Many new players have a difficult time getting into League of Legends because it has so so many unique characters, each with different abilities. Our program aims to assist these players.

What it does

Our app suggests new League of Legends characters to play that are similar to a given user's play-style.

How we built it

We accessed player data using League's public API. With this data, we created a weighted average of a user's play-style. Using 7 critical metrics, we created a multidimensional grid and found the characters closest to the player's profile. These characters are then recommended.

Challenges we ran into

The public API is inconsistent and sometimes does not return all the necessary information.

Accomplishments that we're proud of

We are all League players, and our data is very consistent with our game knowledge.

What we learned

We discovered GitHub collaboration and created our first Hackathon submission. More specifically, we all learned how to compare multiple objects using multiple factors.

What's next for League Champion Recommender

In the future, we plan to add a more professional interface. Additionally, we plan to add new features, such as comparing match ups and finding counters.

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