. Author manuscript; available in PMC: 2021 Jun 1.

Published in final edited form as: Biomech Model Mechanobiol. 2019 Nov 23;19(3):927–942. doi: 10.1007/s10237-019-01261-y

Table A2.

Out-of-sample prediction performances using VT-trained predictors to predict injury on the NFL and SF datasets.

	Performance category	network (acc.)	network (sens.)	network (AUC)	MPS	a_lin (g)	a_rot (rad/s²)	v_rot (rad/s)
NFL	Accuracy	0.755	0.623	0.643	0.640	0.755	0.830	0.774
	Sensitivity	0.850	0.900	0.900	0.850	0.350	0.850	0.850
	Specificity	0.697	0.455	0.485	0.515	1.000	0.818	0.727
	Testing AUC	0.829	0.753	0.846	0.876	0.858	0.905	0.849
	PPV	0.630	0.500	0.514	0.515	1.000	0.739	0.654
SF	Accuracy	0.782	0.627	0.636	0.782	0.927	0.736	0.855
	Sensitivity	1.000	1.000	1.000	1.000	0.000	1.000	0.500
	Specificity	0.778	0.620	0.630	0.778	0.944	0.732	0.861
	Testing AUC	0.894	0.898	0.917	0.889	0.935	0.926	0.889
	PPV	0.077	0.047	0.048	0.077	0.000	0.065	0.063
	Injury threshold	N/A	N/A	N/A	0.25	107.00	5068.89	31.08