Concept: National Football League
The present work provides evidence that people assume a priori that Blacks feel less pain than do Whites. It also demonstrates that this bias is rooted in perceptions of status and the privilege (or hardship) status confers, not race per se. Archival data from the National Football League injury reports reveal that, relative to injured White players, injured Black players are deemed more likely to play in a subsequent game, possibly because people assume they feel less pain. Experiments 1-4 show that White and Black Americans-including registered nurses and nursing students-assume that Black people feel less pain than do White people. Finally, Experiments 5 and 6 provide evidence that this bias is rooted in perceptions of status, not race per se. Taken together, these data have important implications for understanding race-related biases and healthcare disparities.
How much does a fumble affect the probability of winning an American football game? How balanced should your offense be in order to increase the probability of winning by 10%? These are questions for which the coaching staff of National Football League teams have a clear qualitative answer. Turnovers are costly; turn the ball over several times and you will certainly lose. Nevertheless, what does “several” mean? How “certain” is certainly? In this study, we collected play-by-play data from the past 7 NFL seasons, i.e., 2009-2015, and we build a descriptive model for the probability of winning a game. Despite the fact that our model incorporates simple box score statistics, such as total offensive yards, number of turnovers etc., its overall cross-validation accuracy is 84%. Furthermore, we combine this descriptive model with a statistical bootstrap module to build FPM (short for Football Prediction Matchup) for predicting future match-ups. The contribution of FPM is pertinent to its simplicity and transparency, which however does not sacrifice the system’s performance. In particular, our evaluations indicate that our prediction engine performs on par with the current state-of-the-art systems (e.g., ESPN’s FPI and Microsoft’s Cortana). The latter are typically proprietary but based on their components described publicly they are significantly more complicated than FPM. Moreover, their proprietary nature does not allow for a head-to-head comparison in terms of the core elements of the systems but it should be evident that the features incorporated in FPM are able to capture a large percentage of the observed variance in NFL games.
American football remains one of the most popular sports for young athletes. The injuries sustained during football, especially those to the head and neck, have been a topic of intense interest recently in both the public media and medical literature. The recognition of these injuries and the potential for long-term sequelae have led some physicians to call for a reduction in the number of contact practices, a postponement of tackling until a certain age, and even a ban on high school football. This statement reviews the literature regarding injuries in football, particularly those of the head and neck, the relationship between tackling and football-related injuries, and the potential effects of limiting or delaying tackling on injury risk.
Although there is great enthusiasm in both the public and private sector for the further development and use of large-scale consumer-facing public health applications for mobile platforms, little is known about user experience and satisfaction with this type of approach. As a part of the Beacon Community Cooperative Agreement Program, txt4health, a public-facing, mobile phone-based health information service targeting type 2 diabetes, was launched in 3 Beacon Communities: the Southeast Michigan Beacon Community in Detroit, MI, the Greater Cincinnati Beacon Community in Cincinnati, OH, and the Crescent City Beacon Community in New Orleans, LA. This program was marketed via large public health campaigns and drew many users within the respective communities.
Injuries are inherent to the sport of American football and often require operative management. Outcomes have been reported for certain surgical procedures in professional athletes in the National Football League (NFL), but there is little information comparing the career effect of these procedures.
Recent technological advances have allowed the in-vivo measurement of impacts sustained to the head during helmeted sports. These measurements are of interest to researchers and clinicians for their potential to understand both the underlying mechanics of concussive injuries and the potential for real-time injury diagnostics. Following an overview of impact biomechanics, this review will evaluate the following: in-vivo technology being used in American football players; impact frequencies and magnitudes; and the biomechanical threshold for concussion.
Retrospective cohort study.
-Explicitly monitoring one’s own actions has been noted as detrimental to the performance of fine motor skills under duress. Offensive skills rather than defensive skills are typically studied in this context. Defensive techniques typically require skills such as footwork and continuous movement, as opposed to more precise, hand-eye coordinated action. Explicit monitoring theory may be less relevant for defensive skills than offensive skills when playing under pressure. Archival data (66 years) for teams and for individual players was compiled from the National Basketball Association (NBA) and the National Football League (NFL). For basketball (n = 778) and football (n = 515) teams, regular season offensive and defensive statistics similarly predicted success in the postseason, which was assumed to create more pressure. For individual basketball players (n = 5,132), nine indices of offensive (FG, free throw and three-point shooting, offensive win shares, points, and assists) and defensive (defensive win shares, steals, and blocks) production were compared; among these, three-point shooting percentage was least correlated from season to postseason, suggesting it is especially variable under pressure. A balanced basketball or football team that focuses on both offense and defense may be most successful.
To analyze neurodegenerative causes of death, specifically Alzheimer disease (AD), Parkinson disease, and amyotrophic lateral sclerosis (ALS), among a cohort of professional football players.
Reliable prediction and diagnosis of concussion is important for its effective clinical management. Previous model-based studies largely employ peak responses from a single element in a pre-selected anatomical region of interest (ROI) and utilize a single training dataset for injury prediction. A more systematic and rigorous approach is necessary to scrutinize the entire white matter (WM) ROIs as well as ROI-constrained neural tracts. To this end, we evaluated injury prediction performances of the 50 deep WM regions using predictor variables based on strains obtained from simulating the 58 reconstructed American National Football League head impacts. To objectively evaluate performance, repeated random subsampling was employed to split the impacts into independent training and testing datasets (39 and 19 cases, respectively, with 100 trials). Univariate logistic regressions were conducted based on training datasets to compute the area under the receiver operating characteristic curve (AUC), while accuracy, sensitivity, and specificity were reported based on testing datasets. Two tract-wise injury susceptibilities were identified as the best overall via pair-wise permutation test. They had comparable AUC, accuracy, and sensitivity, with the highest values occurring in superior longitudinal fasciculus (SLF; 0.867-0.879, 84.4-85.2, and 84.1-84.6%, respectively). Using metrics based on WM fiber strain, the most vulnerable ROIs included genu of corpus callosum, cerebral peduncle, and uncinate fasciculus, while genu and main body of corpus callosum, and SLF were among the most vulnerable tracts. Even for one un-concussed athlete, injury susceptibility of the cingulum (hippocampus) right was elevated. These findings highlight the unique injury discriminatory potentials of computational models and may provide important insight into how best to incorporate WM structural anisotropy for investigation of brain injury.