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This paper aims to predict a college football team’s competitiveness using physical resources, human resources and organizational resources.

Guided by the resource-based theory, the study used archival data of 101 college football teams. The dependent variable was competitiveness (indicated by win-loss records), the independent variables were physical resources (operationalized as home attendance and total revenues), human resources (measured as coaches’ salary and coaches’ experience) and organizational resources (specified as conference rankings and the number of sports). Kendall Tau correlation and binary logistic regression were used to examine the associative and predictive competitive advantages.

The binary logistic regression model showed an overall percentage predictive correctness of 71.3%, with a Negelkerke R² of 41.1% of the variance of all predictors – with coaches’ experience, total revenues and home attendance being the best predictors of generating competitive advantages that produced superior win-loss records.

The research focused exclusively on physical, organizational and human resources as sources of competitive advantage and not physiological and/or psychological variables.

College football teams aspiring to be competitive may benefit from this study by applying a three-fold strategy of hiring well-paid high performing and experienced coaches who can increase attendance and revenues.

The study was unique in two ways – one, it made clear the positive significance of coaches’ experience as a source of competitive advantage, and second, it highlighted the catalytic effects of revenues and attendance in fueling competitiveness.

This article seeks to enhance the understanding as to why head coaches and general managers (GMs) in the National Basketball Association (NBA) and the National Football League (NFL) exit from their positions.

Three hypotheses were investigated using a series of quantitative and qualitative data from the past 30 years. The samples analyzed are comprised of 891 GM and coach annual observations for the NBA clubs and 949 GM and coach observations for the NFL clubs. Analyses include a logit analysis for coach exit/retention, a logit analysis for GM exit/retention and textual analysis via topic modeling via latent Dirichlet allocation.

Results show a correlation between a coach exiting and a GM exiting simultaneously, thus amplifying the importance of these two roles in enhancing or destroying the success of a club and supporting the need for a deeper understanding of both roles, particularly the GM. The results further highlight cultural differences across clubs in terms of GM and coach turnover, a factor that often is heavily influenced by club ownership.

The results support the role of owners in exits, confirm the importance of winning in avoiding an exit, find a high level of interrelationship between GM and coach exits and show that past culture of firings influences future exit decisions.

The purpose of this paper is to analyse the effects of first-mover advantage (FMA) on revenue generation capacity (RGC) of US college football programmes during the 2008 global financial crisis.

The study used archival data analysed quantitatively using non-parametric regression in the form of binary logistic regression. The study was then framed and interpreted by the resource-dependence theory.

FMA was positively and statistically associated with donations, branding, media rights and ticket revenues, but not win–loss records. The binary logistic regression model was correctly classified at 82.1 per cent of the variance and indicated that branding and ticket revenues were mostly associated with FMA.

The study was delimited to public college football programmes in the USA during the 2008 global financial crisis.

The findings indicated that despite the 2008 global financial crisis, FMA was positively associated with RGC but not win–loss records.

The study was pioneering in evaluating the effects of FMA as a source of competitive advantage in college football programmes during the challenging time of the 2008 global financial crisis.

This study aims to predict the determinants of net income of 101 US university football programs.

Guided by stakeholder theory, financial capacity model and resource dependency theory, the dependent variable was net income (indicated as profit or loss) and independent variables were measured as the number of women and men’s team sports, average home attendances, win–loss records, conference ranking, endowment funds and age of football programs. Statistical analysis was performed using Kendell tau and binary logistic regression (BLR).

Net income was positively and statistically associated with home attendance, win–loss record, conference rankings and endowment funds, but not number of women’s sports, age of football program and number of men’s sports teams. The BLR indicated that home attendance was the best predictor of net income.

The research was delimited to 101 Football Bowl Subdivision football programs from public universities.

The findings indicate that home attendance and conference rankings had the highest association with net income, but the former was the best predictor of net income and not football tradition nor number of sports teams.

The study was pioneering in the predictive evaluation of the possible determinants of loss or profitability in college football programs.

This study examined the determinants of attendance at the Chilean national soccer tournaments between 1990 and 2002. A multilevel model approach was taken to estimate the effects of several factors, including unobserved sources, hypothesised to influence attendance in Chile. Results regarding team success, team division, population, stadium size and habitual persistence were found to influence professional soccer attendance; other factors such as admission price, age of team, international success, availability of soccer teams in the same vicinity and stadium ownership did not.

