Using AWS to Automate and Visualize Sports Betting Odds

During my Cloud Computing class, my team and I decided to dive into something we were all genuinely interested in—sports betting odds. With so many sportsbooks offering different lines, we saw an opportunity to bring automation and analytics into the mix. The goal was to build a system that could collect real-time odds from multiple sportsbooks, find the best ones for each game, and even identify potential arbitrage opportunities where a bettor could guarantee profit regardless of the outcome. This project allowed me to turn what I learned from earning the AWS Cloud Practitioner certification into something practical, using tools like AWS Lambda, S3, and QuickSight to bring our idea to life.

I started by building Python script (that can be found here) to pull odds data from an API and clean it up for analysis. Using AWS Lambda, I automated the entire process, from doing an API pull to showing relevant information based on which sport we want to look at. From there, we stored the data in S3 and created an interactive heatmap in QuickSight that made it easy to spot discrepancies in odds across sportsbooks. This was especially important for identifying arbitrage opportunities, where you could place two opposite bets and lock in a profit. We also made sure our system updated automatically every day, so bettors could act on the most current info. This could be changed to a higher frequency, but we were limited by the free-trial version of the API.

While there were plenty of challenges—like AWS Lambda’s limitations with Python packages such as pandas, our free trial token limits, and the learning curve that comes with working in the cloud—we built a system we were proud of. Our final product can help people make smarter betting decisions and gave me hands-on experience applying cloud services to solve real problems. Scroll down to check out our slides and see exactly how it all came together.