In fantasy, each category is a little different. For example, players who get a lot of blocks are rare, rebounds aren’t so rare, and a single free throw albatross (such as Shaq for the past 10 years) can sink your team. Unfortunately, however, most of this type of knowledge comes from intuition, observation, editorial opinion, or other informal sources. Let’s look at some hard data that will hopefully help you evaluate the differences across the categories, and make decisions to help your teams.
The following is the distribution of scores, in each category, for the top 180 players in the RotoPoll rankings.
And here’s a distribution of each category (click to see a larger version):
So what can we learn from this data? Here are some initial thoughts.
- The category with the highest average is free throws, and if you look at the chart, you can see that it drops off precipitously at the end (in fact, it has a noticeably different shape than all other categories, which tail off gradually), meaning that there are just a few guys who are really dangerous. It seems you want to avoid those guys (Ben Wallace, Tyson Chandler, etc.), and if you need to bump up your FT% a little, there are a lot of guys out there who can help you.
- By contrast, the category with the lowest line on the graph is points. This means that it’s harder to find someone who can help you in the points category than any other category. This might seem counterintuitive, since almost everyone scores some points, and it’s not that hard to find a waiver pickup who can give you 10-12 per game, but it’s harder to find someone who can actually help you than in other categories.
- Blocks is the most top-heavy category on the graph. It has the highest minimum and maximum, which suggests that production is concentrated in fewer players than in other categories. Conversely, a player who gets no blocks doesn’t hurt you as much as a player with a zero in another category (or poor percentages).
And of course, these observations apply to each category in greater or lesser degrees.
There’s certainly a lot more to take away from this data, but that’s a start.