Automatically Discovering Offensive Patterns in Soccer Match Data

In recent years, many professional sports clubs have adopted camera-based tracking technology that captures the location of both the players and the ball at a high frequency. Nevertheless, the valuable information that is hidden in these performance data is rarely used in their decision-making proce...

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Bibliographic Details
Published inAdvances in Intelligent Data Analysis XIV Vol. 9385; pp. 286 - 297
Main Authors Van Haaren, Jan, Dzyuba, Vladimir, Hannosset, Siebe, Davis, Jesse
Format Book Chapter
LanguageEnglish
Published Switzerland Springer International Publishing AG 2015
Springer International Publishing
SeriesLecture Notes in Computer Science
Subjects
Artificial intelligence
Image processing
Pattern recognition
Spatial data
Sports analytics
Strategy detection
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Summary:In recent years, many professional sports clubs have adopted camera-based tracking technology that captures the location of both the players and the ball at a high frequency. Nevertheless, the valuable information that is hidden in these performance data is rarely used in their decision-making process. What is missing are the computational methods to analyze these data in great depth. This paper addresses the task of automatically discovering patterns in offensive strategies in professional soccer matches. To address this task, we propose an inductive logic programming approach that can easily deal with the relational structure of the data. An experimental study shows the utility of our approach.
ISBN:3319244647
9783319244648
ISSN:0302-9743
1611-3349
DOI:10.1007/978-3-319-24465-5_25