Diversified Modeling of College Sports Athletics Data and Its Optimization Based on Computational Methods

The article explores the method of diversified modeling of college sports track and field data, aiming to provide a basis for scientific training of college sports track and field.In this article, the diversified modeling of college sports track and field data is carried out by using multiple linear regression model, testing method and mathematical statistics method in order to analyze the sports characteristics and training needs of college track and field athletes.Using multiple linear regression model to analyze the influencing factors of track and field special movement patterns, then, on the basis of clarifying the training needs of track and field special movement patterns, combining the theoretical study of functional movement screening with the actual practice of track and field sports, carrying out the FMS test of the research object, and proposing the optimization plan of college sports track and field training after analyzing the results of functional movement screening of different track and field events.By using the multi-dimensional modeling method of college sports track and field data proposed in this paper to analyze the influencing factors of athletes' track and field special action patterns, it is found that there is a significant medium correlation between the "torso forward swing and hip and knee rotation speed" in the buffer action link and the "torso extension speed" in the kick and stretch action link and the in-situ jump height.At the same time, there was a significant correlation between the common factor "trunk forward swing and hip and knee rotation speed" and the "trunk extension speed" in the push and extension link.