BPCoach: Exploring Hero Drafting in Professional MOBA Tournaments via Visual Analytics

Author:

Liu Shiyi1ORCID,Ma Ruofei1ORCID,Zhao Chuyi2ORCID,Li Zhenbang1ORCID,Xiao Jianpeng3ORCID,Li Quan1ORCID

Affiliation:

1. School of Information Science and Technology, ShanghaiTech University, Shanghai, China

2. Tufts University, Medford, MA, USA

3. Guangzhou Qucheng Culture Media Co., Ltd, Guangzhou, China

Abstract

Hero drafting for multiplayer online arena (MOBA) games is crucial because drafting directly affects the outcome of a match. Both sides take turns to "ban"/"pick" a hero from a roster of approximately 100 heroes to assemble their drafting. In professional tournaments, the process becomes more complex as teams are not allowed to pick heroes used in the previous rounds with the "best-of-N" rule. Additionally, human factors including the team's familiarity with drafting and play styles are overlooked by previous studies. Meanwhile, the huge impact of patch iteration on drafting strengths in the professional tournament is of concern. To this end, we propose a visual analytics system, BPCoach, to facilitate hero drafting planning by comparing various drafting through recommendations and predictions and distilling relevant human and in-game factors. Two case studies, expert feedback, and a user study suggest that BPCoach helps determine hero drafting in a rounded and efficient manner.

Funder

National Natural Science Foundation of China

Publisher

Association for Computing Machinery (ACM)

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