An evaluation of the physical demands of American football training in the NFL

American football is one of the most popular sports in the United States. However, unlike other football codes, little is known about its physical demands. Aside from a limited amount of research conducted on college players during training and matches, no research exists on players at the elite level, in the National Football League (NFL). Therefore, the primary aim of this thesis was to evaluate the physical demands of training in the NFL. This aim was achieved by establishing a systematic approach to training evaluation using three main phases of study: (1) Evaluation of monitoring strategies in American football; (2) Description of American football training demands with an emphasis on periodization; and, (3) Examination of the consequences of training with an emphasis on injury risk. The first study of this thesis (Chapter 3) showed that three commercially available inertial sensors were able to differentiate between fundamental American football actions (e.g., sprinting, change of direction, and collisions) during movement tasks in a controlled setting and may be useful for quantifying the physical demands of training. During training sessions, Session Rating of Perceived Exertion exhibited a variety of individual responses making sRPE challenging to use when exclusively evaluating the physical demands of training (Chapter 4). Therefore, more objective measures (e.g., GPS and inertial sensors) were evaluated during training (Chapter 5) and indicate that commonly used measures of distance and velocity may not adequately describe the physical demands for some position groups. As such, inertial sensors offer more flexibility to classify a broad range of activities within the sport. A number of inertial sensor metrics are available to the practitioner in commercially used systems. Chapter 6 utilized a principal components analysis to reduce eleven variables to 3 principal components, explaining 79% of the variance within the data. These findings suggest that a small number of variables (e.g., Player Load and IMA) may be adequate when describing the training demands of the sport. Given the reduction in measures to report, Chapter 7 used Player Load and IMA to describe the periodization strategies across a season and within the training week employed by the coaches of one NFL team. Training load was observed to decreases across the season with no clear periodization structure. Conversely, within the weekly micro-cycle, coaches appear to employ some pattern of periodization whereby training load is seen to systematically decrease as the game nears. The final phase of this thesis (Chapter 8) investigated the consequences of American football training by exploring the relationship between training load measures (Player Load, IMA, and Impacts) and non-contact soft tissue injury. Several logistic regression models were compared using Bayesian Information Criterion (BIC). The best model suggested that sessions with greater volume (PLTotal) and intensity (ImpactsHigh) were associated with non-contact soft tissue injury in American football players and may have implications for practitioners when designing training programs within the sport. Collectively, this thesis has the potential to not only offer practitioners within American football a way forward in terms of evaluating training demands but also may be influential to the broader scope of sports science given some of the novel statistical approaches taken to understanding training load monitoring.