IEEE Transactions on Knowledge and Data Engineering

IEEE Transactions on Knowledge and Data Engineering (TKDE) is an archival journal published monthly designed to inform researchers, developers, managers, strategic planners, users, and others interested in state-of-the-art and state-of-the-practice activities in the knowledge and data engineering area. Read the full scope of TKDE

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From the November 2016 issue

Forecasting the Next Shot Location in Tennis Using Fine-Grained Spatiotemporal Tracking Data

By Xinyu Wei, Patrick Lucey, Stuart Morgan, and Sridha Sridharan

Featured ArticleIn professional sport, an enormous amount of fine-grain performance data can be generated at near millisecond intervals in the form of vision-based tracking data. One of the first sports to embrace this technology has been tennis, where Hawk-Eye technology has been used to both aid umpiring decisions, and to visualize shot trajectories for broadcast purposes. Despite the high-level of accuracy of the tracking systems and the sheer volume of spatiotemporal data they generate, the use of this data for player performance analysis and prediction has been lacking. In this research, we use ball and player tracking data from "Hawk-Eye" to discover unique player styles and predict within-point events. We move beyond current analysis that only incorporates coarse match statistics (i.e., serves, winners, number of shots, and volleys) and use spatial and temporal information which better characterizes the tactics and tendencies of each player. Using a probabilistic graphical model, we are able to model player behaviors which enables us to: 1) find the factors such as location and speed of the incoming shot which are most conducive to a player hitting a winner (i.e., "sweet-spot") or cause an error, and 2) do "live in-point" prediction - based on the shots being played during a rally we estimate the probability of the outcome (e.g., winner, continuation, or error) and the location of the next shot. As player behavior depends on the opponent, we use model adaptation to enhance our prediction. We show the utility of our approach by analyzing the play of Djokovic, Nadal, and Federer at the 2012 Australian Tennis Open.

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Editorials and Announcements


  • We are pleased to announce that Xuemin Lin, a Scientia Professor in the School of Computer Science and Engineering at the University of New South Wales, Australia, has been named the new Editor-in-Chief of the IEEE Transactions on Knowledge and Data Engineering starting in 2017.

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  • TKDE celebrates its 25th Anniversary. Editor-in-Chief Jian Pei says, "We are celebrating the 25th Anniversary of TKDE. Since its first issue in March 1989, TKDE has published 2,981 articles, and another 220 articles in the early access portal. With 898 submissions and 79 accepted articles in 2012, TKDE is now the premier journal in the broad and general fields of data management, data mining, and knowledge engineering. We thank all the authors, reviewers, and readers for their continuing support to TKDE. As always, we are eager to hear your ideas and suggestions, and will do our best to meet your expectations. With all your passions, contributions, and supports, TKDE is embracing the new era of big data and big data analytics. Happy birthday to TKDE!"


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