NHL and Fans Score with Predictive Analytics

How the National Hockey League is using sensors and predictive analytics to learn more about fans and game play.

Lisa Morgan, Freelance Writer

March 23, 2017

2 Min Read

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If you're a hockey fan, you've probably noticed that the statistics are more comprehensive than they once were. That's not happening by accident.

The National Hockey League (NHL) uses predictive analytics to learn more about fans, improve its direct marketing efforts, track players' performance on the ice, and improve fan engagement.

Making an IoT Play

During the 2015 All-Star game, sensors were embedded inside pucks and players' jersey collars which provided insight into where the puck and players were, how fast they were moving, puck trajectory, players' time on ice and more.

The information was used during replays to better explain how a particular outcome came about. Fans were able to visualize the paths players and pucks had taken, giving them more insight into players' performance. Experimentation continued at the World Cup of Hockey 2016, which was substantially the same thing -- tracking pucks and players.

The key to winning a hockey match is puck possession. If Team A possesses the puck longer than Team B, Team A will score more points over time.

The information derived from the devices, particularly the jerseys, can be used for training purposes and to minimize injuries.

A Data Scientist Predicted Winners and Losers

A couple of years ago, the NHL worked with a data scientist who reviewed historical data including player statistics and team statistics over several seasons. When he crunched the data, he found that there are certain statistics and factors that, over time, can help predict team performance on the ice, especially in the playoffs.

Thirty-seven different factors were weighted in certain ways and applied to the 16 teams that started the playoffs in April 2015. The goal was to predict how the playoff teams would do when playing against each other. And, as the rounds progressed, how the teams would perform in new matchups.

The results were very interesting. The data scientist was able to predict at the start of the season that the Chicago Blackhawks would win the Stanley Cup. He also was able to predict which team would win each playoff game, most of the time.

"What's interesting about that is our sport is a pretty unpredictable sport," said Chris Foster, director of Digital Business Development at National Hockey League, in an interview. "The action is so fast, goals happen rather infrequently and a lot of it has to do with a puck bouncing here or a save there. It' very fast action that is sometimes hard to predict, but it just shows that data, when properly analyzed, and really smart models are put around it, that predictive analytics can tell you a lot about how a team is going to perform."


About the Author(s)

Lisa Morgan

Freelance Writer

Lisa Morgan is a freelance writer who covers business and IT strategy and emerging technology for InformationWeek. She has contributed articles, reports, and other types of content to various publications and sites ranging from SD Times to the Economist Intelligent Unit. Frequent areas of coverage include big data, mobility, enterprise software, the cloud, software development, and emerging cultural issues affecting the C-suite.

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