ISSN: 1543-9518

The New Era of College Athletics Has Gone a Bridge Too Far

Author: Matthew J Williams1

1Department of Education, The University of Virginia’s College at Wise, Wise, VA, USA 

 

Matthew J. Williams D.S.M., M.B.A., M.S., is an Associate Professor of Sports Management at The University of Virginia’s College at Wise. His areas of research interest include NASCAR, COVID-19, college athletics, professional sports, and issues in sports management.

ABSTRACT 

The NCAA has always had a firm stance that to survive, it must keep its amateurism status. The NCAA had rules in place that required colleges and universities to recruit student-athletes to play for them.  It could only offer them compensation through free tuition, textbooks, room, and board; no direct money could be involved.  Over the past decades, the NCAA has grown in popularity and generated a tremendous amount of revenue. At the same time, society was noticing that the NCAA was taking advantage of the student-athlete through its amateurism rules.  The NCAA found itself constantly in court defending its actions regarding amateurism. After years of litigation, the NCAA settled out of court, resulting in the House Settlement, which created a new era in college athletics. These changes will allow student-athletes to receive financial compensation directly from colleges and universities. This new era will continue to bring a tremendous amount of financial burden to athletic departments’ budgets. This may lead to reductions in non-revenue sports, team roster sizes, and athletic staff.  

KEYWORDS: Revenue sports, non-revenue sports, House Settlement, NCAA, amateurism, revenue sharing, NIL

INTRODUCTION 

In the past, student-athletes were very satisfied with receiving an academic/athletic scholarship from a college or university that included free tuition, textbooks, room, and board. In return, student-athletes would participate in varsity athletics for the college or university.  Today’s philosophy has shifted, emphasizing that student-athletes should be directly compensated financially.  Over the past twenty years, college athletics has witnessed a massive growth in popularity that has resulted in bigger television contracts, sold-out stadiums, increased revenue from corporate sponsorships, and souvenir sales. Student-athletes started to take notice of the popularity of college athletics, financial success, and the abundance of revenue that they were producing for the NCAA, colleges, and universities. They felt they should receive more compensation than just free tuition, textbooks, room, and board. At the forefront of every collegiate student-athlete’s mind in recent years is the question: “should I be getting paid for this?” (Tremps, 2024).

Most college fans, alumni, television announcers, media, and state governments believed the NCAA, colleges, and universities were exploiting the student-athletes. They all believed that student-athletes should receive more financial compensation than just free tuition, textbooks, room, and board. After all, student-athletes were generating all the revenue.

The NCAA became a billion-dollar industry off these young men and women, and they received no monetary compensation in return. Some argued that students were getting a free education out of it, but over time, that seemed to become irrelevant to many college players (Cabibi, 2022).

Discussion

NCAA’s History with Amateurism

When the NCAA was formed in the early 20th century, its cornerstone belief was built around amateurism and did not revolve at all around pay-to-play. Colleges and universities that were NCAA members in any division of athletics were not allowed to financially pay student-athletes directly. During its formation in 1906, the NCAA highlighted amateurism, or unpaid participation, as a core aspect of its student-athletes (Hart, 2024).  NCAA athletes playing for free has always been a feature of the product (Lombardi, 2024).

The only type of financial support that the NCAA would allow colleges or universities to offer student-athletes was free tuition, textbooks, and room and board. The trend of not paying student-athletes financially was accepted by fans, alumni, and media. It was considered an honor and a privilege of amateurism. Many fans felt that the student-athletes were playing for the pride of the college or university and the love of the game. For many fans, amateurism was an endearing aspect, suggesting that young athletes are playing for pride, the love of the game, and the honor of their institution (Lombardi, 2024).

Over the past few decades, societal thoughts have shifted around feelings of amateurism in college athletics, and now think that student-athletes should be financially compensated. The NCAA has held a firm stance on the importance of keeping the amateurism status in college athletics. If they were to allow student-athletes to be financially paid directly, other than through free tuition, textbooks, room, and board, it would significantly hurt the student-athletes’ amateur status. The NCAA prohibited student-athletes from being paid in the past to protect their “amateurism” (McCool, 2023).

With the philosophy changing about financially paying student-athletes, the NCAA found itself in the crosshairs with the media, fans, athletes, and state governments demanding that the NCAA has to do more than just allow colleges and universities to offer student-athletes free tuition, textbooks, room, and board.  They were pressuring the NCAA to eliminate its ancient rules on amateurism and allow student-athletes to be financially compensated by colleges and universities.

However, the NCAA failed to act on eliminating amateurism and stuck to its core belief about the importance of amateurism. Unfortunately, failing to act on this issue resulted in numerous lawsuits against the NCAA. Numerous lawsuits have challenged the amateur aspect of NCAA competitions (Hart, 2024).

Pressure from the media, sports broadcasters, and fans to allow student-athletes to profit from the use of their name, image, and likeness kept growing rapidly. Unfortunately, the NCAA continued to ignore the pressure to change bylaws that would allow student-athletes to do this. The failure to change its stance on this issue resulted in new state legislation.

The California State Legislature was the first to propose a bill to allow student-athletes to accept endorsement money for the use of their name, image, or likeness and not be punished by California universities. The state legislature passed this bill, and in 2019, California Governor Gavin Newsom signed the first bill to allow student-athletes to accept endorsement money. California Governor Gavin Newsom signed a bill in September 2019 stating that, starting in 2023, universities in the state couldn’t punish athletes for accepting endorsement money while in college (Moore, 2022).

The passage of California’s legislation created pressure on other states to do the same.  Passing legislation to allow student-athletes to receive compensation for their endorsement deals concerning name, image, and likeness.

NCAA’s Litigation Battles

In 2014, the NCAA found itself in litigation with NCAA v. Alston. The lawsuit brought against the NCAA was that they were violating the Sherman Antitrust Act by not allowing student-athletes to profit from their Name, Image, and Likeness. The case went all the way to the U.S. Supreme Court, and in July 2021, the U.S. Supreme Court ruled in favor of Alston. In July 2021, the Supreme Court’s ruling on NCAA v. Alston allowed college athletes to receive money based on their Name, Image, and Likeness (Munn, 2023).

The Alston ruling was a tremendous blow to the NCAA’s stance on amateurism, forcing them to adopt new bylaws that would allow student-athletes to profit from their Name, Image, and Likeness. This was a complete turnaround from student-athletes being punished for receiving financial assistance.  Members of the NCAA’s Board of Directors decided Wednesday to hop on this NIL train instead of getting crushed while trying to stand in front of it (Moore, 2022).

Litigation cases against the NCAA did not slow down after the Alston ruling. Instead, the lawsuits became bigger with more at stake financially for the NCAA, colleges, and universities. In 2020, House v. NCAA. Grant House, a student athlete who was a swimmer from Arizona State, and Sedona Prince, who was a women’s basketball player, and two other suits that were filed by college athletes. All three lawsuits against the NCAA were combined into one. A 2020 lawsuit by Arizona State swimmer Grant House and women’s college basketball player Sedona Prince, along with two separate suits by other college athletes, which were combined into one case (Jones, 2025).

The House lawsuit was based on the NCAA’s alleged violation of antitrust laws. The bylaws set by the NCAA prohibited the opportunity for student athletes to benefit financially from their Name, Image, and Likeness.  Violated antitrust law by collectively agreeing to not provide benefits and compensation to student-athletes and denying student-athletes the opportunity to profit from the use of their name, image, and likeness (Jones, 2025).

The loss of previous antitrust lawsuits against the NCAA led to the realization that the current NCAA bylaws, allowing student-athletes only to receive free tuition, textbooks, room, and board, could no longer exist. They recognized there was no chance of winning the case and decided to settle out of court. On June 6th, 2025, Judge Claudia Wilkens approved the House settlement. The settlement would now allow colleges and universities to directly pay student-athletes for their participation in college athletics. On June 6, 2025, the Northern District of California in House v. NCAA approved a landmark settlement deal allowing colleges and universities to pay their students directly for their participation in college athletics (Cernea & Pennesi, 2025). 

The House settlement also eliminated three additional antitrust lawsuits against the NCAA, which was accused of not allowing student-athletes to profit off their Name, Image, and Likeness. The House v. NCAA settlement ends three separate federal antitrust lawsuits, all of which had claimed the NCAA was illegally limiting the earning power of college athletes (Murphy, D., 2025). The House settlement agreement also included continuation of the NIL along with back pay, roster limits, and revenue-sharing, which started July 1, 2025.

Financial Fallout from House Settlement

The most significant part of the House Settlement was the revenue-sharing agreement that required all Power Five Conferences to participate in. The agreement was put into place to allow student-athletes to be paid directly from colleges or universities. All other Division I Universities were not required to participate in the agreement, but each college or university could choose to either opt in or opt out. Schools are now free to begin paying their athletes directly, marking the dawn of a new era in college sports (Murphy, D., 2025). 

The agreement now allows athletic departments to distribute directly to the sports programs of their choosing about a fourth of their annual revenue, roughly $20.5 million, this academic year. The annual percentage of revenue-sharing will increase each academic year after that. The athletic department’s revenue comes from ticket sales, corporate sponsorships, onsite advertising, concessions, auctions, donations, and, most importantly, media rights. Schools may distribute up to 22% of their revenue from ticket sales, sponsorship revenue, and media rights (Cernea, 2025). Schools will be allotted $20.5 million of revenue per school (Cernea, 2025).

Before the House settlement, colleges and universities’ athletic departments relied on a variety of revenue-generating streams, including ticket sales, corporate sponsorships, and, most importantly, media rights to finance their athletic programs. The implementation of revenue-sharing will create tremendous financial challenges for presidents and athletic directors to keep their athletic programs profitable.

Not all Division I athletic sports offered at colleges and universities are profitable at all. However, there are some sports that either break even or generate a profit: these include men’s basketball, women’s basketball, and football. Even more profitable programs are questioning how they will come up with the money. The Associated Press quoted Alabama Athletic Director Greg Byrne, who told Congress “Those are resources and revenues that don’t exist” (Jones, 2025).

Most colleges and universities’ athletic departments’ budgets at the Division I level across the country will either end in a deficit or break even every year; very few colleges or universities’ athletic departments make a profit. According to financial filings, Alabama reported a $28 million operating deficit during the last fiscal year (Peterson, 2025).  All but a handful of Division I athletic departments operate as revenue-neutral (Schnable, 2025). 

Each year, Division I conferences receive revenue distribution from the NCAA, which helps athletic departments fund all their sports. Because of the House settlement, along with the massive legal issues that the NCAA has gone through in the past few years. The NCAA was forced to distribute less money to all Division I conferences. It’s also expected to reduce the annual distributions all D-I conferences receive, as the NCAA covers damages (Christovich, 2025).

 To survive the new era of college athletics and be competitive in athletics, presidents and athletic directors will have to redistribute monetary resources from non-revenue sports to their three revenue-generating sports. We have one team that makes a healthy profit in football. We have one that turns a profit in men’s basketball.  We have 19 that don’t,” Byrne said (Peterson, 2025).

Texas Tech Red Raiders athletic director made a clear message to the public that the new revenue-sharing model would concentrate almost all revenue-generating sports, which are football, men’s basketball, and women’s basketball. Red Raiders will allocate $15.1 million to its football roster (74%), $3.6 million to men’s basketball (17.5%), $410,000 to women’s basketball (2%) (Dellenger, 2025). 

A big challenge facing presidents and athletic directors is justifying non-revenue sports and why they should keep them. An argument can be made that non-revenue sports simply do not generate enough revenue to pay their bills. Athletic departments are under tremendous pressure to make a profit or at least break even every year. It gets harder to pay for sports that lose money, which is everything that’s not football or basketball (Talty, 2025).

 Five years ago, when the COVID-19 pandemic hit college athletics, it decreased many revenue streams that colleges and universities’ athletic departments relied on.  The pandemic forced presidents and athletic directors to find creative ways to trim their athletic budgets. They eliminated some non-revenue sports and laid off athletic support staff to balance their athletic budgets. To this day, some colleges and universities’ athletic departments still have not fully recovered financially from the pandemic.

 No one would have ever thought that college and university athletic departments would have to do the same thing again. Because of the House settlement, athletic directors and presidents will continue to look and see where cuts can be made to fund the new era of college athletics. Just as they did during the COVID-19 pandemic, they will be forced once again to eliminate some athletic support staff and some non-revenue sports.  “I didn’t think another year would be as tough as COVID [in 2020], but this year has done that,” Yurachek said (Murphy, T, 2025).

Restructuring of Athletics Programs

With the new era of college athletics now in place, athletic directors and presidents will be forced to devote more money to the three revenue-generated sports, which could inflict damage on non-revenue sports budgets. Some non-revenue sports, such as cross country, volleyball, tennis, wrestling, track and field, could either be eliminated or have their roster size reduced. Athletic budgets no longer have enough money to support all the non-revenue sports that generate zero revenue for the athletic departments.   As more NIL money is dedicated to football over all other sports on campus, many teams are at risk to be disbanded when there is no money to support their program (Stankovich, 2025).  The doomsday option is eliminating sports altogether, which some schools are already doing with sports like tennis that neither bring in revenue nor television exposure (Talty, 2025). 

A big concern about athletic departments cutting non-revenue sports is the fact that they produced many of our current or future Olympic athletes. If this does happen, many of our future Olympic athletes could be in jeopardy. Schools have outright used the House v. NCAA settlement as justification to cut Olympic sports programs (Christovich, 2025).  There are deep concerns about the potential impact on sports that feed the U.S. Olympic teams (Carey, 2025).

To help reduce financial increases, athletic departments are facing now and in the future. The NCAA has decided to move away from the standard rules of scholarship limits. Now they will impose roster sizes instead for all Division I competing sports. Unfortunately, by the NCAA implementing these new rules on roster sizes, it could effectively eliminate walk-ons. Roster limitations is expected to leave walk-ons, partial scholarship earners, nonrevenue sport athletes and high school recruits at risk (Carey, 2025).

One of the biggest revenue generators for athletic departments is NIL collectives. These collectives are organizations separate from colleges or universities’ athletic departments that generate revenue to help pay for the students’ athletic performance. Unfortunately, most collectives’ money is usually designated for the revenue-producing sports. Collectives generally pay for the athlete’s performance (Hart, 2024). NIL collectives generate revenue from fundraisers, local or national businesses, donations from boosters, alumni, and fans. Collectives are organizations that collect funds from businesses and boosters to facilitate NIL deals for athletes (Hart, 2024).

Financial Cost to Student Body and Fans

To generate more revenue for athletic departments, state legislators have gotten involved in paying student-athletes.  Legislation has been passed that will allow institutional funds from colleges or universities to be given to athletic departments to help pay student-athletes. In Missouri, a state law has existed for more than a year permitting the school’s collective to receive institutional funds for distribution to athletes (Dellenger, 2024).  Some colleges or universities either have or are in the process of raising student fees to help athletic departments pay their student-athletes. South Carolina announced a new annual $300 athletics auxiliary fee (Rumsey, 2025). 

