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.
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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.”