Week 4 Fantasy Basketball Trade Value Chart
If you play fantasy basketball – ok, there’s no if. You’re reading this because you play fantasy hoops. More specifically, you’re reading this because you play fantasy hoops, and you want to start wheeling and dealing.
Luckily, I’m here to help. Below is a new and improved fantasy trade value chart that doesn’t just offer values. Far from it, my friend. Instead, these values are calculated based on Z-Scores that help you see exactly what’s going into a trade from all categories.
Trade Chart is based on 9-cat, H2H formats
As mentioned above, the following values come from Z-Scores. If you’re not familiar with Z-Scores, I’ll break it down in the simplest way possible.
If we take a data set (in this case, player stats), find the average, and find the standard deviation, we can determine the Z-Score using this formula:
Player A Stat – Average divided by Standard Deviation
That determines just how far above the average a player is in a certain category. Sure, Ja Moran is a high scorer, but how much higher of a scorer is he than Bradley Beal, relative to the average of all players?
For FG% and FT%, the calculations are a little different. It’s not enough to just calculate the Z-Score based on average, because that wouldn’t take into account the attempts a player is taking. For example, a 100% FT average is the best possible percentage, but when the player who sports it only takes 0.5 FT attempts per game, his value in that category drops significantly. Conversely, a guy sporting an 85% FT average on 10 attempts per game has a much higher value to your fantasy hoops squad.
So, for those categories, I calculated in this way:
(Player % – % Average) x shot attempts = %Value
I then calculated the Z-Score based on that %Value to account for shots taken.
The total of all Z-Score values is the player’s “trade value.” In a categories league, trades are not as simple as Player A for Player B. When trading, you must consider the categories in which you’re lacking and the categories in which you can afford to give away a little value.
Trading two players who are similar in overall value isn’t the best method for executing a trade. Instead, consider a category where you need help and target a player who can offer the most value while not causing you too many hits in other categories. In fact, it’s worth noting that many players have negative Z-Scores in some categories, which further perpetuates the idea of giving a little to get a little.
When going through these values, keep in mind that I used FantasyPros consensus ROS projections and tweaked them a little based on current production and where I think certain players might finish by the end of the season. Trade values are not an exact science, but these are designed to give you an idea of where you can find value, where you might lose value, and which players are worth targeting based on team need.