This paper investigates the role of competitive balance among teams in a league in predicting attendance at spectator sporting events. It also controls for the demographic and economic characteristics of the league's markets, and changes in the number of teams in the league. The research relies on a sample that includes 707 non-major professional team seasonal win-loss records (12,956 games) from five sports, aggregated into 75 seasons to develop a model consistent with extant literature. The authors find that competitive balance and average income in the league's markets are significant predictors of leaguewide attendance.

The purpose of this paper is to address the problem of designing league regulatory mechanisms given the multi-dimensionality of competitive balance and the proliferation of empirical measures.

A three-stage approach is adopted. Firstly, a taxonomy of empirical measures of competitive balance is proposed, identifying two fundamental dimensions – win dispersion and performance persistence. Secondly, a simple two-team model of league competitive balance is used to explore the dispersion–persistence relationship. Third, correlation and regression analysis of seven empirical measures of competitive balance for the 18 best-attended top-tier domestic football leagues in Europe over the 10 seasons, 2008–2017, are used to (1) validate the proposed categorisation of empirical measures into two dimensions; and (2) investigate the nature of the dispersion–persistence relationship across leagues.

The simple model of league competitive balance implies a strong positive dispersion–persistence relationship when persistence effects increase for big-market teams relative to those for the small-market teams. However, the empirical evidence indicates that while leagues such as the Spanish La Liga exhibit a strong positive dispersion–persistence relationship, other leagues show little or no relationship, and some leagues, particularly, the English Premier League and top-tier divisions in Belgium and Netherlands, have a strong negative dispersion–persistence relationship. The key policy implication for leagues is the importance of understanding the direction and impact of dispersion and persistence effects on the demand for league products.

The variability in the strength and direction of the dispersion–persistence relationship across leagues is an important result that undermines the “one-size-fits-all” approach to designing league regulatory mechanisms.

Given the importance of image matching as a rationale for sponsorship investment, this paper examines the extent to which image matching occurs in U.S. intercollegiate athletics. Utilizing student-athlete education and athletic program ethics as image dimensions, while controlling for winning, the authors find that individual corporations tend to sponsor athletic programs that project very different images. The authors then prescribe an approach that prospective sponsors could use to determine appropriate image matches.

The purpose of these studies is to determine how maximizing sport fans seek optimal outcomes through team identification. Maximizers seek optimal outcomes but do not always obtain them. This may be particularly true of sport fans, who often identify with teams for reasons that run deeper than team success. Maximizing fans may be more concerned with being the best fans than following the best teams.

In Study 1, the authors measured maximizing tendency and identification with participants’ favorite National Football League (NFL) teams. The authors then used moderated regression to predict identification levels from the interaction of maximizing and the historical win–loss records of these teams. In Study 2, the authors manipulated team success by providing participants either an optimistic or pessimistic preview of their college basketball team’s upcoming season. The authors measured maximizing tendency as a moderator of this relationship and identification with the college basketball team as the dependent variable.

In Study 1, maximizers identified more strongly with their favorite NFL team when their favorite team was a historically unsuccessful team. In Study 2, maximizers identified more strongly with their college basketball team after reading a pessimistic preview of the team’s upcoming season than after reading an optimistic preview of that season.

Study 1 required participants to self-report their favorite NFL teams, so the results were only correlational. However, the authors were able to address this limitation with an experimental Study 2.

There are a number of potential implications for sport marketing strategy. For one, sport marketers may want to appeal to fans’ desire to be the best by supporting their teams when they need it most, particularly for teams that are not performing well.

This is the first examination of team or fan identification in the context of maximizing tendency.

The aim of this study is to demonstrate suitability of the continuous improvement framework and use of benchmarking method in the context of sports.

This study uses non‐financial performance measures that are indicative of performance and are closely related to the desired outcomes. Use of such measures seems necessary in the sports and appropriate in relation to professional sports organizations' recruiting, attendance, and profit maximizing objectives. Analyses of this study are based on data of National Basketball Association (NBA) games over three basketball seasons.

The results indicated significant correlation between attendance and winning percentages. Furthermore, the results suggest that a team can improve its winning percentages by changes in the roster that help it emulate superior teams. Comparing teams that advanced in a given season and reach the playoffs with those that did not, revealed the more important skill factors for success in the NBA. The results also indicated that some players' skills might be more critical for a given team in reaching the playoffs.

The results presented in this paper are influenced by the NBA's basketball rules. Because basketball rules are not the same for all leagues and such rules change over time, the findings are time‐specific and should be considered in that light. Additionally, the research design used in this study must be modified for other professional sports.

This paper provides an example for application of continuous improvement framework to professional sports.