Thanks to the movie Moneyball, almost everyone now is familiar with how professional sports teams are using the power of analytics to pick potential star performers. However, analytics software tools are also aiding many teams make crucial decisions on other important aspects of the game.

Take game schedules for instance. Every team owner knows that some games are just harder to sell to fans than others. For teams that do not have a huge fan base, empty seats can really hurt.

As director of ticket operations for the National Hockey League team the Carolina Hurricanes, Bill Nowicki has an uncanny sense of telling which matchups are going to be sold out and which ones will be not. For the larger part of his career, the 20-year ticket industry veteran has been relying on his experience, knowledge of the sports and his gut feelings to determine which games will attract fans and what dates might require additional promotion.

Recently, the Hurricanes and other pro sports teams across North America have been filling stadium seats with the help of some of the same data analytics technologies enterprise business to predict business trends or uncover fraudulent activities, according to a recent report in the daily the National Post.

As early as 2005, the Hurricanes had been using a ticketing technology that tracked all the purchase made by an individual fan. However, it was not until the Hurricanes added analytics technologies into the mix that better insight into the data became available.

The team had “years and years of data,” said Nowicki but it “we hadn’t really minded any of it” to gain a deeper insight into the Hurricanes’ customers.

Now the team is using its new tools to build a profile of its ticket plan holders to create “a picture about what our plan holders look like.”

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