C9 StratOS

login
dashboard
opponents
G2
G2 amercias stage 2 match
heatmap
economy
First bloods and site performance
AI coaching report

Inspiration

I'm a huge Valorant fan having attended VCT Masters Toronto and being a computer science student I felt like this is an amazing hackathon to enter

What it does

This webapp is like the HQ for C9 to take an overview at their recent matches and have an in depth analysis of what they did right and wrong. The main function is the AI coaching report which send all the summarized data to Gemini to then create the report for a specific map.

How we built it

This was built with next.js for the front end and backend but I first started with exploring the data I had which I used python and Junie with MCP to explore the data files I downloaded from the GRID API

Challenges we ran into

The main challenge was the vast amount of data that was contained in each file. For every series played there was about 5GB of raw data which I then had to pluck out data that can be used in generating a summary of that match. I wanted to add a lot of features like the heatmap which was one of the last features I added but couldn't perfect it in time. The heatmap data points are a little off or even out of the map boundaries.

Accomplishments that we're proud of

The biggest accomplishment is the fact that I got to implement mongoDB and python in a real world project. I got to learn these tools in school last semester but using them and building something feels great. My favorite feature is the heatmap which is not 100% complete since the heatmap data points are off in the minimaps.

What we learned

I learned how Jetbrains IDE and Junie can help my coding efficiency. As well as learning next.js and typescript.

What's next for C9 StratOS

Some next steps for my project is to add the features that are currently missing data visualizations like the heatmap exists in the website but it's not perfect or the highlight tab which doesn't contain any highlights.