Graphical Fantasy Rankings: Catchers

I think we all understand that not everyone learns and retains information the same way. I’m a visual learner and it created some difficulty in the majority of my math classes. The first time I sat down and got serious about fantasy baseball and read through rankings, they failed to get through to me in a way that would allow me to retain the information. So, slowly over time, I developed a system to help identify a player’s strengths and weaknesses. I developed a loose tier system that’s been ever evolving, and now I would like to share this information with you.

So, over the next few months we at Baseball Prospectus will be rolling out our comprehensive fantasy baseball package. I was brought on to provide a visual wrinkle to the product in an effort to better communicate the ideas we’re going to be trotting out there for you guys.

The first infographics we will be debuting will feature what a player does well and not so well when compared to the top players at their respective positions. The data I used is PECOTA information that will be featured in the book. Both baseline production numbers and projected stats are all based off the PECOTA information.

They break down like this:

• C – Top 30 by WARP
• 1B – Top 30 by WARP
• 2B – Top 30 by WARP
• 3B – Top 30 by WARP
• SS – Top 30 by WARP
• OF – Top 90 by WARP
• SP – Top 150 by WARP
• RP – Top 60 by WARP

I then created a baseline production for each position complete with tiered bins of data using a simple standard deviation model. For the graphic I’ll be using the basic 5×5 stats as projected by PECOTA.

With that information I created a tiered color system which is again, relative to the other top 30 players at their positions:

With this infographic specifically, you’ll notice that there are some odd pairings within the tiers. There is no specific rank within the tiers themselves, and this was made to mirror Mike Gianella’s list of catchers. So, you’ll get a guy like Wilson Ramos ahead of Jason Castro for that reason. Playing time obviously plays a major role in counting statistics so keep that in mind as well.

I hope this is a good guide for you guys to use when drafting so that you can understand where a guy helps you or hurts you relative to other players at the same position.

And for the curious, here are the data bins at catcher: