Betting with OpenAI: Transforming Sports Betting with ChatGPT
Redefining odds and market efficiency with cutting-edge AI-driven insights.
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Authored by María Sol Stiep, Víctor Losada, Carlos Torrecillas and Máximo Albornoz
Introduction
The world of sports betting is entering a new era, driven by the advanced capabilities of Azure OpenAI’s GPT. SOUTHWORKS’ “Betting with OpenAI” proof of concept (POC) integrates artificial intelligence (AI) to replace or complement traditional mathematical models, transforming pricing mechanisms and enhancing market generation efficiency. By leveraging AI-generated insights, this system introduces groundbreaking improvements in speed, resource optimization, and decision-making for bookmakers.
Revolutionizing Sports Betting with AI
The "Betting with OpenAI" POC is designed to:
- Enhance efficiency: Rapid pricing calculations minimize bottlenecks.
- Optimize resources: AI reduces dependency on conventional mathematical modules, cutting costs and infrastructure needs.
- Enable independence: Bookmakers can generate key market data without relying on external providers.
Real-world Validation:
Comparative analyses of AI-generated odds against high-street bookmakers revealed striking accuracy, underscoring the potential for improving market generation speed, reducing dependencies, and minimizing operational overhead.
Key Benefits
- Replacing Traditional Pricing Models: Leverage AI to predict odds and calculate player and other key markets.
- Increasing Efficiency: Eliminate delays caused by traditional pricing modules.
- Optimizing Resources: Streamline infrastructure for cost-effectiveness and scalability.
- Enabling Scalability: Dynamic architecture supports high-demand scenarios with ease.
System Workflow
- Team Selection: Users select a squad of 16 players (starters and substitutes) per team.
- Competition Selection: Users choose competitions, automatable via football fixture data.
- Betting Margin Application: AI applies an overround margin for odds adjustment and compares results with real bookmaker data.
- Outputs:
- Predicted Lineups: AI predicts the starting 11 players and substitutes.
- Odds Prediction: Generates probabilities for Home Win, Away Win, and Draw (Classic Match Winner 3-Way).
- Data Persistence: Stores results for analysis and future reference.
System Architecture
Frontend (UI)
- Purpose: Facilitates team and player selection, displays odds predictions.
- Technology Stack:
- React with Vite: User interface development.
- TypeScript: Ensures type safety and reliability.
Backend (API)
- Purpose: Processes data, integrates with OpenAI for predictions, and stores match data.
- Technology Stack:
- .NET 8: High-performance API development.
- OpenAI Integration: Generates predictive insights.
- CosmosDB (Azure): NoSQL database for scalable storage.
Infrastructure and DevOps
- Infrastructure:
- Kubernetes (AKS): Manages backend and frontend workloads with autoscaling.
- Terraform: Automates provisioning and configuration of Azure cloud resources.
- DevOps:
- Azure DevOps Pipelines: Enables Continuous Integration/Continuous Deployment (CI/CD).
Frontend Key Functionalities
- Fixture Definition:
- Team selection as well as the 16 players called for the match.
- Fixture competition (examples: La Liga, UEFA Champions League, etc).
- Market margin to specify the overround for the Match Winner market prices.
- Results Display:
- Prediction for the starting eleven given the §6 players submitted and the 5 substitutes for each team.
- Prediction for the match winner 3-way prices for the given fixture including the target margin specified.
- Expandability: Feed in new competitions and teams.
Backend Key Functionalities
- Competition and Team Management:
- Feed in new data via specific endpoints to include new competitions and teams with players and playing positions.
- Match Predictions:
- Tailored Open AI prompt management for predicting both teams' lineups and match winner prices.
Usage Flow
- Frontend Interaction: Users configure teams, players, competitions and margins through an intuitive UI.
- AI Integration: Backend communicates with Azure OpenAI to generate lineups and odds predictions.
- Result Visualization: Predictions are displayed and stored for analysis.
Conclusion
By incorporating OpenAI’s GPT, the "Betting with OpenAI" POC demonstrates the transformative potential of AI in sports betting. The system’s ability to enhance efficiency, reduce costs, and provide rapid, accurate predictions paves the way for a new standard in betting market operations. Whether it’s improving scalability or enabling data independence, AI is redefining the future of this industry.
Check out the Repo on Github here!
Powering a Smarter Betting Experience with AI
Leveraging the cutting-edge capabilities of OpenAI's GPT, SOUTHWORKS introduces a proof-of-concept that redefines traditional sports betting. By integrating AI-driven insights, bookmakers can replace or complement conventional mathematical modules, resulting in faster pricing calculations, enhanced resource efficiency, and actionable market insights.
