Many of us make the leap from season-long fantasy leagues to dynasty because of the thrill of becoming a prospector.
We’re obviously not out panning for literal gold, sifting through actual silt to find tangible treasures, but the word “prospect” first came into English in the 1400’s from the Latin roots pro- (meaning “forward”) and specere (meaning “to look at”) – a word created to represent the idea of peering into the future. That’s the whole idea behind dynasty basketball prospecting: we’re simply trying to look into these young players’ futures, see who the hidden gems in the river of talent could be coming into the NBA, and then hopefully dig them up to add to our dynasty hoops teams’ coffers. But where do we start?
That’s my whole reason for joining TFU and starting dynasty basketball research: I want to help you identify trends, undervalued individuals or skills, and edges that your leaguemates haven’t begun to dream of yet. In this article and every other I write, I’ll be looking at metrics and analytics that help us evaluate player talent and fantasy success better than just mere rankings and guesswork. Let your friends bring a hunch to a technology fight; you’ll be the one finding the diamonds in the rough in your dynasty basketball leagues.
In this piece, we’ll test a simple notion and see if it can help us: does the NBA know what they’re doing when they draft, and can NBA Draft results help us determine which players will be fantasy-valuable down the road?
Stake a Claim
The notion that the money and time that an NBA front office can invest will far outstrip sheer luck (not to mention our armchair scouting at home) in the search for quality basketball players seems to make perfect sense. Who better than to locate the next generations of talent on the court than the professionals themselves?
But – since we can never assume team leaderships will make rational decisions – it’s worth checking the receipts to see if NBA general managers really are making quality choices with their draft picks.
Using the repository of hoops knowledge that is Basketball-Reference.com, I pulled NBA draft results from 2007 to 2016, so that even the most recent players in our dataset had had a chance to play three or four seasons. I then assigned standard fantasy point scoring to their career totals in the three main offensive categories (points, total rebounds, assists) and averaged those out on per-game and per-minute bases. The final step was simply charting the comparison between draft position and each of these value metrics (I also threw in Win Shares per 48 Minutes for fun too) and running an R correlation to see how closely each pair was linked.
If you’re not familiar with R correlations or the neat little number it spits out (the coefficient), the R correlation is simply a mathematical way of depicting the strength of a relationship between two sets of variables. While I’ll caution you to never confuse correlation for causation, this test can show us a benchmark of the strength of a statistical relationship. The closer the value of the R coefficient is to 1 or -1, the stronger the relationship between variables; the closer the value is to 0, the more chaotic or random the relationship.
With all that in mind, let’s get into the meat of this: how closely related are the NBA draft slots and fantasy production?
Hit the Mother Lode
Eureka! After digging into the data, it’s clear that there is something there.
The graphs below shows the plot of NBA Draft slot compared to career fantasy points per game, and the relationship is reasonably solid.
As you can tell from the datapoints, this isn’t an ironclad relationship. For instance, the lower left point hanging out by himself is Nikola Jokic; selected 41st overall in 2014, he has still put up 43.5 offensive fantasy points per game. Of course, there are outliers on the other side too; the upper-left corner shows us 2009’s 2nd overall selection Hasheem Thabeet (Who? Exactly).
On the whole, though, the 0.46 R-coefficient falls just into what we’d describe as a moderate strength relationship between the variables: there is some indication that they are connected, but there is hardly a cause-and-effect happening, and this definitely jives with our perception of talent and production in the NBA. The Draft isn’t an open-and-shut case where the highest pick gets the best player every time, whether because talent isn’t always clear in college or foreign leagues (hey there, Luka Doncic), and production is contextually contingent too.
Average production isn’t the only metric we should look at. In addition to on-the-court value, I looked at the success rate of picks to see how likely a high pick is to flop.
The chart below depicts the percent of players by draft position to not play at least two seasons in the NBA – one-and-done or never playing a year in the league is my definition of a bust.
We can see a very neat downward trend here – as the picks get later in the draft, the likelihood that a player does not make it in the league increases. This is another thing to keep in our minds when drafting in our own dynasty rookie drafts, that even NBA teams take high-upside but high-risk fliers on players as they get into the second round. Some of those pan out, sure, but many simply do not.
The table below also illuminates a summary of the rates and percentages split out between different categories: lottery picks (i.e. top-14), non-lottery first-rounders (picks 15-30), non-lottery picks (15-60), and second rounders (31-60).
Not one top-14 selection has failed to reach two years in the league over the last decade, and in fact these lottery selected players average 7.2 seasons in the NBA. Even non-lottery first-round players only busted at a 4 percent rate, and all players drafted in the top-30 of their class have averaged about 20 fantasy points per game at the barest of minimums.
The above all seems to indicate that draft capital matters when selecting our own rookies in dynasty leagues, but we’re not just going to stop there. It’s important to not only ask if higher-picked succeed more than their peers, but why.
You may notice that in the previous table I included two categories I didn’t discuss: fantasy points per minute (FPTS/Min) and minutes per game (MPG). I’ll get to the latter shortly, but let’s start with the former.
As you can tell from this handy table, the gap in fantasy production between lottery players and the rest of the pack diminishes significantly when controlling for minutes (13.3 percent better than non-lottery) rather than games (42 percent better).
That indicates – and an R-correlation of 0.89 between fantasy points per game and minutes per game helps to further reinforce – that the real boon of a high draft pick isn’t so much increased talent as it is a signal of a team’s confidence and willingness to give a player chances to succeed. A high draft pick ensures that the team that drafted (or made a draft day trade for) that player will give them plenty of game appearances and plenty of minutes to prove themselves. Even teams that sign the player in free agency or trade for them will look to that draft price tag and think “there must have been a reason they were a top pick once” (remember that lotto picks average over 7 years in the NBA; all others average under 4).
That’s why we have to conclude that – while a high draft pick does seem to point to those players with more innate talent – the real value of drafting rookies taken with a high NBA Draft selection is in the implied security of their playing time: more minutes, more games, more seasons, more chances to develop.
And oftentimes a consistent guarantee of opportunity can be even more valuable than a rare gold nugget of talent.