If talent determines whether a player can embark on the road of professional football, then injury determines how far a player can go on the professional road. There are too many talented players who have failed to reach the expected height due to injuries. C Ronaldo, an "alien", won the title of World Footballer of the Year at the age of 20. If there were no injuries, he might become another king after Pele and Diego Maradona. Van Basten, a dancer on the front line of the Dutch Three Musketeers, may lead the Netherlands to completely remove the hat of the "uncrowned king" without injury; Kaka, the last Golden Globe winner before the Mero era, was not injured, and his peerless pride may become a tripartite confrontation. How to keep the players in the youth training stage away from injuries and grow into professional players smoothly, medical insurance is also one of the important functions of the big data background.
Application of Big Data in Health Care
Football players may suffer many kinds of injuries in the field and training ground, including various muscle and soft tissue injuries caused by frequent running, fractures and even concussion caused by fighting. Injury classification is the first interface of personal big data medical care. Almost all the common diseases of athletes are classified by the musculoskeletal diagram of the human body. After the player is injured, the team doctor will classify the injury type and diagnosis of the player into the system. The big data system will automatically record the injury time of players (the injury record will automatically stop after the team doctor marks the player's recovery, and the injury time will be relatively reflected in the player's attendance time), and the relevant team doctors will also input the treatment plan and related processes during the player's injury into the big data system. For more serious injuries, such as fractures and torn ligaments, players can go to hospitals with professional sports medicine departments in China for treatment, and their image data will also be recorded in the big data background. Players can also view their injury records, team doctors' treatment plans and suggestions for diet recovery training through their personal big data background accounts. With the help of professional hospitals and school sports rehabilitation centers, players can follow the doctor's advice, actively exercise and recover from injuries more quickly.
Big Data established the injury catalogue of each team and each player in Luneng Youth Training. It can help manage the injury and treatment process, record the data of each athlete, help physiotherapists monitor the key health data of athletes, and enhance the treatment efficiency of athletes. Catapult's wearable devices mentioned in the previous training articles are equipped with sensors such as gyroscopes and accelerometers, which can monitor running distance, speed, direction change, acceleration, deceleration, bounce, heartbeat and other data. In fact, these data are not only helpful to improve the quality of training, but also transmitted to the big data background. At the same time, team doctors and athletes can also see clearly the amount of exercise of everyone and know the impact of exercise on the health of players.
Big data needs to be improved in medical applications.
Sports monitor can help people find the changes of athletes' performance as early as possible. Big data can make it more visible by sorting out the data of sports monitors, and to some extent, it can show the health trend and the increase of injury risk. However, excessive exercise is also an important cause of injury, and the boundary between improving athletes' sports threshold and excessive injury is not obvious.
At present, the data research service of sports injury prevention is still in the exploratory stage, and the subjective will of players and the experience judgment of coaches are still the main indicators of injury prevention and contract signing. In the transfer operation of introducing Henderson, Ferguson rejected the deal because of his running posture. Later, Henderson was influenced by plantar fasciitis, which also proved Sir Alex Ferguson's foresight. But what everyone didn't expect was that Henderson, who later changed his style of play, led Liverpool to the Premier League title that Gerrard didn't win. Look at Manchester United's current midfield and see if it is right or wrong to give up the introduction of Henderson. No matter personal decision or big data, I am afraid no one can tell.
Kong Pani, the former Manchester City captain, was out for six weeks due to a muscle strain in the 20 15/ 16 season. He came off the bench for a few minutes on Boxing Day, and then immediately left with a muscle strain, which greatly disturbed the team. Kong Pani is an athlete with a habitual muscle strain. Based on all the injury data of Kong Pani in the last five years, after repeated analysis, the staff of Manchester City think that he needs to participate in several low-confrontation competitions steadily to adapt to the rhythm of official competitions and avoid repeated injuries. Similarly, our big data is also a place to provide experience. Under the background of big data, the team coach can better determine the injury types of players by looking at the injury history of players, and judge whether players can play in key games and contribute to the victory of the team through their performance in training.
The core of the application of big data in sports training is prediction, and its essence is to discover laws from data and improve cognitive ability, so as to make predictions and guide decision-making. The traditional manual recording of athletes' training results has some defects, such as being easily influenced by subjective factors, excessive workload, inaccurate statistics and difficult to save data. The big data system we are using now can generate enough data with training guidance value in real time and comprehensively.
It is believed that in the future, more professional technicians can accurately predict, track and calculate the injury risk by analyzing a large number of historical data and real-time data, and professional sports medical teams can help players take timely intervention and treatment measures.