Dataset Proposal
My project will study the a large dataset containing various statistics and salaries for every NBA player on a roster for the 2022-23 season. This will allow me to examine which statisitics are most valued by NBA front offices when deciding how much money they offer a given player, as well as the most important statistics, both basic and advanced, when deciding to give a player a “max” contract. With advanced statistics and analytics consistenly becoming more important in league circles, this will allow me to examine if advanced statistics that go beyond the naked eye have become more valued if front offices. I can also see which stats are most strongly correlated with higher salaries, as well as winning the most games. This will also allow me to see which basic stats are most strongly correlated to certain adavanced stats and vice versa. I plan to utilize a wide range of ggplot methods to examine these results such as correlation heat maps, bar graphs, and basic plots.
Looking at the dataset
Below, I have provided code to load and then examine the first 20 frames of the dataset I plan to use for my project:
<- read.csv ("nba_2022-23_stats_salary.csv" )head (final_project_dataset, n= 20 )
X Player.Name Salary Position Age Team GP GS MP FG FGA
1 0 Stephen Curry 48070014 PG 34 GSW 56 56 34.7 10.0 20.2
2 1 John Wall 47345760 PG 32 LAC 34 3 22.2 4.1 9.9
3 2 Russell Westbrook 47080179 PG 34 LAL/LAC 73 24 29.1 5.9 13.6
4 3 LeBron James 44474988 PF 38 LAL 55 54 35.5 11.1 22.2
5 4 Kevin Durant 44119845 PF 34 BRK/PHO 47 47 35.6 10.3 18.3
6 5 Bradley Beal 43279250 SG 29 WAS 50 50 33.5 8.9 17.6
7 6 Kawhi Leonard 42492492 SF 31 LAC 52 50 33.6 8.6 16.8
8 7 Paul George 42492492 SF 32 LAC 56 56 34.6 8.2 17.9
9 8 Giannis Antetokounmpo 42492492 PF 28 MIL 63 63 32.1 11.2 20.3
10 9 Damian Lillard 42492492 PG 32 POR 58 58 36.3 9.6 20.7
11 10 Klay Thompson 40600080 SF 32 GSW 69 69 33.0 7.9 18.1
12 11 Kyrie Irving 38917057 PG-SG 30 BRK/DAL 60 60 37.4 9.9 20.1
13 12 Rudy Gobert 38172414 C 30 MIN 70 70 30.7 5.1 7.8
14 13 Khris Middleton 37984276 SF 31 MIL 33 19 24.3 5.4 12.3
15 14 Anthony Davis 37980720 C 29 LAL 56 54 34.0 9.7 17.2
16 15 Jimmy Butler 37653300 PF 33 MIA 64 64 33.4 7.5 13.9
