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The Globalization of Professional Basketball: Context and Competition Matters in the NBA, WNBA, and Olympics

Authors: Howard Bartee, Jr., Ed.D.¹

1School of Public and Allied Health, Division of Kinesiology and Physical Education, Prairie View A & M University, Prairie View, TX, USA

Corresponding Author:

Corresponding Author:
Howard Bartee, Jr., Ed.D.
Prairie View A & M University
700 University Drive
Prairie View, TX 77446
[email protected]
770-314-4415

Howard Bartee, Jr., Ed.D. is an Assistant Professor of Health and Kinesiology-Sport Management at Prairie View A & M University in Prairie View, TX. His research interests include sports management and communication, sports analytics, and organizational behavior within the context of health and kinesiology. With nearly twenty-five years in higher education, Dr. Bartee has served in administrative capacities and previously taught sports management and sports administration courses at Houston Christian University in Houston, TX and Belhaven University in Jackson, MS. Dr. Bartee has further spearheaded initiatives related to sports career services, student advisement, and program and curriculum development.

ABSTRACT
The role of professional basketball has evolved through the years given socio-historic and current perspectives involving the NBA, WNBA, and Olympics. Such perspectives have shaped the context and competition for globalization and the subsequent impact and implications for the broader basketball industry.

Key Words: athletic competition, sports history, international ambassadors

INTRODUCTION

Professional basketball for both men and women, as a globalized sport, has grown tremendously from the days of the peach basket on the basketball court to now being played in a virtual environment of NBA 2K video games. Globalization refers to global, international merging of diverse national economic, socio-cultural, political, and technological forces into a single and coalesced society (14). Internal and external forces have influenced the expansion of the game and which, in effect, draw attention to professional basketball leagues and the Olympics in understanding how they have impacted these outcomes.

From a practical viewpoint, while the careers of LeBron James (NBA), Kevin Durant (NBA), Steph Curry (NBA), Tina Charles (WNBA) and Diana Taurasi (WNBA) may have reached a twilight stage, when considering their careers in totality, their contributions to professional basketball arena and the broader public of media and related markets informed globalization given their appeal across the world stage. When considering the emerging careers of Jaylen Brown (NBA), Victor Wembanyama (NBA), Caitlin Clark (WNBA), A’ja Wilson (WNBA), and Angel Reese (WNBA) launch, their emerging careers offer a unique opportunity for the professional game of basketball within the United States to (re)define a model for how to expand globally within the current state of professional basketball and the role of the Olympics.

Thus, using sociohistorical and current perspectives and demographical information, the following questions guide this exploration:

What is the impact of the WNBA and NBA, post-1992 Olympics to the present, for the globalization of the game of basketball?
What implications do the globalization of professional basketball hold for WNBA, NBA, and the broader Olympics?

These questions provide the context for understanding how the game of basketball and some marketing aspects has evolved given expanding technological aspects and the unique comparisons between the different eras of growth since 1904.(13) These questions show how competition within the NBA and WNBA contributes to overall globalization and marketing outcomes. (1). Using the implications of both context and competition, these questions offer a broader understanding of the impact of the globalization of basketball and how it informs the future state of the game, the players and related marketing components (9).

Context Matters for the NBA and WNBA and Olympics Demographics as Globalization Impacts

A View on the 1992 to the 2024 Olympics on Men’s Basketball for Globalization

Context matters for globalization of men’s basketball, particularly given how the 1992 Olympics for men brought forth a new playing field of competition. The competition that became apparent was focused on the United States closing the gaps between amateurism, professionalism, and international competition. With the convergence of these three concepts came the entrance of NBA players into the Olympics Games as well as the first steps toward globalization. According to Olympic history, “in 1992, for the first time, NBA players were allowed by FIBA to represent the USA and all other countries in national team competition” (7). At the time, the 1992 U.S. team was considered the greatest team ever assembled as they dominated the 1992 Olympic tournament, led by Michael Jordan, Magic Johnson and Larry Bird, on their way to winning the gold medal. Photo #1 features this team of NBA professional players competing on the international scene changed the game of basketball forever. (2)

Photo Credit: Bill Bender The Sporting News) Inside the ‘Dream Team’: A complete roster & history of USA’s 1992 Olympic men’s basketball team | Sporting News

And so, from the 1992 Olympics to the 2024 Olympics, globalization of basketball has increased on various levels, both domestically and internationally. The resulting impact of these changes has resulted in different responses from different nations. It is important to note that not all countries are excited to release their valuable athletic resources for the capitalistic society of the NBA in the United States, yet there are many countries that do support the globalization movement to a more diverse marketplace of professional basketball.

