Skip to main content
SpringerLink
Log in

Machine Learning and Data Mining for Sports Analytics

7th International Workshop, MLSA 2020, Co-located with ECML/PKDD 2020, Ghent, Belgium, September 14–18, 2020, Proceedings

  • Conference proceedings
  • © 2020

Overview

Editors:
  1. Ulf Brefeld

    1. Leuphana University of Lüneburg, Lüneburg, Germany

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  2. Jesse Davis

    1. Katholieke Universiteit Leuven, Leuven, Belgium

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  3. Jan Van Haaren

    1. SciSports, Amersfoort, The Netherlands

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  4. Albrecht Zimmermann

    1. Université de Caen Normandie, Caen, France

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Communications in Computer and Information Science (CCIS, volume 1324)

Included in the following conference series:

Conference proceedings info: MLSA 2020.

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (11 papers)

  1. Front Matter

    Pages i-x
    Download chapter PDF

  2. Football

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Routine Inspection: A Playbook for Corner Kicks

      • Laurie Shaw, Sudarshan Gopaladesikan
      Pages 3-16

    3. How Data Availability Affects the Ability to Learn Good xG Models

      • Pieter Robberechts, Jesse Davis
      Pages 17-27

    4. Low-Cost Optical Tracking of Soccer Players

      • Gabor Csanalosi, Gergely Dobreff, Alija Pasic, Marton Molnar, László Toka
      Pages 28-39

    5. An Autoencoder Based Approach to Simulate Sports Games

      • Ashwin Vaswani, Rijul Ganguly, Het Shah, Sharan Ranjit S, Shrey Pandit, Samruddhi Bothara
      Pages 40-50

    6. Physical Performance Optimization in Football

      • Gergely Dobreff, Péter Revisnyei, Gábor Schuth, György Szigeti, László Toka, Alija Pašić
      Pages 51-61

    7. Predicting Player Trajectories in Shot Situations in Soccer

      • Per Lindström, Ludwig Jacobsson, Niklas Carlsson, Patrick Lambrix
      Pages 62-75

  3. Other Team Sports

    1. Front Matter

      Pages 77-77
      Download chapter PDF

    2. Stats Aren’t Everything: Learning Strengths and Weaknesses of Cricket Players

      • Swarup Ranjan Behera, Vijaya V. Saradhi
      Pages 79-88

    3. Prediction of Tiers in the Ranking of Ice Hockey Players

      • Timmy Lehmus Persson, Haris Kozlica, Niklas Carlsson, Patrick Lambrix
      Pages 89-100

  4. Individual Sports

    1. Front Matter

      Pages 101-101
      Download chapter PDF

    2. A Machine Learning Approach for Road Cycling Race Performance Prediction

      • Leonid Kholkine, Tom De Schepper, Tim Verdonck, Steven Latré
      Pages 103-112

    3. Mining Marathon Training Data to Generate Useful User Profiles

      • Jakim Berndsen, Barry Smyth, Aonghus Lawlor
      Pages 113-125

    4. Learning from Partially Labeled Sequences for Behavioral Signal Annotation

      • Anna Aniszewska-Stępień, Romain Hérault, Guillaume Hacques, Ludovic Seifert, Gilles Gasso
      Pages 126-139

  5. Back Matter

    Pages 141-141
    Download chapter PDF
Back to top

Other volumes

  1. Machine Learning and Data Mining for Sports Analytics

Keywords

About this book

This book constitutes the refereed post-conference proceedings of the 7th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2020, colocated with ECML/PKDD 2020, in Ghent, Belgium, in September 2020. Due to the COVID-19 pandemic the conference was held online. 

The 11 papers presented were carefully reviewed and selected from 22 submissions. The papers present a variety of topics within the area of sports analytics, including tactical analysis, outcome predictions, data acquisition, performance optimization, and player evaluation.


Editors and Affiliations

  • Leuphana University of Lüneburg, Lüneburg, Germany

    Ulf Brefeld

  • Katholieke Universiteit Leuven, Leuven, Belgium

    Jesse Davis

  • SciSports, Amersfoort, The Netherlands

    Jan Van Haaren

  • Université de Caen Normandie, Caen, France

    Albrecht Zimmermann

Bibliographic Information

Publish with us

Policies and ethics

Back to top

Search

Navigation