Draft-Analysis of the Ancients: Predicting Draft Picks in DotA 2 using Machine Learning
Adam Summerville, Michael Lee Cook, Ben Steenhuisen · Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment · 2016
Analysing strategic decision-making in eSports is an increasingly important problem -- for players, for teams, for commentators, for viewers and for broadcasters. Such analysis is extremely difficult, however, because of the comparatively small quantities of data, the ever-shifting state of competitive play, and the huge complexity of the game. In this paper we describe a system for predicting drafting decisions in DOTA 2, and evaluate both how the system performs compared to human experts, as well as the new kinds of analysis made possible by automation.