Transforming Sports Predictions with a Scalable Web AI

The Problem: The Guts of the App was Missing

Building and deploying sports prediction algorithms at scale is no small feat. We faced four major app development hurdles:

• Dynamic Machine Learning Algorithm: Their algorithm was static and designed only for NBA predictions; it was outdated and trained on static data from several years ago. The NBA model needed to be relevant and dynamic.
• Multi-Sport Coverage: Similarly, the platform needed real-time predictions for the NFL, MLB, and NHL to ensure a premium user experience across all sports.
• Backend Deficiency: The frontend existed. However, it required a new backend, including database architecture, to support real-time data processing, ML model generation, and user management.
• Monetization Strategy: The company needed an integrated subscription model to enable seamless transactions and recurring revenue generation.

The Problem: The Guts of the App was Missing

Building and deploying sports prediction algorithms at scale is no small feat. We faced four major app development hurdles:

• Dynamic Machine Learning Algorithm: Their algorithm was static and designed only for NBA predictions; it was outdated and trained on static data from several years ago. The NBA model needed to be relevant and dynamic.
• Multi-Sport Coverage: Similarly, the platform needed real-time predictions for the NFL, MLB, and NHL to ensure a premium user experience across all sports.
• Backend Deficiency: The frontend existed. However, it required a new backend, including database architecture, to support real-time data processing, ML model generation, and user management.
• Monetization Strategy: The company needed an integrated subscription model to enable seamless transactions and recurring revenue generation.

The Solution: A High-Performance, AI-Powered Application

Following an extensive discovery phase, the Uplancer Agency team architected a scalable and intelligent solution powered by machine learning and cloud computing.

Machine Learning-Powered Sports Predictions

To deliver accurate game predictions, Uplancer:

• Integrated a data feed from Sportradar to train advanced machine learning models.
• Developed four distinct AI-driven algorithms, each dedicated to an individual sport.
• Designed dynamic models that improved as new sports data was ingested, ensuring up-to-date and precise predictions.

Backend Development & Infrastructure Overhaul

A complete backend transformation was essential for the platform’s success. We:

• Engineered a scalable SQL database to handle large datasets efficiently.
• Developed a high-performance backend using TypeScript for seamless communication with the frontend.
• Leveraged AWS cloud services, including Lambda, S3, EC2, VPC, and Route 53, to ensure reliability, security, and scalability.

Subscription-Based Monetization Model

To drive revenue and user retention, we implemented a robust subscription system by:

• Integrating Authorize.net to handle secure payments.
• Designing a flexible pricing model, allowing users to choose between monthly or discounted annual plans.
• Ensuring compliance with the Click to Cancel law, making cancellations as frictionless as sign-ups.