With the implementation of revenue sharing and the NIL athletic departments are now being forced to find creative ways to generate new revenue streams. The University of Tennessee’s athletic department has found an additional revenue source in its ticket sales. They now charge each ticket purchased a 10% talent fee to generate more revenue to pay their student-athletes.  Tennessee fans for all sports will be charged a 10% “talent fee” on tickets to help pay athletes as part of the new revenue-sharing plan set to begin in 2025 (Low, 2024). During the Football bowl season, the NCAA has allowed bowl sponsorship patches to be placed on football jerseys. Now conferences and or individual schools are seeking approval from the NCAA to allow advertisement on their game day jerseys to generate additional revenue for the athletic departments. The NCAA’s expected and eventual approval of commercial jersey patches looms large (Dellenger, 2025).

CONCLUSIONS

Athletic department budgets had already been strained from the COVID-19 pandemic. There was a heavy financial toll on many college and university athletic budgets. The House Settlement created additional expenses for athletic departments’ budgets. Presidents and athletic directors know that to be competitive, they must allocate all the necessary resources that they have to their revenue-generating sports to survive financially.

The settlement has caused catastrophic destruction to college athletics. The settlement could seriously damage our U.S. Olympic stronghold; it will eliminate the walk-on dreams and take away the chance for many student-athletes’ opportunities to play college athletics. The settlement rewards only a minority of student-athletes, not the majority. It has created a new era of college athletics that is hurtful and not financially sustainable long term. Lastly, this settlement has created a new era of college athletics that has truly gone a bridge too far.

REFERENCES 

1. Cabibi, S. R. (2022, March 15). How money, greed, and the nil destroyed college football… or did it?. Medium. https://medium.com/@seancabibi/how-money-greed-and-the-nil-destroyed-college-football-or-did-it-5e1ea268df4d

2. Carey, M. (2025, May 8). “hands tied”: Athletes left in dark as NCAA settlement leaves murky future for nonrevenue sports. AP News. https://apnews.com/article/ncaa-house-settlement-37ad7713f540c4597627116b1f219483

3. Cernea, E. H., & Pennesi, E. J. (2025, June 18). Long-awaited settlement agreement raises new challenges for Nil Licensing deals. Long-Awaited Settlement Agreement Raises New Challenges for NIL Licensing Deals –. https://www.morganlewis.com/blogs/sourcingatmorganlewis/2025/06/long-awaited-settlement-agreement-raises-new-challenges-for-nil-licensing-deals

4. Christovich, A. (2025, June 19). Olympic sports face cuts in wake of House v. NCAA settlement. Front Office Sports. https://frontofficesports.com/dozens-of-olympic-sports-have-been-cut-in-wake-of-house-v-ncaa-settlement/

5. Dellenger, R. (2024, May 28). The next evolution of Nil Collectives and the battles that await: “this is a big inflection point.” Yahoo! Sports. https://sports.yahoo.com/the-next-evolution-of-nil-collectives-and-the-battles-that-await-this-is-a-big-inflection-point-120051261.html

6. Dellenger, R. (2025, January 7). With nil era ending, college sports is on verge of seismic change. how will schools adapt with industry in upheaval?. Yahoo! Sports. https://sports.yahoo.com/with-nil-era-ending-college-sports-is-on-verge-of-seismic-change-how-will-schools-adapt-with-industry-in-upheaval-154722732.html

7. Hart, J. (2024, September 27). Is nil a good thing or a bad thing? sports industry expert weighs in. Temple Now . https://news.temple.edu/news/2024-06-10/nil-good-thing-or-bad-thing-sports-industry-expert-weighs

8. Jones, S. (2025, May 16). House v. NCAA settlement complicated–and still not yet settled. University Times. https://www.utimes.pitt.edu/news/house-v-ncaa-settlement

9. Lombardi, E. (2024, October 3). Right now, nil is bad for college football. Medium. https://spec.hamilton.edu/right-now-nil-is-bad-for-college-football-809c8af4b9ec

10. Low, C. (2024, September 17). Tennessee increases ticket prices by 10% to help pay athletes. ESPN. https://www.espn.com/college-football/story/_/id/41302985/tennessee-ups-season-ticket-prices-10-help-pay-athletes

11. McCool, J. (2023, November 9). Why name, image and likeness policies could ruin college sports. FSView. https://www.fsunews.com/story/opinion/2023/11/09/why-name-image-and-likeness-policies-could-ruin-college-sports/71508112007/

12. Moore, T. (2022, November 9). NCAA had no choice, but nil rule will damage college football and basketball. Forbes. https://www.forbes.com/sites/terencemoore/2021/07/06/the-ncaa-hadnt-a-choice-but-nil-rule-will-damage-college-football-and-basketball/

13. Munn, T. (2023). What is name, image, and likeness? explained by NCC News. NCC News. https://nccnews.newhouse.syr.edu/college-athletes-can-now-get-paid-but-how-name-image-and-likeness-explained-by-ncc-news/

14. Murphy, D. (2025, June 6). Judge OK’s $2.8B settlement, paving way for colleges to pay athletes. ESPN. https://www.espn.com/college-sports/story/_/id/45467505/judge-grants-final-approval-house-v-ncaa-settlement

15. Murphy, T. (2025, June 27). Arkansas Athletic Department makes staff cuts in preparation for “major changes” with revenue sharing. Whole Hog Sports. https://www.wholehogsports.com/news/2025/jun/27/arkansas-athletics-department-makes-staff-cuts-in-preparation-for-major-changes-with-revenue-sharing/

16. Peterson, D. (2025, June 20). Alabama athletic director comments on future of non-revenue tide teams. Saturday Down South. https://www.saturdaydownsouth.com/news/college-football/alabama-athletic-director-comments-on-future-of-non-revenue-tide-teams/

17. Rumsey, D. (2025, June 23). Colleges raising student fees to pay for athlete revenue-sharing. Front Office Sports. https://frontofficesports.com/colleges-are-raising-student-fees-to-pay-for-athlete-revenue-sharing/

18. Schnable, A., & Thompson, S. (2025, July 1). House Settlement FAQ: What will college sports look like after landmark legal case?. Post-Gazette. https://www.post-gazette.com/sports/pitt/2025/07/01/house-settlement-faq-ncaa-nil/stories/202506300051

19. Stankovich, C. (2025, March 19). College athletics at a crossroads: Nil, transfer portals, and eliminating non-revenue sports. The Sports Doc Chalk Talk with Dr. Chris Stankovich . https://drstankovich.com/college-athletics-at-a-crossroads-nil-transfer-portals-and-eliminating-non-revenue-sports/

20. Talty, J. (2025, June 7). The biggest winners and losers from House v. NCAA settlement: Amateurism is dead and the class divide grows. CBSSports.com. https://www.cbssports.com/college-football/news/the-biggest-winners-and-losers-from-house-v-ncaa-settlement-amateurism-is-dead-and-the-class-divide-grows/

21. Tremps, N. (2024, October 14). The memorandum heard around the college athletics world: Why student-athletes in non-revenue-generating sports should not enjoy the status of “employee” under the NLRA. Wake Forest Law Review. https://www.wakeforestlawreview.com/2024/04/the-memorandum-heard-around-the-college-athletics-world-why-student-athletes-in-non-revenue-generating-sports-should-not-enjoy-the-status-of-employee-under-the-nlra/

2025-10-31T13:04:38-05:00July 7th, 2026|Contemporary Sports Issues, Research, Sports Coaching, Sports Management, Sports Studies|Comments Off on The New Era of College Athletics Has Gone a Bridge Too Far
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Basketball and black America: Exploring the intersections of race, fan involvement and community engagement

Author: Isabell L. Mills1

1Department of Kinesiology, Health and Sport Sciences University of Indianapolis

Corresponding Author:

Isabell L. Mills, Ph.D.

1400 E Hanna Ave., HEAL 364

Indianapolis, IN  46227

Email: Dr. Mills ([email protected])

Office Phone: 317-788-2403

Departmental Fax: 317-788-3542

ABSTRACT

Purpose:
This study explored the cultural, social, and community significance of basketball within Black America through a case study of The City League in Indianapolis. The purpose was to understand how basketball functions as a cultural anchor, pathway for opportunity, and tool for community engagement among African American spectators and participants.

Methods:
A qualitative approach was used with one semi-structured focus group of eight African American spectators (four men, four women), all over 18 years old. The session lasted 60 minutes and was audio recorded, transcribed, and analyzed using margin coding by two independent coders. Triangulation with field notes from league games and events enhanced trustworthiness.

Results:
Seven themes emerged across two domains: basketball in the Black community and The City League’s role. Participants viewed basketball as a foundation of cultural identity, family heritage, and social connection. The sport served as a vehicle for education, leadership, and personal development, while also providing emotional support and belonging. The City League was described as more than a competition; it fosters mentorship, service, and community pride. Key challenges included limited resources for smaller leagues and barriers to women’s participation linked to time and family responsibilities.

Conclusions:
Basketball operates as both a cultural cornerstone and a platform for empowerment within Black communities. The City League exemplifies how grassroots initiatives can strengthen social bonds, promote resilience, and address systemic inequities through sport.

Applications in Sport:
Sports professionals and organizations can use these insights to create inclusive, culturally grounded programs that expand access and foster authentic community relationships. Investment in local leagues, support for women’s participation, and collaboration with community partners can enhance engagement and sustainability while advancing social impact through sport.

Key Words: cultural identity, community development, marketing, grassroots sports

INTRODUCTION

Introduction

Basketball is deeply embedded within Black culture and functions as more than just a sport. It serves as a mechanism for identity formation, community-building, and economic mobility. The NBA has the highest share of Black viewers of any major American sport, with nearly twenty percent of its audience identifying as Black (Statista, 2025). Viewership alone, however, does not capture the depth of engagement. Basketball extends into grassroots initiatives, recreational leagues, and social justice movements, demonstrating its role as both cultural cornerstone and avenue of empowerment.

Beyond entertainment, basketball is linked to broader issues of economic and social mobility. In 2023, the NBA generated approximately $10.58 billion in total revenue (TOI Sports Desk, 2024). Yet, persistent inequities remain as more than one in three Black children in the United States live below the poverty line, and systemic barriers continue to restrict economic opportunities (IBW21, 2024). Against this backdrop, community-based organizations such as The City League provide essential opportunities for mentorship, engagement, and development pathways for youth and adults alike. This study explores basketball’s cultural and community roles in Black America, focusing on Indianapolis’ The City League. By examining fan and community member perspectives, the research highlights basketball’s role in identity, resilience, and grassroots development.

LITERATURE REVIEW

Scholars have long examined the role of basketball in shaping Black identity and community aspirations. Carrington (2010) conceptualized basketball as part of the sporting Black diaspora, while Spencer (2016) highlighted the sport’s role in cultural politics and resistance. Similarly, Cummings (2018) identified basketball as a tool for youth mentorship and leadership development. Together, these studies frame basketball as both cultural practice and social instrument. The City League embodies these dynamics in practice, serving as a contemporary example of how basketball continues to foster cultural pride, leadership, and community cohesion within Black America.

Basketball also shapes economic and consumer landscapes. Armstrong (2001) demonstrated how race influences NBA consumption behaviors, while Rich (2022) analyzed marketing strategies directed at Black basketball fans. These findings illustrate how basketball extends beyond recreation into the realms of consumer culture and social influence.

Other research emphasizes local and community contexts. Brooks (2011) explored how grassroots leagues foster young Black athletes’ aspirations, while Vieyra (2016) examined pickup basketball’s role in sustaining community ties. These insights reinforce the idea that basketball is not only competitive but also central to cultural preservation and social connectedness. Building on this body of work, the present study investigates how spectators and participants in The City League conceptualize basketball’s broader significance.

The City League

The City League originated in 2013 when members of a Crosstown Neighborhood Association meeting partnered with Little Bethel Missionary Baptist Church to host free basketball open gyms for local youth. The initiative quickly evolved into competitive tournaments, designed not only to enhance basketball quality but also to generate revenue to sustain programming. Early success highlighted the importance of community partnerships, leading to broader collaborations with local businesses and organizations.

Today, The City League has expanded to include both men’s and women’s leagues, with 16 and 7 teams respectively. Partnerships with corporate sponsors, such as CareSource, have further strengthened the league’s ability to provide opportunities for community development, mentorship, and engagement. More than a sporting event, The City League has become a cultural institution within Indianapolis, bridging high-level basketball, local businesses, and grassroots empowerment.

METHODOLOGY

This study employed a qualitative design using semi-structured focus group interviews. One focus group was conducted with eight participants (four male, four female). The purpose of this qualitative study was not to generalize findings to a broader population, but rather to capture rich, nuanced perspectives of African American spectators engaged in local basketball culture. The decision to use one focus group aligns with qualitative traditions that prioritize depth over breadth, particularly when participants share a common context and cultural connection (Krueger & Casey, 2015; Morgan, 1997). The participants were African American spectators of community and recreational basketball leagues in Indianapolis. All participants were over the age of 18.

Materials and Measures

Data were collected during a summer recreational basketball league through a semi-structured focus group lasting approximately 60 minutes. A moderator used a prepared script to guide discussion and ensure that relevant topics were addressed. The focus group session was audio recorded for accuracy.

Procedures

Participants were recruited using purposeful-criterion sampling. Flyers were distributed at league games and open gym sessions, containing QR codes that directed potential participants to an informed consent form and sign-up sheet. Professional basketball game tickets were provided as an incentive for participation.

Data Analysis

Margin coding was conducted by two independent coders. This analysis involves writing preliminary codes or thematic notes in the margins of transcripts to identify emerging patterns and concepts during the early stages of qualitative analysis. Triangulation with secondary sources, including participant observations and field notes collected during league games and a banquet, were used to enhance validity and trustworthiness.

RESULTS

Seven themes were identified across the focus group discussion and confirmed with supplemental field notes. Participants ranged in age from 30 to 58, with equal gender representation. Two overarching categories emerged: (a) basketball and the Black community, and (b) The City League specifically.

Themes Related to Basketball and the Black Community

Basketball as a Cultural and Historical Anchor.
Participants described basketball as deeply rooted in Black history, functioning as a cultural thread that unites families and neighborhoods across generations. One participant shared that their father had been “on the 1955 Crispus Attucks team, one of the first all-Black high school teams to win a state championship,” underscoring how basketball continues to serve as both a point of pride and a source of collective identity within the community.

Basketball as a Vehicle for Personal Growth and Opportunity.
Many participants emphasized basketball’s role in providing pathways for education, leadership, and personal advancement. As one participant explained, the league has helped “over 500 players earn scholarships,” demonstrating how community-level engagement in the sport can translate into tangible academic and professional opportunities.

Basketball as a Community Builder and Mental Health Outlet.
Participants also highlighted basketball’s importance in fostering emotional well-being and providing a sense of belonging. Several described the sport as a “catch net” for Black men, with one participant explaining that it helps “catch men and broken barriers that are systemically in our houses, our communities, our families.” For many, basketball was not simply recreation but a safe space for connection, mentorship, and healing.

Themes Related to The City League

The City League as More Than Basketball.
Participants consistently framed The City League as a transformative community institution. One participant noted that “they aren’t just a basketball league—they are doing fundraisers, feeding people, and collaborating with other organizations,” illustrating the league’s holistic approach to community engagement and service.

