Fantasy NBA Snake Draft – Predictability of each Pick

It took me way more time than I expected but ironically it could have been a very short post.
Frankly, the main point you can sum up in one sentence:
“fantasy NBA stars are valuable in snake draft not only because they offer the most stats and an unfair advantage but also they are… the most predictable group of players“.

In a longer version I’ll throw-in a couple of nuggets, I’ll explain how I’ve came up with this conclusion [be advised! This post contains some math ;-)] and how does it translate into different scoring systems.

Let’s start with the easier one, fantasy points and a typical 12-team 10-slots per team league. Again as an example I’ll use Yahoo’s Default Points Scoring [FGA (-0.45), FGM (1.0), FTA (-0.75), FTM (1.0), 3-pt Made (3.0), Point Scored (0.5), Rebound (1.5), Assist (2.0), Steal (3.0), Turnover (-2.0), Blocked Shot (3.0)].

I collected players’ statistics from dougstats.com, for every season in the last 10 years I sorted them from best to worst according to aforementioned formula [average per game not total].
Then I checked what players from every draft slot in Top120 did during next season and finally calculated average and standard deviation for a change in rating for each pick.

OK, if it sounds too complicated, here’s an example, according to Yahoo’s Default Points Scoring…
in 2009/10 3-rd best player was Jason Kidd who finished 20-th in 2010/11.
in 2008/09 3-rd best player was Dwyane Wade who finished 5-th in 2009/10.
in 2007/08 3-rd best player was Marcus Camby who finished 27-th in 2008/09.
in 2006/07 3-rd best player was Gilbert Arenas who finished 61-st in 2007/08.
in 2005/06 3-rd best player was Kevin Garnett who finished 1-st in 2006/07.

So for pick #3 in the last 5 years we have data points of -17 [because 20-3], -2, -24, -58, +2. Got it? In short it means “how would you do at each draft slot if you pick only by ranking from previous season?”.

I’ll spare you a whole table because it’s too long but I did the same thing as above for each pick from Top 120 for the last 10 years [you can find results in this file].

For a better view, here’s a graph for standard deviation of such change in ranking: