## 1 Introduction  
Running is one of the most popular forms of physical activity in Western countries [1] and one of the most efficient ways to achieve physical fitness [2], reduce risk factors for cardiovascular disease [3], generate weight loss, and improve cognitive performance [4]. A major drawback of this sport is the high risk of running-related injuries. Several studies have shown an injury incidence of 19-79% per year [1, 2, 4]. The knee is the most common site of lower extremity injuries in runners, followed by the lower leg [5]. Running injuries have been found to be related to several intrinsic factors, including leg length discrepancy [6], running techniques [2], and abnormal limb biomechanics [2, 7]. Gait analysis can be expressed in a single score by the Gait Deviation Index (GDI) and the Gait Profile Score (GPS) [8, 9]. The GPS, introduced by [PERSON] et al. [8], summarizes the overall deviation of kinematic gait data from normative data. This single index provides gait variable scores to the nine key component kinematic gait variables that comprise the GPS score. The movement analysis profile (MAP) is a graph consisting of 10 columns; nine representing each gait variable, and the tenth equaling the GPS score. The GPS as well as the GDI are represented by the same units (\({}^{\circ}\)) as the kinematic variables, but as these scores denote the distance from the normal average, the smaller values indicate less deviation from the norm or better results. In the literature, the GPS has been found to be a valid tool reflecting the quality of the gait pattern in several pathologies, including multiple sclerosis, Parkinson's disease, and cerebral palsy [10; 11; 12]. The Gait Deviation Index (GDI), a methodology described by [PERSON] in 2008 [9], incorporates nine features, including three-dimensional rotation angles for the pelvis and the hip, the sagittal plane at the knee, and the sagittal plane at the ankle, as well as the foot progression angle. Kinematic variables include pelvic obliquity, tilt and rotation, hip ab/adduction, flexion/extension, rotations, knee flexion/extension, ankle dorsi/plantar flexion, and foot progression angle. Patella femoral pain syndrome (PFPS), iliotibial band syndrome (ITBS), and medial tibial stress syndrome (MTSS) are some of the most common injuries observed in long distance runners [7]. PFPS commonly presents as a gradual onset of knee pain in the area of the patella and is associated with patellofemoral loading activities such as running and squatting. A diagnosis is usually formulated by past history and a physical examination, rarely requiring imaging studies [13]. ITBS, characterized by lateral knee pain in the active athletic population, is typically diagnosed by past history and a physical examination without requiring imaging studies. Possible etiologies are friction of the iliotibial band against the lateral femoral epicondyle, compression of the deep fat and connective tissues in the region, and the chronic inflammation of the iliotibial band bursa [14]. MTSS, also known as shin splints, present as pain or discomfort in the area around the lower half of the medial tibia. Diffuse tenderness over the posteromedial border of the tibia is the most sensitive sign [15; 16; 17; 18]. It has been suggested that PFPS is linked to several lower limb malalignments such as increased peak hip adduction [19], internal rotation, and contralateral pelvic drop [20]. Other studies have reported inconsistent results or no correlations between hip, knee kinematics, and injury [15; 17; 18]. In [PERSON] et al. 's systematic review, the authors presented conflicting findings as to hip internal rotation and its correlation to patellofemoral pain [17]. [PERSON] et al. discovered that subjects with PFPS demonstrated a significant hip weakness, but, no altered hip and knee kinematics (measured during a standardized stair-stepping task), as previously theorized [18].