Effective and Efficient Sports Play Retrieval with Deep Representation Learning

author: Gao Cong, Nanyang Technological University
published: March 2, 2020,   recorded: August 2019,   views: 26

Related Open Educational Resources

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.


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.

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Reviews and comments:

Comment1 Kessedi, October 19, 2023 at 9:31 a.m.:

Based on statistics, football is the most popular game all over the world. I am also a big football fan and have long dreamed of making money from my knowledge about football. Now I was lucky and I found an excellent site https://melbet.com with high odds for making money on football and other sports. If you are well versed in any sport or cyber sports (which is very fashionable now), then you should definitely go to the Melbet website.

Write your own review or comment:

make sure you have javascript enabled or clear this field: