Faculty Research

Big Data Innovation is a Slam Dunk

March 24, 2017
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By Alisha Pillay

Using big data research, Peter Chow-White, professor and director at Simon Fraser University’s School of Communication and his team at GeNA Lab have developed an innovative system that gives basketball teams a competitive advantage. This performance tracking and analysis tool rivals the ones used by some professional teams in the National Basketball Association (NBA).

Inspired by the Michael Lewis book and Aaron Sorkin film Moneyball, Peter’s system helps identify structural patterns in basketball games. “We often see the world as a chaotic movement of people and things – but what science wants to do is find some sort of pattern within the chaotic mess,” says Peter. “Humans are creatures of habit and there are a lot of underlying patterns in what we do. Whether it’s how we talk to each other or how we organize traffic, big data helps instrument the world. If we capture the way things, people or objects move, we can then analyze what they are doing. If we can analyze what they are doing, then hopefully we can find ways to predict what they are going to do next.”

Peter’s interest in basketball is personal. He played university basketball and continues his passion for the game by coaching kids in elementary and high school. Peter was able to bridge academics and athletics in a unique way through his personal and professional interests. “I was interested in some very core questions about communication technology. How do we use the symbolic world and how does the symbolic world use us? How do we create the world around us through communication as agents of change in our own personal worlds?” In a time when public interest was centered on front-end technology (deciphering the images and words displayed on screens), Peter was interested in learning what went on behind the scenes. “Digital infrastructures are incredible databases. I wanted to know how this information was being used to organize the social world without us even knowing it.”

During his research project on the role of communication in the adoption of ‘moneyball’ in the NBA, Peter met Alex Rucker, head of analytics for the Toronto Raptors at the time and now vice-president of analytics and strategy for the Philadelphia 76ers. Peter found their conversations fascinating, but limited as Alex could only speak generally due to the proprietary nature of the Raptor’s data. Instead, Peter suggested they talk about his own basketball data, which he didn’t actually have at the time, but shortly after, partnered with the SFU men’s team coach to begin working on his innovative analytics system.

Working closely with SFU’s basketball teams, Peter meets weekly with coaches to provide in-depth game reports. These reports show coaches important trends and provide opportunities to assess the performance of teams and players. In addition, Peter and his lab collect data on every team in the Great Northwest Athletic Conference (GNAC), mining for signals and providing SFU teams with a competitive advantage. They also conduct big data analysis on the 2000+ men’s and women’s basketball teams in all three National Collegiate Athletic Association (NCAA) divisions.

Is big data the key to developing a winning team? Peter explains: “Using big data helps us see our work differently. It helps us find structure within all the noise so that when we make decisions, we can make them based on objective observations. Data is helpful but it doesn’t turn a low-performance team into a high-performance team. The job of data is to help coaches see things they wouldn’t otherwise see, confirm what they do see and challenge what they think they’ve seen.” This is exactly what KEY, SFU’s Big Data Initiative helps us accomplish. KEY brings people together in a collaborative environment to make sense of big data and deliver innovative, real-world insights.

As for future plans, Peter and the GeNA Lab are enthusiastic about their newest partnership with Canada’s women’s national soccer team – a high-level team who views their success intimately related to data analytics.

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