Super Bowl LX Predictive Analytics Event
Thursday, February 05, 2026 at 4:00 pm
UCI Paul Merage School of Business
4293 Pereira Drive • SB-1 Main Auditorium
Submittal Information for Individuals or Teams
If you or your team would like to present in front of fellow students, faculty, and local business executives, this is an outstanding opportunity to showcase your analytics expertise and presentation skills! Below are submission guidelines for any student within the UCI Paul Merage School of Business interested in being selected to present their predictive analytics model for the exact score of Super Bowl LX within a 10-minute slide presentation highlighting your methodology, assumptions, and insights.
ABOUT THE EVENT. As you may or may not know, the biggest sporting event in America is the Super Bowl, which is going to played on Sunday, February 8 at 3:30 pm PT televised on NBC, with streaming available on Peacock and NFL+. The Super Bowl is the championship game of the National Football League (NFL).
VIDEOS. If you are new to football, here are videos to help!
A Guide To American Football (Funny) https://www.youtube.com/watch?v=uE7qVAtNwQk
Guide to American Football (Serious) https://www.youtube.com/watch?v=uM9iLQJzMO0&t=281s
How to Understand American Football: A Primer https://howtheyplay.com/team-sports/How-to-Understand-Football
A Beginner's Guide to American Football https://www.youtube.com/watch?v=3t6hM5tRlfA&t=76s
CORE DATA. Data can be accessed many ways to assist in your predictive modeling. The easiest data set to download data from can be found here:
https://www.pro-football-reference.com - The data set reflects 12 key metrics for each of the 17 games each team played this past season plus all playoff games:
Wins, Losses, Points scored by the offense, Points allowed by the defense, Total yards gained by the offense, Total yards given by the defense, Rushing yards gained by the offense, Rushing yards given by the defense, Passing yards gained by the offense, Passing yards given by the defense, Turnovers recoveredTurnovers given up
OTHER DATA SOURCES. There are myriad data sources available . . . so here is a list of other data sources you may wish to explore and supplement with the above data. Also, feel free to gather and analyze ANY other data source you wish! Or, just use the Core Data . . . it entirely up to you!
https://www.advancedsportsanalytics.com/nfl-raw-data
https://www.footballdb.com
https://fantasydata.com/nfl/team-stats
https://www.kaggle.com/datasets/kendallgillies/nflstatistics
https://www.nflfastr.com
https://www.nfl.com/stats/team-stats/offense/passing/2022/reg/all
SUBMITTAL PROCESS. The assignment is to develop a predictive model (as simple or as complex as you wish) that generates a prediction of the FINAL SCORE between the AFC Champion and NFC Champion. Said another way, your model should output a prediction of the total points scored by the AFC Champion and output a prediction of the total points scored by the NFC Champion. And by default, your model will be predicting the winner of the Super Bowl! The game CAN NOT end in a tie! You can use any processes, methodologies, software, or data sets you wish. You can even ignore all the aforementioned data sets and utilize your own data. As long as you develop some form of a predictive model and can explain and support the process you used to produce the final score.
STEP ONE - UPLOAD KEYNOTE FILE OR POWERPOINT FILE THAT PRESENTS YOUR PREDICTION BY MONDAY, FEBRUARY 2 at 11:59 PM PT
ELEMENTS OF YOUR SLIDE DECK SHOULD INCLUDE:
Contact Information. Full name, email, and mobile number of each student or students within the team.
Introduction: Name of your team, name of individual team members. Feel free to include images, interests, etc.
Prediction: Present your prediction results on one slide.
Methodologies: Present what methodologies, approaches, processes, software, etc.
Confidence: Present a probability percentage to your team's forecast and describe why.
Topics of Interest: Address any interesting issues, concerns, topics, questions, future areas of research, strengths/weaknesses of forecast method, etc.
Model and Code: Submittals that also upload models, code, and other supporting documnatation will get preference.
UPLOAD HERE!
https://www.dropbox.com/request/wFd5rCKO4qIJDGyFiBm1
STEP TWO
Competitive Analytics will review all submittals and email winning presenters Tuesday Afternoon, February 3 and offered the unique opportunity and privilege to present at Thursdays Super Bowl LX Predictive Analytics Event on February 05, 2026 at 4:00 pm in front of fellow students, faculty, and local business executives! Again, this will be an excellent opportunity to showcase your analytics expertise and presentation skills!