Wait- I mean Dennis Schroder and Luka Doncic. It’s an understandable mistake- in addition to their strikingly similar appearance, these two share one very useful trait when it comes to DFS data and decisions around rostering them. Let’s find out what it is.

(Note: The numbers used for today’s piece are from FanDuel. Mobile users need to go to landscape mode to see all table columns!)

On the surface, you might not think this is much of a connection. One player is an MVP stud, the other a mercurial sometime starter and daring hair-color fashionista. However, the power of historical analysis finds one trend that they have in common- you are not properly understanding when to play and fade them, because you’re undervaluing a key metric for these particular players. Yes, you- the general public. Let’s take a look at this quite understandable mistake you’re making.

Quick basics here- hitting 6.0x value on FanDuel is a pretty sure path to the cash line. There may only be a handful of days that 360 points (6.0x for your whole team) wouldn’t cash. On some nights when the chalk busts, you’d be in the top few percent. Accordingly, 6.5x is an elite finish. On a fair number of nights it’s enough to take down a GPP, and even if not, you’re solidly into the green. These are good measuring sticks for how well certain picks help us win the (big) money.

If you’ve played any DFS, you’re quite familiar with DvP, defense vs. position. It’s an indicator of how many points a team/defense allows to a certain position. There’s certainly debate about the value, accuracy, and usefulness, but what my analysis finds is that this metric is very player-dependent. Let’s look at two players and how they perform similarly in matchup types. We’re looking at DvP rank in groups of thirds- in other words, when facing a top 10 DvP matchup, we’ll call that the Tough third. For ranks 11-20, the Mid, and for ranks 21-30 the Easy matchups. We’re only considering games that are at least 6 games into the season, as there is by at that point at least some established DvP to look at. “DvP? But it’s Luka,” you whine. “He’s an elite player, can beat the best, no one can stop him- ESPN told me so!!” Alright, well how do Dennis and Doncic stack up over the last 2 years?

Wow- in easy matchups Schroder hits 6x an excellent 37.2% and hits 6.5x an elite 23.3% . Overall, Schroder has been a solid play on FanDuel the past two years. But quite simply, he is an ELITE option in a positive matchup. Now for Luka:

With a high-salary player, we won’t see so many super-high value 6.5x games, but the focus here is the difference- as a stud salary tier player, Luka’s production in easy matchups was excellent - those 6.5x days are going to shoot you to the top of the GPP board. But he did not produce like an elite player in tough matchups- in fact, he probably sunk your lineup well below the cash line . He was nearly unplayable.

“I paid good money for THIS? Play good players in easy matchups??” you fume, your anger rising like Derrick Jones Jr. for a garbage time dunk. First of all, you didn’t pay a dime, even though you should really buy my data set so you can learn all these cool things yourself. Secondly, you’re right my friend- you paid good money for THIS :

The same charts with ownership attached. Even though Dennis & Doncic (great name for a CBS comedy) perform radically different based on the matchup, the general public is not adjusting for this in ownership . This creates a huge leverage opportunity for you- grab Dennis when the public doesn’t bother to care that he’s in an easy matchup, and fade Luka in the tough games when the public rides him anyway.

***TWEEEEET*** “That’s a foul!” you say. Wait…where did you get that referee shirt and whistle? “Don’t worry about it,” you say. “Schroder was a starter often in 2018-19, and a backup last year. Maybe that’s why the data is all screwy!” and do you ever look smartly smug about this.

Doesn’t matter- while his success rate was higher last year, and the public at least a little bit accounted for matchup, his performance drops and the lack of ownership adjustments are quite similar. In fact, last year he hit 6.0x an outrageous 50.0% of the time in Easy matchups, yet have average ownership under 12% in those same matchups.

***TWEEEEET*** “Technical foul!” you shriek with the animation of prime Joey Crawford. “FanDuel actually listed Luka as a SG in 2018-19, so they weren’t even accurately matching up to his position!” Okay, this is a fair point. But it’s possible that tough and easy DvPs might also reflect the opponents at large. Let’s investigate by looking at how the defenses fared overall, based on the averages coming into each game (metric excludes turnovers):

Ah, so in addition to being stingy at the guard position(s), these defenses just allow fewer fantasy points overall, and were able to slow down Slovenian Superman.

One reasonable discussion to be had is whether past is prologue- will these same players have these same splits in the coming season with new teams/teammates? There are two key takeaways (well, maybe more) out of this article- the first is that it’s worth revisiting these scenarios after the first 20-30 games for these players. Many player-specific trends will continue to be applicable, and if you find confirmation, you have a big edge on the field. But secondly, whether they do or don’t continue for these specific players, you can be rest assured that SOMEONE – or actually many someones since I just picked two players for this article out of many others who also fit the bill- will follow this same formula. They’ll crush easy matchups, disappear in tough ones, and the public won’t be savvy enough to take advantage. Your optimizer might not know this- but now you do.   Historical analysis is so critical because it teaches you how to think and what kind of valuable information to be looking for .

Well- I hope you’ve enjoyed this edition of NBA Analytics Master Class. Happy to hear any feedback/questions in the comments or via email. I’m certainly not giving away all I know, so find true value by picking up the ULTIMATE Dataset for yourself.

Learn the Game. Beat the Game. Thanks for reading!

The primary purpose of this website is to offer you the data to find your own valuable insights. Therefore, do not expect these insights to be regularly updated- this is not a DFS tout site. However, these articles demonstrate the incredible value made possible by analyzing the data in the right way and creating an informed decision-making process