The Trade Value Chart is a tool to help evaluate potential trades. The basic idea is simple: Add up the scores of two players, and that sum is roughly the amount of value you should look to get back in any trade.

For example, a trade of Eric Gordon (13 points) and Donovan Mitchell (20 points) is approximately fair value for either Andre Drummond (33 points) or the package of Dario Saric (19 points) and Lauri Markkanen (14 points).

In a sense, this is just a rest of season ranking, except (hopefully) in a more useful format.

A few notes on how to best use the Trade Value Chart:

  • Fit is more important that “value”: If your team loses value but improves in competitive categories, then your team gets better and you should make the trade.
  • This is a tool, not a rule: Similar to point 1, but it’s important. Don’t reject a trade simply because you might lose a couple points in value. This is a tool designed to facilitate trades, not to discourage them.
  • League size matters more than Roto vs. H2H, pt. 1: For the overwhelming majority of players, trade value is identical whether you play roto or H2H. The only players for whom it makes a significant difference are the ones with glaring negatives in a single category – think James Harden‘s turnovers, or DeAndre Jordan‘s free throws. The rankings below are for roto, and players are listed with an asterisk if their value would change significantly for H2H. Other than those few asterisked players, the difference between the two is not addressed here.
  • League size matters more than Roto vs. H2H, pt. 2: In shallower leagues, the difference between the 30th-ranked fantasy player and the 40th-ranked fantasy player is more important. The Trade Value Chart shows trade values for managers in 12- and eight-team leagues. If you play in a league with more than 12 teams, then every player’s score should increase. If you play in a league with fewer than eight teams, then every player’s score should decrease.

That’s enough preamble – let’s get to the chart. This assumes nine categories, but most players’ values would be very similar in eight-category leagues. After the chart, I’ve included a few paragraphs about how the Trade Value Chart was constructed.

The basic framework for this chart, and the first draft of player values, was made from algorithm that heavily weights production from this season, and in particular production from the past month. The algorithm also builds the rough framework that says “in a 12-team league, the 60th ranked player should have a score of approximately 19; in an eight-team league, that player should have a score of approximately 12.”

After the algorithm spits out a first draft, the rest of the work has to be done ‘by hand’ – just me, analyzing, one player at a time, and hoping desperately that I didn’t accidently miss someone because my algorithm didn’t like them.

If you have any questions or comments, as always feel free to leave a reply.


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