Challenges in Women’s Participation.
Female participants discussed barriers related to work, family responsibilities, and limited incentives for women’s involvement. As one participant explained, “Most of us are 30–40, moms, and everything else, so it’s just kind of hard. We need to pass it on and include younger ladies.” This highlights the need for more inclusive structures to sustain women’s engagement in community-based sports.

Lack of Resources for Smaller Leagues.
A recurring concern was the limited access to funding and institutional support for smaller, community-driven leagues compared to larger organizations. One participant reflected, “We all talk about diversity, inclusion, and equity, but nobody is including the inner city,” pointing to perceived disparities in local sports development and municipal investment.

The Future of The City League.
Finally, participants expressed optimism and a shared vision for the league’s growth, particularly in expanding youth involvement. As one participant stated, “We want The City League to impact the youth because the future are the children.” This sentiment underscores participants’ belief in basketball as a conduit for intergenerational continuity, mentorship, and community advancement.

Participants consistently conveyed conviction and passion in describing basketball’s cultural and community significance.

Figure 1. Conceptual model that visually connects basketball’s cultural/community roles with marketing implications and opportunities.

DISCUSSION

The findings highlight basketball’s role as both cultural anchor and tool for empowerment within Black communities. Participants’ reflections align with Carrington (2010) and Spencer (2016), who described basketball’s deep cultural resonance. Basketball was not only entertainment but also a source of identity, support, and resilience. These findings echo Cummings’ (2018) work on basketball’s role in youth development.

Challenges identified such as women’s participation barriers and inequitable funding mirror broader structural inequities. Brooks (2011) noted similar struggles in sustaining community-based leagues, while Rich (2022) argued that authenticity and resource allocation are critical for long-term sustainability. The City League’s model of grassroots empowerment demonstrates potential pathways for bridging sport, community development, and cultural preservation.

Practical Implications

Brands seeking to engage Black basketball fans must ground their efforts in authentic community investment (Rich, 2022). Participants emphasized that basketball represents more than a sport; it embodies culture, history, and connection. The following practical implications emerge from these findings:

  • Prioritize authenticity. Marketing strategies should reflect basketball’s cultural, social, and community-building dimensions. Campaigns that highlight mentorship, historical pride, and empowerment are more likely to resonate.
  • Promote representation and inclusion. Addressing barriers to women’s participation offers opportunities for differentiation. Brands can invest in inclusive programming—such as childcare support or flexible scheduling—to expand engagement among women athletes and fans.
  • Invest in grassroots sponsorships. Supporting smaller, underfunded community leagues builds trust and positions brands as genuine stakeholders rather than transactional outsiders.
  • Adopt a holistic brand perspective. Viewing basketball as a lifestyle rooted in education, mental wellness, and resilience allows brands to align their identities with values central to Black basketball communities.

Limitations

As with all qualitative research, this study has several limitations that should be considered when interpreting the findings. First, the data were drawn from a single focus group with eight participants in Indianapolis, which limits generalizability to broader populations or other geographic contexts. The use of a single focus group represents both a methodological strength and a design limitation. While this approach allowed for rich, interactive discussion and depth of understanding, it also limited the diversity of perspectives that could have been captured through multiple groups or individual interviews. Second, participant perspectives may have been shaped by self-selection bias, as individuals who chose to participate were likely already engaged with basketball culture and The City League. Third, while triangulation with field notes enhanced validity, the absence of additional data sources, such as surveys or interviews with league organizers and sponsors, constrains the depth of analysis. These limitations provide important context for the findings and point toward avenues for future exploration.

Future research

This study provides an exploratory look at the cultural significance of basketball in Black America through the case of The City League. Future research could expand on these findings in several ways. First, additional studies might examine multiple community leagues across different U.S. cities to compare how regional contexts shape the role of basketball in Black communities. Second, quantitative research could complement these qualitative insights by measuring the social, economic, and psychological impacts of community basketball programs on participants. Third, future work could focus on longitudinal outcomes, tracking how sustained involvement in leagues like The City League influences educational attainment, career development, and community engagement over time. Fourth, more focused research on women’s basketball participation in grassroots leagues is needed to better understand gendered barriers and strategies for inclusivity. Finally, scholars might investigate how brands and organizations can authentically partner with community leagues, exploring both best practices and pitfalls in sports marketing and corporate social responsibility.

REFERENCES 

  1. Armstrong, K. L. (2001). The influence of race and fan identification on NBA consumption behaviors. Journal of Sport Management, 15(2), 195-209.
  2. Brooks, S. N. (2011). City of basketball love: Philadelphia and the nurturing of Black males’ hoop dreams. The Journal of African American History, 96(4), 522–536. https://doi.org/10.5323/jafriamerhist.96.4.0522
  3. Carrington, B. (2010). Race, sport, and politics: The sporting Black diaspora. SAGE Publications.
  4. Chin, C. B. (2015). ‘We’ve got team spirit!’: Ethnic community building and Japanese American youth basketball leagues. Ethnic and Racial Studies, 39(6), 1070–1088. https://doi.org/10.1080/01419870.2015.1103878
  5. Cummings, T. (2018). Hoop dreams and community: How basketball fosters Black youth development. Journal of African American Studies, 22(3), 245-263.
  6. Evans, A. B., & Piggott, D. (2016). Shooting for Lithuania: Migration, national identity and men’s basketball in the east of England. Sociology of Sport Journal, 33(1), 26–38. https://doi.org/10.1123/ssj.2015-0028
  7. French, D. (2022). A game and its culture. National Review, National Review.
  8. Institute of the Black World 21st Century. (2024, September 17). New 2024 data highlights ongoing economic disparities faced by Black people due to systemic discrimination. https://ibw21.org/news/2024-data-economic-disparities-systemic-discrimination/
  9. Krueger, R. A., & Casey, M. A. (2015). Focus groups: A practical guide for applied research (5th ed.). SAGE Publications.
  10. Morgan, D. L. (1997). Focus groups as qualitative research (2nd ed.). SAGE Publications.
  11. Rich, A. (2022). Black consumers and the business of basketball: A marketing perspective. Sport Marketing Quarterly, 31(1), 50-68.
  12. Spencer, R. (2016). Ballin’ outta control: Basketball, race, and cultural politics. Rutgers University Press.
  13. Statista Research Department. (2025). Interest level in NBA by ethnicity. Statista. https://www.statista.com/statistics/1098410/interest-level-nba-ethnicity/
  14. Thomas, M. B., & Wright, J. E., II. (2022). We can’t just shut up and play: How the NBA and WNBA are helping dismantle systemic racism. Administrative Theory & Praxis, 44(2), 143157. https://doi.org/10.1080/10841806.2021.1918988
  15. TOI Sports Desk. (2024, September 21). Top 10 richest sports leagues in the world including National Football League, Indian Premier League, and others. Times of India.             https://timesofindia.indiatimes.com/sports/top-10-richest-sports-leagues-in-the-world-including-national-football-league-indian-premier-league-and- others/articleshow/113548384.cms
  16. Vieyra, F. (2016). Pickup basketball in the production of Black community. Qualitative Sociology, 39(2), 101–123. https://doi.org/10.1007/s11133-016-9324-9

2025-10-13T15:23:20-05:00June 10th, 2026|Contemporary Sports Issues, General, Research, Sport Education, Sports Marketing|Comments Off on Basketball and black America: Exploring the intersections of race, fan involvement and community engagement
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Reducing absenteeism and turnover among part-time labor in community sport settings: A case study example and project guidelines for sport management students

Authors: Michael J. Diacin1

1Department of Kinesiology, Health, and Sport Sciences, University of Indianapolis, Indianapolis, IN, USA

 

Corresponding Author:

Michael J. Diacin, Ph.D.

1400 E. Hanna Ave.

Indianapolis, IN 46227

(317)791-5703

[email protected]

Michael J. Diacin, Ph.D., is an Associate Professor in the sport management program at the University of Indianapolis. His research interests focus on sport management pedagogy, experiential learning, and consumer incentives within spectator and participatory sport organizations.

ABSTRACT 

Part-time employees are critical to the daily operation at many sport and recreation focused businesses. Managers at many sites regularly deal with turnover and absenteeism among part-time workers. Absenteeism among the part-time workforce is problematic when less than a full staff is present to perform critical tasks. It negatively impacts customers through longer wait times and employees through increased workload. Therefore, managers in these settings should be making attempts to retain quality employees for as long as possible and offset the detrimental consequences of absenteeism. Managers could develop initiatives to ensure attendance from employees scheduled to work at times of peak customer presence as well as incentivize employees to replace absent workers on short notice. Therefore, the purpose of this work is to provide students with a case study situated within the possible employment setting of community-based sport and recreation facilities and complexes and have them develop initiatives to improve attendance and longevity of employment among part-time workers.

The application to sport management is that current students could likely work in businesses that employ part-time, seasonal workers. Commercial sport and recreation facilities and complexes exist in many locations; therefore, there is a strong likelihood that current sport management students will be working in these settings after graduation. Furthermore, they could benefit from imagining themselves overseeing a labor force of part-time workers and developing initiatives aimed at those part-time workers ranging from high school aged students to senior citizens. As future managers in these settings, students could be challenged to find ways to reduce absenteeism, fill staff shortages created by absenteeism on short notice, and retain quality workers for longer durations. The efficiency and effectiveness of the operation is highly dependent upon part-time workers; as a result, it would be worthwhile to develop initiatives to best ensure the operation is running at a maximum level of efficiency and effectiveness.

KEYWORDS: management, incentives, employees

INTRODUCTION 

Commercial sport and recreation businesses may range from single buildings to expansive multi-sport complexes. These complexes might be referred to as “sports campuses.” The size of these sites could range from an indoor facility measuring 50,000 square feet to a larger complex measuring hundreds of acres. The activities that take place within could include any assortment of team-based and individual activities. Basketball, hockey, tennis, gymnastics, soccer, flag football, cornhole, and pickleball are among the activities conducted at these sites. Regarding ownership and management of these facilities and complexes some might be owned by a municipality and managed by the municipality’s sport and recreation division. Some municipalities choose to outsource the daily management to a private company while other facilities and complexes are privately owned.

At many of these sites, a core of full-time managers directs the overall operation. The quantity of full-time employees could vary based upon the size and scope of the operation. A common aspect within these facilities and complexes is that the full-time managerial core depends on a team of part-time employees who execute many significant tasks related to customer service and maintenance. The part-time staff includes people from different age groups ranging from high school aged students to senior citizens. They receive an hourly wage, and some might receive fringe benefits such as free use of the facility (e.g., swimming pool, fitness equipment). With rare exception, part-time employees do not receive health insurance, retirement contributions, and/or other benefits that are often provided to full-time workers.

An operation in which part-time employees are heavily relied upon presents challenges to the management. Despite being counted on to execute important tasks, part-time workers are not highly compensated, nor do they receive the same benefits given to full-time staff. Unlike full-time staff, the job might not be their primary focus nor primary source of income. This population could be more likely to leave if other opportunities become available or not report for duty if other circumstances arise. Consequently, reliability and retention of part-time employees have consistently been identified as a critical issue facing managers that work in commercial sport and recreation settings (McCole, Jacobs, Lindley, & McAvoy, 2012). Consequences resulting from frequent absenteeism and rapid turnover of part-time employees could negatively impact the operation in numerous ways; therefore, management should attempt to be proactive to best mitigate the negative effects associated with frequent absenteeism and rapid turnover.

Although turnover is an inevitable aspect associated with operating any business, lessening the amount of turnover can be beneficial. The cost associated with turnover can be significant. McKinney, Bartlett, and Mulvaney (2007) identified the consumption of time and financial resources as consequences of turnover. First, there could be a cost to announce vacancies through sites that charge for posting them (e.g., classified listings in the local newspaper, websites targeting job seekers). In addition, there would be a cost associated with additional wages being paid out because a new hire could be working alongside another employee to learn the job. Since that new hire is earning a wage while working alongside another employee earning a wage, the aspect of paying two wages to do one job exists until the new hire has been fully trained and able to do a job on their own.

In addition, the cost of time spent by management on screening and interviewing candidates could be significant. Although part of the job, these activities command time, and frequent turnover means that the managerial staff is frequently spending time on screening and interviewing activities to fill vacancies. If management consistently spends time on these activities, the time spent on other aspects of the operation decreases. In a setting where there are small quantities of managerial staff and each manager “wears many hats,” retention of part-time workers would benefit management because less of their time would be dedicated to finding replacements for departed employees.

Frequent absenteeism and turnover could be especially problematic because of the negative impact to an operation when inexperienced staff is working shorthanded. For example, absenteeism could add to the workload and stress to the employee who did show up for work. In addition, there could also be a negative consequence for customers, as staff shortages could result in negative outcomes such as longer lines and wait times. If customers repeatedly have negative experiences, they might be motivated to go elsewhere to pursue their leisure interests.

On the other hand, a fully staffed operation with an experienced workforce benefits coworkers and customers. When a full contingent of experienced employees is working, no one is placed in a position of having to cover for the absent worker. In addition, the accumulation of experience increases efficiency and effectiveness within the operation. Shorter lines and shorter wait times benefit the customer. Ensuring the customer has a positive experience is critical to securing their ongoing patronage. Although absenteeism and turnover will occur, management should strive to incentivize those employees to work when scheduled as well as remain for an entire busy season (McCole et al., 2012). Management could establish various initiatives to minimize absenteeism and turnover. The details of those initiatives are expanded upon in the following section.

INITIATIVES TO REDUCE TURNOVER AND OFFSET STAFF SHORTAGES 

Commercial sport and recreation facilities are highly reliant on part-time labor to execute many important tasks. There are many circumstances that would cause these employees to miss their scheduled shift on short notice or leave the job altogether. Regardless of the legitimacy of the reason for absenteeism, such occurrences negatively impact both part-time and managerial staff, as well as customers. Therefore, a full complement of staff is needed to ensure maximum efficiency and effectiveness occurs on any given day.

These facilities and complexes are also potential employment settings for sport management students. Graduates may begin as mid-level managers in community-based sport and recreation facilities and complexes as a first job in the sport industry after graduation. Because sport management students could be working in a setting where turnover and absenteeism could be frequent, it would be worthwhile for them to engage in an exercise before entering the setting that would challenge them to think proactively and create a program designed to reduce incidents of frequent turnover and absenteeism. Although they will never eliminate absenteeism and turnover, they should be thinking proactively to minimize absenteeism as well as increase longevity among part-time employees.

Therefore, the purpose of this case study exercise is to provide students with an opportunity to engage in a managerial challenge within the possible employment setting of community-based sport and recreation facilities/complexes. It is designed to help students understand the challenges of working in settings where there is a high level of reliance upon part-time labor as well as challenge them to create a proposal designed to entice potential part-time workers to stay for a particular duration, fulfill their scheduled shifts, and/or assist in situations of absenteeism by filling shifts left open by an absent employee. The initiative could focus on a period as short as a single day to an entire peak season lasting several months. The proposal might also include focus on performance-based initiatives. For this case study exercise, the student could take the role of a mid-level manager. This mid-level manager would supervise part-time staff and reports to a higher-level full-time staff member, such as a General Manager. The proposal would be presented to the General Manager (the course instructor and/or an invited guest such as a manager of a local facility or complex).

