Spring Racing
Hackathon
Learn about AI in forecasting and apply your knowledge to horse racing using historical data.
Virtual kick-off
Wednesday, April 9th at Noon via Zoom (recorded)
- Meet the Center for Applied AI (CAAI) Team
- Introduction to the challenge, overview of forecasting with AI, and review of competition rules
- Dataset distribution (historical racing data)
- Explanation of AI tools CAAI offers for teams’ use (including LLM Factory and CLASSify )
- Teams are welcome to use their own resources and tools
- Teams (1-3 people per team) may begin development on their model following the virtual kick-off
In-Person Event & Competition
Sunday, April 13th from 10 AM – 6 PM at The Cornerstone (Lunch provided!)
- CAAI software developers will be available as advisors; teams will have the opportunity to share their unique approaches and receive expert feedback
- Competition begins at 1:00 PM
- Teams submit their predicted win, place, and show positions before each race
- Live leaderboard updates throughout the event
- Teams will have the opportunity to refine models between races
- Prizes* will be awarded to 1st, 2nd, and 3rd place teams
*Only full-time students are eligible to win prizes.
The Challenge
Use AI to develop a forecasting model. Evaluate it by predicting win, place, and show positions of live races based on historical data.
The Center for Applied Artificial Intelligence invites you to put your data science and machine learning skills to the test at our Spring Meet Hackathon! Using historic horse racing data, teams will develop predictive models to forecast race outcomes. Compete to create the most accurate predictions while working with real-world datasets.
Though the challenge focuses on horse racing, AI-driven forecasting has broad applications in industries like healthcare and finance. This student-focused event is a chance to explore new methods, sharpen your skills, connect with CAAI developers, and compete for prizes .
Collaborate, innovate, and showcase your expertise. Whether you’re passionate about AI, the horse racing industry, or cutting-edge analytics, this is your opportunity to learn, network, and win!
Sign up today!
Event Details
Virtual Kick-Off
April 9 – Online via Zoom (recorded)
The 1-hour virtual kick-off session will introduce the challenge, outline competition rules, and provide an overview of forecasting with AI. Participants will gain insights into key techniques used in predictive modeling and learn about CAAI’s self-service AI tools available for experimentation.
- Dataset Distribution: Teams will receive a historical dataset of race outcomes. It will be up to each team to define their training and testing sets with this shared data.
- AI Tools Overview: Participants will have access to CAAI self-service tools such as LLM Factory and CLASSify to support their model development.
- Recording Available: If your team is unable to attend the live virtual session, a recording will be made available for review.
After the virtual session, teams can begin independent model development. Bring your personal laptops to the in-person competition on Sunday, April 13!
In-Person Event & Competition
April 13 @ The Cornerstone
10:00 AM – 11:00 AM: Teams arrive, check in, and bring up their models on their computers.
11:00 AM – 1:00 PM: Mentorship session with CAAI advisors—an opportunity to refine models, receive expert feedback, and connect with CAAI software developers.
1:00 PM – 6:00 PM: Live competition begins with live races.
- A Daily Racing Form will be provided for additional data extraction.
- Predictions will be tracked on a live leaderboard as teams submit their forecasts.
- Teams may refine their models between races to improve accuracy.
This event is designed to be both educational and competitive, providing hands-on experience with AI forecasting in a real-world setting.
Rules & Requirements
Teams will predict win, place, and show positions before each race.
A live leaderboard will update throughout the event to track predictions.
Teams may refine their models between races to improve accuracy.
This competition is UK-only—participants must be affiliated with the university.
UK staff are not eligible for prizes. Participants must be full-time students at the University of Kentucky in order to win prizes. However, we welcome participants of all student status!
Each team must bring a personal laptop for model development and submission.
Teams can consist of 1–3 members.
No wagering or betting is involved in this event.
