Application of FCM optimization algorithm and Sensor Technology in Football Training Ability Mining

Football players have more physical training content and complex items. For teenagers and children, according to their growth process and physical characteristics, a football training plan that meets their personal characteristics should be developed. The more basic training items include energy, speed, physical strength, and mental state functional training. In actual endurance training, there are many different methods, such as continuous method and interval method. The training disciplines are also diverse, such as effective allocation and recording of players' training content, and scientific research exercise plans can also be developed for football players' bodies. Transformation and ability mining, and timely adjustment of exercise plans are essential. At this stage, in the management of physical training for teenagers and children, coaches generally adopt a "one-pot" method to manage all players, and sometimes they also improve training for some outstanding players. The training record of football players is also relatively rough, or the method of segment recording is adopted. According to the information management method of football players' training information, football players, especially young football players and coaches can reasonably improve their efficiency. The intelligent player training management system created by sensor technology can manage football players' personal information, coach information, and football players' training content based on a dynamic incremental clustering algorithm. This paper studies the dynamic incremental clustering algorithm and sensor technology, and applies it to the mining of football training ability, aiming to promote its vigorous development.