Table 2.

Results of models predicting the success of rest defending situations (successful/unsuccessful rest defense).

Classifier	Number of features	Accuracy	Precision	f1-Score	AUC
Logistic regression (ridge regression regularization)	17	0.87	0.56	0.57	0.76
Logistic regression (elastic net regularization)	17	0.82	0.54	0.54	0.74
Random Forest Classifier	17	0.84	0.55	0.56	0.78
Gradient Boosting	17	0.97	0.48	0.49	0.50
XGBoost Classifier	17	0.92	0.59	0.62	0.75
AdaBoost Classifier	17	0.96	0.63	0.61	0.60
AdaBoost Classifier (excluding distance variables)	15	0.97	0.73	0.64	0.60