Trajectory Analysis for Soccer Players

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Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06)

Hong Kong, China

December 18-December 22

ISBN: 0-7695-2702-7

	ASCII Text	x
	Chan-Hyun Kang, Jung-Rae Hwang, Ki-Joune Li, "Trajectory Analysis for Soccer Players," Data Mining Workshops, International Conference on, pp. 377-381, Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06), 2006.

	BibTex	x
	@article{ 10.1109/ICDMW.2006.160, author = {Chan-Hyun Kang and Jung-Rae Hwang and Ki-Joune Li}, title = {Trajectory Analysis for Soccer Players}, journal ={Data Mining Workshops, International Conference on}, volume = {0}, year = {2006}, isbn = {0-7695-2702-7}, pages = {377-381}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICDMW.2006.160}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Data Mining Workshops, International Conference on TI - Trajectory Analysis for Soccer Players SN - 0-7695-2702-7 SP377 EP381 A1 - Chan-Hyun Kang, A1 - Jung-Rae Hwang, A1 - Ki-Joune Li, PY - 2006 KW - null VL - 0 JA - Data Mining Workshops, International Conference on ER -

Chan-Hyun Kang, Pusan National University, South Korea

Jung-Rae Hwang, Pusan National University, South Korea

Ki-Joune Li, Pusan National University, South Korea

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDMW.2006.160

In order to make good strategies, soccer coaches analyze the archives of matches, which can be effectively considered as a set of trajectories. We can extract several useful information by analyzing the trajectories of moving objects, which consist of 22 players and a ball. Since each moving object interacts with others and produces a trajectory, its trajectory has a certain number of relationships with others, which are a basic type of information to make soccer strategies. In this paper, we propose a model to quantitatively express the performance of soccer players. This model is based on the relationships between trajectories of 22 players and a ball and allows to evaluate the performance of several players in quantitative way.

Citation:

Chan-Hyun Kang, Jung-Rae Hwang, Ki-Joune Li, "Trajectory Analysis for Soccer Players," icdmw, pp.377-381, Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06), 2006

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