mlsanityData to 7 Oct 2026

A Foundation Model for Soccer

arXiv 2407.14558 ↗First posted 18 Jul 2024cs.LGcited by 3

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Abstract (arXiv)

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.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 8 of its 12 references that are in the map. First posted on arXiv 18 Jul 2024.

Builds on

8 of 12 references.

References · 8

  1. 2017Attention Is All You Needcited by 59,932
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  3. 2020Scaling Laws for Neural Language Modelscited by 6,411
  4. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,346
  5. 2018UMAP: Uniform Manifold Approximation and Projection for Dimension Reductioncited by 2,841
  6. 2018Actions Speak Louder Than Goals: Valuing Player Actions in Soccercited by 90
  7. 2020A framework for the fine-grained evaluation of the instantaneous expected value of soccer possessionscited by 24
  8. 2024Forecasting Events in Soccer Matches Through Languagecited by 5

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 1.

3 papers.

  1. 2025OpenSTARLab: Open Approach for Spatio-Temporal Agent Data Analysis in Soccercited by 7
  2. 2025Beyond Pixels: Leveraging the Language of Soccer to Improve Spatio-Temporal Action Detection in Broadcast Videoscited by 5
  3. 2026Modeling Matches as Language: A Generative Transformer Approach for Counterfactual Player Valuation in Footballcited by 0