Call for Papers

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The Machine Learning and Data Mining for Sports Analytics workshop at ECML/PKDD 2013 solicits papers on Machine Learning, Data Mining, and other related approaches for sports analytics. The application of analytic techniques is rapidly gaining traction in both professional and amateur sports circles. The majority of techniques used in the field so far are statistical. While there has been some interest in the Machine Learning and Data Mining community, it has been somewhat muted so far. The goal of this workshop is two-fold. The first is to raise awareness about this emerging application area. The second is to bring members of the sport analytics community into contact with typical ECML/PKDD contributors, and to highlight what the community has done and can do in the field.

To this end, we invite submissions on all topics related to the automated analysis of sports data. Possible topics include:

We are open to all sports, including, but not limited to, football/soccer, basketball, baseball, American football, etc. Papers can report on empirical findings, novel metrics, new problems, novel algorithms, etc.

Authors can submit long papers or extended abstracts. Long papers should report on novel, unpublished work that might not be quite mature enough for a conference or journal submission. Papers can be a maximum of 8 pages excluding references. Extended abstracts can be a maximum of 2 pages including references and should summarize recent publications that fit the theme of the workshop. Authors should submit a PDF version in Springer LNCS style through this website.

Each paper will be reviewed by at least two members of the Program Committee on the basis of technical quality, relevance, significance, and clarity. Submitting a paper to the workshop means that if the paper is accepted, at least one author should attend the workshop to present the paper.

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