Predicting NBA Rookie Performance By Draft Position

Nate Silver (and others) have tracked how NBA draft position relates to total career performance, see for example this article. But what about first-year performance?

I pulled two sets of data from basketball-reference.com to answer this question:

I then merged them using Power Query and then created a pivot table to calculate the average number of rookie season “win shares” by draft position. You can download my Excel workbook here. Here is what I found:

AverageWinSharesByDraftPosition

The first pick in the draft averages nearly five Win Shares in his rookie season, and while the pattern is irregular, win shares decrease as we get deeper into the draft (duh). (The blip at the end is due to Isaiah Thomas, drafted by the Kings who promptly screwed up by letting him go.) I have drawn a logarithmic trendline which fits the data not-to-shabbily: R^2 of 0.7397. Obviously we could do much better if we considered additional factors related to the player (such as their college performance) and team (the strength of teammates playing the same position, who will compete with the rookie for playing time). Here are the averages for the first 30 draft positions:

Draft POSITION Win Shares
1 4.96
2 2.69
3 2.96
4 4.14
5 2.23
6 1.84
7 3.36
8 1.68
9 2.59
10 1.52
11 0.84
12 1.51
13 1.48
14 1.36
15 1.64
16 1.19
17 2.37
18 1.02
19 0.71
20 1.09
21 1.74
22 2.14
23 1.54
24 2.29
25 0.98
26 1.23
27 1.08
28 0.40
29 0.54
30 0.94
31 0.79

Author: natebrix

Follow me on twitter at @natebrix.

1 thought on “Predicting NBA Rookie Performance By Draft Position”

  1. Hey Nathan, I previously tried to estimate the value of draft picks using a (somewhat similar) method.

    I took the WS/48 of all draft picks from 1998-2008, generated a histogram, and then fitted two distributions to them – the normal distribution and the “Extreme Value” (Gumbel) distribution. While both distributions showed good agreement, I decided to use the minimum extreme value distribution for reasons explained later. (http://i.imgur.com/cMPxWAz.png)

    I then simulated drafts by generating 30 players using each of the two distributions and having each GM select the “best player available”. I did 1000 such drafts and plotted my results here: The results seem very intuitive – there’s a noticeable premium for the first few picks, a gentle decline for the mid-round picks, and a steep drop at the end. (http://i.imgur.com/P8G280t.png)

    I am not sure how to calculate a R^2 for these predictions, but the curve seemed a bit intuitive – the first few picks have a great value, the relative value of picks from 10 to 20 is about even, and the last few picks decline precipitously in value.

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