R Notebook
# Read in the data
NBA = read.csv("C:/Users/iambi/OneDrive/Documents/NBA_train.csv")
str(NBA)## 'data.frame': 835 obs. of 20 variables:
## $ SeasonEnd: int 1980 1980 1980 1980 1980 1980 1980 1980 1980 1980 ...
## $ Team : chr "Atlanta Hawks" "Boston Celtics" "Chicago Bulls" "Cleveland Cavaliers" ...
## $ Playoffs : int 1 1 0 0 0 0 0 1 0 1 ...
## $ W : int 50 61 30 37 30 16 24 41 37 47 ...
## $ PTS : int 8573 9303 8813 9360 8878 8933 8493 9084 9119 8860 ...
## $ oppPTS : int 8334 8664 9035 9332 9240 9609 8853 9070 9176 8603 ...
## $ FG : int 3261 3617 3362 3811 3462 3643 3527 3599 3639 3582 ...
## $ FGA : int 7027 7387 6943 8041 7470 7596 7318 7496 7689 7489 ...
## $ X2P : int 3248 3455 3292 3775 3379 3586 3500 3495 3551 3557 ...
## $ X2PA : int 6952 6965 6668 7854 7215 7377 7197 7117 7375 7375 ...
## $ X3P : int 13 162 70 36 83 57 27 104 88 25 ...
## $ X3PA : int 75 422 275 187 255 219 121 379 314 114 ...
## $ FT : int 2038 1907 2019 1702 1871 1590 1412 1782 1753 1671 ...
## $ FTA : int 2645 2449 2592 2205 2539 2149 1914 2326 2333 2250 ...
## $ ORB : int 1369 1227 1115 1307 1311 1226 1155 1394 1398 1187 ...
## $ DRB : int 2406 2457 2465 2381 2524 2415 2437 2217 2326 2429 ...
## $ AST : int 1913 2198 2152 2108 2079 1950 2028 2149 2148 2123 ...
## $ STL : int 782 809 704 764 746 783 779 782 900 863 ...
## $ BLK : int 539 308 392 342 404 562 339 373 530 356 ...
## $ TOV : int 1495 1539 1684 1370 1533 1742 1492 1565 1517 1439 ...# How many wins to make the playoffs?
table(NBA$W, NBA$Playoffs)##
## 0 1
## 11 2 0
## 12 2 0
## 13 2 0
## 14 2 0
## 15 10 0
## 16 2 0
## 17 11 0
## 18 5 0
## 19 10 0
## 20 10 0
## 21 12 0
## 22 11 0
## 23 11 0
## 24 18 0
## 25 11 0
## 26 17 0
## 27 10 0
## 28 18 0
## 29 12 0
## 30 19 1
## 31 15 1
## 32 12 0
## 33 17 0
## 34 16 0
## 35 13 3
## 36 17 4
## 37 15 4
## 38 8 7
## 39 10 10
## 40 9 13
## 41 11 26
## 42 8 29
## 43 2 18
## 44 2 27
## 45 3 22
## 46 1 15
## 47 0 28
## 48 1 14
## 49 0 17
## 50 0 32
## 51 0 12
## 52 0 20
## 53 0 17
## 54 0 18
## 55 0 24
## 56 0 16
## 57 0 23
## 58 0 13
## 59 0 14
## 60 0 8
## 61 0 10
## 62 0 13
## 63 0 7
## 64 0 3
## 65 0 3
## 66 0 2
## 67 0 4
## 69 0 1
## 72 0 1# Compute Points Difference
NBA$PTSdiff = NBA$PTS - NBA$oppPTS
NBA$PTSdiff## [1] 239 639 -222 28 -362 -676 -360 14 -57 257 484 323
## [13] -96 -94 346 295 -67 -31 -340 382 -493 -209 -254 482
## [25] 162 -398 -689 -39 -518 -97 27 115 1 315 596 -494
## [37] 133 644 452 73 236 -130 -135 -483 1 44 523 -166
## [49] -698 -363 43 -75 85 -3 -153 -254 399 449 56 -219
## [61] 470 283 49 189 -606 339 -464 72 -78 439 -401 -610
## [73] -34 51 -33 -297 -951 -480 119 455 361 227 201 629
## [85] 415 175 300 -396 263 -344 -11 -106 538 -425 -349 35
## [97] -90 294 -279 -253 -395 -121 308 341 90 315 180 73
## [109] 291 -22 -267 -14 93 -237 -119 545 -69 -226 178 200
## [121] 204 -602 141 -509 -219 -368 603 562 19 -380 336 -173
## [133] 279 75 -446 -9 -22 194 772 -312 -235 90 107 96
## [145] -283 214 -273 -568 635 741 -163 -460 193 -245 87 -252
## [157] -152 -8 -30 -148 593 545 73 -313 517 -71 282 -192
## [169] 82 -53 -937 763 321 -414 -514 -16 -200 257 -264 -418
## [181] 38 33 -112 295 487 279 62 358 334 424 -682 114
## [193] -65 -846 479 44 -665 -40 -118 -367 371 -472 -400 169
## [205] 302 -63 403 95 -699 118 623 -99 139 476 -25 78
## [217] -342 -813 588 -921 296 -521 309 123 631 120 -455 -597
## [229] 238 412 -177 84 327 -641 267 -25 6 116 499 -257
## [241] 120 13 -278 556 -797 -64 -347 -645 116 -731 409 582
## [253] 518 -415 286 85 393 -177 63 477 -430 746 -202 -375
## [265] -895 268 134 287 -32 -283 553 -491 203 -322 -370 -19
## [277] -326 -15 537 712 -556 370 101 273 -408 -123 297 -320
## [289] 856 447 -627 -645 167 320 -141 155 88 -90 -345 -140
## [301] -578 -139 319 -567 -104 487 