_1, df_2)
df_test$BustSteal <- df_test$VORP_a - df_test$VORP_re
df_test <- df_test[c("Rk", "BustSteal")]
df_yr <- left_join(df_yr, df_test)
df_yr
})
df_BustSteal2 <- Reduce(x = tables_test3, f = rbind)
df_BustSteal2 <- na.omit(df_BustSteal3)
#Team Bust/Steal Value
team <- unique(df_BustSteal2$Tm)
tables_test4 = lapply(team ,function(tm){
df <- subset(df_BustSteal2, Tm == tm)
df_teamVORPsum <- sum(df$VORP) %>%
as.data.frame(stringsAsFactors=FALSE) %>%
cbind(tm)
colnames(df_teamVORPsum) <- c("teamVORP", "Tm")
df_teamVORPsum
})
df_teamVORPsum <- Reduce(x = tables_test4, f = rbind)
#The Best Year
tables_test5 = lapply(c(1989:2008) ,function(yr){
df_test <- na.omit(subset(df_redraft2, Year==yr))
maenVORP <- mean(df_test$VORP) %>%
as.data.frame(stringsAsFactors=FALSE)
maenVORP
})
df_meanVORP_total <- Reduce(x = tables_test5, f = rbind)
colnames(df_meanVORP_total) <- c("meanVORP")
df_meanVORP_total$Year <- c(1989:2008)
head(df_meanVORP_total , 60)
#Top 10
tables_test6 = lapply(c(1989:2008) ,function(yr){
df_test4 <-subset(df_redraft2, Year==yr) %>%
na.omit()
df_test4 <-subset(df_test4[c(1:10),])
maenVORP <- mean(df_test4$VORP) %>%
as.data.frame(stringsAsFactors=FALSE)
maenVORP
})
df_meanVORP_topten <- Reduce(x = tables_test6, f = rbind)
colnames(df_meanVORP_topten) <- c("meanVORP")
df_meanVORP_topten$Year <- c(1989:2008)
head(df_meanVORP_topten , 60)
#Top 5
tables_test7 = lapply(c(1989:2008) ,function(yr){
df_test4 <-subset(df_redraft2, Year==yr) %>%
na.omit()
df_test4 <-subset(df_test4[c(1:5),])
maenVORP <- mean(df_test4$VORP) %>%
as.data.frame(stringsAsFactors=FALSE)
maenVORP
})
df_meanVORP_topfive <- Reduce(x = tables_test7, f = rbind)
colnames(df_meanVORP_topfive) <- c("meanVORP")
df_meanVORP_topfive$Year <- c(1989:2008)
head(df_meanVORP_topfive , 60)