Table 4 Studies implicating biomechanical variables about the knee in generating large KJLs

Havens et al., 2015 [34]

25 (12 F, 13 M) healthy soccer players

45° and 90° PP cutting tasks with 7.5 m approach and 7.5 exit

KEM sig determinant of KAM (R² change 0.17, p = 0.041)

Jones et al., 2015 [36]

26 elite and sub-elite F soccer players

10 m approach 3 m exit of PP 90° cut

Initial KAA sig predictor of KAM (R = − .67, p = 0.001; R² = 45%)

Kristianslund et al., 2014 [61]

123 F handball players

Handball-specific protocol—self-selected PP cut when receiving a ball and cutting around a static defender mean 67°

KAA sig predictor of pKAM (ß = 0.704, p = <0.001), moment arm (ß = 0.00218, p = <0.001) and GRF at time of pKAM (ß = 0.212, p = .001)

McBurnie et al., 2019 [60]

34 elite and sub-elite M soccer players

70–90° PP cutting task with a 10 m approach and 3 m exit

Peak KFM and KRM sig determinants of KAM (R = 0.549 and − 0.488; p = 0.002 and 0.003 respectively)

McLean et al., 2005 [51]

20 NCAA athletes (10 M, 10 F)

45° PP cutting task

KAA predictive of KAM (R² = 0.21—males, R² = 0.35—females; p = 0.05)

Sigward et al., 2015 [37]

45 (20 F, 25 M) healthy soccer players

45 and 110° UP cutting tasks with 7 m approach

vGRF, lGRF, Hip INT ROT and KAA = R² 62.9% in 45° cuts (F_4,40 = 19.654, p < 0.001) in KAMs

pGRF, Hip INT ROT and KAA (R² = 41.5(F_3,41 = 11.413, p < 0.001) in KAMs

Weir et al., 2019 [54]

30 F hockey players (15 junior, 15 elite)

UP 45° cutting task

KFA at IC sig predictor of KAM (ß = − 0.019, p = 0.001)