To that end, when it comes to the global sports marketplace, professional basketball has grown as indicated by the countries represented. This has allowed new players and fans to enter the game. One of the most important entrances into the NBA was that of Yao Ming from China being drafted by the Houston Rockets in 2002 as the #1 pick and later a global ambassador for the 2008 Olympic Games. During these years, following the Beijing Olympics until 2012, basketball competition highlighted the effect of how global inclusion started affecting the outcome of games as the European league players were competing more closely with NBA players. The progression of basketball globalization moved to whole new levels not only based upon player competition in the Olympic Games, but also, based upon player entrance into the professional ranks of the NBA. Over the last sixteen years, the team has won gold in 2012, 2016, 2021 (during the pandemic years, following postponement in 2020), and most recently, in 2024. With the influx of new players, fans, and corporate sponsors, especially since the 1992 Barcelona Olympics until the 2024 France Olympics, consideration of different aspects of this globalization are provided.

As a result, what is of interest to note for the NBA teams is that the countries now performing well on the Olympic stage are also sending players to the NBA through the draft. The impact of this new wave of draftees is not only influencing the Olympics, but it is also influencing the draft classes, as history shows us. For example, the NBA and the Olympic Games have both seen shifts in roster makeups and globalization efforts over the last 32 years, since the 1992 Dream Team played in Barcelona, Spain. In the following Figure 1, there is a state-by-state visualization of the birthplace of U.S. born NBA and ABA Players. Figure 1 is as follows:

From countries abroad to the United States, a basketball “rite of passage” is being seen in the total number of draft picks being selected between U.S. Born NBA and ABA Players in comparison to those non-U.S. Born basketball players. Figure 1 shows the top 5 states are as follows: California (443), New York (440), Illinois (302), Pennsylvania (250), and Texas (211).

As a result, Figure 1 provides the foundation for understanding how opportunities could be provided through the NBA draft on a worldwide scale, particularly given the relationships or networks that can be established within each of these countries. These contacts help to create a context for toward globalizing efforts. And while these networks or relationships do not guarantee NBA stardom or a roster spot, they do provide a glimmer of hope and expanded area for recruitment. This hope extends for not only the individual players, but for their countries, communities, families, and friend, which, in effect, is an upside trend of a new global basketball marketplace is emerging. Table 1 particularly identifies the birthplace of non-US born NBA and ABA Players. Table 1 indicates the following:

Table 1, according to (16), shows most of the non-US born NBA and ABA players are born in the top three (3) countries of Canada (n=54, France (n=38), and Germany (n=27). Table 1 also shows the gap existing between the birthplaces of those coming from larger countries compared to those coming from smaller countries. What can be surmised from Table 1 is that while the competition gap has gotten smaller, the challenge to enhance greater roster structures has become increasingly important. Owners, general managers, and coaches are feeling the need to scout not only the colleges of America, but they must also scout the high schools and the international leagues of the world. The increased attention on these different talent pools is not only affecting NBA business locally, but it is also affecting NBA business globally. Particularly within this structure, global scouting is being shown through current NBA rosters. The NBA is experiencing expanded growth internationally. Table 2 particularly identifies the countries of those players from the different countries. Table 2 is as follows:

Table 2, according to (11), shows that the majority of the players come from the country of Canada with the next highest number of players coming from the country of France. A number of countries have only one player that comes from there. Table 2 identifies the frequency in which foreign players (N=125) were on opening day NBA rosters during the 20232024 season. The table reveals that 20.8% of the players were from Canada, while 79.2% of the players were from 39 other countries. In effect, it can be surmised that over a period of one season, Canada had more players on 2023-2024 Opening Day NBA rosters as compared to the other 39 countries represented on the 2023-2024 rosters. Table 3 shows the nationalities of the

NBA All Star players. Table 3 is as follows:

Table 3, according to (11), identifies the frequency in which foreign players (N=7) were on the NBA All-Star rosters during the 2023-2024 season. The table reveals that 27% of the player appearances were from seven countries, while 73% of the player appearances were from the United States during this same period. As a result of these findings, it can be assumed that over a period of the most recent NBA All-Star Game, players with a primary United States nationality had more All-Star game appearance in the 2023-2024 season as compared to the other7 foreign countries and 7 foreign players represented during this same period inclusive of the Eastern and Western Conferences. Context matters.

A View on the 1976 Olympics on Women’s Basketball for Globalization

Context matters, too, with regards to women’s basketball. Starting in 1976 at the Olympics and continuing in 2024, there has been tremendous growth in the sport of women’s basketball. During these past forty-eight years, the United States has led the world in the number of gold medals received during Women’s Basketball Olympics competition. With this level of dominance, the United States and women’s basketball players have evolved since winning a silver medal in 1976. Their first year of competition included players Luisa Harris, Nancy Lieberman, Ann Meyers, Cindy Brogdon, Susan Rojcewicz, Nancy Dunkle, Charlotte Lewis, Gail Marquis, Patricia Roberts, Mary Anne O’Connor, Patricia Head and Juliene Simpson and Photo #2 features this Women’s Basketball Olympic Team. (5)

