Galán Sales, Francisco JavierLinares Barrera, María LourdesReina Jiménez, PabloRodríguez López, AnaJiménez Navarro, Manuel Jesús2025-03-192025-03-192024Galán Sales, F.J., Linares Barrera, M.L.,...,Jiménez Navarro, M.J. (2024). Toward Explaining Competitive Success in League of Legends: A Machine Learning Analysis. En Advances In Artificial Intelligence. Volum. 14640. Lecture Notes in Computer Science (pp. 184-193). Springer Nature.https://hdl.handle.net/11441/170556Machine learning techniques have recently transformed the way we analyze competitive games. However, accurately detecting the impact of different insights on match outcomes remains a challenge. This study focuses on League of Legends, a popular multiplayer online battle arena game known for its strategic depth and teamwork requirements. We aim to understand how various actions and strategies influence match results, using a dataset from professional tournaments. Factors like “building damage”, “total gold”, and “assists” are analyzed as predictors. We employ tree-based and linear models to predict outcomes, supplemented by SHapley Additive exPlanations for explaining both local and global model outcomes. Our article offers a generalizable match analysis approach, compares explainable methods, and delves into key determinants of victory. The results, showcasing a remarkable 98.8% accuracy with the top-performing model, provide strong support for our conclusions, underlining their reliability.application/pdf10 p.engAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Performance analysisEsportsFeature importanceExplainable machine learninginfo:eu-repo/semantics/bookPartinfo:eu-repo/semantics/openAccesshttps://doi.org/10.1007/978-3-031-62799-6_19