Since you were willing to wait on behalf of the exclusive club of Brooklyn Nets fans (they thank you), I was already in the midst of web scraping other sports data from the web, so I just had to do a few tweaks to make it work for this. So this didn't take me too long .
Take this as not condescending to your basketball knowledge, but just an interesting set of charts I made.
Ok so I went and scraped draft data and ran some numbers on a per-pick basis. i.e., how valuable is the first pick versus the last pick, and every pick in between? My assumption in modelling is that there should be an exponential decay from top to bottom, mostly because the NBA drafts more players than are worthy for the NBA., and most players don't last out (and to compliment that, a share of undrafted players make it in their place). I scraped 2005 to 2017, because that's all basketball-reference.com had uniform tables for and I wasn't about spending more than an hour or so on this.
Off the bat, I took a look at games played .
That's a graph of all games played at that pick position since 2005. This is clearly linear, and my best guess as to why is because bad players are more likely to be given a chance if their pick was higher.
Similarly, minutes played holds the same trend. Apologies for not making that linear - it appears to be.
Things get a little more interesting when you start to digest the numbers at the position. That's a look at the total rebounds per pick. Again, this is all players at any single number, so all the first overalls combined, then the second overalls, etc. So it's important to maybe not look at an individual point, but the trend line itself, because you're talking n=12 data points. So one awful player or one amazing player can totally ruin the numbers at one spot.
None of this is really any shocking surprise. Top 10 picks are usually better players. Something to pay attention to, though, is how scattered the values get after around 10 or 15. Aside from that outlier at 21 (who was picked at 21? Rajon Rondo, and he's a a dramatic outlier for assists). If you remove him from the equation, you sort of have a flat-lined scatter from 10 to 30.
So this is a bit more in depth here. Those two charts show the median player as a data point , with the red bars representing the 75th and 25th percentile on the first chart, and the 95th and 5th percentile from top to bottom on the second chart. So you can translate that into conversion rates. 75% and 95% of players picked at those positions will score less than the top of those bars, respectively. Obviously that's Jimmy Butler being *exceptional* for the position he was picked at, because he's *above* the 95th percentile at 30.
Last but not least, VORP per pick at 25-median-75 for the percentiles. This is quite literally saying 'somewhere after pick #10, your pick has a 50% chance of being ~absolutely worthless~.
Point to be made here... 4 first round picks, even if not protected... you'll likely get two average NBA contributing players.
What did they get? Two average NBA contributing players, a relatively worthless player, *and a relatively worthless 2nd round pick*.
1st Rounder A: Converts - Covington
1st Rounder B: Converts - Saric
1st Rounder C: Fails - Bayless
1st Rounder D: Fails - a 2nd round pick
They definitely got fleeced, but I'm not seeing how 4 likely bad1st round picks
over like 8 years is any more enticing of an offer.