Search results

In baseball, a run scored on offense carries the same on-field (win) value as does a run prevented on defense. Both outcomes bear the same score margin implication. This presumption of unit equality is implicit in the Wins Above Replacement (WAR) measure, which treats units of offensive WAR (oWAR) and units of defensive WAR (dWAR) as perfectly substitutable toward win production. The purpose of this paper is to ask whether the salaries of Major League Baseball (MLB) players reveal such an equal valuation among MLB teams.

The authors examine the relationship between offensive output, defensive output and subsequent salary from free agency in MLB using a set of log-linear OLS, fixed effects regression specifications.

In general, estimated annual salary from free agency increases significantly and substantially with unit increases in a player's (prior season) wins above replacement WAR. Across specifications, the authors estimate a 42.5–43.4% increase in salary for year t for each additional unit of WAR in year t−1. The authors disaggregate WAR into offensive and defensive components (oWAR and dWAR) and estimate a 52.4–53.3 (4.8–7.2)% increase in salary for each additional unit of oWAR (dWAR).

The efficiency of the baseball labor market has been studied previously with mixed results. The novelty of the present study is its treatment of inputs not as positions or individual players but as the underlying offensive and defensive win production of players. The authors estimate free agency salary returns to (contract season) oWAR and dWAR in MLB to establish whether (to what extent) a salary premium for offensive output exists within MLB.

Since recent research has found that offensively oriented players receive a salary premium, the current study recognizes this observed premium might exist because offense is worth more in terms of revenue generation. Given the popular sports saying, “Offense sells tickets, defense wins championships,” the authors quantify whether offense really does sell more “tickets” than defense in the NBA.

Using NBA team revenue data as well as team offensive and defensive win shares, the authors estimate several econometric specifications to test if teams generate more revenue for offensive wins compared to defensive wins. The authors also employ a multi-year free agency study to identify if NBA players receive more compensation for offensive production than they do for defensive production.

The authors find no statistical difference in revenue generation from offense compared to defense. The authors confirm these findings both before and after revenue sharing. These results are also robust to alternative specifications. Therefore, the authors conclude that fans do not prefer offense to defense in terms of their spending. Contrary to previous research, the authors find no evidence of an offensive premium paid to NBA players.

Based on their findings, offensively oriented players should not receive a salary premium. The clear implication for team decision makers is that offensive production should be compensated at a similar rate as defensive production. Since the authors do not find evidence of an offensive premium for offensive production, their research suggests a likely labor market equilibrium in the NBA for both profit-maximizing and win-maximizing teams.

Sports economists have consistently found that winning positively impacts team revenue fans prefer to allocate their entertainment dollars to winning teams. Previous research has also found that fans do not have a preference for how their team wins. However, this research ignores the significant variability in revenue that can exist between teams with similar attendance figures. The authors contribute to the literature by testing whether profit maximizing teams should pay different amounts for different types of production by estimating the marginal revenue product of a win due to offense, defense and pitching.

Using data from the 2010–2017 Major League Baseball seasons and an Ordinary Least Squares-Fixed Effects approach, the authors test whether a unit of offensive, defensive and pitching production generates differing amounts of team revenue both before and after revenue sharing. The authors then test if team Wins Above Replacement is a good approximation of actual wins while accounting for the previously observed nonlinear relationship between wins and revenue.

The authors found that marginal revenue product estimates in the postrevenue sharing model for mowar, pwar and dwar are nearly identical to each other. Further, after predicting prerevenue sharing, the authors find that fans have no preference for mowar, pwar or dwar play styles.

The findings illustrate that team decision-makers appear to be acting irrationally by paying more for offense than they do for defense. Thus, the findings suggest that team decision-makers should value defensive wins and pitching wins at the same rate as offensive wins on the free agent market.

We introduce a novel type of basketball shot chart, a true shot chart, that incorporates total points, accounting for both field goals and free throws, corresponding to each shot taken. We then create a shot selection measure called shot selection efficiency that summarizes the efficiency of a team’s shot chart. Lastly, we validate the measure using fixed effects regression analysis and determine whether shot selection is priced efficiently in the NBA player labor market.

We utilize fixed effects regression analysis to validate a measure and also to determine managerial payroll efficiency in the NBA.

We find that shot selection efficiency is a source of wins not fully explained by team payroll. That is, it is not fully priced into the player labor market.

Teams are in need of the shot chart summary measure provided, as they are not efficiently pricing players in the player labor market with respect to shot selection.

This research introduces a novel shot chart type for basketball as well as a novel shot chart summary measure. It also validates the measure and establishes an NBA player labor market inefficiency related to the measure.

Revenue sharing is ubiquitous among North American professional sports leagues. Under pool revenue sharing, above-average revenue teams of a league effectively transfer revenues to below-average revenue teams. Herein, the authors find and prove that a league will vote into policy a pool revenue sharing arrangement if and only if mean team revenue is greater than presharing median revenue, where this condition is equivalent to the presence of positive nonparametric skewness in a league’s distribution of team revenues. This represents a median voter theorem for league revenue sharing.

The authors consider the case of revenue sharing for the National Football League (NFL), a league that pools and equally shares national revenues among member teams.

The authors find evidence of positive and significant nonparametric skewness in NFL team revenue distributions for the 2004–2016 seasons. This distribution is observed amid annual majority rule votes of League owners in favor of maintaining the incumbent pool revenue sharing model (as opposed to no team revenue sharing). Distribution of revenues – namely the existence of outlying large market NFL teams – appears to consistently explain the historical popularity of NFL revenue sharing.

The median voter theorem uncovered in the case of NFL applies to all professional sports leagues and can be used predictively as well as descriptively.

