This project aims to help LOL players and amateurs gain clear intuitive information by using multidimensional visualization tools.

This project was implemented as a part of the course Information Visualization at KTH - the Royal Institute of Technology. The project proceeded for weeks and at the beginning of the project different responsibilities were distributed among the team members to make sure that everyone had responsibilities.

Under Covid-19, the esports industry is growing and becoming more popular compared to the past. In this project, we focused on the MOBA game and we chose League of Legends as our object. We were inspired by previous works in the competitive sports field [2] and video game fields [1]. All the data we use are from Oracle's Elixir. [3] The concept idea and design were set through iterative and explorative analysis of different visual structures and mappings, at the same time, the code structure was set up. Prototyping of the user interface was conducted before the development of the visualization components.

In our project, we divide the data into three parts for visualization with aims for providing competitor analysis for gamers, acting as game guidance for users. Different visualization structures were applied to show the three parts separately, and add different interaction methods for each structure.

Learning objectives reached

Project Top Teams League is the useful tool that we make, in order to give guidance. We as a group worked together to reached three of our goals mentioned in our proposal:

1. We applied a parallel coordinate, radar chart, map view, and data sheet to visualize data in different ways.
2. We tackled a large amount of data and selected suitable data for our target user to analyze the game-League of Legend.
3. With all the pages and functions we have, we made a comprehensible game tool that followed the visual information seeking mantra of: overview, zoom, filtering and details on demand.

By building this website we have learned d3, Echarts, javascript, and python in 2 months, we also improved teamwork ability and time management during this project. Feedback from the audience and our website users also help us have a better understanding of user experience and evaluation.

References:
[1] Analytics of Play: Using Information Visualization and Gameplay Practices for Visualizing Video Game Data. Ben Medler, Brian Magerko. 2011
[2] State of the Art of Sports Data Visualization. C. Perin R. Vuillemot C. D. Stolper J. T. Stasko J. Wood S. Carpendale. 2018
[3] Oracle's Elixir - Match Data Downloads