Seymour native Xander Good scores third with team in data analytics challenge

Seymour native Xander Good and his Rose-Hulman computer science teammates placed third in the NCAA Crossroads Classic Analytics Challenge on March 8 in Indianapolis.

Along with the NCAA, the competition was co-sponsored by Tableau and Visualize Your Technology.

This was the first year that Rose-Hulman has participated in the Crossroads Classic Analytics Challenge. The challenge required application of the team’s problem-solving and data analytical skills.

Good is a senior at Rose-Hulman Institute of Technology and served as an intern at AISIN U.S.A. Manufacturing Inc., a global automotive components supplier located in Seymour.

On the Rose Miner team with Good was William Gardner, Nathan Loafman and Xianshun Jiang. Faculty advisors that assisted the team were Olga Scrivner and John McSweeney. In the challenge, the Rose Miner team placed third within the undergraduate division consisting of 67 teams from seven Indiana colleges and universities.

Rose Miner and the other teams were asked to create predictive models that could help NCAA officials identify potential ticket purchasers based on previous customer datasets.

The game they used to predict the purchasing outcomes was the 2024 Division I Women’s Basketball Championship. Rather than solely sticking to the data from the past, teams were encouraged to use external data to improve their models’ predictive abilities.

“We were ready for this challenge because of the many types of assignments we’re asked to tackle in our [computer science] classes,” Gardner said. “However, we were pleasantly surprised with how well we did. There was some stiff competition.”

Gardner acted as the team’s leader and has accepted a post-graduate job where he can utilize his computing skills within financial services.

“This was really a real-world situation that pushed us to learn and apply some new software. That just required a little more work for us,” Loafman said. After this spring, he is planning on working with Artisan Electronics.

For the final-round presentations, Jiang’s second major in data science helped create the quality analytical models. The teams in the final round practiced in separate conference rooms before making their 10-minute presentation, along with a five-minute question-and-answer period, in front of a panel of Salesforce Inc. and the NCAA judges and professionals.

The teams were scored on these factors, in order of importance: business application, creativity, presentation, technical skills and visualization. This criteria was not revealed until after the competition.

Team advisor Scrivner said that their “team held their heads high and did a great job under some challenging circumstances.”

Scrivner also congratulated their ability to utilize skills from computer science classes such as their data mining course along with learning new skills such as presenting data with Tableau software and learning about sports analytics.

Not only was Good focused on the month-long NCAA challenge, but this challenge overlapped with senior-year capstone projects and final exams for the winter’s academic quarter.

Good said for the NCAA challenge, he and his team tried to do at least an hour of work on the project a day. When possible, they would complete as much as they could in their allotted time.

The Rose Miner team’s model, presentation and business solutions will be shared with NCAA analytics unit members.

Following the success of the Rose Miner team, Rose-Hulman plans to continue participating in the Crossroads Classic Analytics Challenge. Starting next year, they want to expand to include teams from colleges and universities across the country.