Table 1. Overview of the classification tasks.

Classification Task	Model	Types and number of variables included	Training data set data points (before oversampling)	Training data set data points (after oversampling)	Test data set data points
Injury prediction	linear SVM	Training load, blood, fitness, questionnaire, jump variables (247)	1.085 (incl. 7 injuries)	1.347 (incl. 269 injuries)	300 (incl. 4 injuries)
Illness prediction	linear SVM	Blood variables (40)	283 (incl. 11 illnesses)	543 (incl. 271 illnesses)	60 (incl. 1 illness)
Illness determination	linear SVM	Blood variables (40)	177 (incl. 9 illnesses)	337 (incl. 169 illnesses)	42 (incl. 1 illness)

Injury prediction: 11 injuries present in the sample, with 8 different players affected; Illness prediction: 12 illnesses present in the sample, with 10 different players affected; Illness determination: 10 illnesses present in the sample, with 5 different players affected. Differences in the numbers of illness prediction and detection possible due to non-appearance for blood collection, when already ill.