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

Ulf Brefeld; Jesse Davis; Jan Van Haaren; Albrecht Zimmermann

doi:10.1007/978-3-031-86692-0

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

Ulf Brefeld (Herausgeber*in)
, Jesse Davis (Herausgeber*in)
, Jan Van Haaren (Herausgeber*in)
, Albrecht Zimmermann (Herausgeber*in)

Publikation: Bücher und Anthologien › Konferenzbände und -dokumentationen › Forschung

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.

Originalsprache	Englisch

Erscheinungsort	Cham
Verlag	Springer Verlag
Seitenumfang	119
ISBN (Print)	978-3-031-86691-3
ISBN (elektronisch)	978-3-031-86692-0
DOIs	https://doi.org/10.1007/978-3-031-86692-0
Publikationsstatus	Erschienen - 2025
Veranstaltung	11th International Workshop on Machine Learning and Data Mining for Sports Analytics - MLSA 2024 - Vilnius, Litauen Dauer: 09.09.2024 → 09.09.2024 Konferenznummer: 11

Publikationsreihe

Name	Communications in Computer and Information Science
Verlag	Springer Science and Business Media Deutschland GmbH
Band	2460
ISSN (Druck)	1865-0929
ISSN (elektronisch)	1865-0937

Fachgebiete und Schlagwörter

Informatik

Zugriff auf Dokument

10.1007/978-3-031-86692-0

Dieses zitieren

@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",

}

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

Publikation: Bücher und Anthologien › Konferenzbände und -dokumentationen › Forschung

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 - https://www.scopus.com/pages/publications/105002007939

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 -

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

Abstract

Publikationsreihe

Fachgebiete und Schlagwörter

Zugriff auf Dokument

Fingerprint

Dieses zitieren