Predicting the features of behaviour of big data and multivariable systems has been a research subject in various fields of science. When it comes to football, as it is a field of sports followed by the whole world, the number of studies carried out aiming at predicting the results of football games has been increasing in the field of football science. Although the result of a football match depends on various variables, it is mainly determined over the offensive and defensive strengths of the teams. Different variables have so far been determined in the literature to figure out these strengths of the teams. In this study, it was aimed to predict correctly how many goals a team could score or concede in the last 5 weeks based on the average number of goals they scored and conceded since the beginning of the season in 6 European leagues. For this reason, a Poisson distribution model was established based on these offensive and defensive strengths. A total of 4264 matches and 5938 goals were analysed in the study and the established model yielded affirmative results at the level of 50% in the leagues analysed.

中文翻译：

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使用泊松模型预测欧洲足球的进球数

预测大数据和多变量系统的行为特征一直是各个科学领域的研究课题。说到足球，作为一个全世界都在关注的运动领域，足球科学领域进行的旨在预测足球比赛结果的研究越来越多。虽然一场足球比赛的结果取决于各种变量，但主要是由球队的攻防实力决定的。迄今为止，文献中已经确定了不同的变量来确定团队的这些优势。在这项研究中，目的是根据球队自赛季开始以来在 6 个欧洲联赛中进球和失球的平均数，正确预测球队在过去 5 周内可以进球或失球的数量。为此，基于这些攻防优势建立了泊松分布模型。研究共分析了 4264 场比赛和 5938 个进球，建立的模型在所分析的联赛中产生了 50% 的肯定结果。