Analysis Of The Winning Factors In Football Match Based On The Perspective Of Fitness Indicators

The analysis of the scientific competition of Big Data is an important step in the development of modern football.Through statistical analysis on video tapes,we try to find out the problems in football matches and the inherent laws of football projects,aiming at seeking higher space for the development of Chinese football.Physical fitness is a prerequisite for its athletic ability and development,also it is a material basis for the sport of football.It has become a consensus in the world of sports that football players should focus on physical fitness.It is necessary to understand the characteristic rules of football items and to work out a corresponding physical training program for athletes in different positions,so as to improve the athletics level.Through the methods of documentary,video analysis and mathematical statistics,this paper analyzes the running performance data on 30 rounds of the Chinese Super League of the 2017 season and the data of AMISCO,and studies the overall running situation of the athletes and the running characteristics of the athletes in different situations.Based on the general linear model and the multiple logistic regression model,this paper analyzes and defines the physical data indicators that determine the outcome of each game of the Super League in the 2017 season and the different strength teams against different strength teams,and the following conclusions are drawn:1.In the top of the league table,The total running distance of the low-level teams are generally higher than the high-level teams,and the winning team is always running at a higher distance than the losing team.There is no significant correlation between the total running distance of the Super League and the winning probability of the competition in 2017.After incorporating the situation into the model,when the high-level team against the low-level team,the total running distance can be the winning factor of the football match.2.In the top of the league table,both the sprint distance of the high-level teams and the number of sprints is generally higher than that of the low-level teams.The winning team has a higher sprint distance and has more times than the losing team.The sprint distance of the Super League in the 2017 season can be the winning factor of the football match,and there is no significant correlation between the sprint number and the winning probability.Incorporate the situation into the model,when the low-level teams against the high-level teams,sprint distance can be a football match winning factor.When the high-level teams against the low-level teams,the number of sprints is the winning factor for the football match.3.In the top of the league table,both the high-speed running distance of the high-level teams and the number of high-speed running is generally higher than that of the low-level teams.The winning team has a higher high-speed running distance and has more times than the losing team.The high-speed running distance of the Super League in the 2017 season can be the winning factor of the football match,and there is no significant correlation between the high-speed running number and the winning probability.Incorporate the situation into the model,when the low-level teams against the high-level teams,high-speed running distance can be a football match winning factor.When the high-level teams against the low-level teams,the high-speed running number of times is the winning factor for the football match.4.In the top of the league table,both the high intensity running distance of the high-level teams and the number of high intensity running is generally higher than that of the low-level teams.The high intensity running distance of the Super League in the 2017 season can be the winning factor of the football match,and there is no significant correlation between the high intensity running number and the winning probability.After incorporating the situation into the model,there is no significant correlation between the two sides.5.In the top of the league table,the ball running distance of the high-level teams is generally higher than that of the low-level teams,the no-ball running distance of the high-level teams is generally lower than low-level teams.And the winning team is always running at a higher distance than the losing team with ball and running at a lower distance without ball.The ball running distance of the Super League in the 2017 season can be the winning factor of the football match,and there is no significant correlation between the no-ball running distance and the winning probability.After incorporating the situation into the model,when the high-level teams against the high-level teams,low-level teams against high-level teams,low-level teams against the low-level teams,the ball running can be the winning factor of the football match.When the high-level teams against the low-level teams,no-ball running distance is the winning factor for the football match.