This article shows the whole process using known datasets to estimate two football teams up-coming performances. The math process (modeling) includes linear regression, probability expectations, and using graphs to express the modeling process. In this article, from the process of modeling, there are conclusive results and conclusions which is beneficial in researching sport management and football team management which includes basic two types of management structure and basic strategy in data analyzing of football financial expenditure. The whole research contains four parts, including introduction, methods, analytical conclusions, and applications. First, the article discussed some basic assumptions and preparations for modeling, and researched on some of the topics according to the whole theme. In the part methods, the research uses linear regression to fit a suitable relationship each between the factors that affect expenditure and rankings. In the part conclusion, which includes analytical conclusion and quantized applications, which can also be separated to two parts. Analytical conclusions state some of those findings depend on the previous research process, which those findings illustrate particularly kind of relationship. In the quantized applications, the research fit data into the model and acquire an intermediate result and some beneficial suggestions to each of the studies.