Classify documents using a set of known vocabularies
First of all you need to have available a train set, which means that you should annotate manually which document is related to soccer and which not. Then you need to process the available corpus (remove numbers, stop-words etc., stemming) and build a vocabulary. After that you should choose the appropriate feature representation. Each term is a feature and you have to decide how you are going to reprsent each feature, which means what kind of weight you will assingn. One way is the tf-idf representation. Then you will be able to train a classifier. 

*The only way to avoid labeling manually the texts is to find some already labeled in the same language.