Introduction

Anterior cruciate ligament (ACL) ruptures count among the most devastating injuries in sports. Annual injury incidence ranges from 0.15 to 3.67% in professional athletes and from 0.03 to 1.62% in amateur athletes across various sports [1]. When expressed relative to athlete exposures, female athletes exhibit a higher incidence rate of 1.5/10,000 compared with men, at 0.9/10,000 [2]. Furthermore, there is a high risk for a second ACL injury (pooled incidence: 16.9%; 8% for contralateral ACL injuries and 10% for ipsilateral ACL injuries [3]). Ruptures of the ACL are typically associated with long (around 9 ± 2 months [3]) return to sport (RTS) times or unsuccessful RTS, functional impairments, and potential long-term health consequences such as osteoarthritis [4, 5], overall leading to a significant burden and associated societal costs [6].

ACL injuries can be categorized as direct contact, indirect contact, or noncontact traumas [7]. Contact injuries result from direct blows or tackles to the proximal lower leg, knee, or distal thigh. Indirect contact injuries occur without direct force application to these regions (e.g., push on the upper body or contact to the foot). Noncontact injuries are sustained without any physical contact with another player. Differentiating between contact mechanisms is essential because preventive strategies for specific mechanisms differ substantially. While noncontact injuries can be reduced through neuromuscular training and technique modification, direct contact injuries often require sport-specific rule changes or the use of protective equipment; thus, accurate classification directly informs the design of targeted prevention measures [7, 8].

Although exercise programs have been demonstrated to be effective for ACL injury prevention, they may be further optimized by precisely identifying the specifics of the injury scenario [9]. Knowing the game situations (e.g., offensive/defensive play, ball possession, early/late game) and movement patterns (e.g., cutting, landing) performed in the moment of injury, as well as potential dependencies on the type of sport, would allow for the development of more specific prevention approaches.

Different sports are characterized by distinct movement patterns and constraints, including, e.g., variations in intensity, relative proportions of linear and nonlinear motions, technical demands, visual–spatial requirements, or the degree of physical contact. Understanding the differences and similarities between situations that lead to ACL injuries across various sports enables the identification of both universal risk factors and sport-specific mechanisms.

Therefore, identification of the most frequent injury-inciting situations has direct implications for targeted prevention strategies. For sports governing bodies, evidence of high-risk actions under specific contextual conditions may inform rule modifications or equipment standards designed to better protect athletes in critical situations. For coaches and practitioners, such knowledge helps prepare athletes to cope with high-risk scenarios by integrating specific drills and strengthening programs aimed at improving both technique and the capacity of biological structures to protect the ACL. For researchers, the synthesized situational patterns provide a framework for, e.g., detailed biomechanical analyses. Such analyses can clarify which structures are most critically loaded at the time of injury. They can evaluate the efficacy of preventive interventions, ranging from targeted training drills to innovations in footwear or protective equipment, under conditions that realistically reflect the injury mechanisms observed in a sport.

Video analysis provides direct observation of real-world injury events—including, e.g., task demands, opponent interactions, and unanticipated perturbations—that cannot be ethically or reliably reproduced in the laboratory and are prone to recall bias when obtained retrospectively from athlete interviews [10]. As a complement to laboratory biomechanics and prospective epidemiology, video analysis is now a rigorously appraised method [11] with growing adoption across sports in recent years, offering the potential to synthesize insights on injury situations through a systematic review and meta-analysis. While systematic reviews on ACL rupture situations have been conducted previously [12, 13], they did not include the large number of articles published in the last 2 years (2024 and 2025). Furthermore, one review neither systematically analyzed situational patterns nor performed a quality rating of the included studies [12]. Additionally, neither of the published systematic reviews performed a meta-analysis to synthesize the findings [12, 13].

Consequently, the purpose of this systematic review with meta-analysis was to comprehensively analyze video-identified ACL injury patterns across different sports. Our objectives were (a) to quantify the proportions of noncontact, indirect contact, and direct contact ACL injuries with respect to characteristics of game situations and specific movement patterns and (b) to identify potential differences between sports.