Introduction

While the NBA and the sport of basketball as a whole hasn’t quite caught up to baseball and MLB’s boom of sabermetrics, they have come quite a long way in recent years. From installing cameras in stadiums to developing sophisticated on/off and Plus/Minus metrics, the basketball community has really grown in terms of advanced statistics.

However, there is still a wide gap between advanced NBA analytics and fantasy basketball. In a sport like MLB, sabermetrics and fantasy baseball don’t go perfectly hand-in-hand, but it’s pretty darn close. I think the reason is the nature of the game – it’s hard to be “bad” in baseball and still put up numbers. It just doesn’t work that way. In the NFL, you certainly can just because of volume, but sample sizes are typically too small for that to matter that much.

The NBA is in an interesting spot, where fantasy basketball is – at its core because of its scoring – pretty far off from advanced metrics. What I mean is this: there are a lot of very productive fantasy basketball players that advanced metrics do not think highly of. Take Minnesota guard Zach LaVine – he put up solid numbers in several games last year, especially when Ricky Rubio was out with an injury and the Timberwolves turned over the point guard keys to LaVine. However, ESPN’s Real Plus/Minus metric (don’t worry, we’ll go over these metrics in this course) rated him as one of the worst players in the league, with a mark of -6.87.

So the obvious question that I’m going to address in this course is, which advanced stats matter? Do any of them?

To answer this question, we have to think of the idea of value – when we look at statistics, trends, or whatever else in our DFS research, we have to think of value in two specific ways:

1. Is it valuable to DFS production?
2. Do others know and use its value?

We often spend a lot of time and read a lot of articles on #1, very often think very little about #2, when in fact it’s equally as important. Think about it this way – if you knew that Anthony Davis was going to score 65 fantasy points on DraftKings and be the best play, you would probably play him, right? Of course. But what if everyone else thought the exact same thing? What if his ownership was thus 100% across tournaments? At that point, being on the Davis play isn’t really useful for anyone. No one gets ahead.

And that’s the point of DFS right? You don’t want to finish in the middle of the pack in GPPs and large-field tournaments. You want to win them! And since that’s our goal (at least it’s mine and I hope it’s yours as well), we need to find information that is not only valuable in a vacuum, but also valuable in the specific situation of DFS contests. Vacuums are nice and it’s fun to debate things in them, but DFS isn’t a vacuum and if you treat it as such, you’ll have a hard time winning.

Anyway, let’s move on to the next lesson and start talking about advanced NBA metrics and their potential use – or not – in daily fantasy basketball.

About the Author

bcmears
Bryan Mears (bcmears)

Bryan Mears is a writer for RotoAcademy and FantasyLabs. He can be found on twitter @bryan_mears.