Spatial Analysis and the Superbowl

NFL playoff brackets are nearing their end as those in company and fantasy pools will watch, along with over 100 million other viewers, this upcoming Sunday’s Superbowl match up between the Baltimore Ravens and the San Francisco 49ers. As people settle in to watch with friends and neighbors they can now determine which Harbaugh brother, John or Jim, (ESPN link) the folks in the county over are most likely to be rooting for.

Geography has joined in on the Superbowl hype. Just in time for Sunday, New York University PhD candidate Sean Taylor in collaboration with Facebook , released a map of the United States that combined data from Facebook ‘likes’ of NFL teams, with GIS technology and geography to give a county by county map of NFL fans and which team they support .

The spatial patterns reveal some interesting quirks.

For one, the Pittsburgh Steelers are popular, and have loyal pockets of fans throughout the country, including in Oregon and Alaska.

The New York Jets, not so much. They command only a small bastion of support from a single zone in Long Island, NY.

Photo by Kristy Potter. Heinz Field with the city of Pittsburgh in the background.

Photo by Kristy Potter. Heinz Field with the city of Pittsburgh in the background.

Moreover, the map demonstrates a fun and interesting application of spatial analysis and GIS. For instance, the map now offers questions to inquiring and enterprising geographers that include, why are there pockets of ‘Steeler Nation’ throughout the country? Is it something about the counties themselves? Did large migration happen into these counties from Pennsylvania, Ohio and West Virginia? Is there a positive spatial correlation, where Steeler fans want to live in neighborhoods next to other Steeler fans?

Some of these may seem far-fetched, but here is the genius of this NFL Fan Map and more widely, spatial analysis. It could have taken months or years to sort out these patterns using window decals or bumper stickers, but through this collaboration of Facebook’s data with the visualization of GIS, anyone can look at a map, see and pick up on patterns and pose questions that formerly, no one would have thought to ask.

But it also offers good practice in recognizing the bias in the data and how that may affect spatial patterns, like population density of counties and the age range of data, which in the case of Facebook, is younger and as PC Mag suggests, perhaps more fickle in their allegiences.

For good measure, the map also includes an evolution of shifting support throughout the playoffs, as teams dwindled and fans were forced to switch alliances to teams still in the running. Ultimately, only Sunday will tell whether it is the San Francisco 49ers or the Baltimore Ravens who will succeed in wiping their opponent off the map.

Written by Emily Connor, National Geographic Education Intern

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