Student Enrichment

10th Annual Deloitte MDMC Competition, 2023

SPONSORED BY DELOITTE

This past March, the Center for Digital Transformation held its annual “March Data Crunch Madness,” during which student teams use their analytics skill to predict the outcome of the NCAA Basketball tournament using publicly available data. The competition is open to all Fordham students, although most participants are in the Gabelli School of Business (GSB) M.S. in Business Analytics and M.S. in Information Technology programs.

This year, 19 teams started in the competition. After the initial phase of the competition, 10 teams were allowed to participate in its final stage. These finalists presented their work in an open forum held on March 31. A panel of GSB faculty members, alumni, and representatives of the competition’s sponsor, Deloitte—one of the top four consulting firms in the world, judged and ranked the teams based upon the analytics methods, tools, and presentation.  This year’s winners are:

1st Place (each team member received a prize of $250)

Team JORDAN YEAR

• Jennifer McFadden
• Yujoon Jang
• Masaya Sugimoto

2nd Place (each team member received a prize of $125)

Team LIVN

• Vidushi Rai
• Nisera Vaughan
• Imaobong Undieh
• Leonard Chiang

3rd Place (each team member received a prize of $62.50)

Team MATHEMATICAL MADNESS

• Carissa Arceri
• Peter Warzecha
• Ben Rinella
• Tony Wang

Professor Jie Ren, a member of the judging panel, described why team JORDAN YEAR won the competition: “Their team demonstrates excellent data analytical techniques in data collection and preprocessing, selecting and testing models, and presenting their findings. Specifically, they focused on the inputs of Pythagorean Win Percentage, Distance from Home, and Team 1 & Team 2 Difference. They also attended a basketball game and surveyed the audience about factors affecting a basketball team’s chances of winning. They identified three other important inputs: Team Budget, Top Scorers Per Team, and Injured Players. The team JORDAN YEAR extracted these variables from different data sources. It tested five different models and finally chose Logistic Regression based on log loss.”

Jennifer McFadden, a member of the team Jordan Year, describes her team’s unconventional approach as the key to building a robust prediction model.