Communication Dans Un Congrès Année : 2026

Formal Concept Analysis as a Biclustering Approach for Champion Drafting in eSports

Résumé

Data-driven methods are increasingly used to support strategic decision-making in competitive esports, yet champion drafting in League of Legends still relies largely on empirical knowledge and subjective judgment. This work proposes a Formal Concept Analysis (FCA) framework to support champion selection at the start of a match and to identify suitable replacements when a desired pick is unavailable due to bans or draft constraints. Champion characteristics are encoded in a binary formal context derived from aggregated in-game statistics describing offensive, defensive, and utility aspects of gameplay. Formal concepts extracted from this context define groups of champions that share similar strategic profiles, and the resulting concept lattice enables structured exploration of champion similarities as well as generalization and specialization of strategic intents. For initial picks, the framework recommends champions whose attribute sets match a targeted strategic profile, while in replacement scenarios it selects alternatives from the same or closely related concepts, thereby preserving team-level strategic coherence. Experiments on real League of Legends data show that the FCA-based recommendations are interpretable and consistent, underscoring the potential of FCA as an effective decision-support tool for draft-phase strategy in esports.

Dates et versions

hal-05579678 , version 1 (03-04-2026)

Identifiants

Citer

Anthony Feudjio, Malika Charrad, Mondher Maddouri. Formal Concept Analysis as a Biclustering Approach for Champion Drafting in eSports. ICAART'2026 -Special Session on eSports Performance, Artificial Intelligence and Knowledge in Esports - Trends & Applications, Mar 2026, Marbella, Spain. pp.963-974, ⟨10.5220/0014738700004052⟩. ⟨hal-05579678⟩
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