Creating an NFL Division Cheat Sheet in SAS Visual Analytics
It's 2018 National Football League (NFL) draft season here in the United States so there's been a lot of news about all the NFL teams and which players they might select. There’s also been a lot of discussion about what divisions the teams play in. The different leagues and divisions in the NFL used to be confusing to me. However, a few years ago I saw this article from The Business Insider which displayed a basic map of the NFL divisions. After seeing the teams and divisions laid out geographically, it made a lot more sense to me how the league is set up.
However, sometimes I still forget which league and division certain teams are in. What I need to help me keep track of everything is an interactive version of the map. Sort of an "NFL Division Cheat Sheet" that can allow me to quickly select an NFL League and Division, and then see geographically how they are grouped together.
So, in the spirit of the draft, I've created a #MikeD_VARemix version of the NFL Division map in SAS Visual Analytics! I started off with a few quick google searches to look up each team, each team's division and the location of their stadiums. From there, I was able to build a small dataset that feeds the following report.
This map was very easy to create in SAS Visual Analytics 8.2 by using the Network Analysis object (which is now available as a reporting object). This object allows report designers to create groups of nodes and (most importantly) overlay them on a map! More so, a Network Analysis object can be used in interactions. So we can now give users the ability to filter the map by league and division to help them better understand how the teams are grouped.
With just a few clicks, you can rebuild this report in your own SAS Visual Analytics environment.
First things first: data preparation
Start by importing the csv file "NFL_Divisions.csv" (attached to this post) to your SAS Viya Visual Analytics environment. We are first going to need to create two geographies from the variables "Primary_Team" and "Secondary_Team". This is done by reassigning each of these variables from category to geography.
You will want to use these options :
- Geography data type: Custom coordinates
- Latitude (y): Primary_Y
- Latitude (x): Primary_X
*Do the same for the "Secondary_Team" variable (however use the Secondary_Y and Secondary_X values for Latitude and Longitude)
The fun part: building the report
Now that our data has been prepared, select the Network Analysis Object from the Objects menu and add it to the reporting canvas:
First we will need to assign some roles to the object. In the roles menu on the right, assign the following roles:
- Source: Primary_Team
- Target: Secondary_Team
- Color: Division
- Link Color: Division_Color
The next step (and the really cool one!) is to edit the Network Analysis Object's options to get the report to display correctly.
From the options menu add the following options:
- Click the "Map Background" checkbox
- Change the map transparency to be 35%
- Change the "Node Size" to 10%
- Also turn the Legend's visibility to "Off"
Finally, (still within the Network Analysis Object's options menu) select the "Node labels" checkbox:
And that's it! You have made an NFL Divisions map using the Network Analysis report object:
However with all the data on the map at once, it looks a little busy. The BEST part of the Network Analysis Object is we can use our new "NFL Division map" in interactions! In my final report, I created a drop-down filter for "League" and a button bar for "Division". Both of these controls filter the Network Map. This allows the user to select certain leagues and divisions to help them see which teams fall where. In the screenshot below, I've selected the teams in the AFC League.
Now that I am armed with my interactive SAS Visual Analytics NFL Divisions Map, watching all the NFL games this season will be a lot more fun!
How to make the example work for you
This example was created in SAS Visual Analytics 8.2. Attached is a JSON file containing this article's completed report and data source. Import the data on your SAS Visual Analytics instance. Import the report via the "Import via GUI" section of these instructions.
