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A Foundation Model for Soccer

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arxiv 2407.14558 v1 pith:SV4CBCSO submitted 2024-07-18 cs.LG

Ethan Baron , Daniel Hocevar , Zach Salehe This is my paper · ORCID
classification cs.LG
keywords modelsocceractionsarchitecturefoundationtransformerableadditionally
verification ladder T0 review T1 audit T2 compute T3 formal
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We propose a foundation model for soccer, which is able to predict subsequent actions in a soccer match from a given input sequence of actions. As a proof of concept, we train a transformer architecture on three seasons of data from a professional soccer league. We quantitatively and qualitatively compare the performance of this transformer architecture to two baseline models: a Markov model and a multi-layer perceptron. Additionally, we discuss potential applications of our model. We provide an open-source implementation of our methods at https://github.com/danielhocevar/Foundation-Model-for-Soccer.

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Cited by 1 Pith paper

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  1. AIx4Soccer: A Unified Platform Architecture for Football Club Management and Structured Athlete Development

    cs.CY 2026-07 conditional novelty 4.0 of 10

    A conceptual multi-tenant football-club SaaS design embeds a PDI development cycle and a 75/25 certified video-analyst marketplace on a proposed event-sourced knowledge-graph substrate.

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