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Machine Learning and Data Mining for Sports Analytics

5th International Workshop, MLSA 2018, Co-located with ECML/PKDD 2018, Dublin, Ireland, September 10, 2018, Proceedings

  • Conference proceedings
  • © 2019

Overview

Editors:
  1. Ulf Brefeld

    1. Leuphana University, Lüneburg, Germany

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  2. Jesse Davis

    1. Katholieke Universiteit Leuven, Heverlee, Belgium

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  3. Jan Van Haaren

    1. SciSports, Enschede, The Netherlands

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  4. Albrecht Zimmermann

    1. Université de Caen Normandie, Caen, France

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11330)

Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)

Included in the following conference series:

Conference proceedings info: MLSA 2018.

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Table of contents (15 papers)

  1. Front Matter

    Pages i-x
    Download chapter PDF

  2. Soccer

    1. Front Matter

      Pages 1-1
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    2. Measuring Football Players’ On-the-Ball Contributions from Passes During Games

      • Lotte Bransen, Jan Van Haaren
      Pages 3-15

    3. Forecasting the FIFA World Cup – Combining Result- and Goal-Based Team Ability Parameters

      • Pieter Robberechts, Jesse Davis
      Pages 16-30

    4. Distinguishing Between Roles of Football Players in Play-by-Play Match Event Data

      • Bart Aalbers, Jan Van Haaren
      Pages 31-41

    5. Player Valuation in European Football

      • Edward Nsolo, Patrick Lambrix, Niklas Carlsson
      Pages 42-54

    6. Ranking the Teams in European Football Leagues with Agony

      • Stefan Neumann, Julian Ritter, Kailash Budhathoki
      Pages 55-66

  3. US Team Sports

    1. Front Matter

      Pages 67-67
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    2. Interpreting Deep Sports Analytics: Valuing Actions and Players in the NHL

      • Guiliang Liu, Wang Zhu, Oliver Schulte
      Pages 69-81

    3. Player Pairs Valuation in Ice Hockey

      • Dennis Ljung, Niklas Carlsson, Patrick Lambrix
      Pages 82-92

    4. Model Trees for Identifying Exceptional Players in the NHL and NBA Drafts

      • Yejia Liu, Oliver Schulte, Chao Li
      Pages 93-105

    5. Evaluating NFL Plays: Expected Points Adjusted for Schedule

      • Konstantinos Pelechrinis, Wayne Winston, Jeff Sagarin, Vic Cabot
      Pages 106-117

  4. Individual Sports

    1. Front Matter

      Pages 119-119
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    2. Real-Time Power Performance Prediction in Tour de France

      • Yasuyuki Kataoka, Peter Gray
      Pages 121-130

    3. Automatic Classification of Strike Techniques Using Limb Trajectory Data

      • Kasper M. W. Soekarjo, Dominic Orth, Elke Warmerdam, John van der Kamp
      Pages 131-141

  5. Challenge Papers

    1. Front Matter

      Pages 143-143
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    2. Predicting Pass Receiver in Football Using Distance Based Features

      • Yann Dauxais, Clément Gautrais
      Pages 145-151

    3. Football Pass Prediction Using Player Locations

      • Philippe Fournier-Viger, Tianbiao Liu, Jerry Chun-Wei Lin
      Pages 152-158

    4. Deep Learning from Spatial Relations for Soccer Pass Prediction

      • Ondřej Hubáček, Gustav Šourek, Filip Železný
      Pages 159-166

    5. Predicting the Receivers of Football Passes

      • Heng Li, Zhiying Zhang
      Pages 167-177
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  1. Machine Learning and Data Mining for Sports Analytics

Keywords

About this book

This book constitutes the refereed post-conference proceedings of the 5th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2018, colocated with ECML/PKDD 2018, in Dublin, Ireland, in September 2018.

The 12 full papers presented together with 4 challenge papers were carefully reviewed and selected from 24 submissions. The papers present a variety of topics, covering the team sports American football, basketball, ice hockey, and soccer, as well as the individual sports cycling and martial arts. In addition, four challenge papers are included, reporting on how to predict pass receivers in soccer. 

Editors and Affiliations

  • Leuphana University, Lüneburg, Germany

    Ulf Brefeld

  • Katholieke Universiteit Leuven, Heverlee, Belgium

    Jesse Davis

  • SciSports, Enschede, The Netherlands

    Jan Van Haaren

  • Université de Caen Normandie, Caen, France

    Albrecht Zimmermann

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