It's late. Very very late, or ridiculously early, depending on your point of view. I have fixation issues when I get to thinking about data, and had an idea tonight, when seeing some player ratings on CBS to how those ratings would equate to team success, i.e., wins and losses. This curiosity would prove to be a bad idea. This from the guy whose uncle once offered him five bucks to untie a fishing line snarl on a lakeshore after I decided I wasn't as interested in our fishing outing as he'd hoped. Five hours later, I had my five bucks. Eight-year-old OCD slave labor is what that was. I loved it. I have a problem.
The CBS player ratings made me wonder where Nuggets players had landed, and so I went out to CBS’ player ratings page online, and downloaded the file to a spreadsheet. From that spreadsheet, I intended to loop every player back in under their team and see what an aggregate score of their player ratings would be. If player ratings equated to team success, then surely the higher teams would have far higher aggregate player ranking scores, right? Hmmm…
Four hours later, I finally had my answer. I'm proud to report that (drumroll, please)
Player ratings (at least as equated by CBS.com) don't mean diddly-jack-squat to team success.
Wait, back up… four hours? Yeah, see, I love data, but it doesn't love me. My relationship with data is exactly like my relationship to garlic. They both taste delicious, and they both give me gas. But I digest. Er, digress. Both.
After I got that data set into the spreadsheet, I don't know how to write query strings or anything like that, let alone output those results. So I built the lists from scratch. And I was going to prove my point about the player ratings by looping in every player. All 438 of them. Yeah… my data scientist pals laugh their asses off at me.
About an hour in, the data was already giving me my answers, just in watching the individual teams flow in from the top of the player rating list. I wish I could have animated the build, it was visually telling. Seven teams had five players on their list before the last team to have none (Indiana) notched a player. A dozen players later, I had to decide if I was going to tack on sixth members for some teams before getting a couple of teams player number two or three. It would take me three more hours just to drop the players in. And it's already obvious the teams are filling in sporadically. How could I see something in this data and not lose the work? I may not have been successful.
I filled each team in to their top five ‘player rated' players (even if a player came in off the bench), and added up the aggregate scores. The list of players who were sixth/seventh/etc. men was as intereting as the guys on this list. Though the top teams have higher scores than the lowest teams, there are 300+ point teams in the lowest 5, and teams barely above 300 in the top six. Indiana had an aggregate score 17 points lower than your Denver Nuggets, and still were five spots ahead in overall league rankings. Example after example of no pattern. You all may see pattern here I'm not (do higher ranked teams have more starters in their top five? Do more successful teams have high-player-rated positional overlaps? Can I have just a little bit of peril?)
Here's the data that didn't tell me a thing after a long evening.
|
TEAM |
|
|
PLAYER |
RATING |
|
4. Stephen Curry, GS |
