## 1 Introduction  
American football is a field-based collision sport characterized by high intensity multi-directional movements and repeated high-velocity sprints separated by periods of rest [1, 2]. The combination of high-intensity accelerations and decelerations, high-velocity running, and collisions from blocking and tackling, collectively, may place American football players at an increased risk for injury compared to other team sports [3]. In the National Football League (NFL), 60% of all injuries occur in the lower extremity, resulting in a considerable number of player-days missed [4]. As such, the prevention and treatment of lower extremity injuries remain a priority for medical and performance staff aiming to maximize player availability. While many lower extremity injuries are multifactorial in nature [5, 6, 7, 8], the literature has found a relationship between player workloads and soft tissue injury [9, 10]. A deeper understanding of the position-specific game demands may assist practitioners in developing training programs to prepare athletes for competition and potentially mitigate injury risk [11]. Furthermore, understanding competitive demands may provide increased insight to position-specific training programs to better optimize on-field performance [3, 11]. The utilization of wearable sensor technology for player tracking has been commonplace in team sports for over a decade and has facilitated the understanding of movement demands across competition and training [12]. The technology, including global positioning systems (GPS) and local positioning systems (LPS), has been validated within the scientific literature for the quantification of athletic movements associated with team sport, including distance, velocity, and acceleration [13; 14; 15; 16; 17]. Recently, this technology has emerged in American football to provide greater context around the physical requirements of the sport, which have previously relied on observational reports [18]. Much of the reported data associated with game and training demands in American football have been conducted at the high school [19] and collegiate [3; 20; 21; 22] levels. These studies have generally found that players on the offensive and defensive lines accumulated less total distance and high velocity distance compared to non-linemen [3; 19; 20]. Conversely, linemen tend to engage in a higher volume of collisions and contacts compared to other positions [22]. These positional trends represent a useful starting point for exploring the physical activities of the game but may lack specificity to the capabilities of an elite professional athlete during an NFL game. [PERSON] et al. [10] reported on the movement demands of NFL players during practice and reported differences in running volumes, intensities, and sport-specific movements across positions. They found that defensive backs and wide receivers had a greater total distance than other positions, while offensive and defensive linemen had the largest number of sport-specific movements. These authors also found that distances observed in their study were greater than those reported during a collegiate football practice [10]. These authors were the first to report on position-specific movement demands of NFL football players; however, these data were collected on a single team during one preseason training camp. Due to the limited number of datasets, these findings may not be representative of every NFL football team. Furthermore, the investigation did not provide detail on specific movement demands associated with competitive games. In 2015, the NFL implemented a league-wide initiative, called Next Gen Stats (NGS), to quantify the movement demands of NFL players during games [23]. Through NGS, an LPS tracking system (Zebra Technologies, Lincolnshire, IL, USA) captured player data, including on-field location and velocity, during every game using ultra-wide band receivers and radiofrequency identification (RFID) tags installed in the players' shoulder pads.