Data plays a huge role in eSports to support players improving their performance. Dota 2, in particular, is a competitive moba and needs multiple features of data to accurately access the performance of players.
Aim The aim of the project is to integrate multiple dimensions and features of players data to accurately display and evaluate the performance of players.
Dataset We get our data from Kaggle which is already been processed. We would like to integrate the data to present an overview of players using data integration and we would like to predict the winning rate using machine learning and algorithms for future matches giving that we have a 400 megabits of data set. For the dataset, we get tables for each important component of a match such as items used, ability upgrade timeline, the clusters of area for which most battle happened, most used heroes. We hope to build a predictive model for outcome of a game given the players' data from the set. At the same time, we are going to build an overall performance matrix for players to understand their performance.
Dota 2 is a multiplayer online battle arena (MOBA) video game developed and published by Valve Corporation. The game is a sequel to Defense of the Ancients (DotA), which was a community-created mod for Blizzard Entertainment's Warcraft III: Reign of Chaos and its expansion pack, The Frozen Throne. Dota 2 is played in matches between two teams of five players, with each team occupying and defending their own separate base on the map. Each of the ten players independently controls a powerful character, known as a "hero", who all have unique abilities and differing styles of play. During a match, players collect experience points and items for their heroes to successfully defeat the opposing team's heroes in player versus player combat. A team wins by being the first to destroy a large structure located in the opposing team's base, called the "Ancient"...
Ziqi Tang: Senior in applied data sciences at PSU, EMAIL:firstname.lastname@example.org
Yifeng Chen: Senior in applied data sciences at PSU, EMAIL:email@example.com
Zhengyang Luo: Senior in applied data sciences at PSU, EMAIL:firstname.lastname@example.org