Although it would take time and effort to create and manage such initiatives, the benefit to colleagues, customers, and the business resulting from fewer incidents of absenteeism and turnover could make the initiative worth the effort and expense. These types of facilities and complexes could generate revenues in the hundreds of thousands to several million dollars. Expenses such as utilities, maintenance, personnel, and equipment/supplies will use up most of the revenues. Therefore, the financial resources available would be limited as the quantity of dollars available for this case study exercise would be $12,000 to $18,000 annually ($1,000 to $1,500 monthly), with the fiscal year starting September 1 and ending August 31 the following year.

“Survive the Day” Initiatives

This initiative is designed to offset staffing shortages that occur when a part-time worker calls off on short notice or does not show up without any notice given. It is intended to ensure enough employees are present to execute various tasks. This initiative could be focused upon accomplishing two ideals. They are to 1) incentivize the people who are scheduled that day to show up for their shift and 2) if someone must call off, incentivize someone who wasn’t originally scheduled to take the place of the worker who called off on short notice or did not show up for work (e.g., “no call, no show”).

“Survive the Season” Initiatives

Although open for business year-round, the amount of customer activity within commercial sport and recreation facilities and complexes fluctuates based on the season. The greatest amount of customer traffic occurs during the winter months (early December through late February). Ice surfaces have been booked from the late afternoon (4pm) until late night (1am) on weekdays and booked from 6am to 1am on Saturday and Sunday. Youth association and high school hockey teams are conducting their games in the early evening. Adult leagues occupy the latter hours. In addition to the presence of these user groups, youth and high school games bring a greater amount of spectator traffic as friends, classmates, and family members of the participants attend the contests. It is also the period when public skating attendance peaks. As many as 300 customers could be admitted for a two-hour session on a Saturday or Sunday afternoon.

The ice surfaces are booked for similar hours during the months of September and October. Practice and scrimmages are typically conducted. These activities bring user groups but do not bring spectator traffic. Public skating is offered but would bring a fraction of the traffic seen during the winter months. To ensure employees are present to cover the hours in which user groups are present, a “survive the season” initiative could be designed to incentivize part-time employees to stay with the job from September through February. Contingencies could also be added. For example, employees would need to work a specified quantity of shifts/hours (especially on weekends). In addition, limits to the number of times an employee is absent from a scheduled shift, especially weekends, could be implemented.

Recognition for Performance Initiatives

This initiative would focus on rewarding employees for engaging in certain behaviors outside of the attendance-based actions. Employees who engage in quality work would be rewarded for doing so. Support for recognizing employees was revealed by Kellison, Kim, and Magnusen (2013) as they surveyed 522 part-time college aged (18-23 years old) campus recreation center employees from eleven universities to gain insight regarding factors that influenced their intentions to continue working in a part-time capacity at their respective university recreation centers. Recognition was identified as a key factor that positively influenced intentions to remain with the job/organization. Because many of the part-time workers in this case study exercise are in the age range of 18-23, these findings lend support to attempting recognition-based initiatives that have potential to retain employees.

Many organizations have a performance-based initiative in place, commonly referred to as an “employee of the month” program. This is often a competition-based system where one person is selected from the entire staff and receives the award. Various challenges to implementing initiatives where an employee is rewarded in this fashion exist. First, there is a challenge to objectively measuring and documenting the employee’s work. Because many of the part-time support staff members working in commercial sport and recreation settings do not engage in tasks that are easily quantifiable, measuring “good work” could be subject to opinion and perspective. Second, there are different employee groups, each engaging in different tasks. For instance, some of the workers are front of the house workers who are frequently interacting with customers. Others would be considered back of the house workers who do not regularly engage with customers. Consequently, there would be difficulty in comparing the performance of front of the house to back of the house workers because of the differences in their jobs. As a result, it would be the responsibility of the manager to establish parameters, standards, and/or benchmarks for each employee group.

Although an initiative for rewarding good deeds/good work is well-meaning, a system that relies on opinion, relationships, and other subjective criteria could result in more employees feeling less valued if they perceive they earned the reward but were passed over. Instead of having a competition among all employees working different jobs, an alternative is to establish the initiative so that each employee would be able to “control their own destiny.” That means each employee could receive the reward if certain benchmarks and/or standards are reached. If the commitment is made to proceed with such an initiative, an objective system of measurement is needed so that the employee could clearly understand what is expected to obtain the reward. Otherwise, employees could perceive the initiative as subjective, biased, and/or arbitrary.Regardless of the initiative(s) chosen, the proposal should include the following content:

  • The parameters/standards/actions that the employee will take (e.g., filling in for an absent employee, working “x” number of peak busyness shifts over a particular period) to receive the reward.
  • The rewards that will be given.
  • The costs are associated with implementing the initiative.
  • Argument behind why this initiative is feasible in this setting and with this workforce.
  • Identification of potential obstacles for success; why could this initiative be implemented and still not provide the desired results?

PROJECT DETAILS

The following sections for this case study exercise include further description of the setting, operating schedule, manager and part-time worker job descriptions and categories. The quantity of part-time workers hired for each area and the quantity of workers from each category that is on duty at a given time is provided. In addition, the times of day and days of week they typically work as well as the duration of their shifts are indicated.

Facility Setting and Description

The facility that will be utilized for this case study is a multi-purpose facility in which the terms “ice arena” or “hockey arena” might be used. The activities that commonly take place would be ice sports such as hockey, figure skating, and recreational skating. The facility is approximately 180,000 square feet. Two arenas that each house an ice surface of 85×200 feet are the primary activity spaces. When the ice is removed, activities can be conducted on the concrete floor. During off-peak months, various events and programs such as trade shows, exhibitions, and circuses could be conducted.

Each arena consists of stationary spectator seating in the form of metal bleachers with a seating capacity of 1,000. Each arena has six locker rooms (four for hockey teams, one for referees and one additional room to be used on an “As Needed” basis (e.g., for girls participating on boys’ youth hockey teams). There are storage areas and a large garage area where the ice resurface machines are housed. Other areas not accessible to the public include mechanical rooms where the ice cooling equipment is housed. Public areas would consist of a large lobby in which numerous benches and tables are present for the convenience of the patrons. Accessible from the lobby is the concession stand, pro shop (equipment and merchandise sales), arcade, office space, fitness center, restrooms, and two multi-purpose rooms where staff meetings, birthday parties, and team banquets could be held.

Facility Operating Schedule

Many sport and recreation related businesses are open for business seven days a week and typically see most customer activity during weeknights (after 5pm, Monday through Friday) and weekends. On weekends, activity could start as early as 6am and continue as late as midnight or 1am during the peak season. This is when staff is most needed to cover these hours. The amount of customer activity will be at its peak from early December until early March. This is the peak period for youth hockey games, which increases the amount of spectator traffic as family members attend the contests. High school programs could rent space for their practices and games as well. Their games bring additional spectator traffic. It is also peak season for public skating sessions. A public skating session on a weekend afternoon during the winter months could attract as many as 300 paying customers for a two-hour window of skating time. 

Regular business hours (e.g., Monday-Friday from 8am-5pm) are typically the periods with the least amount of customer activity. During this time, most maintenance and cleaning activities occur. Deliveries from vendors also occur during this time. Therefore, there is a need for management and custodial personnel to be present during times of minimal customer activity.

Full-Time Manager Descriptions

The facility is overseen by a general manager and additional full-time, salaried assistant managers. The general manager and assistant managers participate in various aspects of the operation. It is not uncommon for each assistant manager to not only have a primary responsibility regarding some managerial aspect, but also “wear many hats” and participate in other aspects of the operation. For example, one of the assistant managers might be responsible for overseeing tasks in connection with human resources. This person would be responsible for writing and disseminating job descriptions, screening applicants, and conducting interviews. The other assistant managers could be responsible for overseeing facility maintenance/cleanliness, the concessions operation, the pro shop/retail operation and/or marketing/programming. In addition, full-time managers participate in other aspects of the operation as they should be able to step in and assist anywhere on an “as needed” basis. This would include driving the ice resurface machine, operating cash registers, distributing rental equipment, and spot cleaning.

At least one of the full-time, salaried staff members are present when the building is open for business. This would include coverage during regular business hours as well as weeknights and weekends. It is possible that during peak times of business, more than one manager could be present. It would not be uncommon for 4-5 full-time management members to be employed at this type of facility.

Part Time Staff Descriptions

Perry (2018) identified different categories of employees that seek part-time employment in commercial sport and recreation facilities and complexes. The first category consists of individuals who are looking for some work to keep busy and gain supplementary income. A retired individual, perhaps a senior citizen, would fall into this category. The second category consists of post-college aged workers with full-time jobs who want or perhaps need a second job to help pay bills, accumulate extra savings, etc. The third category would consist of high school and college aged individuals who are looking to gain work experience and obtain income. This demographic is typically working around their schooling.

Regardless of the demographic, these jobs are often not the primary focus in the employee’s life. Other aspects are higher on the priority scale; therefore, employees might not alter other life aspects (e.g., primary job, school, family commitments) to work these jobs. Because the employee is not intending to make a career out of the part time job in this setting, this could have an impact upon attendance and performance.

These part-time workers fulfill “front of the house” and “back of the house” positions. In this setting, front of the house positions consists of duties such as cash handling/cash register operation, serving food products, collecting participation fees, distributing rental equipment, monitoring customer conduct, and being present in the event customers have questions and/or need assistance. Front of the house positions that often exist in the setting include concessions, skate staff, pro shop/merchandise sales, and front desk workers/receptionists.

Back of the house employees largely contribute to the cleanliness and upkeep of the facility. In this setting, custodians and ice resurfacing machine drivers/building attendants are common types of back of the house workers. They have little interaction with customers and in the case of custodians, often work when few to no customers are present in the facility.

These employees are paid an hourly wage and could work as little as 10 hours a week or as many as 40 hours a week. Accumulated hours are monitored so that the employee does not exceed 40 hours a week. If 40 hours in a week are exceeded, overtime compensation of one and a half times the employee’s standard hourly wage would be paid. In many cases, the hourly wage could be at or slightly above the locally mandated minimum wage.

For this case study exercise, seven part-time worker categories exist, consisting of several front and back of the house positions. Several people are on the roster within each worker category. Not everyone who has been hired and appears on the roster is working at the same time. Saturday and Sunday will be the busiest days requiring the greatest amount of part-time worker participation. Key duties, the time of day and quantity of hours per shift that employees within each of these categories are typically scheduled, and worker demographics are provided.

Concessions

Concession stand workers are responsible for preparing and serving food and beverages. “Quick serve” foods are usually prepared and then held in a warming bin or warming rollers (e.g., pizza, popcorn, hot dogs). Some facilities might possess a deep fryer, which would allow workers to prepare items such as fries, mozzarella sticks, etc. Concessions workers work when customer traffic is heaviest (evenings and weekends), except for periods when school is out of session such as winter break. High school and college aged employees are common. Post college aged adults working part-time, perhaps around another full-time day job, also staff the concessions operation. One person will be on duty most of the time. During the periods of peak customer traffic, such as public skating sessions during the winter months, two people could be scheduled to work at the same time. Shift duration is commonly 4-6 hours. There could be 6-8 employees on the roster in this area.

Skating staff

The skate staff would consist of counter/desk workers who are responsible for collecting admission fees and distributing “skate passes” to patrons participating in public skating sessions. Skate passes are often colored stickers the patron can wear on their clothing so that staff can easily see they paid their admission fee for that public skating session. They would also distribute rental skates to patrons who do not own their own set of skates. The other type of worker in the skating staff category is the “skate guard.” These individuals ensure those who enter the ice have paid their admission, indicated by the skate pass they are wearing. They also watch for and report any injuries or incidents of dangerous behavior to management. This worker group commonly consists of high school and college age individuals. Their work schedule aligns with public skating sessions, which are typically on Saturday and/or Sunday. With a two-hour skating session, for instance, workers could be scheduled for a 3.5 to 4-hour shift. This duration allows for them to be on duty before customers arrive and allows for post-session cleanup, putting skates away, etc. The roster could consist of 4-8 employees in this category. 1-2 skate guards would be on duty for each session (2 during the busiest winter sessions) as well as 1-2 counter/desk workers (2 during the busiest winter sessions).

Pro shop staff

Merchandise such as tape, water bottles, mouthguards, sticks, helmets, and other equipment is commonly sold in the “pro shop.” These workers are responsible for operating the register and assisting customers. Some light cleaning within the area is periodically assigned. In some facilities, skate sharpening is offered, and the pro shop employees will sharpen customers’ skates. During slow periods, the pro shop staff often is charged with sharpening the rental skates that will be used during the public skating sessions. The pro shop would be open during the evening and weekends. This worker group commonly consists of high school and college age individuals. The shift duration could last from 4-6 hours. On weeknights, one person would likely be on duty. During the weekends, especially the times around public skating sessions, two people could be on duty. There could be 4-6 people on the roster within this worker category.

Fitness center workers

The facility in this case study has a fitness center on site. The fitness center would include equipment that would commonly be found at commercial fitness centers, such as treadmills, elliptical trainers, and free weights. Monthly and/or annual memberships could be sold. This area could be open from early morning until late evening (6am-11pm) seven days a week. Fitness center workers would ensure members have checked in, engage in light cleaning duties and conduct minor troubleshooting of equipment. These workers do not conduct personal training sessions. During the weekday mornings and afternoons, the workers would mostly consist of senior citizens or other post-college aged adults. High school and college aged individuals would typically work evening and weekend hours. Because this area is staffed seven days a week from early morning to late evening, 6-8 individuals could be on the roster for this position. One worker would be working at a time for a shift typically lasting 4-6 hours.

After hours reception desk

These workers would be on duty after regular business hours on weekdays and on weekends. This person would likely distribute keys for the locker rooms to hockey teams, provide information to basic inquiries (e.g., assigned locker room number), answer phone calls, and serve as a point of contact for patrons who report a circumstance in need of attention, such as cleaning up a spill, restocking paper products in restrooms, etc. The desk worker would contact the manager on duty and/or other worker groups to address the need. In some facilities, the desk worker might assume duties such as collecting fees and distributing passes for public skating patrons. Workers in this group could range from high school or college students to post college aged individuals and senior citizens. One person at a time would be on duty and there could be 3-4 people on the roster in this category.

Building attendant/ice resurface machine driver

Building attendants are responsible for resurfacing the ice for each new user group. In between ice resurfacing duties, they are responsible for surface cleaning in locker rooms, restrooms, spectator seating areas, and lobbies/foyers. Restocking restrooms and mopping up spills are among cleaning and light maintenance duties that a building attendant would be expected to perform. They are scheduled during times when user groups are present in the building; therefore, the schedule consists of mostly evening and weekend work. Building attendants are required to be a minimum of 18 years old because the job includes operation of the ice resurfacing machine. Middle-aged individuals working around a primary job could also be working in this role. One person would be scheduled to work in this capacity on a weeknight; however, two people could be scheduled to work on weekends during peak times. The shift duration would likely be 7-8 hours. There could be 4-6 employees on the roster.