In golf, strokes gained (SG) unify different shot types under a single system, including off the tee (SG: OTT), approach (SG: APP), around the green (SG: ARG) and putting (SG: PUTT). Despite SG having equal value across types, each shot type requires different skills and physical attributes. This paper analyzes how professional golfers leverage these diverse shot types to achieve wins and maximize their earnings.

This paper explores shot type consistency, demonstrating the superior consistency of the long game compared to the short game through regression and correlation analyses. These analyses are conducted season-to-season, tournament-to-tournament and round-to-round using seven seasons of professional golf data. Additionally, we examine the types of shots that contribute to improvements within the field.

Through analyzing average gains across evenly distributed groups and employing a regression model, we find that SG: APP is the most important type of shot, followed by SG: PUTT, SG: OTT and finally SG: ARG. Additionally, when considering both empirical earnings data and a regression model, we find that SG: PUTT becomes less important. Top players primarily win their earnings through SG: APP, followed by SG: OTT, SG: PUTT and finally SG: ARG shots. Next, we examine where strokes are gained at different levels of earnings and find that SG: APP makes up most of the SG increases across the field, followed by SG: PUTT, then SG: OTT and SG: ARG.

In this paper, we extend previous research by analyzing the entire professional golf association field rather than focusing solely on amateurs or small sections of the professional field; we also conduct our analysis using SG instead of traditional stats.

Purpose of the study is to further expand insights into how weather impacts attendance at sporting events. With the NFL having only eight home games a year per team, it is more of an event than other North American sports. We explore this in terms of how sensitive fans are to weather, by not only looking at traditional factors, but also other weather variables available through Accuweather. In addition, the authors explore team success, outcome uncertainty and other factors as determinants of demand.

The method includes Tobit model of attendance in terms of percent of capacity in the National Football League. Model includes factors such as outcome uncertainty, team success, etc. but mainly focuses on weather. Weather factors studied include traditional variables such as temperature and precipitation, and also includes cloud cover, barometric pressure, wind speed and humidity. Different model specifications are included to explore results. Key findings allow for differences between games played outdoors versus indoors.

In terms of control variables, team success, new stadiums and stadium age play a significant role in attendance in terms of percentage of capacity. Outcome uncertainty does not appear to be important, and fans desire the opposite when the home team is an underdog. The main results concern the weather. When only traditional weather variables are included, precipitation plays a key role. With further expansion of the weather variables, it appears that cloud cover offers some additional information beyond precipitation. In addition, barometric pressure plays a minor, but statistically significant role as it relates to attendance in terms of capacity.

Including deeper and richer weather data helps to further explain attendance at sporting events. With the NFL, this may be limited by it being such as event due to the scarcity of games in a season. In addition, the weather variables are not truly independent, although they are not as correlated as may be anticipated on the surface. Use of different types of weather variables in models of attendance may help to deepen our understanding of factors influencing consumer decisions. These factors may play larger roles in sports with wider variance in attendance during the season.

The practical implications are that other weather-related variables besides temperature and precipitation may offer insight into consumer decisions related to attendance at sporting events. Cloud cover gives insights into anticipated poor weather in addition to it directly leading to less of a sunny day to be outdoors at an event. Barometric pressure has been shown to influence headaches and joint pain and may also influence consumer decisions to venture out to sporting events.

As data becomes more widely available in general, it's possible to add additional insights into factors influencing various forms of decision-making. In this study, we show that more information on weather can shed insights into consumer decisions as it relates to attending events such as sports. These decisions likely differ based upon whether the event is held outdoors or indoors. With more entertainment choices as substitutes, it is important to identify key factors which influence consumer decisions to help better structure events in the future.

Weather variables beyond temperature and precipitation are included in a Tobit model for NFL attendance using percentage of capacity as the dependent variable. These weather variables are cloud cover, wind speed, humidity, and barometric pressure. Cloud cover and barometric pressure were found to have some significant effects on percentage of capacity. When included, precipitation itself is no longer found to be significant, but precipitation interacted with games played in domes retains statistical significance as there are key differences between games held outdoors versus indoors.

The purpose of this paper is to analyze how the coronavirus disease 2019 (COVID-19) countermeasures will affect the financing of the North American leagues. In particular, we focus on the missed revenue from gate receipts for the Big Four leagues.

The authors forecast the 2020 revenue for each of the four major leagues under two scenarios: (1) expected revenue under the normal conditions of fans in attendance and (2) expected revenues in the absence of fans due to the countermeasures in place. Then, the authors calculate the loss in gate receipts as a difference in the revenue under fans and no-fans scenarios.

Based on the current estimates, the combined financial loss of the clubs from NFL, MLB, NBA and NHL is expected to be above 6.8bn dollars in gate receipts alone.

The findings are useful to the league management to prepare for the suboptimal financial situation.

To the best of our knowledge, this is the first study that explores the effect of the COVID-19 pandemic across the major league sports leagues in North America.

Undergraduate leadership courses are becoming increasingly important venues to promote civic engagement. Despite their prominence, the nature of civic engagement in leadership courses has not been examined systematically. This study examined 77 introductory undergraduate leadership courses and the role of civic engagement in these courses. Results indicate that civic engagement components are not widely utilized, and when they are part of the curricula, their implementation and design vary. Recommendations for improving undergraduate leadership curricula are offered.

Using administrative, longitudinal data on felony arrests in Florida, we exploit the discontinuous increase in the punitiveness of criminal sanctions at 18 to estimate the deterrence effect of incarceration. Our analysis suggests a 2% decline in the log-odds of offending at 18, with standard errors ruling out declines of 11% or more. We interpret these magnitudes using a stochastic dynamic extension of Becker’s (1968) model of criminal behavior. Calibrating the model to match key empirical moments, we conclude that deterrence elasticities with respect to sentence lengths are no more negative than − 0 . 13 for young offenders.