Comparing the contribution of NBA draft picks

When it comes to the NBA draft, experts tend to argue about a number of things: at which position will a player be selected? what is the best draft class ever? etc… Luckily, the wealth of data made available by the great people of http://www.basketball-reference.com/draft/ make it possible to address a number of these, and other questions.

To begin, I started off by writing a quick Python script to scrape draft data for the time period of 1980-2014 (see at the end of this post for the source code, or on my GitHub). For the purpose of this analysis, I focussed on some key metrics that I deemed to be informative and useful enough to investigate further, which included:

  • Name of player (player)
  • College of drafted player (college)
  • Year of draft (draft_year)
  • Draft pick rank (rank)
  • Team that drafter the player (team)
  • Total games played (gp)
  • Total minutes played (mp)
  • Minutes per game (mpg)
  • Points per game (ppg)
  • Assists per game (apg)
  • Rebounds per game (rbg)
  • Win shares (ws)
  • Win shares per 48 minutes (ws_48)
  • Total years in league (yrs)

Once this was achieved, I began by measuring the respective contribution of each pick position during the period of 1980-2014. Here, I simply computed and normalized the median statistics for each pick position. Not too surprisingly, higher draft picks tend to be contribute more to their respective teams, although we do notice that some late 2nd round draft pick have high win shares per 48 numbers. It turns out that these correspond to the picks at which Kurt Rambis (57th) and Manu Ginobilli (58th) were picked…but more on this later

pick_performance
Next, I decided to estimate the quality of each draft year by measuring how players performed in comparison to players picked at the same rank during other years. I was somewhat surprised to discover that the draft crop of 2008 was the one with the highest win shares, although looking back at the players that participated at that draft, it makes a lot of sense! On the other hand, the vaunted draft class of 1984 (Olajuwon, Barkley, Jordan) and 2003 (James, Anthony, Wade, Bosh) did not fare as well, which may be attributable to the fact that these included more elite players, but were far less deep in the lower picks of the draft.
draft_year_performance
Next, I looked at the longevity of each draft pick, in other words how long each draft pick is expected to remain in the NBA league, which can be achieved by using survival curves. Not too surprisingly, higher draft picks are much more likely to stay longer in the league. As a general observation, this also means that NBA teams are quite proficient at selecting the right players at the right position.

pick_survival_curve

At this point, we can examine the relative performance of NBA teams with regards to their drafting skills. To do this, I compared the performance of each player compared to the average performance of other players drafted at the same position, computed the respective ratios, and summed these up for each NBA team. This analysis revealed that the top 5 drafting teams were Detroit Pistons, Cleveland Cavaliers, Memphis Grizzlies, Phoenix Suns and the San Antonio Spurs (I purposely ignored the Brooklyn Nets and the New Orleans Hornets because of the small number of years these two teams have been in the league.)

team_draft_ranking

Finally, I decided to look for the best players picked at each position. Again, I compared each player’s career stats to the average numbers obtained by other players picked at the same position. For display purposes, I only show the top three players at each pick position, although you can easily reproduce the results by re-running my code here. (At this point, I should take the opportunity to advertise the great stargazer R package, which allows to quickly output R objects into LaTex or HTML tables). The results I obtained made a lot of sense, and I was very interested to learn that even at pick position 13, Kobe Bryant was only the 2nd best pick, as he was outnumbered by none other than the Mailman himself (i.e. Karl Malone). Of course, this analysis only considers numbers as opposed to achievements and trophies, but I think it is still amusing to find that Kobe Bryant isn’t even the most productive player at his position.