596 -497 272 154 524 -366
## [313] -71 73 -20 516 529 -1246 -143 -114 -81 347 139 29
## [325] -104 -94 -306 -638 103 505 108 -473 546 255 -260 219
## [337] 580 178 -577 432 -351 -18 253 330 -713 122 -638 143
## [349] 354 283 -469 -352 219 -531 -568 180 573 319 -625 397
## [361] 216 -473 431 745 346 -605 105 -154 269 396 51 -238
## [373] 69 -598 -444 174 303 -751 -18 -134 -358 -738 -257 255
## [385] 579 -416 318 313 -82 489 671 655 -459 100 -279 -47
## [397] 1004 212 -402 -222 205 -119 143 266 -295 365 117 -435
## [409] -439 -347 190 456 -820 27 193 -222 517 639 -616 540
## [421] -818 87 446 -601 153 886 151 -521 -515 430 -386 367
## [433] 80 -193 350 450 -155 -121 -374 256 -29 -536 54 342
## [445] -277 -646 630 -256 721 -839 133 288 -215 164 583 224
## [457] -501 -966 129 -748 -62 499 -604 635 404 -157 58 129
## [469] 202 -88 -196 425 115 -458 327 588 -760 536 -599 48
## [481] -441 -62 219 -771 -287 -47 -174 118 -678 -71 377 -945
## [493] 701 255 18 207 -85 120 56 110 428 525 239 487
## [505] 78 -13 366 -461 -269 -427 -175 172 -746 -348 351 -202
## [517] -139 -742 188 -16 -237 277 188 318 111 -414 216 81
## [529] 351 181 344 477 636 2 185 385 -470 -547 -347 181
## [541] 79 -700 -273 349 -477 175 -443 -401 22 -38 584 -610
## [553] -126 -18 277 341 -327 129 131 -56 245 624 509 248
## [565] -36 73 -115 -292 -32 -421 -789 638 -679 302 -93 121
## [577] 286 -338 191 -265 -414 19 170 428 173 -111 11 189
## [589] 93 214 533 444 -10 -481 196 -83 -381 -119 -521 -215
## [601] 364 88 479 -60 142 472 -376 320 200 43 87 450
## [613] 205 -8 -121 -576 -204 -307 -104 411 592 -52 -247 -100
## [625] -462 -796 71 -491 87 65 471 166 317 -177 331 62
## [637] -63 -243 188 535 -245 119 -123 -580 -200 -184 -61 584
## [649] -328 177 640 188 -133 -350 -27 -390 -126 -328 52 183
## [661] 498 19 547 -111 -130 155 129 205 303 317 -85 -154
## [673] 112 -231 -525 -88 -160 455 -775 126 559 -248 -245 -216
## [685] 152 -390 -280 -307 411 314 592 133 341 -28 398 -200
## [697] -38 -6 -422 -75 -359 -301 -63 -129 -234 64 -248 599
## [709] -352 -148 691 -237 81 235 -42 -149 841 -359 -253 -29
## [721] 372 304 606 181 384 -115 -596 595 -509 -709 -565 -556
## [733] -415 433 -542 448 34 414 -80 -185 393 -718 238 564
## [745] -27 129 616 -104 -23 732 162 280 -40 -307 328 -91
## [757] -719 628 -448 21 -89 -403 -200 127 -214 -500 549 6
## [769] 158 438 -718 308 -231 217 -612 382 300 120 -134 535
## [781] 223 335 -419 -295 -30 -247 -521 387 -124 187 139 -787
## [793] -748 -202 -313 286 614 -320 402 271 -358 417 -146 438
## [805] -392 -67 440 -328 600 -739 347 390 -295 -191 179 -88
## [817] -257 501 192 612 -69 -544 -512 73 64 311 448 123
## [829] -73 125 -438 468 -515 -150 -607# Check for linear relationship
plot(NBA$PTSdiff, NBA$W)
# Linear regression model for wins
WinsReg = lm(W ~ PTSdiff, data=NBA)
summary(WinsReg)##
## Call:
## lm(formula = W ~ PTSdiff, data = NBA)
##
## Residuals:
## Min 1Q Median 3Q Max
## -9.7393 -2.1018 -0.0672 2.0265 10.6026
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 4.100e+01 1.059e-01 387.0 <2e-16 ***
## PTSdiff 3.259e-02 2.793e-04 116.7 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 3.061 on 833 degrees of freedom
## Multiple R-squared: 0.9423, Adjusted R-squared: 0.9423
## F-statistic: 1.361e+04 on 1 and 833 DF, p-value: < 2.2e-16#Wins = 41+0.03259*(PD)
# We created an object containing 49 wins minus the intercept estimate (41) divided by the PTSdiff coefficient estimate
PD = (49-41)/0.03259
PD## [1] 245.4741##Our data shows that a team with 49 wins has never missed the playoffs. What is the expected points difference for a team to make it to the postseason? Use the lecture solution file and more specifically the WingsReg model.
#A point difference of 245 will guarantee a presence in the playoffs