Publication

Using Deep Convolutional Neural Networks to Predict Goal-Scoring Opportunities in Soccer

Wagenaar, M., Okafor, E., Frencken, W. & Wiering, M., 2017, International Conference on Pattern Recognition Applications and Methods (ICPRAM). 8 p.

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Deep learning approaches have successfully been applied to several image recognition tasks, such as face, object, animal and plant classification. However, almost no research has examined on how to use the field of machine learning to predict goal-scoring opportunities in soccer from position data. In this paper, we propose the use of deep convolutional neural networks (DCNNs) for the above stated problem. This aim is actualized using the following steps: 1) development of novel algorithms for finding goal-scoring opportunities and ball possession which are used to obtain positive and negative examples. The dataset consists of position data from 29 matches played by a German Bundlesliga team. 2) These examples are used to create original and enhanced images (which contain object trails of soccer positions) with a resolution size of $256 \times 256$ pixels. 3) Both the original and enhanced images are fed independently as input to two DCNN methods: instances of both GoogLeNet and a 3-layered CNN architecture. A K-nearest neighbor classifier was trained and evaluated on ball positions as a baseline experiment. The results show that the GoogLeNet architecture outperforms all other methods with an accuracy of 67.1%.
Original languageEnglish
Title of host publicationInternational Conference on Pattern Recognition Applications and Methods (ICPRAM)
Number of pages8
Publication statusPublished - 2017
Event6th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2017) - Porto, Portugal
Duration: 24-Feb-201726-Feb-2017

Conference

Conference6th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2017)
CountryPortugal
CityPorto
Period24/02/201726/02/2017

Event

6th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2017)

24/02/201726/02/2017

Porto, Portugal

Event: Conference

    Keywords

  • Deep Learning, Sport Analytics, Machine Learning, Computer Vision

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