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Machine Learning and Data Mining for Sports Analytics: 11th International Workshop, MLSA 2024, Vilnius, Lithuania, September 9, 2024, Revised Selected Papers

Research output: Books and anthologies › Conference proceedings › Research

Standard

Machine Learning and Data Mining for Sports Analytics: 11th International Workshop, MLSA 2024, Vilnius, Lithuania, September 9, 2024, Revised Selected Papers. / Brefeld, Ulf (Editor); Davis, Jesse (Editor); Van Haaren, Jan (Editor) et al.
Cham: Springer Verlag, 2025. 119 p. (Communications in Computer and Information Science; Vol. 2460).

Research output: Books and anthologies › Conference proceedings › Research

Harvard

Brefeld, U, Davis, J, Van Haaren, J & Zimmermann, A (eds) 2025, Machine Learning and Data Mining for Sports Analytics: 11th International Workshop, MLSA 2024, Vilnius, Lithuania, September 9, 2024, Revised Selected Papers. Communications in Computer and Information Science, vol. 2460, Springer Verlag, Cham. https://doi.org/10.1007/978-3-031-86692-0

APA

Brefeld, U., Davis, J., Van Haaren, J., & Zimmermann, A. (Eds.) (2025). Machine Learning and Data Mining for Sports Analytics: 11th International Workshop, MLSA 2024, Vilnius, Lithuania, September 9, 2024, Revised Selected Papers. (Communications in Computer and Information Science; Vol. 2460). Springer Verlag. https://doi.org/10.1007/978-3-031-86692-0

Vancouver

Brefeld U, (ed.), Davis J, (ed.), Van Haaren J, (ed.), Zimmermann A, (ed.). Machine Learning and Data Mining for Sports Analytics: 11th International Workshop, MLSA 2024, Vilnius, Lithuania, September 9, 2024, Revised Selected Papers. Cham: Springer Verlag, 2025. 119 p. (Communications in Computer and Information Science). doi: 10.1007/978-3-031-86692-0

Bibtex

@book{916cfedd7b264980a925420090c65dba,
title = "Machine Learning and Data Mining for Sports Analytics: 11th International Workshop, MLSA 2024, Vilnius, Lithuania, September 9, 2024, Revised Selected Papers",
abstract = "The proceedings contain 9 papers. The special focus in this conference is on Machine Learning and Data Mining for Sports Analytics. The topics include: Large Language Models on Race Commentary: Towards Granular Data in Cycling Analytics; GraphEIV: A Framework for Estimating the Expected Immediate Value in Basketball Using Graph Neural Networks; mathematical Models for Off-Ball Scoring Prediction in Basketball; an Analysis of the Influence of Game Context on Team Playing Style; Augmented Intelligence for FIFA Predictions; transformer-Based Framework for Versatile Analysis of Events Data in Soccer; Automated Detection of Shot Events in Game Phases Using GNSS Data from a Single Team.",
keywords = "Informatics",
editor = "Ulf Brefeld and Jesse Davis and {Van Haaren}, Jan and Albrecht Zimmermann",
year = "2025",
doi = "10.1007/978-3-031-86692-0",
language = "English",
isbn = "978-3-031-86691-3",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
address = "Germany",
note = "11th International Workshop on Machine Learning and Data Mining for Sports Analytics - MLSA 2024, MLSA 2024 ; Conference date: 09-09-2024 Through 09-09-2024",

}

RIS

TY - BOOK

T1 - Machine Learning and Data Mining for Sports Analytics

T2 - 11th International Workshop on Machine Learning and Data Mining for Sports Analytics - MLSA 2024

A2 - Brefeld, Ulf

A2 - Davis, Jesse

A2 - Van Haaren, Jan

A2 - Zimmermann, Albrecht

N1 - Conference code: 11

PY - 2025

Y1 - 2025

N2 - The proceedings contain 9 papers. The special focus in this conference is on Machine Learning and Data Mining for Sports Analytics. The topics include: Large Language Models on Race Commentary: Towards Granular Data in Cycling Analytics; GraphEIV: A Framework for Estimating the Expected Immediate Value in Basketball Using Graph Neural Networks; mathematical Models for Off-Ball Scoring Prediction in Basketball; an Analysis of the Influence of Game Context on Team Playing Style; Augmented Intelligence for FIFA Predictions; transformer-Based Framework for Versatile Analysis of Events Data in Soccer; Automated Detection of Shot Events in Game Phases Using GNSS Data from a Single Team.

AB - The proceedings contain 9 papers. The special focus in this conference is on Machine Learning and Data Mining for Sports Analytics. The topics include: Large Language Models on Race Commentary: Towards Granular Data in Cycling Analytics; GraphEIV: A Framework for Estimating the Expected Immediate Value in Basketball Using Graph Neural Networks; mathematical Models for Off-Ball Scoring Prediction in Basketball; an Analysis of the Influence of Game Context on Team Playing Style; Augmented Intelligence for FIFA Predictions; transformer-Based Framework for Versatile Analysis of Events Data in Soccer; Automated Detection of Shot Events in Game Phases Using GNSS Data from a Single Team.

KW - Informatics

UR - http://www.scopus.com/inward/record.url?scp=105002007939&partnerID=8YFLogxK

U2 - 10.1007/978-3-031-86692-0

DO - 10.1007/978-3-031-86692-0

M3 - Conference proceedings

SN - 978-3-031-86691-3

T3 - Communications in Computer and Information Science

BT - Machine Learning and Data Mining for Sports Analytics

PB - Springer Verlag

CY - Cham

Y2 - 9 September 2024 through 9 September 2024

ER -

Other publications by the same author(s)

Interactive sequential generative models for team sports

Fassmeyer, D., Cordes, M. & Brefeld, U., 02.2025, In: Machine Learning. 114, 2, 15 p., 38.

Research output: Journal contributions › Journal articles › Research › peer-review

Masked autoencoder for multiagent trajectories

Rudolph, Y. & Brefeld, U., 02.2025, In: Machine Learning. 114, 2, 18 p., 44.

Research output: Journal contributions › Journal articles › Research › peer-review

The promise and challenges of computer mouse trajectories in DMHIs – A feasibility study on pre-treatment dropout predictions

Zantvoort, K., Matthiesen, J., Bjurner, P., Bendix, M., Brefeld, U., Funk, B. & Kaldo, V., 06.2025, In: Internet Interventions. 40, 40, 7 p., 100828.

Research output: Journal contributions › Journal articles › Research › peer-review

Toward Learning Distributions of Distributions

Wohlstein, M. & Brefeld, U., 2025, In: Proceedings of Machine Learning Research. 265, p. 269-275 7 p.

Research output: Journal contributions › Conference article in journal › Research › peer-review

Studying properties of water data using manifold-aware anomaly detectors

Paulsen, T. & Brefeld, U., 23.04.2024, (Submitted) Design of Cyber-Secure Water Plants. Mathur, A., Zhou, J. & Raman, G. (eds.). MDPI AG, (Water).

Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review

DOI