Effective and Efficient Sports Play Retrieval with Deep Representation Learning

author: Gao Cong, Nanyang Technological University
published: March 2, 2020,   recorded: August 2019,   views: 21

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With the proliferation of commercial tracking systems, sports data is being generated at an unprecedented speed and the interest in sports play retrieval has grown dramatically as well. However, it is challenging to design an effective, efficient and robust similarity measure for sports play retrieval. To this end, we propose a deep learning approach to learn the representations of sports plays, called play2vec, which is robust against noise and takes only linear time to compute the similarity between two sports plays. We conduct experiments on real-world soccer match data, and the results show that our solution performs more effectively and efficiently compared with the state-of-the-art methods.

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Reviews and comments:

Comment1 Maximilian Hohenzollern , February 2, 2023 at 3:15 p.m.:

I can say that the sport industry is gaining popularity in general, and nowadays, many people also turn to sport betting to improve their experience from sport matches. I'm not the exception, and I can say that with platforms like https://www.mightytips.com/bookmakers... , it's not a problem for me to find reliable platforms and betting tips for that, so I don't see anything wrong with it.

Comment2 Emory Scott, February 16, 2023 at 12:46 p.m.:

Yes it's true. Another thing is, sports betting is quite famous now and its my way of making money online. How nice right?

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