81.1 |
|
16. Klay Thompson, GS |
75.95 |
|
44. Draymond Green, GS |
68.27 |
|
78. Harrison Barnes, GS |
61.99 |
|
138. Marreese Speights, GS |
54.33 |
|
341.64 |
|
|
22. Paul Millsap, ATL |
73.27 |
|
30. Jeff Teague, ATL |
70.43 |
|
32. Al Horford, ATL |
70.09 |
|
45. Kyle Korver, ATL |
68.1 |
|
85. DeMarre Carroll, ATL |
61.17 |
|
343.06 |
|
|
1. James Harden, HOU |
86.25 |
|
54. Trevor Ariza, HOU |
66.16 |
|
71. Dwight Howard, HOU |
63.11 |
|
79. Josh Smith, HOU |
61.78 |
|
97. Donatas Motiejunas, HOU |
59.24 |
|
336.54 |
|
|
4. Los Angeles Clippers |
|
|
5. Blake Griffin, LAC |
80.29 |
|
10. Chris Paul, LAC |
78.62 |
|
27. DeAndre Jordan, LAC |
71.69 |
|
76. J.J. Redick, LAC |
62.19 |
|
89. Jamal Crawford, LAC |
60.39 |
|
353.18 |
|
|
13. Marc Gasol, MEM |
76.62 |
|
32. Mike Conley, MEM |
70.09 |
|
34. Zach Randolph, MEM |
69.99 |
|
65. Jeff Green, MEM |
64.7 |
|
81. Courtney Lee, MEM |
61.75 |
|
343.15 |
|
|
6. San Antonio Spurs |
|
|
40. Tim Duncan, SA |
68.71 |
|
66. Danny Green, SA |
64.64 |
|
98. Kawhi Leonard, SA |
59.14 |
|
125. Cory Joseph, SA |
56.31 |
|
127. Manu Ginobili, SA |
56.11 |
|
304.91 |
|
|
3. LeBron James, CLE |
82.9 |
|
11. Kyrie Irving, CLE |
76.88 |
|
21. Kevin Love, CLE |
73.97 |
|
94. Tristan Thompson, CLE |
59.63 |
|
108. Timofey Mozgov, CLE |
|
|
351.15 |
|
|
8. LaMarcus Aldridge, POR |
79.11 |
|
9. Damian Lillard, POR |
79.06 |
|
49. Wesley Matthews, POR |
67.38 |
|
57. Arron Afflalo, POR |
65.57 |
|
90. Nicolas Batum, POR |
60.12 |
|
351.24 |
|
|
6. Jimmy Butler, CHI |
79.63 |
|
7. Pau Gasol, CHI |
79.27 |
|
95. Derrick Rose, CHI |
59.62 |
|
116. Taj Gibson, CHI |
57 |
|
139. Joakim Noah, CHI |
54.3 |
|
329.82 |
|
|
10. Dallas Mavericks |
|
|
28. Monta Ellis, DAL |
71.64 |
|
37. Dirk Nowitzki, DAL |
69.29 |
|
38. Tyson Chandler, DAL |
69.08 |
|
50. Chandler Parsons, DAL |
67.15 |
|
87. Rajon Rondo, DAL |
60.69 |
|
337.85 |
|
|
11. Toronto Raptors |
|
|
14. Kyle Lowry, TOR |
76.36 |
|
74. Jonas Valanciunas, TOR |
62.48 |
|
91. Amir Johnson, TOR |
59.93 |
|
103. Lou Williams, TOR |
58.39 |
|
114. Patrick Patterson, TOR |
57.05 |
|
314.21 |
|
|
15. John Wall, WAS |
76 |
|
68. Marcin Gortat, WAS |
63.66 |
|
72. Bradley Beal, WAS |
62.91 |
|
86. Paul Pierce, WAS |
61.09 |
|
136. Nene, WAS |
54.59 |
|
318.25 |
|
|
13. New Orleans Pelicans |
|
|
2. Anthony Davis, NO |
85.82 |
|
31. Tyreke Evans, NO |
70.2 |
|
51. Jrue Holiday, NO |
66.83 |
|
84. Ryan Anderson, NO |
61.54 |
|
132. Omer Asik, NO |
55.6 |
|
339.99 |
|
|
39. Russell Westbrook, OKC |
68.85 |
|
48. Serge Ibaka, OKC |
67.41 |
|
58. Kevin Durant, OKC |
65.54 |
|
67. Reggie Jackson, OKC < /td> |
63.72 |
|
146. Steven Adams, OKC |
53.39 |
|
318.91 |
|
|
15. Milwaukee Bucks |
|
|
29. Brandon Knight, MIL |
70.99 |
|
77. Giannis Antetokounmpo, MIL |
62.14 |
|
101. Khris Middleton, MIL |
58.86 |
|
128. O.J. Mayo, MIL |
55.86 |
|
147. Jared Dudley, MIL |
53.32 |
|
301.17 |
|
|
16. Boston Celtics |
|
|
59. Jared Sullinger, BOS |
65.51 |
|
96. Avery Bradley, BOS |
59.45 |
|
110. Evan Turner, BOS |
57.43 |
|
118. Kelly Olynyk, BOS |
56.88 |
|
136. Tyler Zeller, BOS |
54.59 |
|
293.86 |
|
|
17, Phoenix Suns |
|
|
26. Eric Bledsoe, PHO |
71.79 |
|
42. Goran Dragic, PHO |
68.57 |
|
61. Markieff Morris, PHO |
65.24 |
|
104. Isaiah Thomas, PHO |
58.32 |
|
113. P.J. Tucker, PHO |
57.2 |
|
321.12 |
|
|
18. Brooklyn Nets |
|
|
40. Joe Johnson, BKN |
68.71 |
|
93. Jarrett Jack, BKN |
