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The National Football League (NFL) is the most influential, popular, and prosperous professional sports league in America.As such this book focuses on the development and maturity of the organization and its members, but most importantly, how each of them performed in seasons and postseasons and then to what extent they have succeeded as a.

In this paper, we introduce an R software package for simulating plays and drives using play-by-play data from the National Football League. The simulations are generated by sampling play-by-play data from previous football seasons. The sampling procedure adds statistical rigor to any decisions or inferences arising from examining the simulations. We highlight that the package is particularly useful as a data-driven tool for evaluating potential in-game strategies or rule changes within the league. We demonstrate its utility by evaluating the oft-debated strategy of “going for it” on fourth down and investigating whether or not teams should pass more than the current standard.

System justification theory posits that members of various groups seek to maintain the status quo by reinforcing and internalizing the thoughts, behaviors, and expectations of existing systems. The current study examines these notions in the context of disciplinary actions against Black and white male athletes in the National Football League (NFL), attempting to compare punishment within the league and United States society. Data on all reported fines and suspensions from the 2002 to 2018 NFL seasons were obtained from Spotrac. Imprisonment rates by race and gender from the sampled period were collected from the Bureau of Justice Statistics (BJS). Results from our analyses showed that Black NFL players were fined and suspended at a higher rate than white players, as compared to the actual distribution of players by race in the NFL. Consistent with system justification theory, the data reveal an overrepresentation of Black players who were disciplined by the league relative to their own race group than white players. Limitations of the present study and future directions for research are discussed.

Background: The majority of studies on concussion in the National Football League (NFL) focus on testing, evaluation, and outcomes. Meanwhile, there is a paucity of research on how a team’s style of play influences the risk of concussion. Hypothesis: Style of play, such as offensive and defensive strategies, is associated with the rate of concussions in the NFL. Study Design: Descriptive epidemiology study. Methods: The current study retrospectively analyzed data from the 2012 to 2014 NFL regular seasons. Reported numbers of concussions were stratified by each team and each position and were compared based on style of play, including offensive scheme (West Coast offense, Air Coryell offense, or other offensive schemes) and defensive alignment (3-4 or 4-3), attempts statistics, per-drive statistics, and offensive and defensive productions, along with strength of schedule (SoS) and team quality measured by simple rating system (SRS). Data analyses included descriptive statistics, 1-way analysis of variance, correlation analysis, and regression analysis. Results: There were 437 documented concussions during the 2012 to 2014 NFL regular seasons, with a mean 4.6 concussions per season per team. In general, players most involved in pass plays reported more concussions. The number of concussions sustained by offensive players was significantly higher among the teams adopting the West Coast offense (mean, 3.0) than among those utilizing the Air Coryell offense (mean, 1.6; P = .006) or those with non–West Coast offenses combined (mean, 1.9; P = .004). The multiple regression analysis revealed that the West Coast offense or not, SoS, and SRS explained 25.3% of the variance in the number of concussions by offensive players. After accounting for SRS, the West Coast offense was found to be a significant predictor of the number of concussions (P = .007), while there was a tendency for SoS to be inversely associated with the number of concussions (P = .105). None of the variables for attempts statistics, per-drive statistics, and offensive production were significantly associated with the number of concussions in the regression analysis. Conclusion: In the NFL, players most involved in pass plays appear to be at increased risk for concussions. The West Coast offense may be associated with a greater risk of concussion. Furthermore, teams with easier schedules may have more players sustaining concussions.

In the field of personnel economics, there are few opportunities to convincingly test for salary returns to specialization as against versatility. This paper performs such a test by modeling returns to performance measures associated with two different skills practiced by running backs in the National Football League. We find gains to both specialization and free agency with substantial predicted differences in returns for alternative skills. These differences vary across the salary distribution. In the top half of the salary distribution, model simulations show that specialists in either particular skill generate higher marginal returns than do versatile players.

This article develops a predictive model for National Football League (NFL) game scores using data from the period 1988-1993. The parameters of primary interest-measures of team strength-are expected to vary over time. Our model accounts for this source of variability by modeling football outcomes using a state-space model that assumes team strength parameters follow a first-order autoregressive process. Two sources of variation in team strengths are addressed in our model; week-to-week changes in team strength due to injuries and other random factors, and season-to-season changes resulting from changes in personnel and other longer-term factors. Our model also incorporates a home-field advantage while allowing for the possibility that the magnitude of the advantage may vary across teams. The aim of the analysis is to obtain plausible inferences concerning team strengths and other model parameters, and to predict future game outcomes. Iterative simulation is used to obtain samples from the joint posterior distribution of all model parameters. Our model appears to outperform the Las Vegas \"betting line\" on a small test set consisting of the last 110 games of the 1993 NFL season.

In this study, we test the relationship between price volatility and contract maturity, or the \"Samuelson effect,\" using futures contract prices for a major sports event. Applying four different performance measures, we show supportive evidence of the Samuelson effect in futures contracts for tickets to the Super Bowl XLIII [2009], using the dynamic panel estimation method. Our main contributions are testing the existing theories in a novel setting with unique product features and advancing our understanding of the prediction market for sports events.

After a prolonged battle with District 227 school officials, who didn't want to share financial resources with a charter school, Davis ultimately convinced the state to grant the charter, although negotiations resulted in requirements that Southland accept students from throughout the district (not just Matteson) and that enrollment be limited to 500 students. Would they like to travel far from home, and if so, is that something they could handle emotionally, as well as intellectually? \"We eventually identify a pool of schools, maybe 10 or 15 colleges, where a student has a real chance of acceptance based on their academics and personal needs,\" he said. \"Since I've been in this business for many years, I have contacts in schools across the country, people I know, and then there are people on our staff who may know people there.