Understanding NBA Projections & Advanced Stats
Knowing the basics of NBA DFS is hard enough, and that goes for players of all skill levels. It is no surprise to me that many players talk about the various advanced aspects of a player projection as if it exists in a “vacuum.”
That is to say there is a lot to know and consider on a daily basis, and I forgive anyone who fails to consider how the stats they find in research relate to the bigger picture. I feel that projected player performance is often misunderstood, and this article is designed for our premium users to get a better grasp on how all this information fits together.
By the end of this article, you should be better prepared to understand what a player projection means, what goes into it, and how to make decisions based on a player’s full range of outcomes for the slate.
The Inspiration / Problem Inspiring this Article
You’ll hear references to NBA advanced stats such as team pace, usage rates, and Court IQ queries all the time in articles, shows, and podcasts. The problem is that they are always referenced individually and rarely discussed in the context of a player projection. They will often be referenced as a good or bad thing for the player’s outlook for the night, but almost never will you get the full explanation of why or specifically how much that player is affected by the situation. This leads to stats being taken out of context, and decisions being made based on information that is either already baked into a median projection or is better served as a reference to its effects on floor/ceiling. I will now help you understand those two important concepts and the underlying advanced statistics that shape them.
Understanding Player Projections
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Comments
Great article, thanks for your work.
awesome info. thanks for all you do.
Thanks Chris, that cleared the mud a little bit. Always appreciate more knowledge.
I’ve been playing DFS for about 3 years now with some decent success and I’ve read a lot over those years, and this is definitely one of the best article I’ve read. Thanks for the work put into this!
Very informative and gives insight into how hard it is to be successful without a process and proper research. Thanks
Thanks
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Thanks Chris. Gives me a whole new insight on playing DFS. Some of the tools I was using on the site I was using wrong from what you have listed. Great clarification and a valuable read. #Awesome
Good stuff. I think this info will help a bunch.
Thanks, great article
Well written and insightful article. Thank you
I think this is the best article I’ve seen written on the site.
I completely agree. I need this information.
Basic statistical analysis or as my old stats professor at USD Diego Salazar pronounced it (standard deviation) “tanterd deedeeaton”…..
Good stuff ‘preesh your time and effort.
Did not know about half this stuff. Thanks
Great context on the tools and the math behind the various projections. Good stuff, thank you.
Great article. The information about pace and possessions is a big deal in finding the median outcome. Your incite on projections opens up a whole new avenue on player selection for me
Great article! It really puts some questions you should ask yourself into thought.
Chris, great article. Thanks for sharing!!
well done thanks
2014 FanDuel NFL Survivor Finalist
Tremendous stuff here. This is something I’ve been working on and it is very difficult. I want some autonomy in my projections, but get nervous about flying too far from the nest sometimes. This info along with a RotoAcademy course by Noto I’m working on have really helped with the transition. Thanks for the effort and well written piece.
I wonder the statistical weight that should be applied when a player is on a back to back.
And what if both teams are on back to backs. Home over road?
Rebounds and turnovers go up?
Minutes fall?
Does it hurt big men more than guards
Are some shooters void of this effect. Seems to be true in playoffs.
But Curry missed shots sunday, Thompson did not.
Why
Great info thanks Chris
Outstanding article! Thanks for posting! I really needed a better understanding of all these stats
Thanks for the great article!