LOL Esports Datalake

The LOL Esports Datalake project aims to gather comprehensive information about games, teams, tournaments, and other relevant data from various leagues including CBLOL, LEC, LCS, and others. This data is then fed into a datalake for further analysis and utilization.

Getting Started

Prerequisites

• Python 3.11
• Ensure you have pip installed

Installation

1. Clone the repository:

   git clone https://github.com/your-username/lol-esports-datalake.git

2. Navigate to the project directory:

   cd lol-esports-datalake

3. Install dependencies:

   pip install -r requirements.txt

4. Configure the Database:

   • The default database is SQLite but can be any SQL database. You need to specify the database path in src/model/s.py.

Starting the Datalake

Initialization

To start the datalake, follow these steps:

1. Initialize the datalake:

   python start.py

   This command initializes the datalake and creates the necessary tables for leagues and tournaments.

Populating Data

To populate the datalake with data:

1. Run the main script:

   python feeder_frame_v1.py

   or, the version 2 to get the frame version 2 (less details)

   python feeder_frame_v2.py

   This script allows you to choose a specific tournament and retrieves all matches/games along with their frames (specific moments of the game).

Usage

Once the datalake is populated with data, you can perform various analyses, generate insights, and derive valuable information about esports tournaments, teams, and games.

Contributing

Contributions to the project are welcome! Feel free to submit pull requests, report issues, or suggest improvements.

License

This project is licensed under the MIT License.

API DOCS

https://vickz84259.github.io/lolesports-api-docs

NEXT STEPS

• Machine learnign model using Random Forest Classifier (an ensemble)
• Live Inference of the game using ML Models
• Feature Engineering (add more data)