Best pick 2nd best pick 3rd best pick
1 LeBron James John Wall Allen Iverson
2 Isiah Thomas Jason Kidd Gary Payton
3 Michael Jordan Deron Williams Pau Gasol
4 Chris Paul Russell Westbrook Stephon Marbury
5 Charles Barkley Dwyane Wade Kevin Garnett
6 Damian Lillard Brandon Roy Antoine Walker
7 Kevin Johnson Stephen Curry Alvin Robertson
8 Andre Miller Clark Kellogg Detlef Schrempf
9 Dirk Nowitzki Tracy McGrady Andre Iguodala
10 Paul Pierce Brandon Jennings Paul George
11 Fat Lever Michael Carter-Williams Terrell Brandon
12 Mookie Blaylock Muggsy Bogues John Bagley
13 Karl Malone Kobe Bryant Sleepy Floyd
14 Tim Hardaway Clyde Drexler Peja Stojakovic
15 Steve Nash Al Jefferson Gary Grant
16 John Stockton Nikola Vucevic Metta World Peace
17 Jrue Holiday Josh Smith Shawn Kemp
18 Mark Jackson Ty Lawson Joe Dumars
19 Rod Strickland Zach Randolph Jeff Teague
20 Larry Nance Jameer Nelson Paul Pressey
21 Rajon Rondo Darren Collison Michael Finley
22 Scott Skiles Reggie Lewis Kenneth Faried
23 Tayshaun Prince A.C. Green Wilson Chandler
24 Sam Cassell Kyle Lowry Arvydas Sabonis
25 Jeff Ruland Mark Price Nicolas Batum
26 Vlade Divac Kevin Martin George Hill
27 Dennis Rodman Jamaal Tinsley Jordan Crawford
28 Tony Parker Sherman Douglas Gene Banks
29 Toni Kukoc Josh Howard P.J. Brown
30 Gilbert Arenas Nate McMillan David Lee
31 Doc Rivers Danny Ainge Nikola Pekovic
32 Rashard Lewis Brent Price Luke Walton
33 Grant Long Dirk Minniefield Steve Colter
34 Carlos Boozer Mario Chalmers C.J. Miles
35 Mike Iuzzolino DeAndre Jordan Derek Smith
36 Clifford Robinson Ersan Ilyasova Omer Asik
37 Nick Van Exel Mehmet Okur Jeff McInnis
38 Chandler Parsons Chris Duhon Steve Blake
39 Rafer Alston Earl Watson Khris Middleton
40 Monta Ellis Dino Radja Lance Stephenson
41 Cuttino Mobley Popeye Jones Otis Smith
42 Stephen Jackson Patrick Beverley Matt Geiger
43 Michael Redd Eric Snow Trevor Ariza
44 Chase Budinger Malik Rose Cedric Henderson
45 Goran Dragic Hot Rod Williams Antonio Davis
46 Jeff Hornacek Jerome Kersey Voshon Lenard
47 Paul Millsap Mo Williams Gerald Wilkins
48 Marc Gasol Micheal Williams Cedric Ceballos
49 Andray Blatche Haywoode Workman Kyle O’Quinn
50 Ryan Gomes Paul Thompson Lavoy Allen
51 Kyle Korver Jim Petersen Lawrence Funderburke
52 Fred Hoiberg Anthony Goldwire Lowes Moore
53 Anthony Mason Tod Murphy Greg Buckner
54 Sam Mitchell Shandon Anderson Mark Blount
55 Luis Scola Kenny Gattison Patrick Mills
56 Ramon Sessions Amir Johnson Joe Kopicki
57 Manu Ginobili Marcin Gortat Frank Brickowski
58 Kurt Rambis Don Reid Robbie Hummel
59 NA NA NA
60 Isaiah Thomas Drazen Petrovic Robert Sacre

As usual, all the code for this analysis can be found on GitHub account.

CAVEATS

With regards to the analysis shown above, it is important to highlight a few potential caveats:

  • I worked with career averages, which somewhat ignores the years of peak performance achieved by certain players. However, I feel it that career averages are a reasonably good proxy for overall player competence.
  • I completely ignored the fact that some teams had more opportunities to select higher draft picks than others (cough…Cleveland…cough). As such, there may be a bias towards historically bad teams that would have been in the top 5 picks more often than others. However, I did compare each player to others that were picked at the same position, some hopefully this will bypass the issue (for example, if a team had plenty of NO 1 picks that were bad compared to other NO 1 picks, this insight will be revealed in the analysis)