Football match victory and defeat real-time prediction method based on machine learning

Abstract

The invention provides a machine learning-based football match victory and defeat real-time prediction method, which comprises the following steps of: firstly, according to statistical historical data and real-time event data recorded in a football match, respectively establishing a scoring model to obtain historical features and real-time features; historical features and real-time features are fused and screened in a stacking mode, and then the average number of goals, the average number of shoots, the score ranking and the like are used for expansion to complete feature generation. A football match result is predicted in real time by establishing a graph convolution deep neural network model. Compared with an algorithm which only uses historical data to carry out match prediction, the accuracy is improved.

Description

technical field [0001] The present invention relates to the field of prediction of the outcome of football matches, in particular to a method for predicting the outcome of a football match in real time based on machine learning Background technique [0002] As the most popular sport in the world, football can bring obvious economic and social benefits. Although the performance of Chinese football is not very satisfactory, its market still occupies a dominant position in the country. Therefore, the progress of the football industry has a positive role in promoting the expansion of the entire domestic sports market. The data analysis of football games can quantitatively represent the stadium information and player status, and provide reliable help for the formulation of tactical arrangements and the prediction of the outcome of the game. [0003] In terms of predicting the outcome of football games, most of the current methods are aimed at pre-match predictions, which are ma...

AI Technical Summary

Problems solved by technology

[0004] In order to solve the above technical problems, a machine learning-based real-time prediction method for the outcome of football games is provided, which solves the problem that the current football game outcome prediction can only be based on historical information, and cannot use the on-site information of the game, resulting in low real-time performance.

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