Just pick the game and enter your IGN(In-game name) and that's all
These are my trends and it seems like Im doing pretty good :P
Some initial design docs
I play video games, some of my group members play games, and many of our friends play games. But normally, we don't care how well we are playing and whether our skills are still improving in the game, while we are enjoying a game. Suddenly, we may reach a point where we just get stuck at a game or perhaps never reach the next rank. Our team wish to use data to provide gamers with insight to how they are performing and whether they are improving, and how they compare to other gamers in competitive games.
What it does
By providing Gamealytics with your IGN for the game, League of Legends or Team Fight Tactics, we are able to scrape performance data for individual gamers. We then apply regression/machine learning processes to show visually how a player is doing as well as predict how long it takes to get to their next rank in the competitive scene.
How we built it
We used Python and BeautifulSoup to Scrap data about each user on the backend, using Flask as the server. We built the client with React and Chart.js to visualize a player's performance. Each unique user's performance data is logged into a Firebase Database which we can use in the future to improve the algorithm, as well as provide new users with how they compare to other players similar to their rank.
Challenges we ran into
Accomplishments that we're proud of
Actually building a functional full-stack application! None of the members walked out! Having a great group dynamic and getting food together. Performing a nice brain-storming session rather than jumping in wihtout any specific ideas.
What we learned
How to work with the Firebase API and that the database defaults to not being accessible when just getting started. Building and handling custom APIs and running that with a server. That there were exceptionally helpful mentors at Hackthe North.
What's next for Gamealytics
A proper user system where a user can be updated on whether they are performing up to par as before, performing exceptionally well, or perhaps need a bit more practicing. Simple ways for users to improve their gameplay and improve their rank. Perhaps classifying users and identifying similar points where users can continously improve their gameplay through more Machine Learning and Analytics.