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Background: Concussions in American football remain a high priority of sports injury prevention programs. Detailed video review provides important information on causation, the outcomes of rule changes, and guidance on future injury prevention strategies. Purpose: Documentation of concussions sustained in National Football League games played during the 2015-2016 and 2016-2017 seasons, including consideration of video views unavailable to the public. Study Design: Descriptive epidemiology study. Methods: All reported concussions were reviewed with all available video footage. Standardized terminology and associated definitions were developed to describe and categorize the details of each concussion. Results: Cornerbacks sustained the most concussions, followed by wide receivers, then linebackers and offensive linemen. Half (50%) of concussions occurred during a passing play, 28% during a rushing play, and 21% on a punt or kickoff. Tackling was found to be the most common activity of concussed players, with the side of the helmet the most common helmet impact location. The distribution of helmet impact source—the object that contacted the concussed player’s helmet—differed from studies of earlier seasons, with a higher proportion of helmet-to-body impacts (particularly shoulder) and helmet-to-ground impacts and with a lower proportion of helmet-to-helmet impacts. Helmet-to-ground concussive impacts were notable for the high prevalence of impacts to the back of the helmet and their frequency during passing plays. Conclusion: Concussion causation scenarios in the National Football League have changed over time. Clinical Relevance: The results of this study suggest the need for expanded evaluation of concussion countermeasures beyond solely helmet-to-helmet test systems, including consideration of impacts with the ground and with the body of the opposing player. It also suggests the possibility of position-specific countermeasures as part of an ongoing effort to improve safety.

Wearable sensors that accurately record head impacts experienced by athletes during play can enable a wide range of potential applications including equipment improvements, player education, and rule changes. One challenge for wearable systems is their ability to discriminate head impacts from recorded spurious signals. This study describes the development and evaluation of a head impact detection system consisting of a mouthguard sensor and machine learning model for distinguishing head impacts from spurious events in football games. Twenty-one collegiate football athletes participating in 11 games during the 2018 and 2019 seasons wore a custom-fit mouthguard instrumented with linear and angular accelerometers to collect kinematic data. Video was reviewed to classify sensor events, collected from instrumented players that sustained head impacts, as head impacts or spurious events. Data from 2018 games were used to train the ML model to classify head impacts using kinematic data features (127 head impacts; 305 non-head impacts). Performance of the mouthguard sensor and ML model were evaluated using an independent test dataset of 3 games from 2019 (58 head impacts; 74 non-head impacts). Based on the test dataset results, the mouthguard sensor alone detected 81.6% of video-confirmed head impacts while the ML classifier provided 98.3% precision and 100% recall, resulting in an overall head impact detection system that achieved 98.3% precision and 81.6% recall.

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This study quantified the mechanical interactions between an American football cleat and eight surfaces used by professional American football teams. Loading conditions were applied with a custom-built testing apparatus designed to represent play-relevant maneuvers of elite athletes. Two natural grass and six infill artificial surfaces were tested with the cleated portion of a shoe intended for use on either surface type. In translation tests with a 2. 8-kN vertical load, the grass surfaces limited the horizontal force on the cleats by tearing. This tearing was not observed with the artificial surfaces, which allowed less motion and generated greater horizontal force (3.2 kN vs. 4.5 kN, p < 0.05). Similarly, rotation tests generated less angular displacement and greater torque on the artificial surfaces (145 N m vs. 197 N m, p < 0.05). Translation/drop tests, in which the foot-form was launched into the surfaces with both horizontal and vertical velocity components generated less peak horizontal force on the natural surfaces than on the artificial surfaces (2.4 kN vs. 3.0 kN, p < 0.05). These results suggest a force-limiting mechanism inherent to natural grass surfaces. Future work should consider implications of these findings for performance and injury risk and should evaluate the findings' sensitivity to cleat pattern and playing conditions.