Rice University junior Lucca Ferraz is living a dream as a finalist in the 2025 Big Data Bowl, the NFL’s premier sports analytics competition. Ferraz, who is double majoring in statistics and sport analytics, had the opportunity to present his work on the big stage, sharing his team’s insights with nearly 200 NFL executives.
“I’m so excited! I feel like this is a dream come true for me,” said Ferraz, who is minoring in data science and financial computation and modeling.
The Big Data Bowl is an annual competition hosted by the NFL, bringing together data scientists, students, and analysts to tackle football-related analytical challenges using cutting-edge data.
“Obviously, being a sport analytics major, I’ve heard about the Big Data Bowl, and this past summer my research mentor made the finals, but I never imagined I would have this opportunity,” he said.
Ferraz, Lindsay Fleishman (University of Georgia), Daniel Soriano (University of California, Davis) and Eric Steinberg (Emory University) formed their team in an unexpected way — through LinkedIn. After an introduction via the NFL’s mentorship program, the group came together last October, collaborating remotely for four months without ever meeting in person. They presented their creation, TendencIQ, at the NFL Data Bowl during the league’s scouting combine in Indianapolis, where top college football players showcase their skills in front of coaches, scouts and executives from all 32 NFL teams. It is also a major networking event for analysts, coaches and data scientists looking to make an impact in the league. For Ferraz and his team, it was the perfect stage to showcase their project, which applies data-driven insights to football strategy.
“This year’s challenge was all about presnap movements — the shifts and motions teams use to keep defenses guessing before the play even begins,” Ferraz said. “The goal was to analyze how these presnap formations influence what happens after the snap. For our project, we focused on tight ends, using their alignment and movement to predict whether they would stay in pass protection or break out into a route to try to make a play.”
Ferraz said their ability to formalize and quantify presnap movements set their project apart.
“If you’re a coach or watching the game, you can instinctively recognize different types of movements,” Ferraz said. “But being able to put formal definitions on them is something we did really well. I think that’s one of the reasons we’re being recognized, just being able to innovate in ways teams might not have seen before.”
Out of 400 submissions, Ferraz and his team were one of only five to reach the finals. While they did not take home the top prize, their achievement in reaching the finals is a testament to their innovative work in sports analytics.
“Just being able to be recognized for our work is really nice, and honestly, about all I can ask for,” Ferraz said. “Everything else is the cherry on top.”
Building on experience with Owls’ football team
Ferraz brings a unique perspective to the competition, combining classroom knowledge with hands-on experience. He is part of a student-led analytics group for the Rice football team and will take over as the student head of analytics next season, further solidifying his role in the program’s data-driven strategy.
“Being able to take my football knowledge from working with the team and combine it with my statistics background made this project come together really well,” Ferraz said. “I’ve had incredible professors like Dr. [Scott] Powers, who has real-world experience working with professional sports teams. Without taking his classes, I wouldn’t have been able to develop the skills necessary for this.”
Recognizing Rice’s impact in sports analytics
The Big Data Bowl has become a major hiring pipeline for teams across the NFL and other professional leagues. Finalists’ work is publicly available, and many teams actively scout participants.
“This is the biggest sports analytics competition out there,” Ferraz said. “I’ve already had a few teams reach out about our project and potential meetings at the Combine. It’s an incredible opportunity to get into the field.”
Beyond competition day, Ferraz and other participants had the opportunity to network with NFL analysts and executives, gaining exposure to the professional sports analytics landscape. Many past Big Data Bowl projects have gone on to be integrated into Next Gen Stats, featured on Amazon Prime’s “Thursday Night Football” broadcasts, and Ferraz said reaching the finals is an opportunity for their work to potentially make a real impact in the league.
Other Rice students shine as finalists and semifinalists
In addition to Ferraz, fellow Rice students Jonah Lubin and Charles Wells were honored as semifinalists with their project analyzing receiver openness, a key factor in offensive performance. Titled Keep ’Em Separated, the project focused on the factors influencing a receiver’s openness and how presnap information plays a role.
“Traditional views often take a player’s separation value at face value,” Lubin said. “We wanted to show how offensive scheming plays a role in receiver performance, providing analysts with a more comprehensive framework for player evaluation.”
The pair faced a significant challenge in working with the massive dataset, which tracked every player and the ball’s movement down to tenths of a second. “Running predictive modeling on that data was tough,” Wells said. “We spent months refining our process to ensure we could extract meaningful insights.”
It was the second time Lubin and Wells entered the Big Data Bowl, having competed the previous year without receiving recognition. “After spending weeks on our submission last year and not making the cut, it meant even more for us to be recognized as semifinalists this time,” Lubin said.
Both students credited Rice’s rigorous academic programs for preparing them for the challenge. “Rice’s sport analytics and sport management programs gave me hands-on experience that translated directly into our project,” Lubin said. “The coursework, combined with access to real-world datasets, was instrumental in refining our approach.”
Wells echoed the sentiment. “Rice’s computer science and math programs gave me the technical foundation I needed,” he said. “Working on this project showed me how to apply those skills in a way I hadn’t before.”
“As far as I know, this is the first time Rice students have ever made it to the semifinals or finals,” Ferraz said. “Seeing fellow Rice Owls recognized is amazing. It speaks to the strength of our sport analytics program.”
Looking ahead
Following the Big Data Bowl, Ferraz will intern with Major League Baseball’s Tampa Bay Rays this summer, furthering his experience in professional sports analytics.
“I definitely see myself working in sports analytics after graduation,” he said. “This competition is a huge boost to my resume, and I’m excited to see where this opportunity takes me.”
Lubin, meanwhile, is actively pursuing a career in football analytics and has already received interest from multiple NFL teams following the competition. Wells, while set on his path in software development, said the experience broadened his ability to apply coding in new ways.