The project is a model that predicts the win rate of a League of Legends game in real time.
The popularity and scale of annual E-sports is growing every year. With the advent of the untact era due to Covid-19 and more time at home, the number of people who enjoy and watch games and E-sports has increased significantly. To keep pace with these changes, E-sports was piloted at the 2018 Asian Games, and E-sports was adopted as an official event for the first time at the Hangzhou Asian Games in 2022.
However, in E-Sports, the rules of the game are simple and not intuitive. In other words, if you have never played the game, it is difficult to understand the game. On the other hand, in the case of sports such as the Olympic Games, even if you do not know the rules of the game, you can know who has the advantage through the game score, and you can easily infer the game rules by looking at winning or losing the game score.
Like the match score of the Olympic Games, an intuitive numerical indicator is required, and this can be replaced by ‘predicting the win rate’. The project wants to model the win rate predictor of LoL, the flagship e-sports game.
=> Project Description and result (detail) (My Blog)
click Code - Download ZIP and unzip it
- Open the
jupyter notebookwith python installed. - Run
rawLoL project.ipynb.
If you don't have the jupyter notebook on your computer, install it from this link.
I am looking for someone to help with this project. Please advise and point out.
Please read CONTRIBUTING.md for details on our code
of conduct, and the process for submitting pull requests to us.
- jangThang - Wooyoung Jang - star7sss@naver.com
See also the list of contributors who participated in this project.
MIT License
Copyright (c) 2022 jangThang
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