Live Dashboard: (https://lane-dominance-tracker-lol.streamlit.app) Developer: Aditya Mathew
This project is a full-stack, automated data analytics dashboard designed to ingest, process, and visualize complex JSON data from the official Riot Games REST API. It serves as a comprehensive player profiling tool, transforming raw match histories into actionable macro-level insights and chronological performance trends.
The application was built to demonstrate end-to-end data engineering skills, including API authentication, rate-limit handling, dynamic ETL (Extract, Transform, Load) processes, and interactive front-end data visualization.
- Dynamic Data Ingestion: Securely queries the Riot
Match-V5andAccount-V1APIs to fetch real-time player data. - Psychological Profiling (Radar Chart): Uses normalized data scaling to map a player's tendencies across four axes: Combat Aggression (KP%), Resource Generation (CS), Map Control (Vision), and Objective Focus (Damage).
- Macro Trends Dashboard: Plots chronological performance metrics (KDA, Net Gold Differential, Kill Volume) using
Plotly Graph Objectsfor high-fidelity, interactive visualizations. - Heuristic Analytics Engine: A custom algorithmic text-generator that evaluates in-game metrics (e.g., gold deficits at specific timestamps, suboptimal itemization) to output automated performance judgments.
- Session State Optimization: Minimizes API payload and latency by caching complex dataframes locally during the user session.
- Language: Python 3
- Front-End / Deployment: Streamlit, Streamlit Community Cloud
- Data Manipulation: Pandas
- Data Visualization: Plotly (Express & Graph Objects)
- Networking: Requests (REST API Integration)
To run this dashboard locally, you will need a Riot Games Developer API Key.
- Clone the repository:
git clone [https://github.com/A17PRO/Lane-Dominance-Tracker.git](https://github.com/A17PRO/Lane-Dominance-Tracker.git) cd Lane-Dominance-Tracker