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A data mining approach to solve the goal scoring problem

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6 Author(s)
Oliveira, R. ; Center of Inf., Fed. Univ. of Pernambuco, Recife, Brazil ; Adeodato, P. ; Carvalho, A. ; Viegas, I.
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In soccer, scoring goals is a fundamental objective which depends on many conditions and constraints. Considering the RoboCup soccer 2D-simulator, this paper presents a data mining-based decision system to identify the best time and direction to kick the ball towards the goal to maximize the overall chances of scoring during a simulated soccer match. Following the CRISP-DM methodology, data for modeling were extracted from matches of major international tournaments (10691 kicks), knowledge about soccer was embedded via transformation of variables and a Multilayer Perceptron was used to estimate the scoring chance. Experimental performance assessment to compare this approach against previous LDA-based approach was conducted from 100 matches. Several statistical metrics were used to analyze the performance of the system and the results showed an increase of 7.7% in the number of kicks, producing an overall increase of 78% in the number of goals scored.

Published in:

Neural Networks, 2009. IJCNN 2009. International Joint Conference on

Date of Conference:

14-19 June 2009

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