A University of North Texas mathematics class recently provided the Dallas Cowboys organization and Legends Hospitality with predictive models for events held at the Ford Center in Frisco, Texas. The project is part of an ongoing partnership between the university and the Cowboys and was overseen by Dr. Michael Monticino, the Program Director for the Advanced Data Analytics Program (a part of UNT's Toulouse Graduate School) and professor of the participating class, MATH 5810 (Fall 2018) at UNT's New College at Frisco.
The Ford Center is a unique, multiuse arena that is a first-of-its-kind facility in professional sports. It is a venue that will be used for everything from concerts to high school football games. The Cowboys organization turned to UNT's Advanced Data Analytics Program to provide staffing recommendations based on the forecasted demand of events taking place at the center.
"In order to better serve their customers, we offered the Cowboys a way to predict the center's attendance levels for various events as well as determine concession staffing needs during events," said Dr. Monticino. "In order to tackle this project, the class of graduate students was divided into two teams: a demand forecasting team and a staffing recommendation team."
The demand forecasting team developed a model to predict event attendance at the Ford Center. The team collected data on a number of variables. For High School football games, the variables included the distance from the schools to the stadium, demographics, the schools' football records and rankings, and whether the game was a regular or post season match-up.
Forecasting attendance levels is key for the staffing recommendation team. Students on this team developed a staffing recommendation model using the forecasted attendance number to predict concession stand staffing needs. The team collected data including demand at the various concession stands in the center, service times during different points of a game and average sales per customer. Using this data, the team created a software tool that recommends staffing needs at different times in order to meet desired service levels. The goal of the engine is to reduce the time a customer spends in line and limit the length of lines at concession stands. Both of these result in a better customer experience and more potential sales.
"Sport teams are finding that data analytics can be applied throughout their operations," said Dr. Monticino. "That's just another reason why UNT is leading the way with its Advanced Data Analytics Program." To learn more about the Adavanced Data Analytics Program out of Frisco, visit https://frisco.unt.edu.