59.8 |
|
112. Deron Williams, BKN |
57.33 |
|
121. Mason Plumlee, BKN |
56.5 |
|
131. Brook Lopez, BKN |
55.74 |
|
298.08 |
|
|
19. Indiana Pacers |
|
|
92. Solomon Hill, IND |
59.84 |
|
111. Roy Hibbert, IND |
57.39 |
|
134. Rodney Stuckey, IND |
55.22 |
|
141. David West, IND |
54.09 |
|
149. Luis Scola, IND |
53.27 |
|
279.81 |
|
|
20. Utah Jazz |
|
|
19. Gordon Hayward, UTA |
74.8 |
|
45. Derrick Favors, UTA |
68.1 |
|
82. Enes Kanter, UTA |
61.7 |
|
83. Trey Burke, UTA |
61.68 |
|
120. Rudy Gobert, UTA |
56.57 |
|
322.85 |
|
|
21. Miami Heat |
|
|
25. Chris Bosh, MIA |
72.14 |
|
52. Dwyane Wade, MIA |
66.76 |
|
53. Luol Deng, MIA |
66.21 |
|
99. Mario Chalmers, MIA |
59.11 |
|
179. Shawne Williams, MIA |
50.23 |
|
314.45 |
|
|
24. Kemba Walker, CHA |
72.16 |
|
60. Al Jefferson, CHA |
65.43 |
|
130. Gerald Henderson, CHA |
55.79 |
|
157. Cody Zeller, CHA |
52.75 |
|
178. Marvin Williams, CHA |
50.27 |
|
296.4 |
|
|
23. Detroit Pistons |
|
|
47. Greg Monroe, DET |
67.9 |
|
56. Andre Drummond, DET |
65.76 |
|
72. Brandon Jennings, DET |
62.91 |
|
100. Kentavious Caldwell-Pope, DET |
59.03 |
|
159. D.J. Augustin, DET |
52.53 |
|
308.13 |
|
|
24. Denver Nuggets |
|
|
19. Ty Lawson, DEN |
74.8 |
|
62. Wilson Chandler, DEN |
65.05 |
|
80. Kenneth Faried, DEN |
61.77 |
|
204. Jameer Nelson, DEN |
47.6 |
|
207. JJ Hickson, DEN |
47.4 |
|
296.62 |
|
|
25. Sacramento Kings |
|
|
17. DeMarcus Cousins, SAC |
75.62 |
|
18. Rudy Gay, SAC |
75.3 |
|
35. Darren Collison, SAC |
69.75 |
|
88. Ben McLemore, SAC |
60.5 |
|
184. Jason Thompson, SAC |
49.43 |
|
330.6 |
|
|
26. Orlando Magic |
|
|
12. Nikola Vucevic, ORL |
76.75 |
|
36. Tobias Harris, ORL |
69.44 |
|
64. Victor Oladipo, ORL |
64.81 |
|
102. Evan Fournier, ORL |
58.73 |
|
122. Channing Frye, ORL |
56.44 |
|
326.17 |
|
|
27. Los Angeles Lakers |
|
|
43. Kobe Bryant, LAL |
68.35 |
|
75. Jordan Hill, LAL |
62.2 |
|
105. Carlos Boozer, LAL |
58.23 |
|
109. Wesley Johnson, LAL |
57.64 |
|
115. Jeremy Lin, LAL |
57.02 |
|
303.44 |
|
|
70. Michael Carter-Williams, PHI |
63.54 |
|
126. Nerlens Noel, PHI (Rookie) |
56.18 |
|
135. K.J. McDaniels, PHI (Rookie) |
54.7 |
|
142. Henry Sims, PHI |
53.85 |
|
143. Robert Covington, PHI |
53.68 |
|
281.95 |
|
|
29. New York Knicks |
|
|
23. Carmelo Anthony, NY |
72.84 |
|
154. Tim Hardaway Jr., NY |
53.1 |
|
170. Amar’e Stoudemire, NY |
51.06 |
|
181. Jose Calderon, NY |
50.04 |
|
192. Shane Larkin, NY |
49.15 |
|
276.19 |
|
|
55. Andrew Wiggins, MIN (Rookie) |
65.84 |
|
63. Gorgui Dieng, MIN |
64.84 |
|
69. Thaddeus Young, MIN |
63.63 |
|
117. Mo Williams, MIN |
56.9 |
|
145. Shabazz Muhammad, MIN |
53.48 |
|
304.69 |
Maybe you see something in there I don't… The experiment was a failure, but:
"It's not an experiment if you know it's going to work."
-Jeff Bezos
My wife occasionally shuffles in around 3 am to just shake her head at me writing free and unneccesary basketball drivel and wanders back to sleep. Seems to be something to this beauty sleep thing, looking at us both. There's data you can actually use. Just remember my news flash that you never ever already knew… Player ratings do NOT equate to overall team success. Shocking. Please go back to your homes, nothing to see here.
And miles to go before I sleep. Good morning, Stiff(s). There's a phrase you don't see every day.
#NeverGonnaMakeTheFiveThirtyEight
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