ValoBrain

Match history page (1)
Analytics page (1)
Analytics page (2)
AI insight page (1)
AI insight page (2)
AI insight page (3)

Category #2: Automated Scouting Report Generator

Inspiration

Our inspiration stemmed from our personal experiences and struggles we have encountered during our competitive Valorant Esports journey. From the perspectives of an ex-professional GC player and Tier 2 professional Coach, we noticed that both scenes had a lack of quality insights going into matches and practice, which made it hard for us to be equipped playing against teams with that level of support behind them. We wanted to create ValoBrain in hopes of helping competitive players who are looking to gain a competitive edge and get insights on how their opponent plays at a macro and micro level. We also hope to increase the player’s knowledge and help them be aware of the tendencies on their future matches against their opponents.

What it does

ValoBrain is an web application that allows a user to view competitive matches, overall team analytics, and generate AI insights of a VALORANT team.

How we built it

We built ValoBrain using React.js, Node.js, Express, TypeScript, GoogleGenerativeAI, and AI Coding Agent Junie.

Challenges we ran into

Parsing positional data to be fit into map zones
Prompt engineering

Accomplishments that we're proud of

We are proud of making an application that can support a community that we are passionate for. We were able to have former professional players/coaches test our application, and they were satisfied with the insights that our app gave. Our most exciting accomplishment would be leveraging AI into creating a detailed insights page.

What we learned

We learned to find a balance for the features we had and how the generation of the report needs to cater for a broader range group of the Valorant community, such as the T1, T2, and GC players to make sure the user experience can be beneficial to every level of players. We learned to not make it too complicated for a less experienced player compared to a T1 player. We learned to cater towards a wide-range audience to ensure everyone’s experience is met with our goal, which is providing detailed insights on the what, why, and how on how a team plays a specific map.