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Friday, February 2 • 10:45am - 11:15am
The Impact of Deep Learning on Object Identification in Sports Sponsorship (Featuring a Case Study on Pepsi and the Dallas Cowboys)

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Can we accurately determine the quantity and quality of the media value the Dallas Cowboys deliver for an international brand? Can we do it in real time to inform and optimize creative decisions? Those are exactly the questions that Pepsi was looking to answer after securing signage rights for a new LED tunnel cover at the Dallas Cowboys’ AT&T Stadium. Pepsi was focused on more than how many people saw the logos of Pepsi, Lipton and Tostitos during games. It needed to determine how long the logos appeared on screen (time), how closely the logos were to the focal points of the screen (centricity), how much of the screen the logos took up (prevalence), and how likely it was that its core consumers were watching the game (fit). 

Pepsi used to have to wait weeks or months to obtain these types of results.  More specifically, people used to have to watch games with stopwatches and manually record where, when and how long logos appeared on screen. Recent advances in machine learning have made it possible to significantly reduce the time it takes to complete this process. Pepsi turned to Block Six Analytics to employ its Media Analysis Platform (MAP) to evaluate the performance of its tunnel cover in AT&T Stadium. B6A used a combination of deep convolutional neural networks and computer vision to automate the data collection and analysis process using MAP. 

avatar for Adam Grossman

Adam Grossman

CEO and Founder, Block Six Analytics
Adam is the CEO and Founder of B6A. In addition, he is a professor for Northwestern University’s Masters of Sports Administration program. He is also the co-author of The Sports Strategist: Developing Leaders For A High-Performance Industry. His work has been featured in publications... Read More →

Friday February 2, 2018 10:45am - 11:15am CST
Room 1&2&3