Custodial

Custodians are responsible for the overall cleanliness of the facility. Much of their time is spent cleaning and restocking restrooms and locker rooms, emptying trash bins and cleaning spectator seating areas. These employees typically work when the building is not full of customers so that they can engage in deep cleaning activities. Working during regular business hours (e.g., Monday-Friday 8am-5pm) is common. They could also be scheduled for late night/early mornings on Friday night into Saturday morning and Saturday night into Sunday morning as the facility will typically be full of customers when the doors open on weekend mornings. Worker demographics could vary, ranging from post college age to semi-retired individuals. Some of these employees might be working this job along with another job. There could be 2-4 people employed in this category, with one person on duty at a time. A typical shift duration could be 4-8 hours. If a special cleaning or maintenance project is planned, more than one worker from this category could be scheduled.

APPLICATION TO SPORT MANAGEMENT

Regarding the application of this work to the educational setting, sport management students could find this case study exercise useful because it gets them to imagine themselves working in a setting and engaging in challenges they could face once they enter the workforce as a full-time, managerial employee. Commercial sport and recreation facilities and complexes exist all over the world; therefore, there is at least some likelihood that some will work in these settings. Therefore, it is important to expose students to situations they could experience within possible employment settings. Having students generate content that could be used in an actual setting would be useful because many could be overseeing part-time workers from various demographics and life situations at their respective workplaces.

Students who work in these settings will not only be faced with challenges related to staffing but could also be working in settings where there are not large amounts of financial resources available to them. Many of these facilities and complexes are smaller “mom and pop” businesses that do not generate massive amounts of revenue. Therefore, they will have to find ways to address a challenge with a limited amount of money (in this case study $1,000-$1,500 monthly limit) at their disposal.

The content students create in association with this case study could take the form of a written proposal and/or an oral presentation. In order to give them the opportunity to create the most extensive proposal possible, it is suggested that students create content for each of the three initiatives (survive the day, survive the season, and performance). As a middle level manager who was hired by a superior, the student would report to that individual or perhaps several individuals who occupy a higher position in the organizational chart. For this case, the student could present the content to the instructor of the course who would represent the upper-level member of management. It is suggested that if feasible, managers from a local facility or complex be invited to participate in the presentation of the proposal. Their presence and scrutiny would add an additional layer of authenticity to the endeavor. Furthermore, the instructor might wish to reach out to managers of local facilities and complexes to see if they would like for students to create a proposal specifically for their operation. The manager would possibly first appear as a guest speaker and share details of the operation with the students. Students could use that visit to ask questions and gain a better understanding of the operation and then develop a plan for that manager.

Regarding the execution of the students’ proposal in the “real world,” it is likely that costs and personnel limitations would be presented as reasons as to why these ideas would not reach the execution stage. Therefore, part of the challenge for students is to create a plan that would be financially feasible for a small business as well as a plan that could be executed by a single manager or perhaps a small managerial team of 2-4 people. In closing, it is hoped that this case study exercise will benefit faculty seeking content to add to their courses. This case study could be executed within courses focusing on human resources management, facility management, and/or financial management. Because a large quantity of these operations exists, it is possible that students will secure employment in them. Therefore, this endeavor can help to further prepare students for managing a predominately part-time workforce within commercial sport and recreation facilities and complexes.

REFERENCES 

  1. Kellison, T. B., Kim, Y. K., & Magnusen, M. J. (2013). The work attitudes of millennials in collegiate recreational sports. Journal of Park and Recreation Administration, 31(1), 78-97.
  2. McCole, D., Jacobs, J., Lindley, B., & McAvoy, L. (2012). The relationship between seasonal employee retention and sense of community: The case of summer camp employment. Journal of Park and Recreation Administration, 30(2), 85-101.
  3. McKinney, W. R., Bartlett, K. R., & Mulvaney, M. A. (2007). Measuring the costs of turnover in Illinois Public Parks and Recreation Agencies: An exploratory study. Journal of Park and Recreation Administration, 25(1), 50-74.
  4. Perry, P. M. (2008). Finding great part-time workers. NSGA Retail Focus, 61(2), 10-11, 22.

2025-12-05T10:58:04-06:00June 3rd, 2026|Contemporary Sports Issues, General, Leadership, Research, Sports Management, Sports Studies|Comments Off on Reducing absenteeism and turnover among part-time labor in community sport settings: A case study example and project guidelines for sport management students
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An Analysis of Carbon Emissions from College Football Recruiting Visits

Authors: Jeffrey J. Fountain1, Thomas Wuerzer2, & Peter S. Finley1

1Department of Management, Nova Southeastern University, Fort Lauderdale, FL, USA

2Department of Public Administration and Real Estate Development, Nova Southeastern University, Fort Lauderdale, FL, USA

 

Corresponding Author:

Jeffrey J. Fountain, Ph.D.

3301 College Avenue

Fort Lauderdale, FL 33314

[email protected]

954-262-8129

Jeffrey Fountain, Ph.D., and Peter Finley, Ph.D., are Professors of Sport Management at the H. Wayne Huizenga College of Business and Entrepreneurship at Nova Southeastern University. Their research interests focus on issues in college athletics.

Thomas Wuerzer, Ph.D., is Professor in the Department of Public Administration & Real Estate Development at Nova Southeastern University. His research focus is on Geographic Information Systems.

ABSTRACT 

Recruiting college football players to come play for a National Collegiate Athletic Association (NCAA) Power-5 school is highly competitive, with each school inviting recruits nationwide on official campus visits. By estimating the carbon emissions generated, this study examined the environmental impact of official recruiting visits (n = 7,045) to Power-5 schools from 2013 to 2020. Using Geographic Information Systems (GIS) to geocode recruits’ hometowns and calculate travel distances, a Recruit Visit Carbon Footprint (RVCF) was calculated to approximate the CO2eq emissions for each visit. The analysis focused on the 23 Power-5 schools with over 250 reported official visits. The findings revealed substantial variability in RVCF among schools, with 15 of the 23 schools increasing their carbon footprint in the latter years of the study. Still, the higher-spending athletic departments tended to have lower RVCFs. The findings provide valuable insights into the environmental impact of recruiting activities and highlight the importance of addressing this overlooked aspect of college sports’ carbon emissions.

KEYWORDS: Carbon Footprint, Power-5, Recruiting, Official Visit, College Football

INTRODUCTION 

As societal awareness of the environmental impact of both mega sporting events and routine contests (regular season games) has increased, many sports organizations, teams, and sponsors have come to understand the need to assess the carbon footprint they create (10). As noted by Dolf et al. (13), several researchers have stressed that sports events are worth investigating to leverage broader change because of the high-profile nature of such events, because they are capable of creating real and meaningful action (11, 19). Several athletic departments have promoted their initiatives throughout the last decade and publicized their efforts to reduce and offset their environmental impact by tracking and reducing carbon dioxide-equivalent emissions (CO2eq). The typical path toward claiming to be carbon neutral for college athletic departments is to assess the environmental impact of the day-to-day operations, home game operations, and off-campus travel for official tournaments and games. However, it is important to recognize that the carbon footprint begins long before sporting events are played; for college sports, this goes back to the initial recruitment phase of the athletes, which typically requires them to travel as part of the recruiting process.

In 2020, the Power-5 conferences included the Atlantic Coast Conference (ACC), Big 12 Conference, Big Ten Conference, Pacific 12 Conference, and the Southeastern Conference (SEC). Over the years, the number of Power-5 schools increasing their investment in recruiting athletes has grown, with 38 of the 52 public Power-5 schools reporting a significant growth in overall athletic department recruiting expenditures (37). One extreme example was the University of Georgia’s athletic department, which increased its overall recruiting budget from $308,000 in 2005 to $4.5 million by 2022 (23).

Recruiting

Each recruit is permitted one official visit per school, extendable only if there is a change in the coaching staff, with each visit lasting no more than 48 hours or one weekend (29). Visits are classified by the funding source; when the host school covers expenses such as transportation, lodging, meals, and entertainment for the recruit and their parents or guardians, it is deemed an official visit (29). Historically, recruits were limited to five official visits; however, this cap was removed in 2023, allowing unlimited visits while maintaining the “only one visit per school” rule (30).

College football recruiting visits often feature expensive, extravagant events designed to attract recruits (12, 24, 36). The financial commitment to a recruiting weekend at Clemson University in the fall of 2019, during which the Tigers brought eleven prospects to campus (they would eventually sign ten of them), ended with a total bill of $85,000 (32). While the NCAA prohibits media from attending recruiting events or interacting with prospects while on campus, the expenditures from that weekend provided insight into the itinerary, which included travel by professional car service to and from local airports, flights to Greenville-Spartanburg, and transportation to the campus, about 40 miles away. In addition, two charter buses were used to transport prospects and their families to the finest restaurants in the area, including a steakhouse about 45 minutes from campus (32). Another example was the University of Texas spending over $280,000 during a single weekend in June 2022 to host nine recruits, including highly touted quarterback Arch Manning (20).

Carbon Footprinting

The concept and measurement of an “ecological footprint” was introduced by Wackernagel and Rees (34) and originally quantified the land and sea area necessary to support human populations. Subsequent adaptations of this concept have focused on the “carbon footprint,” which estimates the land required to sequester CO2 emissions attributable to human activities. This notion has evolved into broader assessments such as the “life cycle impact,” which evaluates the environmental impact of products and services throughout their life cycles (31).

Research by Čuček et al. (9) and Pandey et al. (31) expanded the scope of assessment to include calculating sustainability metrics and measuring energy, water, and ecological impacts. These studies defined a carbon footprint as “the quantity of Greenhouse Gases (GHGs), expressed in terms of CO2 equivalents, emitted by an individual, organization, process, product, or event within a specified boundary” (31) and as “a quantitative measurement describing the appropriation of natural resources by humans,” (9). This study adopted these definitions to evaluate the carbon footprint of prospective college football players while making their official recruiting visits to college campuses.

Attempts to measure carbon footprint related to sports have historically focused on major events and the travel of sports teams. Examples include the findings that approximately 560 tons of CO2eq was created during the 2004 Football Association (FA) Cup Final in the United Kingdom (one soccer game) (4), 1,260 tons of CO2eq for the 2004 Wales Rally (an Autosport’s event over four days) (5), and 144,120 tons of CO2eq for the stages of the Tour de France held in the United Kingdom in 2007 (the Prologue and Stage One) (6). Most studies focused solely on the carbon footprint of spectators, though a limited number of studies examined participants, such as teams and staff members.

The environmental impact of all college activities, including collegiate sports has garnered significant attention (28). However, there appears to be no available research that has explicitly focused on the environmental impact (carbon footprint) produced throughout the college football recruiting season. Therefore, the researchers sought to explore and determine the approximate carbon emissions produced during official college football recruiting visits from Power-5 schools. This study utilized the reported official recruiting visits between 2013 and 2020. Using Geographic Information Systems (GIS) to conduct spatial analysis of multimodal travel, including car and plane trips, the researchers were able to calculate the approximate travel distances and corresponding carbon footprint of each recruit.

The Recruit Visit Carbon Footprint (RVCF) was created as a proxy measure utilizing prior carbon footprinting research of sport tourism. This approach enabled a systematic exploration of three primary research questions.

RQ1: Which Power-5 schools generated the largest RVCF between 2013 and 2020?

RQ2: Did RVCF totals increase or decrease over time?

RQ3: Was there a correlation between each school’s financial, recruiting, and performance variables and their RVCF?

METHODS 

Data Collection

Data on official recruiting visits, published by 247sports.com, was collected for the years 2013 to 2020. Previous research has utilized data from 247sports.com, recognizing it as a well-established source of college football recruiting information (21, 27, 35). The dataset included dates of official school visits and recruits’ hometowns. Prior research also utilized GIS to geocode locations such as athletes’ hometowns or high school locations for analysis (1, 26, 38). GIS geocoding takes a specific location, such as addresses or towns, and references it as a mapped location. Therefore, this study geocoded each football recruit’s hometown, the location of each college visited, and the closest major airport to calculate the approximate travel distances for spatial analysis.

The study utilized ESRI ArcPRO 3.5 (Esri, Redlands, CA, USA) software with the Business Analyst extension to geocode the dataset. To focus on the highest-producing RVCF programs and to make the data set more manageable, a minimum threshold of 250 visits was established. Of the 64 Power-5 schools, 23 (35.9%) met the 250-visitor threshold, totalling 7,045 reported official visits. The travel routes for each visit were then calculated using GIS to determine the most efficient mode of travel. Driving directly to the school was the most efficient mode for 1,636 visits. Typically, these distances were around 200 miles or less to the campus. For recruits living over 200 miles from the visiting campus, if their distance from their home to an airport necessitated a long drive followed by a flight, driving was deemed more efficient due to the extensive travel time involved in flying to the campus. For the remaining 5,409 visits, air travel was deemed the most efficient mode. For these visits, three travel distances were calculated: 1) the drive from the recruits’ hometown to the nearest major airport, 2) the flight miles from that airport to the nearest major airport to the campus they visited, and 3) the drive from that airport to the campus. These distances were doubled to account for the return trip and integrated into a travel matrix to approximate CO2eq emissions from transportation.

Additionally, financial data for athletic departments (i.e., Football Revenue, Football Recruiting was sourced from the Knight-Newhouse College Athletics database (25), team performance was sourced from ESPN.com (16). The descriptions and summary statistics for these variables are provided in Table 1. Utilizing these variables allowed for additional analysis to explore potential correlations between an athletic department’s RVCF and financial data, performance data, and recruiting data.

Table 1 Descriptive Analysis of Variables: Mean and Standard Deviation
VariableDescriptionMeanSD
FB_TotalRevTotal Revenue from Football$66,518,526$25,205,244
Mens_TotalRevTotal Revenue from all Men’s Sports (including Football)$84,428,967$25,300,581
FB_MensRev%Football’s Revenue as a Percentage of all Men’s Sports Revenues77.40%11.17%
Dept_TotalRevTotal Revenue from the entire Athletic Department$125,143,966$31,108,327
FB_DeptRev%Football’s Revenue as a Percentage of the entire Athletic Department Revenues52.50%13.10%
Mens_RecruitExpTotal Recruiting Expenses from all Men’s Sports (including Football)$1,391,362$704,861
Dept_RecruitExpTotal Recruiting Expenses from the entire Athletic Department$1,878,962$855,080
FB_OpsExpTotal Operation Expenses for Football$5,683,499$2,558,649
Mens_OpsExpTotal Operation Expenses for all Men’s Sports (including Football)$8,800,193$4,035,500
Dept_OpsExpTotal Operating Expenses for the entire Athletic Department$12,787,529$5,068,156
FB_TotalExpTotal Expenses for the entire Football Program$33,846,192$11,218,516
Mens_TotalExpTotal Expenses for all Men’s Sports Programs (including Football)$53,035,310$13,927,935
FB_MensExp%Football Expenses as a Percentage of all Men’s Sports Expenses63.18%7.58%
Dept_TotalExpTotal Expenses for the entire Athletic Department$116,141,712$27,071,219
FB_DeptExp%Football Expenses as a Percentage of the entire Athletic Department Expenses63.18%7.58%
Win_PercentageFootball teams Win Percentage62.43%19.97%
    

Recruit Visit Carbon Footprint

Calculating CO2eq emissions from travel can vary depending on the methods and formulas used. In this study, the researchers approximated the RVCF utilizing established methods from prior sport tourism carbon footprint research. The framework by Franchetti and Apul (18) required three boundaries. 1) Temporal Boundary, which refers to the period used for analysis, which, in this study, included Power-5 official recruiting visits from 2013 to 2020. 2) Organizational Boundary, which defines the measured entity, ensuring that only emissions produced from the designated entity are included. Here, it refers to the travel for a single recruit’s official visit to a Power-5 school. 3) Operational Boundary, which is based on the scope of emissions, including direct emissions, indirect emissions, and indirect products. The operational boundary was set at direct emissions only for this study.

