How to Make Sense of Team Sport Data: From Acquisition to Data Modeling and Research Aspects
Abstract
:1. Introduction
2. Team Sport Data
2.1. Video and Sensor Data
2.1.1. Movement Data
2.1.2. Event Data
- Rule-induced events are events that occur as a result of the match rules. For example, if the ball passes the sideline of the soccer pitch, it has to be thrown in again by the opposite team.
- Events tagged with prosecution indicate that there was a foul behavior of the related player(s) which is penalized.
- Player interactions with ball is about events that happen when a player is touching the ball. Observable, almost every event that gets tagged falls under this category besides yellow and red cards, the end of a halftime and a substitution.
- Events that interrupt the match gets marked as gameplay interruption.
- If an event has a direct relation to scoring (e.g., a shot on the goal) we mark it as scoring related.
2.1.3. Descriptive (Statistical) Data/Derived Data
2.2. Context
News and Social Media
3. Abstracting the Data Space
4. Research Aspects
4.1. Definitions
4.1.1. Behavior
4.1.2. Movement Pattern
4.1.3. Group Behavior and Movement
4.2. Research Challenges
5. Methodology
5.1. Data Modeling
5.2. Data Mining
5.2.1. Clustering
5.2.2. Classification
5.2.3. Regression
5.2.4. Summarization
5.2.5. Change and Deviation Detection
5.2.6. Dependency Modeling
5.2.7. Summary
5.3. Information Visualization
5.4. Visual Analytics
6. Discussion and Conclusions
Author Contributions
Conflicts of Interest
References
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Statistic | Brazil | Germany |
---|---|---|
Goals | 1 | 7 |
Possession | 52% | 48% |
Shots | 18 | 14 |
Duel Quota | 51% | 49% |
Packing | 341 | 402 |
IMPECT | 53 | 84 |
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Stein, M.; Janetzko, H.; Seebacher, D.; Jäger, A.; Nagel, M.; Hölsch, J.; Kosub, S.; Schreck, T.; Keim, D.A.; Grossniklaus, M. How to Make Sense of Team Sport Data: From Acquisition to Data Modeling and Research Aspects. Data 2017, 2, 2. https://doi.org/10.3390/data2010002
Stein M, Janetzko H, Seebacher D, Jäger A, Nagel M, Hölsch J, Kosub S, Schreck T, Keim DA, Grossniklaus M. How to Make Sense of Team Sport Data: From Acquisition to Data Modeling and Research Aspects. Data. 2017; 2(1):2. https://doi.org/10.3390/data2010002
Chicago/Turabian StyleStein, Manuel, Halldór Janetzko, Daniel Seebacher, Alexander Jäger, Manuel Nagel, Jürgen Hölsch, Sven Kosub, Tobias Schreck, Daniel A. Keim, and Michael Grossniklaus. 2017. "How to Make Sense of Team Sport Data: From Acquisition to Data Modeling and Research Aspects" Data 2, no. 1: 2. https://doi.org/10.3390/data2010002