Predicting Competitive Pokémon VGC Leads Using Latent Semantic Analysis

Summary

Bruno Luvizotto Carli Universidade Federal do Paraná, Curitiba, PR, Brazil. brunolcarli (at) gmail (dot) com Download PDF Competitive Pokémon battles often hinge on the initial selection of Pokémon leads. Anticipating an opponent’s lead choice offers a tactical edge, particularly in high-stakes matches. In this paper, I explore the use of Latent Semantic Analysis (LSA), a natural language processing algorithm, applied to over 5,000 Pokémon Showdown battle logs, to predict likely lead pairs based on team compositions. Evaluated against the Top 8 bracket of the North America International Championships (NAIC) 2025, the model achieved promising results, showcasing the potential of unsupervised learning in strategic game prediction. POKÉMON VGC The Video Game Championships (VGC) are the official competitive format organized by The Pokémon International and Play! Pokémon organizations. These events culminate in the annual Pokémon World Championships, which bring together top players from around the globe in various formats including the video games, the trading card game, and select spin-off titles. In VGC, battles are conducted in a Double Battle format where each player brings six Pokémon, but selects only four to battle. Two are sent out as leads, and two remain in the back for switching. The game begins with a team preview phase, during which players see their opponent’s six Pokémon and their move sets and held items (Bulbapedia, 2025). LATENT SEMANTIC ANALYSIS Latent Semantic Analysis (LSA) is a technique from natural language processing used to discover relationships between documents and terms by mapping them into a lower-dimensional space via Singular Value Decomposition (SVD). In this transformed space, documents can be compared based on the semantic similarity of their content. Originally developed for text retrieval and indexing, LSA (or LSI when used in information retrieval contexts) works by converting documents into a term-document matrix and reducing it t...