Inspiration
We care about this dataset because it will allow us to analyze and predict the gameplay performance for every individual per team. Understanding the agents that were picked the most and least will give the community an insight of what agents are “meta.” We want to use this dataset to predict a fantasy team with current professional players, and see how they would perform against another team. Knowing these answers affects the VALORANT community by gathering intel on who’s currently the best player(s), what’s the best team, what agents the pro players are choosing and on what maps, etc.
What it does
Creates graphs and fantasy teams.
How we built it
We used functions on Python to create graphs and fantasy teams.
Challenges we ran into
Some challenges we ran into were that models were significantly hard to test.
Accomplishments that we're proud of
We are proud of being able to predict gameplay, performance, and agent metas for specific maps, in which we analyze them with other background knowledge of agents being buffed and nerfed.
What we learned
We learned which agents were performing significantly better than others, and which maps were being picked the most and least.
What's next for Analysis of Tier 1-3 VALORANT Tournaments
What's next will be expanding tournament data, looking at specific gameplay and details, and continuing analyzing this dataset.
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