The Super Bowl is so broadly watched in the United States that it shows up as a strong signal in fitness tracker data. We’ve juxtaposed the television footage with how activity in Baltimore and San Francisco compared to the rest of the US during Super XLVII:
During 2012 and 2013, we did a series of projects looking at what could be learned from millions of days of activity data. Most of these analyses were never released, but one that we really enjoyed was looking at the impact of the Super Bowl on the majority of the US, and compared that against individuals’ activity in the home cities for the two teams: San Francisco (the 49ers) and Baltimore (the Ravens). The prototype is a way to explore the activity data and how it coincides with the game broadcast.
Across the US, we see everyone sitting down for the game, then getting up for snacks at the end of the first half, sitting back down again to watch the halftime show with Beyoncé, then getting back up again for another break before the game re-started. During the game itself we see the biggest moments for each team as spikes of activity—with fans jumping up off their couches and cheering. The near-comeback of the 49ers is seen as a series of spikes toward the right, with the final game-winning touchdown for the Ravens as the furthest spike on the right. After the game, most of the US begins winding down their night, while the Baltimore fans remain excitedly milling about, and San Francisco heads home from their parties to finish the day because it was still early evening.
This was a quick sketch to explore the connection between activity and the game footage that never evolved into a final project. Behind the scenes, we also developed analysis tools that enabled us to analyze billions of activity data points in just a few minutes. This was one of dozens of analytical works we created using this fascinating trove of human activity data.