NBA Player Projections: Foundational Knowledge
Learning the baseline elements of NBA DFS is difficult enough, and that is true for players of all skill levels. When it comes to advanced stats and metrics, there is enough noise out there to make the average user’s head spin.
There is a lot to know and consider on a daily basis, and I forgive anyone who struggles to fully understand the terms and stats that get thrown around liberally on a daily basis. The most important thing to keep in mind to separate the signal from the noise: The majority of these stats (or anything that matters) are actually already considered in player projections. Projections are often misunderstood, and this course is designed for you to get a better grasp on how to use them.
By the end of this course, 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 For This Article
You’ll hear references to NBA advanced stats such as team pace, usage rates, and others every single day across the industry. The problem is that they are always referenced individually and rarely discussed in the context of a player projection. You almost never get the full explanation of why or specifically how much that player projection is affected by the information being discussed. 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.
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