In order to operationalize the boundaries, calculations were used to approximate each recruit’s carbon footprint as they travelled from their hometown to their selected school for an official recruiting visit. Cooper’s (2020) approximation of the University of Tennessee’s football gameday tourism carbon footprint was used as a framework for this study. The method for approximating the carbon footprint of sport tourism was applied to the dataset to calculate the approximated total amount of CO2eq emissions produced by each recruiting visit. The total carbon footprint of each visit was calculated by considering direct emissions from transportation (car and flight miles), food consumption per day, waste per day, and hotel stays (8, 14). The EPA formula for the average gasoline-powered passenger vehicle (3.91 × 10^-4 metric tons CO2eq per mile) was applied and converted into kilograms (15). For air travel emissions, the formula (air miles × 0.24 × 1.891) combined the Blue Sky Model formula and the Carbon Fund’s radiative forcing factor (1.891) to provide a total CO2eq per person per pound figure, which was then converted to kilograms (2, 3). Hotel accommodation emissions were calculated using Filimonau’s (17) factor of 11.65 kg CO2eq per night, multiplied by two to account for the typical two-night stay during a recruiting visit. For food and waste emissions, factors from Cooper’s (7) study were used: 7.4 kg CO2eq per person per day for food and 1.1 kg CO2eq per day for waste, multiplied by two for the typical 48-hour visit. Utilizing these formulas allowed the researchers to approximate the RVCF for each reported recruiting visit.

RESULTS AND DISCUSSION

Over the eight years, the top 23 highly-visited schools collectively emitted 2.3 million kg of CO2eq, averaging 328 kg CO2eq per recruiting visit. For context, the global average annual CO2eq emission per person is approximately 4.7 tons (4,263 kg), according to the IEA (22). Thus, the CO2eq for a single 48-hour recruiting visit represents about 7.7% of the average person’s global annual CO2eq footprint.

Table 2 provides a breakdown of RVCF variables along with the means and totals for all 23 schools to address RQ1, “Which Power-5 schools generated the largest RVCF between 2013 and 2020?” Washington State (n = 276) reported the highest total RVCF at 171,489.84 kg CO2eq, and the highest mean RVCF at 621.34 kg CO2eq. In contrast, the University of South Carolina (n = 263) had the smallest carbon footprint, with a total RVCF of 55,621.71 kg CO2eq and an average RVCF per visit of 211.49 kg CO2eq. All official visits to Washington State and South Carolina are depicted using GIS maps in Figure 1, which shows Washington State attracted several recruits from the Midwest, Florida, and Texas. At the same time, South Carolina only invited a few recruits who required a long-distance flight to visit Columbia, South Carolina.

Table 2   RVCF by school for all reported official visits from 2013 to 2020  
Schooln% Drove (No Flight)Car (No Flight)Car  (To/From Airport)FlightHotelFoodWasteMSDTotal
Washington State2762.17%564.4821,782.22137,796.796,405.954,084.79855.60621.34362.98171,489.84
Oregon2813.20%667.817,322.00150,332.796,522.004,158.79871.10604.54323.99169,874.50
Nebraska3735.90%1,437.039,203.29131,283.868,657.325,520.391,156.30421.60171.96157,258.20
Alabama37817.99%6,138.0121,504.7481,842.828,773.375,594.391,171.80330.34219.30125,025.12
Minnesota32815.55%1,543.639,279.4494,019.657,612.874,854.391,016.80360.75190.85118,326.78
Louisville3437.87%1,814.239,356.0792,166.147,961.025,076.391,063.30342.38189.87117,437.16
Oklahoma31521.27%7,627.739,318.5385,483.067,311.144,661.99976.50364.79187.59115,378.96
Tennessee35614.89%5,866.3411,129.2172,691.178,262.755,268.791,103.60293.04213.71104,321.87
Texas A&M32746.18%15,370.2818,162.7656,491.357,589.664,839.591,013.70314.50223.19103,467.35
Washington25122.31%2,329.335,626.1481,958.425,825.713,714.80778.10399.33250.68100,232.49
Ohio State30126.58%7,676.345,596.1469,715.536,986.204,454.79933.10316.82223.4995,362.10
Arkansas32515.38%4,563.0713,222.0664,152.597,543.244,809.991,007.50293.23166.9795,298.46
Indiana27315.38%3,307.9013,293.6462,085.006,336.324,040.39846.30329.34169.1389,909.57
Florida33328.53%8,658.696,782.7656,932.067,728.924,928.391,032.30258.45179.7686,063.13
Miami30139.53%3,920.904,735.8663,566.686,986.204,454.79933.10280.01263.3084,597.54
Florida State31714.20%3,929.026,600.1159,945.347,357.564,691.59982.70262.44182.3083,506.32
Auburn31335.14%9,914.5514,971.1242,452.127,264.724,632.39970.30256.25161.7180,205.21
Georgia27033.70%6,709.3215,279.3141,800.056,266.693,995.99837.00276.78196.7074,888.37
Penn State25429.53%9,210.7316,663.5938,471.375,895.343,759.20787.40289.49192.6574,787.61
Mississippi State29356.31%17,224.2017,413.1326,745.766,800.524,336.39908.30250.61176.9073,428.32
Kentucky27419.71%4,331.997,066.4249,895.236,359.534,055.19849.40264.81146.5772,557.76
LSU30038.00%7,465.215,491.1341,783.316,962.994,439.99930.00222.53146.7367,072.63
South Carolina26332.70%7,526.485,361.7631,921.566,104.233,892.40815.30211.49128.8055,621.71
Total7,04523.57%137,797.27255,161.411,633,532.66163,514.32104,265.8721,839.48328.91203.012,316,111.00
Note: Car, Flight, Hotel, Food, Waste, Mean, Standard Deviation, and Total are in kg CO2eq

To explore the second research question, “Did RVCF totals increase or decrease over time?” the dataset needed to be segmented. During this time period college football programs did not get an entirely new roster of players each year; consequently, examining each year’s change would yield varying results based on how many recruits the school needed that year. Rosters typically turn over every 4 to 5 years. Therefore, with eight years of data available, the dataset was subdivided into two four-year periods (2013-2016 and 2017-2020) to better examine changes over a longer period of time.

Table 3 shows the schools with the largest changes in their mean RVCFs. Fifteen schools experienced an increase in mean RVCF between the two time periods. Ohio State had the largest increase in mean difference (MD = 74.77 kg CO2eq), with its mean RVCF rising from 280.80 kg CO2eq in 2013-2016 to 355.57 kg CO2eq in 2017-2020. Oregon saw the largest overall increase in total RVCF, increasing 29,617.65 kg CO2eq during the latter period. Figure 2 utilizes GIS maps to depict all recruiting visits to Ohio State for each period, highlighting an expanded recruiting range that targeted more players from Texas and the Western United States. Conversely, eight schools showed a reduction in mean RVCF between the two time periods, with the University of Miami experiencing the largest decrease in mean difference (MD = -61.96 kg CO2eq). Although Washington State’s mean reduction was not as considerable as the bottom three schools, it had the largest total reduction in RVCF, decreasing by 19,562.28 kg CO2eq between the two periods.

Table 3 Largest Mean Difference in RVCF between the two time periods
 2013-2016 2017-2020 
SchoolsnTotalM nTotalM DifferenceMD
Ohio State15643,804.86280.80 14551,557.24355.57 7,752.3974.77
Penn State10225,847.68253.41 15247,683.11313.70 21,835.4460.30
Oregon12270,128.43574.82 15999,746.07627.33 29,617.6552.51
Florida St.16546,656.85282.77 15236,535.52240.37 -10,121.32-42.40
Arkansas15349,311.35322.30 17245,987.11267.37 -3,324.24-54.93
Miami15146,944.88310.89 15037,339.37248.93 -9,605.51-61.96
Note: Totals and Means are in kg CO2eq

Wuerzer et al. (38) identified county-level geographical hotspots in the United States overproducing elite college football talent, necessitating migration to other states to find available roster spots on Power-5 football teams. Consequently, Power-5 schools in regions with minimal elite talent and far from these hotspots must expand their recruiting efforts, increasing their RVCF. Schools that rely heavily on air travel for recruiting will naturally have a larger carbon footprint, as air travel is the primary contributor to total RVCF. This is evident from the top three schools with the highest total RVCF also have the lowest percentages of recruits visiting within driving distance to their campuses (Washington State (2.17%), Oregon (3.20%), and Nebraska (5.90%)). Despite this, schools still make strategic choices in their recruiting practices. For example, as shown in Figure 1, Washington State invited several recruits from Florida, a state with prominent county-level recruiting hotspots, instead of focusing on nearby regions or closer recruiting hotspots in California and Texas.

A Pearson correlation coefficient analysis was conducted to address research question three: “Were there any correlations between schools’ financial, recruiting, and performance variables and their RVCF?” The analysis identified two significant correlations, both negative: Total RVCF and Athletic Department Total Annual Revenue [r(176) = -.202, p = .007] and Athletic Department Total Annual Expenses [r(176) = -.198, p = .008]. These findings suggest that athletic departments with higher revenues and expenses tend to have lower RVCFs. This could be attributed to the fact that Power-5 programs with substantial financial resources often have well-established and highly regarded football programs, enabling them to attract top recruits from within a closer geographical range. Consequently, these programs would be less dependent on long-distance recruiting, which typically requires greater air travel, the primary contributor to a school’s RVCF, thereby lowering their overall RVCF.

Overall, these findings highlight the multifaceted nature of college football recruiting, shaped by a complex interplay of positional needs, recruits’ availability, and recruits’ geographical location. The competitive nature of Power-5 college football recruiting requires substantial time and effort to build top-tier recruiting classes, prompting many schools to expand their recruiting reach over time, which subsequently increases their RVCF. The findings show that 15 of the 23 schools increased their RVCF over the two periods. Given the fierce competition for elite talent, it is unlikely that any football program would willingly reduce its recruiting-related carbon emissions if it jeopardizes on-field performance. This creates a significant challenge for universities wanting to adopt more sustainable operations.

CONCLUSION 

This study provides a substantial initial assessment of the carbon footprint associated with college football recruiting. By utilizing GIS for recruits’ hometowns, college locations, and nearest major airports to calculate travel distances, the researchers provided an approximation of each school’s RVCF Recruiting Visit Carbon Footprint (RVCF). The findings reveal substantial variability in RVCF among schools, highlighting the different levels of environmental impact of recruiting. The study also found that higher-spending athletic departments tended to have lower RVCFs, suggesting that successful programs may not need to extend their recruiting reach as widely.

However, several limitations must be acknowledged. The data for this study came from a third-party recruiting website, thus allowing for only an approximate carbon footprint for each official visit. Also, various models and formulas can be used to estimate CO2eq emissions from travel, but each carries assumptions and biases. Moreover, policy changes during the study period, such as the NCAA’s 2016 rule change allowing schools to cover travel costs for up to two parents or guardians accompanying a recruit, could result in a higher actual carbon footprint than the reported RVCF from this study (33). More detailed research is essential for a more accurate and comprehensive understanding of the carbon emissions associated with college football recruiting. Unfortunately, without a governing body mandating standardized reporting of recruiting carbon emissions using consistent formulas, it will remain difficult to fully assess and compare the carbon emissions of different athletic departments.

APPLICATIONS IN SPORT

For universities aiming to reduce their athletic department’s carbon footprint, including all recruiting activities in their calculations is crucial. A comprehensive approach would enable the development of effective strategies that promote sustainability without sacrificing athletic success. Athletic departments can better incorporate sustainability into their planning and decision-making processes by understanding the true carbon footprint generated by each sport, school, and conference.

ACKNOWLEDGMENTS
This research was supported by a college-level seed grant focused on sustainability issues from the Huizenga College of Business and Entrepreneurship’s Societal Impact Seed Grant program.

REFERENCES 

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3. CarbonFund.org. Calculation Methods. 2024; Available from: https://carbonfund.org/calculation-methods/.

4. Collins, A., et al., Assessing the environmental consequences of major sporting events: The 2003/04 FA Cup Final. Urban studies, 2007. 44(3): p. 457-476.

5. Collins, A., C. Jones, and M. Munday, Assessing the environmental impacts of mega sporting events: Two options? Tourism management, 2009. 30(6): p. 828-837.

6. Collins, A., M. Munday, and A. Roberts, Environmental consequences of tourism consumption at major events: An analysis of the UK stages of the 2007 Tour de France. Journal of Travel Research, 2012. 51(5): p. 577-590.

7. Cooper, J.A., Making orange green? A critical carbon footprinting of Tennessee football gameday tourism. Journal of Sport & Tourism, 2020. 24(1): p. 31-51.

8. Cooper, J.A. and D.H. Alderman, Cancelling March Madness exposes opportunities for a more sustainable sports tourism economy. Tourism Geographies, 2020. 22(3): p. 525-535.

9. Čuček, L., J.J. Klemeš, and Z. Kravanja, A review of footprint analysis tools for monitoring impacts on sustainability. Journal of Cleaner Production, 2012. 34: p. 9-20.

10. Daddi, T., et al., Environmental management of sport events: a focus on European professional football. Sport, Business and Management: An International Journal, 2022. 12(2): p. 208-232.

11. Death, C., ‘Greening’the 2010 FIFA World Cup: Environmental sustainability and the mega-event in South Africa. Journal of Environmental Policy & Planning, 2011. 13(2): p. 99-117.

12. Dimengo, N., Crazy Sports Recruiting Stories. Bleacher Report, 2014.

13. Dolf, M. and P. Teehan, Reducing the carbon footprint of spectator and team travel at the University of British Columbia’s varsity sports events. Sport Management Review, 2015. 18(2): p. 244-255.

14. El Hanandeh, A., Quantifying the carbon footprint of religious tourism: the case of Hajj. Journal of cleaner Production, 2013. 52: p. 53-60.

15. EPA. Greenhouse Gases Equivalencies Calculator – Calculations and References. US EPA 2024; Available from: https://www.epa.gov/energy/greenhouse-gases-equivalencies-calculator-calculations-and-references.