17 16 Tobias Harris 37633050 SF 30 PHI 74 74 32.9 5.7 11.4
18 17 Kemba Walker 37281261 PG 32 DAL 9 1 16.0 2.7 6.3
19 18 Trae Young 37096500 PG 24 ATL 73 73 34.8 8.2 19.0
20 19 Zach LaVine 37096500 SG 27 CHI 77 77 35.9 8.7 18.0
FG. X3P X3PA X3P. X2P X2PA X2P. eFG. FT FTA FT. ORB DRB TRB AST
1 0.493 4.9 11.4 0.427 5.1 8.8 0.579 0.614 4.6 5.0 0.915 0.7 5.4 6.1 6.3
2 0.408 1.0 3.2 0.303 3.1 6.7 0.459 0.457 2.3 3.3 0.681 0.4 2.3 2.7 5.2
3 0.436 1.2 3.9 0.311 4.7 9.7 0.487 0.481 2.8 4.3 0.656 1.2 4.6 5.8 7.5
4 0.500 2.2 6.9 0.321 8.9 15.3 0.580 0.549 4.6 5.9 0.768 1.2 7.1 8.3 6.8
5 0.560 2.0 4.9 0.404 8.3 13.4 0.617 0.614 6.5 7.1 0.919 0.4 6.3 6.7 5.0
6 0.506 1.6 4.4 0.365 7.3 13.2 0.552 0.551 3.8 4.6 0.842 0.8 3.1 3.9 5.4
7 0.512 2.0 4.8 0.416 6.6 11.9 0.551 0.572 4.7 5.4 0.871 1.1 5.4 6.5 3.9
8 0.457 2.8 7.6 0.371 5.4 10.3 0.521 0.536 4.6 5.3 0.871 0.8 5.3 6.1 5.1
9 0.553 0.7 2.7 0.275 10.5 17.6 0.596 0.572 7.9 12.3 0.645 2.2 9.6 11.8 5.7
10 0.463 4.2 11.3 0.371 5.4 9.4 0.574 0.564 8.8 9.6 0.914 0.8 4.0 4.8 7.3
11 0.436 4.4 10.6 0.412 3.6 7.6 0.470 0.556 1.7 1.9 0.879 0.6 3.6 4.1 2.4
12 0.494 3.1 8.3 0.379 6.8 11.8 0.574 0.572 4.1 4.6 0.905 1.0 4.1 5.1 5.5
13 0.659 0.0 0.0 0.000 5.1 7.8 0.663 0.659 3.1 4.9 0.644 3.3 8.3 11.6 1.2
14 0.436 1.5 4.9 0.315 3.8 7.4 0.516 0.499 2.8 3.1 0.902 0.8 3.4 4.2 4.9
15 0.563 0.3 1.3 0.257 9.3 15.9 0.589 0.573 6.2 7.9 0.784 3.5 9.1 12.5 2.6
16 0.539 0.6 1.6 0.350 6.9 12.3 0.564 0.560 7.4 8.7 0.850 2.2 3.7 5.9 5.3
17 0.501 1.7 4.4 0.389 4.0 7.0 0.570 0.575 1.5 1.7 0.876 0.9 4.8 5.7 2.5
18 0.421 0.8 3.1 0.250 1.9 3.2 0.586 0.482 1.9 2.3 0.810 0.3 1.4 1.8 2.1
19 0.429 2.1 6.3 0.335 6.1 12.7 0.476 0.485 7.8 8.8 0.886 0.8 2.2 3.0 10.2
20 0.485 2.6 7.1 0.375 6.1 11.0 0.556 0.558 4.7 5.6 0.848 0.5 3.9 4.5 4.2
STL BLK TOV PF PTS Total.Minutes PER TS. X3PAr FTr ORB. DRB. TRB.
1 0.9 0.4 3.2 2.1 29.4 1941 24.1 0.656 0.564 0.248 2.3 16.8 9.7
2 0.8 0.4 2.4 1.7 11.4 755 13.6 0.498 0.322 0.334 2.1 11.4 6.8
3 1.0 0.5 3.5 2.2 15.9 2126 16.1 0.513 0.289 0.317 4.7 16.5 10.8
4 0.9 0.6 3.2 1.6 28.9 1954 23.9 0.583 0.309 0.268 3.7 20.8 12.5
5 0.7 1.4 3.3 2.1 29.1 1672 25.9 0.677 0.267 0.387 1.2 19.5 10.5
6 0.9 0.7 2.9 2.1 23.2 1673 19.7 0.593 0.249 0.260 2.8 9.9 6.5
