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.

翻译：多人联机竞技（MOBA）游戏的英雄扳选环节至关重要，因为该过程直接影响比赛结果。双方队伍需轮流从约100名英雄的阵容中选择"禁用"/"选取"英雄，以构建各自的阵容体系。在职业赛事中，由于"全局BP"规则禁止队伍重复使用前几轮已选英雄，这一过程变得更加复杂。此外，先前研究忽视了团队对扳选的熟悉程度及战术风格等人为因素，而补丁迭代对职业赛事中扳选强度产生的巨大影响也值得关注。为此，我们提出视觉分析系统BPCoach，通过推荐与预测实现多方案对比，并提炼相关人为因素与游戏内要素，辅助英雄扳选决策。两项案例研究、专家反馈及用户研究表明，BPCoach能够全面高效地辅助确定英雄扳选方案。