## 2 Materials and Methods
### Motion Capture and Data Analysis  
Twenty-five retro-reflective markers were positioned on the lower extremities [2], along with a marked rigid pelvic shell [37]. Pelvic and lower extremity segments were tracked at 120 Hz and reconstructed three-dimensionally using an eight-camera motion capture system (Vicon Nexus 1.8, Oxford metrics; Yarnton, UK), synchronized with ground reaction forces (GRF) obtained from an indwelling force plate (Kistler Instrument Corp. Amherst, NY, USA), sampled at 1080 Hz. Standing calibration determined joint centers of rotation, defined respective segmental coordinate axes, and established neutral alignment for reference of kinematic measures. Hip, knee, and ankle joint centers were established via Visual 3D (V3D) software version 5.10-2 (C-Motion, Inc. Germantown, MD, USA). A CODA pelvis model and regression equation format [39; 40] were utilized for the hip joint center, while knee and ankle joint centers were based on distal joint segment position. Data post-processing was performed in V3D. Inverse dynamics were utilized to calculate internal joint moments relative to anatomical segment axes without filtering marker coordinates or GRFs. Moment filtering was performed with a critically damped, dual pass, low pass filter, utilizing different cut-off frequencies calculated for each subject [41]. This filtering method avoids moment artifacts, which occur when coordinates and forces are filtered with different cut-offs [42; 43; 44]. Frontal and transverse plane LSM algorithms were defined by [PERSON] et al., while the sagittal plane LSM formula was first presented by [PERSON] [37; 38]. Support moments were calculated by summing ankle (MA), knee (MK), and hip (MH)joint moments in each plane (Figure 1), assuming that each moment was a single joint actuator. The moment polarity at the proximal aspect of the distal joint segment was the basis of the LSM formulas, with counterclockwise moments being positive as defined in a right-hand, orthogonal axes system. Sagittal and frontal plane LSMs were based on the same algorithm, LSM = MK + (\(-\)MA) + (\(-\)MH). A positive sagittal plane LSM (MKE, MAPF, MHFE, where E is the extensor and PF is the plantar flexor) represents a net extensor pattern preventing flexion collapse; a positive frontal plane LSM (MKAD, MAAB, MHAB, where AD is the adductor and AB is the adductor) represents a net adductor pattern preventing medial collapse. Net transverse internal tibial rotation relative to the femur is thought to elicit ACL strain, while external tibial rotation reduces strain in the ACL [45]. Therefore, a positive transverse plane LSM, derived from the formula LSM = MH + MA + (\(-\)MK), would represent a support pattern that prevents tibial internal rotation relative to the femur (MHIR, MAIR, MKER, where IR is the internal rotator and ER is the external rotator). Joint moment curves, for each joint, plane, and trial, were expressed as a ratio normalized to subject LSM for presentation (Figures 2-4). A positive joint moment ratio was indicative of contributing to the overall LSM, while a negative ratio detracted from the LSM, as defined by the equations. Five trials for each joint moment in each plane and their support moments were averaged for each subject after normalizing to subject mass. Dependent measures were then averaged across all subjects, creating a group average for sex comparisons across landing conditions at IC and 50 ms after IC. IC was defined as the first data sample (8.3 ms) when the vertical ground reaction force was positive and closest to 20 N. The moment values for the 50 ms after IC represent the average of data points over that epoch. This time frame was chosen because ACL injuries are thought to occur from initial contact through 50 ms [25; 46]. Figure 1: Left to right; sagittal (**A**), frontal (**B**), and transverse (**C**) plane representation of the hip, knee, and ankle joint moments during limb support. Counterclockwise moments (+) and clockwise moments (\(-\)).