With the hot development of football, sports injuries caused by football have also received special attention. In football games, although there are medical staff on and off the field always on call to protect the safety of players, because of the complexity of diagnosis work, medical staff can easily lead to diagnostic errors due to factors such as fatigue, which seriously affects the condition of athletes. Image processing is a technology that uses computer to process images, which can greatly overcome the uncertain factors brought by manual diagnosis. Based on this, this paper uses image processing technology and pattern recognition as technical means to explore the specific application of image processing in football injury diagnosis. This paper firstly takes football clubs as the main research object and analyzes and explores the specific utility of image segmentation and feature recognition in sports injury image processing. Then, starting from the relevant image features, the paper analyzes and compares the sensitivity of support vector machine pattern recognition and neural network pattern recognition in football injury diagnosis. This article comprehensively summarizes the application of image processing technology in the diagnosis of football injuries and puts forward constructive suggestions for its subsequent development. Experiments show that the effect of pattern recognition is often different for different injury parts of football. Among them, the sensitivity of pattern recognition based on image processing can reach 68.9%, and the detection rate of football injuries can also be maintained at about 81.2%. This fully shows that image processing technology can play an active role in the actual football injury diagnosis, and provide very valuable information for clinical diagnosis.

Football is one of the sports that is loved by people all over the world. Its sales ability in the league should not be underestimated. Moreover, football has been developed in our country since ancient times and has a huge fan base, and fans are the main target of football league sales. Predicting the sales effect of the football league is helpful for the seller to formulate a suitable sales strategy and avoid the problem of product surplus. This article mainly introduces the prediction research of football league sales effect based on BP neural network, and intends to provide ideas and methods for predicting the sales effect of football league. This paper puts forward the basic method of the sales effect prediction of the football league and the BP neural network football league sales effect prediction method to analyze and predict the sales effect of the football league. In addition, the steps of establishing BP neural network design, building BP neural network football league sales effect prediction model and applying BP neural network football league sales effect prediction model are also proposed. The experimental results of this article show that the difference between the fitting part of the neural network model and the real value of the football league sales effect sample data is in the range of , the error percentage difference is small, and the prediction results are valid。