First AAAI Workshop on A.I. in Team Sports

Sports is a domain that has grown significantly over the last 20 years to become a key driver of many economies. According to a recent report (https://urlzs.com/tsvbY), the estimated size of the global sports industry is $1.3 trillion, and has an audience of over 1 billion. As the market has grown so has the amount of data that is collected. This means that there are a number of challenging problems in sports to predict and optimise performance but, so far, such problems have largely been dealt with by domain experts (e.g., coaches, managers, scouts, and sports health experts) with basic analytics.

The growing availability of datasets in sports presents a unique opportunity for the artificial intelligence (AI) and machine learning (ML) communities to develop, validate, and apply new techniques in the real world. In team sports, real-world data is available over long periods of time, about the same individuals and teams, in a variety of environmental contexts, thereby creating a unique live test-bed for AI and ML techniques. While research in AI for team sports has grown over the last 20 years, it is as yet unclear how they relate to each other or build upon each other as they tend to either focus on specific types of team sports or specific prediction and optimisation problems that are but one part of the whole field. Hence, this workshop will help fuel discussions in the area and bring together the AI and sports analytics communities to encourage new research that will benefit both communities and industry.

Topics
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We invite high-quality paper submissions on topics including, but not limited to, the following:

– Match Outcome Prediction.
– Tactical Decision Making, Player Acquisition and Performance Prediction.
– Fantasy Sports Games.
– Injury Prediction and Prevention.
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We are keen to see applications of AI techniques such as:

– Machine Learning and Deep Learning
– Computer Vision
– Optimisation
– Multi-Agent Systems.
– Human-Machine Interaction

Format:

The workshop will be a full-day and will include a mix of invited talk(s) and peer-reviewed papers (talks and poster sessions). It will conclude with a panel discussion.

Submissions
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Two forms of submissions are invited:
– short position papers (2-4 pages) describing initial work or real-world results of applications of AI.
– full technical papers (6-8 pages) describing original research. Note that there will be no formal publications of the workshop proceedings and hence we will accept resubmissions from other venues.

Manuscripts must be submitted as PDF files via EasyChair online submission system: (https://easychair.org/conferences/?conf=aits20).

Please keep your paper format according to AAAI Formatting Instructions (two-column format).

Papers will be peer-reviewed by the Program Committee (2-3 reviewers per paper).

Organising Committee
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Ryan Beal, University of Southampton, UK
Prof. Sarvapali Ramchurn, University of Southampton, UK
Dr. Georgios Chalkiadakis, Technical University of Crete, Greece
Prof. Onn Shehory, Bar Ilan University, Israel
Prof. Tim Swartz, Simon Fraser University, Canada