16. ESPN.com. College Football Stats. 2024; Available from: https://www.espn.com/college-football/stats/_/view/team.

17. Filimonau, V., et al., Reviewing the carbon footprint analysis of hotels: Life Cycle Energy Analysis (LCEA) as a holistic method for carbon impact appraisal of tourist accommodation. Journal of cleaner production, 2011. 19(17-18): p. 1917-1930.

18. Franchetti, M.J. and D. Apul, Carbon footprint analysis: concepts, methods, implementation, and case studies. 2012: CRC press.

19. Getz, D., Policy for sustainable and responsible festivals and events: Institutionalization of a new paradigm. Journal of Policy Research in Tourism, Leisure and Events, 2009. 1(1): p. 61-78.

20. Glasspiegel, R., Texas spent $280,000 on Arch Manning recruitment weekend. New York Post, 2022.

21. Huml, M.R., et al., If we build it, will they come? The effect of new athletic facilities on recruiting rankings for power five football and men’s basketball programs. Journal of Marketing for Higher Education, 2019. 29(1): p. 1-18.

22. IEA. The world’s top 1% of emitters produce over 1000 times more CO2 than the bottom 1% – Analysis – IEA. 2024 2024/08/31/; Available from: https://www.iea.org/commentaries/the-world-s-top-1-of-emitters-produce-over-1000-times-more-co2-than-the-bottom-1.

23. Jeyarajah, S., College football recruiting expenses by conference: SEC stands out as Georgia spends big for success in 2022, in CBSSports. 2023: CBSSports.com.

24. Jude, A., Ice carvings and lavish dinners: A look at the cost of football recruiting at Washington. Spokesman, 2020.

25. Knight-Newhouse. Knight-Newhouse College Athletics Database 2024; Available from: https://knightnewhousedata.org/.

26. Macaulay, C., J. Cooper, and S. Dougherty, High school football and the athletic-market economy: Recruiting, producing, and manufacturing talent. Sociology of Sport Journal, 2019. 36(3): p. 203-212.

27. Mankin, J.A., J. Rivas, and J.J. Jewell, The effectiveness of college football recruiting ratings in predicting team success: A longitudinal study. Mankin, J., Rivas, J. & Jewell, J.(2021) The Effectiveness of College Football Recruiting Rankings in Predicting Team Success: A Longitudinal Study. Research in Business and Economics Journal, 2021. 14: p. 4-22.

28. Natural Resources Defense Council, Collegiate game changers: How campus sport is going green. 2013, Natural Resources Defense Council.

29. NCAA. Recruiting – Eligibility Center. 2024; Available from: https://www.ncaa.org/sports/2014/10/8/recruiting.aspx.

30. NCSA. Official Visits | How Does an Official Visit Work? 2024; Available from: https://www.ncsasports.org/ncaa-eligibility-center/recruiting-rules/official-visits.

31. Pandey, D., M. Agrawal, and J.S. Pandey, Carbon footprint: current methods of estimation. Environmental monitoring and assessment, 2011. 178(1): p. 135-160.

32. Raynor, G., Behind the scenes of Clemson’s biggest recruiting weekend. New York Times, 2020.

33. VanHaaren, T., NCAA allows schools to pay for two guardians to accompany recruits on official visits, in ESPN. 2016.

34. Wackernagel, M. and W. Rees, Ecological footprint: Reducing human impact on the earth. New Society, Gabriola Island, BC, Canada, 1996.

35. Watkins, J. and K. Slater, Talent level and major distribution in “Power Five” conference football programs. Journal for the Study of Sports and Athletes in Education, 2021. 15(2): p. 150-170.

36. Wiltfong, S., New LSU 2024 QB commit Colin Hurley takes you inside an epic weekend. 247Sports, 2022.

37. Wittry, A., An Analysis Of College Football Recruiting Costs, in Athletic Director U. 2022: https://athleticdirectoru.com.

38. Wuerzer, T., J.J. Fountain, and P.S. Finley, An Analysis of the Geographic Origins and Migration Patterns of Elite College Football Players. Geographical Review, 2023. 114(2): p. 157-179.

2025-10-13T15:18:13-05:00May 27th, 2026|Contemporary Sports Issues, Research, Sports Studies, Sports Studies and Sports Psychology|Comments Off on An Analysis of Carbon Emissions from College Football Recruiting Visits
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Over-promised, under-delivered: Does position in the National Football League draft matter?

Authors: Dennis M. Shaffer1 and Ryanne E. Shaffer

1Department of Psychology, The Ohio State University Mansfield, Mansfield, Ohio, USA

 

Corresponding Author:

Dennis M. Shaffer, PhD

1760 University Drive

Mansfield, OH 44906

[email protected]

Dennis M. Shaffer, PhD, is a Full Professor Psychology at The Ohio State University in Mansfield, Ohio. His research interests focus on how athletes use visual information to pursue and induce collisions with targets in the environment in domains such as Frisbee catching, American football, and baseball, and how cognition and systems of perception and action interact.

Ryanne E. Shaffer is currently a senior at Twinsburg High School in Twinsburg, Ohio.

ABSTRACT 

Purpose. We investigated whether players drafted higher in the National Football League (NFL) over a ten-year period performed better in their first four years in the league, consistent with the trade value charts and rookie wage scale the NFL uses to value players. The purpose was to see whether how the NFL intuits draft values is connected to player performance.

Methods. In Study 1, we collected draft position data for each of the seven rounds of the draft over a ten-year period as well as the values for each of two different trade charts and the salaries in the rookie wage scale. We then coded data by round, third of round (top, middle, bottom), years in the league, and Pro Football Focus (PFF) grades.

Results. We found no correlation between performance and the way the NFL values draft positions and no difference in player performance and years in the league between draft positions in rounds 4 and 5. There were also no differences in player performance or years played in the among top, middle, or bottom thirds of rounds. We also found a distinct advantage in player performance for teams trading down for draft picks compared to those trading up for draft picks, contrary to the way the NFL values draft positions.

Conclusions. Our work shows several player performance-based results that contradict well-established beliefs concerning the value of draft picks in the NFL.

Applications in Sport. Trade values and rookie wage salaries are used as baselines by the NFL. The importance of drafting better players higher in the draft order have important implications for greater success for teams, executives, and players. Our work may inform strategies that might be best to use in drafting prospective players in the National Football League.

Key Words: NFL draft, trade value, intuitive beliefs, player performance.

INTRODUCTION 

The work here tested whether draft position predicts player performance once they are drafted into the National Football League (NFL). The NFL draft is set up so the team with the worst regular season record picks first, followed by the team with the second worst regular season record picking second, and so on. Picking first, though it means you finished with the worst record in the league the previous year, is an enviable position to be in at draft time as you have your pick of ~250-~275 players. The NFL draft consists of seven rounds(since 1994) of draft picks where, at least originally, every team has one pick in every round. Prevailing wisdom in this field and even if you are picking teams for any game whether athletic or not is that higher picks should be valued more than lower picks and that over time the data should bear this out.

The intuitive beliefs that the NFL, individual teams, and executives have about draft order or draft pick position can be measured in two ways. First, this may be measured by what are called ‘trade value charts,’ that define values for each one of the draft picks (3). There are a few different types of trade value charts, but most teams follow one of these versions if they want to trade draft picks with any other team. The classic version of a trade value chart is the Jimmy Johnson (JJ) chart. A more recent chart is the Rich Hill (RH) trade value chart. These charts basically provide teams with a framework or baseline from which to trade draft picks (14). The trade value charts are similar in several ways—(1) values increase exponentially in the first round from about pick 4 to pick 1 and (2) values for picks decrease for each subsequent pick. For instance, Pick #10 in the JJ chart this year was given a value that was 46.3% of Pick#1 (RH chart = 36.9%); Pick #20 was given a value that was 28.33% of Pick #1 (RH chart = 26.9%), and Pick #30 was given a value that was 20.67% of Pick #1 (RH chart = 19.6%). Consistent with this, the ratio of values in the top third : middle third of the first round is 1.824 in the JJ chart, (RH chart = 2); middle third : bottom third is ~1.49 (RH = 1.55); top third : bottom third is ~2.71 (RH = 3.13), and bottom third of 1st : top third of 2nd is 1.3 (RH = 1.5).

The second way the NFL’s intuitive beliefs about draft order may be measured is by the ‘rookie wage scale’ put forth by the player’s labor union and the NFL in 2011, which defines the parameters for what every drafted player will earn in his first four years in the league (3). For instance, this year, the number one overall draft pick will earn $48,757,500 in total value over his first 4 years; the number 10 pick will earn a little less than 55% of that (a difference of over $22M over the first four years); the number 20 pick will earn about 37% of that (a difference of almost $30M), while the number 30 pick will earn about 31.25% of that (a difference of ~$33.5M). While the percentage and salary difference is less in subsequent rounds among those picks (picks 1, 10, 20, and 30 in rounds 2-7), the importance of drafting better players higher in the draft order have important implications for building the best team, paying players the proper amount for their performance, the amount of money that is charged to a team’s salary cap, and the livelihood of the NFL executives who have a hand in drafting these players.

Previous work has investigated several avenues regarding characteristics that affect draft value, that are related to performance once in the NFL (5, 9, 15, 17, 20). The results of some of this work show how draft value does very little to affect probabilities of teams making the playoffs (9, 15), Other work has shown that college performance is a better predictor of performance once in the NFL than tests measuring physical ability (11, 20-21). While other work has shown that total yards gained by running backs in college and overall speed has been shown to be a primary predictor of both draft status and higher salaries once in the NFL over tests of physical ability and combine tests (6, 11, 16-17, 20). Additionally, predicting success based on results of athletic testing including the NFL Combine can yield complicated and somewhat mixed results (16).

The primary focus of this paper was to investigate whether what teams intuit of draft value based on grades in these trade value charts and rookie wage scales matches actual performance data for the players chosen in those spots. More specifically, our primary investigative foci in Study 1 were to: (1) analyze whether differences in player value (as given by trade value charts and the rookie wage scale) from pick-to-subsequent-pick were correlated with differences in player performance from pick-to-subsequent-pick, (2) analyze whether player performance, as measured by Pro Football Focus (PFF) grades and years spent in the league, was different among and within rounds (14), (3) analyze whether PFF grades and years in the league were different among thirds of rounds across and within rounds, (4) and analyze how the NFL valuation and PFF grades for last twelve picks of the first round compared to the first twelve picks of the second round.

STUDY 1

METHODS

Data Sets

We first used the Pro Football Reference site (20) to gather and download data for every player drafted from 2011-2020. We then used the Pro Football Focus (14) site to gather the overall season grades for each player across their first four years in the NFL. This resulted in 2,544 drafted players across 10 years. This study was approved by The Ohio State University Behavioral and Social Sciences Institutional Review Board (Study Number: 2023B0282).

Procedure

Evaluating a Player’s First Four Years in the NFL

Since we were interested in evaluating the success of teams in drafting, we evaluated player performance over the player’s first four years. This is because four years is the length of all rookie (1st year player) contracts. Additionally, the first four years provides a very good indicator of what the teams think the player can do for their team in terms of performance.

Understanding the Pro Football Focus Grading System

PFF analyzes every player on every snap, with each play receiving a grade on a scale from -2 to +2. A score of 0 represents an average or the expected execution of the player’s responsibilities, while a +2 denotes an outstanding play and a -2 indicates a critical error. These assessments are adjusted for factors such as difficulty of assignment and game context. PFF’s system includes tracking over 200 data points per play using the All-22 coaches’ film, including such aspects as player alignment, assignment, and outcome of the play from every aspect of the field (1, 14). PFF then converts these evaluations into a normalized score on a 0–100 scale.

Calculation and Coding of PFF Grades and Years in the League

While PFF normalizes plays to values ranging from 0-100, the overall grades across an entire season of plays are far more restricted, ranging from ~high 40’s-low 90’s (for the requirement of at least 10 games played per season as described below). For every player, we calculated a mean for their overall PFF grade across their first four years after being drafted. For players with a missing grade, we found which of the four years there was a missing grade for and why. If the player was injured and missed the entire year (for any year), we did not count that year for their average and averaged across their other years. For players at most positions, we used the offense or defense overall grade for the given year. Only for punters and kickers did we use the special team grade. Our threshold for counting a PFF grade for the year, was at least ten games played. Additionally, if the drafting team waived the player they drafted, we assigned that player a value of 35, as that is below the lowest grade anyone on a team who played earned across an entire year of play (with a minimum of 10 games played). If they played on a team after they were waived, we filled in the four years with the grade(s) they earned in the remaining year(s) on the subsequent team. We wanted to penalize the drafting team, but we also did not want to assign a 0 as waiving the player was an act but does not represent their PFF grade over an entire year. Additionally, this happened far less often in earlier rounds and since we were calculating means, we did not want these outliers to dramatically influence the results. We assigned a value of 45 for a player who was on an NFL roster, but not active for the minimum number of games (or did not have enough snaps to be graded by PFF). This is a lower grade than any player we graded who played during the season for at least ten games and gave us a baseline for someone who is good enough to be on the team but may not be good enough/needed to dress on game day(s). We did not gather PFF data for rounds 6 and 7 as fewer players in these rounds were active for enough games (i.e., played enough snaps) for which PFF could assign grades.

Finally, we also analyzed the number of years players were in the league. Again, in the interests of evaluating how well teams draft, we were really focused on years in the league of these players over their first four to five years. Therefore, we coded years played in the league in categories of less than two years, two to three years, four years, five years, and more than five years, and then analyzed this coded data.

Availability of Data and Material

Data may be accessed at: https://osf.io/pf5hq/?view_only=28f7350c720f430b92270c76e5b48080

RESULTS

We performed Bayesian analyses throughout the Results sections for all experiments to properly identify and balance the same evidence in favor of as we did evidence opposed to differences, in line with the recommendations of both Dienes (4) and Kruschke (7). The primary independent variables were draft round and position within the round (top, middle, or bottom third), while the primary dependent variables were years in the league and PFF mean overall grade for players’ first four years in the league. We outline each set of analyses below.

Testing for Correlations Between Differences in PFF Grades and Differences in Jimmy Johnson and Rich Hill Trade Chart Values and Rookie Salaries for Each Subsequent Pick

 If players drafted with picks 1-10 are better than players drafted with picks 10-20, and so on, then both the difference in trade chart values and rookie wage scale salaries from pick #1 to pick #2 and pick #2 to #3 and so on through the first five rounds of the draft should be highly correlated with PFF grades. Bayesian correlational analyses showed substantial to strong evidence that there was close to zero correlation between PFF grades and trade chart values, RH trade value chart: Bayes Factor in favor of the null hypothesis (BF01)= 5.594, r = .086, JJ trade value chart: BF01= 10.485, r = .014, and PFF grades and rookie wage scale salaries: BF01= 9.047, r = .043. The Bayes factors may be interpreted that it is 5.594, 10.485, and 9.047 times as likely that there is no correlation between PFF grades and RH trade chart values, JJ trade chart values, and rookie wage scale salaries, respectively, than there is a correlation (12, 24). Values of BF01 or BF10 of 0-1 = no evidence, 1-3 = anecdotal evidence, 3-10 = substantial evidence, 10-30 = strong evidence, 30-100 = very strong evidence, and >100 = decisive evidence in favor of whatever hypothesis is being tested (null (BF01) or alternative (BF10) (12, 24).

