Football Player Injury Full-Cycle Management and Monitoring System Based on Blockchain and Machine Learning Algorithm

Abstract

AbstractFootball injuries are the most common factor affecting a football player's performance, and the last thing a football player wants. To understand the causes of football players’ injuries and how to recover sports injuries most efficiently, the football players’ injuries were managed and monitored throughout the whole cycle. However, the traditional football player injury cycle management and monitoring system are not only insecure in data storage, but more importantly, it lacks intelligent analysis of the collected data. With the continuous development of blockchain and machine learning technologies, blockchain technology is used to collect, store, clean, mine and visualize the full-cycle data of football players' injuries, and machine learning is used to provide intelligent solutions for football players' injury recovery. This paper compared the football player's injury full-cycle management and monitoring system based on blockchain and machine learning algorithm with the traditional football player's injury management and monitoring system. The experimental results showed that the average self-processing capacity of the football player injury MMS based on blockchain and ML algorithm was 70%, while the average self-processing capacity of the traditional football player injury management and monitoring system was 50%. Therefore, the application of blockchain and machine learning algorithm in the football player’s injury full-cycle management and monitoring system can effectively improve the system’s self-processing ability.