March Data Crunch Madness winner boxes out the competition
Graduate | Apr 12, 2017 | Kathleen Clarke
If you wagered on the NCAA basketball tournament this year, you likely conducted some fundamental research to complete your bracket. Or perhaps you selected the national champions based solely on your preferred school mascots.
Whatever your strategy, chances are you did not perform statistical regression analysis or use the bootstrap algorithm to predict the final four teams. But these approaches are exactly what contestants used in the Fordham University Business Analytics Society March Data Crunch Madness competition.
The 17 competing student groups, including two undergraduate teams, were given historical data to predict the results of the 2017 NCAA basketball tournament. Their objective? Demonstrate analytical expertise, modeling creativity, and overall presentation skills to impress a judging panel of four Fordham faculty members and three representatives from Deloitte.
After a suspenseful deliberation, Yi Cai, Yuhan Hao, Nianting Ouyang, and Jiawen Zhou, all MSBA ’17, were awarded first place. By applying data-mining strategies and statistical models similar to those used by Google Translation, the team of four MS in Business Analytics students predicted the tournament results with an impressive 75-percent overall accuracy.
This year marks the third anniversary of the competition sponsored by Deloitte and reflects the Gabelli School’s emphasis on applied learning and experiential education outside of the classroom. The event allows students to expand upon analytical disciplines and statistical methods learned in class and practice soft skills in a formal setting.
Professor “R.P.” Raghupathi, founder of the Gabelli School’s Center for Digital Transformation and competition organizer, commended students for their ability to “tell the story behind the model,” a skill that will prove valuable in the workplace.