Analyzing How the NFL Values Draft Positions Based on the Rookie Wage Scale

We first established how the NFL values draft position across rounds and thirds of rounds. We used the rookie wage scale salaries for the first five rounds of the draft (the same rounds for which we calculated PFF grades for players—picks 1-165). Bayesian analyses showed decisive evidence of differences in salaries across rounds, BF10= 2.806 x 10+37, F(4, 150) = 448.83, p < .001, h2 = 0.71, Cauchy Prior with a scale of .707. Post hoc tests also indicated decisive evidence for differences among all rounds. Bayesian analysis showed substantial evidence of differences in salaries across thirds of rounds, BF10= 4.99, F(2, 150) = 88.19, p < .001, h2 = 0.07, Cauchy Prior with a scale of .707. Post hoc tests confirmed between anecdotal to substantial evidence for differences among all thirds of rounds (top, middle, and bottom). Virtually identical results were found when performing these same analyses using each trade value chart in lieu of the rookie wage scale.

Analyzing Differences in Rounds for Coded Years in League and PFF Overall Mean Grade

 Coded Years in League

 A Bayesian one-way ANOVA analyzing whether there were differences in years played in the league showed that there were: BF10= 2.806 x 10+111 (decisive evidence), > Test value F(6, 2536) = 101.93, p < .001, h2 = 0.19, Cauchy Prior with a scale of .707. Post hoc tests indicated that there was moderate to strong evidence that players drafted in round 1 remained in the league somewhat longer than players drafted in round 2, BF10= 4.312 (moderate to substantial). Players in almost all subsequent rounds remained in the league for less time than the previous round. One exception was that there was no difference in years played in the league between rounds 4 and 5, BF01 = 3.83 in favor of no difference, indicating moderate to substantial evidence in favor of no difference in years played in the league for 4th and 5th round draft picks.

 PFF Overall Mean Grade

A Bayesian one-way ANOVA analyzing whether there were differences in PFF overall mean grade showed that there were: BF10= 2.673 x 10+59 (decisive evidence), > Test value F(6, 2536) = 80.95, p < .001, h2 = 0.16, Cauchy Prior with a scale of .707. Additionally, again almost all post hoc test BF10 evidence showed decisive evidence for differences among all five rounds with values ranging from BF10 = 188.192 to 2.724 x 10+38. The one exception was that there was no difference in PFF overall mean grade between rounds 4 and 5, BF01 = 4.51 in favor of no difference, indicating moderate to substantial evidence in favor of no difference. Figure 1 shows a graph of pick position (x-axis) by PFF grade (y-axis) for picks across all ten years.

Figure 1.

Shown is a plot of the pick number by overall mean PFF grade for the first 4 years. Each symbol represents the average PFF grade across 10 years for a particular position in the draft (picks1-179).

Differences in Thirds of Rounds for Coded Years in League and PFF Overall Mean Grade

A Bayesian one-way ANOVA analyzing whether there were differences in years played in the league in terms of whether a player was chosen at the top, in the middle, or at the bottom third of the round showed decisive evidence that there is no difference: BF01= 20.998, Cauchy Prior with a scale of .707.

PFF Overall Mean Grade

A Bayesian one-way ANOVA analyzing whether there were differences in PFF overall mean grade showed decisive evidence that there also is no difference: BF01= 30.292, Cauchy Prior with a scale of .707.

Differences Among Top, Middle, and Bottom of Rounds for Coded Years in League and PFF Overall Mean Grade Round-by-Round

While our previous analyses show no differences among player longevity and PFF overall mean grade across the top, middle, and bottom of rounds, it could be that any potential differences were washed out by combining rounds for the analysis. For instance, later rounds that have lesser talented players overall may see no differences, or have more talented players at the middle and bottom of rounds than the tops of rounds, whereas earlier rounds may have more talented players at the tops of rounds than at the middle and bottom of rounds. These effects or patterns may cancel each other out by combining all rounds. Therefore, we again tested for differences among the top, middle, and bottom third of rounds, but this time did so within each round. Table 1 shows the results of these analyses.

Table 1.

Shown are Bayes factor in favor of the null hypothesis (BF01) for one-way ANOVAs testing for differences in coded years in the league and PFF overall mean grades for draft picks in rounds 1-7 (for years) and round 1-5 (for PFF grades) from 2011-2020. Values of BF01 of 1-3 = anecdotal evidence, 3-10 = substantial evidence, 10-30 = strong evidence, 30-100 = very strong evidence, and >100 = decisive evidence in favor of the null hypothesis) (12, 23).

Round 1Round 2Round 3Round 4Round 5Round 6Round 7
Years in League2.2373.2847.1034.856.1791.28510.313
PFF Grades8.54318.6256.6032.5219.475  

Predicting PFF Grades from Trade Value Charts and Evaluating Whether Trading Up into the First Round from the Second Round Warranted

Many times, draft experts will argue that some teams may “trade up” into the bottom third of the first round—that is, the last ~twelve to fifteen (~picks 18-32 or so)–from the top of the second round in order to draft a second player for whom they will have the 5th year option (1st round pick). Many teams have done this in the past. In fact, according to the values themselves, the NFL views the bottom 10-15 picks in round 1 as over 7008 times greater in value than the top 10-15 picks in round 2 , BF10= 7008.114, Cauchy Prior with a scale of .707). When we analyzed PFF grades across ten years for the “bottom third” of the first round (12 picks—21-32) and compared them to PFF grades across ten years for the “top third” of the second round (12 picks—33-44), a Bayesian one-way ANOVA showed substantial evidence that there is no difference: BF01= 6.854, Cauchy Prior with a scale of .707 (MBottom10of1st = 63.835; SDBottom10of1st = 10.642, MTop10of2nd= 64.387, SDTop10of2nd = 9.975).

STUDY 2

In Study 1 we found that the NFL values draft positions in the top of a round far more than those in the middle or bottom of a round and those in the middle of the round far more than those in the bottom of a round. However, there was substantial to decisive evidence of no differences in PFF grades across and within rounds, respectively, for top, middle, and bottom thirds of draft positions in rounds. We also found that there was no difference in PFF grades for draft positions in the top third of the 2nd round compared to the bottom third of the 1st round. This predicts that teams should not move up in a draft for players as the player performance will not be better for players drafted even 20-30 picks higher. When teams move up in the draft, they give up more draft capital for at least two reasons. First, while the values in the trade value chart might be even, typically the team moving back must give up more than one pick to do that in order to even out the trade value. Second, the team trading down must be incentivized in some ways to trade down. Sometimes, that team simply needs more players for the values to be even. Other times, the team trading down will ask for more as they are giving up an attractive draft pick. In Study 2, we sought to investigate whether the findings from the ten year period we investigated in Study 1 would predict the outcome of pick-for-pick trades in the 2021 NFL draft.

METHODS

We identified each of the draft pick-for-draft pick trades in the draft immediately after the last season for which we analyzed draft picks (the 2021 NFL draft). We evaluated each of the twenty-nine trades that are listed by the NFL that occurred during the 2021 draft (15). We did this because the 2021 draft was the first draft after the last year for which player performance data was collected so it allowed us to test whether our findings predicted future patterns and because it was the last year that would still allow us to analyze player performance in the first four years of the player’s career. We only looked at trades involving draft picks for draft picks.

Raters

We had two high school football players (MAge = 18 years, MExperiencePlayingCompetitiveFootball = 6 years) who have a strong knowledge of not only the workings of football but also a strong knowledge of the NFL, the NFL draft, and grading players.

Procedure     

We gave raters the series of trades with round(s), pick number(s), and PFF grades across years played listed for each pick. We removed the draft year and team and player names from the list. Raters were also blind to which part of the trade was the “trade up” and which part was the “trade down.” Our list consisted of Team A on one side and Team B on the other. We randomly assigned which team (“trade up” or “trade down”) was Team A and which team was Team B. We instructed raters on how PFF grades are set up and general cutoffs for what PFF grades are generally considered elite, good, above average, average, and poor. We also instructed them to decide which team “won” each trade. While they were instructed that they should use all the information available in making their decisions, they were told that the performance of the players (i.e. PFF grades) should be paramount in making their decisions.

Raters made their judgments independently from one another. They were initially seated in two different areas at the same time while they made their judgments. They then came together, compared their judgments, and went over the judgments that were different to see whether they could come to a consensus on the judgments that were different.

RESULTS

The raters initially agreed on 20/29 trades. After discussing the trades they had originally disagreed on, they came to a consensus on all 29. Of the 9 on which they initially had different answers, neither rater favored the “trade up” team; each of the 9 consisted of one rater deciding on the “trade down” team and the other deciding on “neither.” For 6/9 of the trades they eventually decided on “neither,” and in the other 3 trades they decided on “trade down.” Finally agreed-upon frequencies for each group were: Trade Up: 4, Trade Down: 19, and Neither: 6.

Since we were only interested in testing whether trading up resulted in better player performance, we were most interested in a comparison where we split the categories into the following two groups: Group 1: Trade Up and Group 2: Trade Down and Neither. We performed a Bayesian binomial test on frequencies of what the raters judged as “wins” in each category. Raters judged that there were significantly more wins in terms of better performing players for teams who traded down than for teams who traded up, BF10  = 753.471, Proportion = .832, Prior Distribution with α and β = 1. This is decisive evidence that trading down led to better performing players than trading up and may be interpreted that it is more than 753 times more likely that trading down led to better performing players than trading up. In a second analysis, we compared only trade downs versus trade ups and removed any trade that resulted in a judgement of “neither.” Raters again judged that there were significantly more wins in terms of better performing players for teams who traded down than for teams who traded up, BF10  = 39.472 , Proportion = .826, Prior Distribution with α and β = 1. This indicates very strong evidence that trading down led to better performing players than trading up. Therefore, even when solely comparing trade ups versus trade downs, it is still over thirty nine more times likely that trading down led to better performing players than trading up.

DISCUSSION 

The way the NFL values draft positions in terms of trade values and rookie salaries is not correlated at all with player performance consistent with previous work (14). While time spent in the league and overall PFF grade during their rookie contracts did, for the most part, gradually decline in subsequent rounds as trade value charts, fans, and NFL executives would all predict, this pattern was not straightforward. One large deviation from this gradual decline between rounds was between the  4th and 5th rounds, where there was moderate to substantial evidence in favor of no difference in both years played and overall PFF grades between those rounds, contradicting how the NFL values draft position. In fact, if we use trade values as a representation of people’s intuitions then we should expect far greater value out of 4th round picks than we do from 5th round picks, as a Bayesian independent-samples t-test analyzing trade values in round 4 versus round 5 found decisive evidence that round 4 values are significantly greater than round 5 values, BF10= 7.294 x 10+11, Cauchy Prior with a scale of .707. According to the values themselves, the NFL views round 4 picks as 7.294 x 10+11 greater in value than 5th round picks.

There were several other counterintuitive findings. First, there was decisive evidence of no difference among the top, middle, and bottom thirds of rounds across all rounds for both years in the league and PFF grades. Second, this evidence of no difference for both years in the league and PFF grades among the top, middle, and bottom thirds of rounds was a regularity for every round when evaluating each round individually. Third, we found that the performance of players taken in the top third of the second round was no different from the performance of players taken in the bottom third of the first round across all ten years, contradicting what the trade values tell us—that there is decisive evidence in favor of differences in those respective trade values.

When we looked at trades that occurred in 2021, we found that, in terms of quality of player(s), the large majority—over 82%–and significant number of trades did not favor the team who traded higher up in the draft where that pick had greater value. This result is consistent with what was found with the analyses finding no differences across thirds of rounds across and within rounds across our data. This has important implications for not only player performance, but also because it has been recently shown that teams getting the better end of trades increase their probability of making the playoffs (9).

There were limitations to this study. First, while PFF grades are used by NFL teams, NFL analytics sites, and content creators to assess player performance and are seen as the best tool for doing this, they are not perfect. However, while there may be an argument as to what goes into creating the absolute grades, we analyzed the grades relatively for players so the shortcomings of the grades themselves would apply to all players. A second limitation is that we used trade values and rookie wage salaries to as a measure of how general managers (GMs) of teams and the NFL as a whole assess player quality without directly asking them about how they value draft positions. However, there was a collective bargaining agreement between the NFL and player’s union that put in place the rookie wage scale in 2011 (3), and owners, GMs, and players all had their input into how this would be created. Additionally, every team in the NFL uses these trade values as the standard way to barter before, during, and after the draft. Thus, we feel this was a fair way to assess the way the NFL values draft positions.

Further research should be conducted to see how the player performance grades in the first four years connect with second contracts of players in their next 2-5 years. It may be that it takes certain players four years to blossom in the league. However, the average tenure of a player who makes the opening-day roster is ~6 years (about half of that if you include drafted players who do not make the opening day roster). Other work should focus on directly assessing the executives in charge of the teams who draft players and the intuitions they have regarding trading up or down in the draft and what goes into these decisions. It may be that player performance is not the only factor that drives this decision making.

CONCLUSION 

Differences in the way the NFL values draft positions are not associated with player performance in those respective draft positions. This occurs whether you analyze differences in values assigned to draft positions, different positions within a round, or adjacent positions across rounds. These patterns from our findings also predict the outcomes of future drafts in terms of the assets a team trading up gets compared to a team trading down.

APPLICATIONS IN SPORT

Trade values and trade value charts in the NFL are used as the baselines by which to trade draft picks. These charts serve at least two purposes. First, they give general managers a common mechanism that they generally agree on to trade draft picks. Second, it prevents desperate teams from trading away too much and prevents overly greedy teams from demanding too much. These values assign an assumed or perceived worth of the player picked in that position. The idea is that, while picks that are very close together may result in players that are of equal talent, picks that are several positions away from one another should result in better players for those picks that are higher in the draft order. This is reflected in the draft assets that teams are willing to give up to move up in the draft order. Our work shows that there are several performance-based patterns that contradict these naïve beliefs stemming from values given to players. While some teams might argue that they needed a player at a specific position over the best available player, one would expect that if teams stayed with their original pick, that across a general manager’s tenure they would be better off picking someone who provides better performance and not positional need. One should also expect that over one’s tenure the player performance is more valuable as a better player is more valuable as a trade asset. Our work may inform strategies that might be best to use in drafting prospective players in the National Football League.

ACKNOWLEDGEMENTS

Dennis M. Shaffer conceptualized the studies. For Study 1, the author oversaw investigation, methodology, and data curation. Formal analysis in the paper was conducted by this author. 

Ryanne E. Shaffer contributed to both studies, assisting with data curation for Study 1, and conducting Study 2. Dennis M. Shaffer supervised Study 2. 

The paper was drafted by Dennis M. Shaffer; the paper was reviewed and edited by Ryanne E. Shaffer. 

The authors would like to thank JD Okuma and Gavin Davis for their work as raters.

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2025-10-13T10:22:32-05:00April 29th, 2026|Research, Sports Coaching, Sports Management|Comments Off on Over-promised, under-delivered: Does position in the National Football League draft matter?
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