Analytics in Sports

Ticketing is the cornerstone of sports business and whether it’s defining pricing, packages or exploring value-added opportunities to enhance the customer’s experience, this support function is experiencing significant technological and analytical growth as the ticketing landscape continues to mature. In June, 2013 Michigan Athletics transitioned to a dynamic ticketing model and while they’re not the first university to adopt the approach, they may be the most high profile of a group that includes Cal, Georgetown (basketball), South Florida and Washington. Companies like QCue and Digonex are currently applying infrastructure to these clients allowing them to adjust single-game ticket prices upward or downward based on real-time market conditions, particularly weighting fan demand and ticket scarcity. The concept of dynamic pricing has been widely used throughout the travel industry and is gradually evolving into the standard for sports and entertainment. Hunter Lochmann, chief marketing officer for the Wolverines, noted that the department could generate up to nearly $1 million in additional revenue.
While letting market value dictate how much fans are willing to pay to attend a game, there has been no shortage of backlash from the general public (note, dynamic pricing for UM Athletics applies only to single-game tickets, not season tickets). Some have expressed concern that such models price out diehard fans by empowering only those with means to attend such marquee matchups (Notre Dame, Nebraska, Ohio State in 2013). The needle can obviously shift both ways but many fear that Michigan has become a glorified broker and middle man. Fact of the matter is, the Michigan Athletic Department budget for fiscal year2013-2014 is $137.5 million, with just under a third of that being a derivative of football-related revenue ($85.2 million in 2012)1. If you compare the most profitable football programs in the country to those with typically higher average ticket prices,