7 1.4 0.5 1.7 1.6 23.8 1748 23.9 0.623 0.287 0.320 3.7 17.8 10.8
8 1.5 0.4 3.1 2.8 23.8 1939 19.6 0.588 0.424 0.293 2.6 17.0 9.9
9 0.8 0.8 3.9 3.1 31.1 2024 29.0 0.605 0.134 0.604 7.3 30.0 19.1
10 0.9 0.3 3.3 1.9 32.2 2107 26.7 0.645 0.547 0.464 2.4 12.8 7.6
11 0.7 0.4 1.8 1.9 21.9 2279 14.7 0.576 0.584 0.105 1.9 11.7 6.9
12 1.1 0.8 2.1 2.8 27.1 2241 22.4 0.613 0.412 0.227 3.0 12.3 7.7
13 0.8 1.4 1.7 3.0 13.4 2148 18.9 0.675 0.005 0.623 12.2 29.8 21.2
14 0.7 0.2 2.2 2.1 15.1 801 17.4 0.551 0.399 0.251 3.8 14.0 9.1
15 1.1 2.0 2.2 2.6 25.9 1904 27.8 0.627 0.077 0.462 11.3 27.6 19.7
16 1.8 0.3 1.6 1.3 22.9 2138 27.6 0.647 0.116 0.625 7.5 13.3 10.3
17 0.9 0.5 1.2 2.0 14.7 2436 14.8 0.602 0.383 0.153 3.3 17.0 10.3
18 0.2 0.2 0.4 1.2 8.0 144 15.0 0.543 0.491 0.368 2.4 10.6 6.5
19 1.1 0.1 4.1 1.4 26.2 2541 22.0 0.573 0.331 0.460 2.4 7.0 4.7
20 0.9 0.2 2.5 2.1 24.8 2768 19.0 0.607 0.392 0.308 1.7 12.2 7.1
AST. STL. BLK. TOV. USG. OWS DWS WS WS.48 OBPM DBPM BPM VORP
1 30.0 1.3 0.9 12.5 31.0 5.8 2.0 7.8 0.192 7.5 0.1 7.5 4.7
2 35.3 1.8 1.4 17.1 27.0 -0.4 0.7 0.3 0.020 -0.8 -0.4 -1.2 0.1
3 38.6 1.7 1.3 18.4 27.7 -0.6 2.6 1.9 0.044 0.3 -0.1 0.2 1.2
4 33.5 1.2 1.4 11.6 33.3 3.2 2.4 5.6 0.138 5.5 0.6 6.1 4.0
5 24.5 1.0 3.4 13.4 30.7 4.7 2.1 6.8 0.194 6.0 1.2 7.1 3.9
6 26.6 1.3 1.7 12.9 29.2 2.2 1.2 3.4 0.099 2.9 -1.2 1.8 1.6
7 19.6 2.0 1.4 8.1 27.0 4.9 2.2 7.1 0.194 5.1 0.9 6.1 3.5
8 24.2 2.1 0.9 13.4 29.5 2.3 2.3 4.6 0.114 2.4 0.3 2.8 2.3
9 33.2 1.2 2.1 13.2 38.8 4.9 3.7 8.6 0.204 5.8 2.7 8.5 5.4
10 35.0 1.2 0.8 11.7 33.8 8.2 0.8 9.0 0.205 8.3 -1.2 7.1 4.9
11 11.0 1.0 1.1 8.6 26.4 1.2 1.9 3.1 0.066 1.5 -1.7 -0.3 1.0
12 25.4 1.4 1.7 8.8 28.9 5.4 2.0 7.4 0.159 4.8 -0.7 4.1 3.5
13 5.6 1.2 3.9 14.9 16.3 4.3 3.5 7.8 0.174 0.0 0.7 0.7 1.4
14 30.7 1.4 0.5 13.6 27.4 1.0 1.0 1.9 0.117 1.0 -0.3 0.8 0.6
15 13.0 1.5 5.1 9.5 28.4 5.5 3.4 9.0 0.226 4.6 1.7 6.3 4.0
16 27.1 2.7 1.0 8.2 25.6 9.4 2.9 12.3 0.277 6.7 2.0 8.7 5.8
17 11.4 1.4 1.5 9.0 18.2 3.1 2.8 5.9 0.116 0.6 0.1 0.7 1.7
18 20.1 0.7 1.2 5.7 22.1 0.2 0.1 0.3 0.098 0.3 -0.6 -0.3 0.1
19 42.5 1.5 0.3 15.2 32.6 5.3 1.4 6.7 0.126 5.3 -2.0 3.3 3.4
20 18.7 1.2 0.6 11.0 28.3 4.2 2.9 7.1 0.123 2.7 -0.7 1.9 2.7