2013 for the individual papers
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Machine Learning and Data Mining for Sports Analytics
Proceedings of the 1st Workshop on Machine Learning and Data Mining for Sports Analytics
co-located with 2013 European Conference on Machine Learning and Principles and Practice of Knowledge
Discovery in Databases (ECML PKDD 2013)
Prague, Czech Republic, September 27th, 2013.
Table of Contents
- Why Do Sports Officials Dropout?1-10
Fabrice Dosseville, François Rioult, Sylvain Laborde
- Strategic Patterns Discovery in RTS-games for E-Sport with Sequential Pattern Mining11-20
Guillaume Bosc, Mehdi Kaytoue, Chedy Raïssi, Jean-François Boulicaut
- Maps for Reasoning in Ultimate21-27
Jeremy Weiss, Sean Childers
- Predicting the NFL using Twitter28-38
Shiladitya Sinha, Chris Dyer, Kevin Gimpel, Noah A. Smith
- Use of Performance Metrics to Forecast Success in the National Hockey League39-48
Joshua Weissbock, Herna Viktor, Diana Inkpen
- Finding Similar Movements in Positional Data Streams49-57
Jens Haase, Ulf Brefeld
- Comparison of Machine Learning Methods for Predicting the Recovery Time of Professional
Football Players After an Undiagnosed Injury58-68
- Predicting NCAAB Match Outcomes Using ML Techniques – Some Results and Lessons Learned69-78
Albrecht Zimmemrann, Sruthi Moorthy, Zifan Shi
- Key Point Selection and Clustering of Swimmer Coordination Through Sparse Fisher-EM79-88
John Komar, Romain Herault, Ludovic Seifert
We offer a BibTeX file for citing papers of this workshop from LaTeX.
2017-10-30: submitted by Albrecht Zimmermann, metadata incl. bibliographic data published under Creative Commons CC0
2017-10-30: published on CEUR-WS.org