2015 for the individual papers
by the papers' authors. Copying permitted for private and academic purposes.
This volume is published and copyrighted by its editors.
Machine Learning and Data Mining for Sports Analytics
Proceedings of the 2nd Workshop on Machine Learning and Data Mining for Sports Analytics
co-located with 2015 European Conference on Machine Learning and Principles and Practice of Knowledge
Discovery in Databases (ECML PKDD 2015)
Porto, Portugal, September 11th, 2015.
Table of Contents
- Predictive Efficacy of a New Association Football League Format in Polish Ekstraklasa1-9
Jan Lasek, Marek Gagolewski
- Graph-based Approaches for Analyzing Team Interaction on the Example of Soccer10-17
Markus Brandt, Ulf Brefeld
- Valuation of Climbing Activities Using Multi-Scale Stochastic Neighbour Embedding18-27
Romain Herault, Jérémie Boulanger, Ludovic Seifert, John Aldo Lee
- Identifying Avatar Aliases in StarCraft 228-35
Olivier Cavadenti, Victor Codocedo, Mehdi Kaytoue, Jean-François Boulicaut
- What Can Hawk-Eye Data Reveal about Serve Performance in Tennis?36-45
François Rioult, Sami Mecheri, Bruno Mantel, François Kauffmann, Nicolas Benguigui
- Network-based Measures for Predicting the Outcomes of Football Games46-54
Paolo Cintia, Salvatore Rinzivillo, Luca Pappalardo
- Learning Stochastic Models for Basketball Substitutions from Play-by-Play Data55-64
Harish S. Bhat, Li-Hsuan Huang, Sebastian Rodriguez
- Exploring Chance in NCAA Basketball65-76
- What is the Value of an Action in Ice Hockey? Q-Learning for the NHL77-86
Oliver Schulte, Zeyu Zhao, Kurt Routley
- Football Player's Performance and Market Value87-95
Miao He, Ricardo Cachucho, Arno Knobbe
- Estimating the Maximal Speed of Soccer Players on Scale96-103
Laszlo Gyarmati, Mohamed Hefeeda
We offer a BibTeX file for citing papers of this workshop from LaTeX.
2017-09-26: submitted by Albrecht Zimmermann, metadata incl. bibliographic data published under Creative Commons CC0
2017-09-27: published on CEUR-WS.org