Performance analysis is a well-established discipline in sports science, supported by decades of research. Comparatively, performance analysis in electronic sports (esports) is limited. Therefore, there is an opportunity to accelerate performance outcomes in esports by applying methods grounded in sports science. This study adopted a coach-centred approach to model performance at the 2018 League of Legends World Championship. Three expert coaches rated the proposed relationship between 43 variables and match outcomes in professional League of Legends competition using a Likert scale (1–10). The Likert scale was anchored with ‘no relationship’ at 1 and ‘very strong relationship’ at 10. The coaches’ median ratings were calculated for each variable. Variables with a median score ≥6 were retained for analyses. A total of 14 variables were collected from the 2018 League of Legends World Championship (n = 119) matches via video annotations and match histories. Generalized Linear Mixed Effects Models with binomial logit link function were implemented with respect to the Blue Side winning or losing the match, and individual teams were specified as random effects. Variables were screened for multicollinearity before using a step-up approach. The best model of performance included Tower Percentage (p = 0.006) and Number of Inhibitors (p = 0.029). This model achieved classification accuracy of 95.8%. While Tower Percentage and Number of Inhibitors contributed to winning or losing, further research is required to determine effective strategies to improve these variables, to understand the relevance of these variables across the complete time-series of the match, and to determine whether performance indicators remain stable across game updates.

中文翻译：

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电竞中的表现分析：2018年英雄联盟世界锦标赛的建模表现

表现分析是体育科学中一门成熟的学科，得到了数十年的研究支持。相比之下，电子竞技（esports）的表现分析是有限的。因此，有机会通过应用以体育科学为基础的方法来加速电子竞技的表现。本研究采用以教练为中心的方法来模拟 2018 年英雄联盟世界锦标赛的表现。三位专家教练使用李克特量表 (1-10) 对职业英雄联盟比赛中 43 个变量与比赛结果之间的拟议关系进行了评估。李克特量表以“没有关系”为 1 分，“关系非常密切”为 10 分。教练员的评分中位数是针对每个变量计算的。保留中值得分≥6 的变量进行分析。通过视频注释和比赛历史从 2018 年英雄联盟世界锦标赛（n = 119）比赛中收集了总共 14 个变量。针对蓝方输赢实施具有二项式 logit 链接函数的广义线性混合效应模型，并将单个团队指定为随机效应。在使用递增方法之前，对变量进行了多重共线性筛选。最佳性能模型包括塔百分比 (p = 0.006) 和抑制剂数量 (p = 0.029)。该模型实现了 95.8% 的分类准确率。虽然塔百分比和抑制剂数量对输赢做出了贡献，但需要进一步研究以确定改善这些变量的有效策略，