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BetQL

BetQL

BetQL's computer model identifies mispriced sports bets for 14 sports leagues including NFL, NBA, MLB, NHL, NCAA Football and NCAA Basketball action.
BetQL

Our success story with

BetQL

Step 1 Investigation
Step 1: Investigation
During the investigation phase, our team conducted thorough research to understand the sports betting market, target audience, and competition.One of the main challenges in developing the BetQL app was the complexity of data analysis and modeling required to accurately identify mispriced sports bets across multiple sports leagues.Development process involved acquiring and integrating diverse data sources, implementing sophisticated algorithms, and continuously updating and refining the models to maintain their accuracy. Overcoming these challenges required a strong technical experts of 3 developers, 1 project manager, 2 designers and 1 QA engineer.
Step 2: Planning
The roadmap of the development included setting specific goals and objectives, determining the scope of work, creating a detailed project timeline with milestones and deliverables, allocating resources effectively, and establishing communication and collaboration processes within the team. The planning phase also involved identifying potential risks and challenges, devising mitigation strategies, and ensuring alignment between the app's features, target audience, and business goals. By thoroughly planning the development process, the team set a solid foundation for the project's success and guide the subsequent implementation stages effectively.
Step 2 Planning
Step 3 Design
Step 3: Design
One of the main challenges in the design process for the BetQL app was seamlessly integrating and presenting data from 14 sports leagues. Our team of designers used a powerful designing tool Figma to combine such a diverse range of sports leagues with their unique data structures and formats. We developed a cohesive and unified design approach that accommodates the specific needs of each league while maintaining a consistent user experience across the app.
Step 4: Development and testing
By utilizing Swift for iOS development and Kotlin for Android development in the BetQL app, our development team addressed platform-specific challenges and ensured optimal performance, native user interfaces, and access to platform-specific features. To update betting data throughout the app, the team implemented WebSockets, enabling real-time data streaming and updates. This solution effectively solved challenges such as providing instant updates on live scores and odds, reducing network requests by establishing bidirectional communication, delivering a seamless user experience with timely notifications.
Step 4 Development and testing
Step 5 Release
Step 5: Release
Before launching the app on stores, our team conducted a testing and quality assurance to ensure the app's stability, functionality, and compatibility across different devices and operating systems. After that the app was submitted to App Store and Google Play Store following their guidelines and requirements. Additionally, support and feedback channels were established to gather user insights and promptly address any issues that arise.
Results
Result 1Result 2Result 3
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I’ve been using BetQL for the better part of 2 months and have had nothing but positive things to say about it. Easy to navigate interface and excellent insight.

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Luke Corsano
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