Powered By: Fantasy Knuckleheads
Fantasy basketball is all about lists: the top 20 point guards, the top 10 rookies, the 99 reasons why I hate Bonzi Wells. The game is driven by stats and these stats give us ample opportunity to calculate, sort, rank, and evaluate players in pretty much any way that we can think of, such as with the GMTR player rater. But instead of giving you another list, what if there was a way to visually display players to see how they relate to one another?
I’m sure you’ll be ecstatic to find out there is such a way. It’s called Multidimensional Scaling, but I promise that’s the last time I’ll mention those two words. Basically, the procedure takes information for each player (in this case, the 9 most commonly used statistical categories in rotisserie leagues) and places each player on a two-dimensional map* so that the more dissimilar a pair of players, the further away they are from each other on the map. Got all that? Similar players = close together. Dissimilar players = far apart. And as the distance grows, the more and more dissimilar players become to each other.
Here is the perceptual map of the top 100 fantasy players for 07-08 (Click on the picture to see a version that can actually be read)
First off, does this map pass the smell test? Does it make sense? Well, on one side of the map we have Marcus Camby. On the other side we have Steve Nash. They seem like pretty different players. So far, so good.
Second, this map takes 9 pieces of information on each player and condenses into two dimensions. However, it leaves it up to us to figure out what these dimensions actually are. The first, horizontal, dimension is the easy one. It clearly goes from big men (or guys who play like it) on one side to little men on the other, with a bunch of forwards in the middle. The second, vertical, dimension is a little tougher. I have a guess myself, but I’d like to get your opinion. What’s your take on the vertical dimension?
A couple of other interesting things to be gleamed from the map:
* The map doesn’t necessarily have to be in two dimensions, it can be in 1, 3, 25, it’s just the easiest to interpret using two.