Predicting the results of sport matches and competitions is a growing research field, benefiting from the increasing amount of available data and novel data analytics techniques. Excellent forecasts can be achieved by advanced statistical and machine learning methods applied to detailed historical data, especially in very popular sports such as football (soccer). Here, we show that despite the large number of confounding factors, the results of a football team in longer competitions (e.g., a national league) follow a basically linear trend that is also useful for predictive purposes. In support of this claim, we present a set of experiments of linear regression compared to alternative approaches on a database collecting the yearly results of 746 teams playing in 22 divisions spanning up to five different levels from 11 countries, in 25 football seasons, for a total of 181,160 matches grouped in 9386 seasonal time series.

中文翻译：

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全国足球锦标赛的季节性线性预测。

受益于越来越多的可用数据和新颖的数据分析技术，预测体育比赛和竞赛的结果是一个不断发展的研究领域。通过将先进的统计和机器学习方法应用于详细的历史数据，尤其是在非常受欢迎的运动（如足球）中，可以实现出色的预测。在这里，我们表明尽管存在许多混杂因素，但足球队在较长时间比赛（例如，国家联赛）中的结果遵循基本线性的趋势，这对于预测目的也很有用。为了证明这一点，我们在数据库上进行了一系列线性回归与替代方法的比较实验，该数据库收集了来自11个国家/地区，分布在五个不同级别的22个分区的746个团队的年度结果，