Photo Credit: Bill Bender The Sporting News) Inside the ‘Dream Team’: A complete roster & history of USA’s 1992 Olympic men’s basketball team | Sporting News

These players were coached by Cal State Fullerton Head Coach Billie Moore and assisted by Stephen F. Austin Head Coach Sue Gunter in the first year of Olympics competition to their current eight Olympics gold medal winning streak in 2024. Photo #3 highlights the women’s basketball team winning in 2024. (6)

Photo Credit: Mark J. Terrill/AP (2024 USA Women’s Basketball Team) US women win eighth straight Olympic basketball gold medal – CSMonitor.com

Table 4 highlights the 2024 Olympics Team comprised of players from across the country and is shown as follows:

Source: Kyle Irving (The Sporting News) USA women’s Olympic basketball roster: A’ja Wilson, Breanna Stewart headline 2024 U.S. team for Paris | Sporting News

Table 4 shows that the majority of the women’s basketball players came from the Las Vegas Aces. Only one player came from the Connecticut Sun and the Seattle Sun. Table 5 highlights the coaching staff for this Olympic Team and is shown as follows:

Table 5 shows a diversity of coaches that was inclusive of both university and professional areas. This integrated approach certainly allowed for a broadened perspective on coaching to be enacted. Notwithstanding, with the passage of Title IX in 1972 and the growth of women’s basketball in the United States between 1972 and the bicentennial year of our nation’s founding in 1976, a team was able to be fielded for the Montreal Olympic games in Canada. Though the team from the Soviet Union would win the gold medal in 1976, there was stiff competition as the United States finished with the silver medal and the team from Bulgaria would win the bronze. Consequently, the evolution of women in basketball emerged in various ways within the country and beyond. Context matters.

Competition Matters for NBA and WNBA and Olympics Demographics as Globalization Impacts

A View on The Team and Medals Received in Men’s Basketball for Globalization

Competition matters as part of globalization and impact for the NBA. History shows that since 1936, the United States has led the world in the number of gold medals received during Men’s Basketball Olympics competition. As Table 6, Table 7, and Table 8 show, excluding, 1940 and 1944, in which Olympic Games were not held and noted as N/A, the United States has won 81% of the gold medals, three countries, the old Soviet Union (17.3%), Yugoslavia (17.3%) and France (17.3% )have won 52% of the silver medals, and two countries, Brazil (13%) and

Lithuania (13%), have won 26% of the bronze medal. With this level of dominance, the United States and its’ basketball players are a cut above the rest in terms of Olympic basketball and international participation in both men’s and women’s basketball. More specifically, Table 6 indicates that the men received a substantial number of gold medals. Table 6 indicates the following:

Men’s Olympic Gold Medals Since 1936 (N=21)

Table 6, according to (10), shows how the United States has won substantially more gold medals than any of the other competing countries. No other country has come close to the United States in receiving gold medals in basketball. Table 7 highlights the silver medals received by the United States since 1936. Table 7 is as follows:

Table 7, according to (10), shows that a three-way tie existed between France, the Soviet Union, and Yugoslavia with having four (4) medals. The United States has received one (1) silver medal along with the countries of Canda, Croatia, and Serbia. Table 8 highlights the number of bronze medals received since 1936 by different countries. Table 8 shows the following:

Table 8, according to (10), shows that the countries of Brazil and Lithuania have received three (3) bronze medals. The United States has received two bronze medals along with the countries of the Soviet Union, Uruguay, Yugoslavia, and the one listed as N/A. Thus, the composition of the medals received by the United States is clearly at the gold level with less medals being received at the silver and bronze levels. Table 9, however, provides insights into the competition experienced by those who were part of the NBA finals. Table 9 is as follows:

Table 9, according to (4), identifies the frequency in which players with foreign nationalities (N=6) were on NBA Finals rosters during the 55 years of NBA Finals MVP selections from 1969 to the most 2024 season. The table reveals that 6 of the 35 (17%) of the MVP Finals MVPs were from France, Greece, Nigeria, Serbia, U.S. Virgin Islands, and Germany, while 29 of the 35 (83%) were of United States nationality. As a result of these findings, it can be assumed that over a period of 55 years of NBA Finals from 1969-2024, pre-

1992 and the Olympic Dream Team in Barcelona, all Finals MVP’s were of U.S. Nationality, while post-1992 and until most recently, in 2023, there six individuals that have won the coveted title of NBA Finals MVP as a direct result of globalization of basketball. Table 10 shows the following outcomes in the competition from those involved with the NBA Finals and their background:

Table 10, according to (4), indicates how the players came from the San Antonio Spurs the majority of the times which indicates a priority of producing MVPs might be emphasized within that organization. These players primarily came from the U.S. Virgin Islands which also might indicate a pipeline being utilized to recruit players from that area. Nevertheless, with globalization, competition matters.

A View on The Team and Medals Received in Women’s Basketball for Globalization

Competition matters, too, for women’s basketball when considering globalization. As Tables 11-13 show aggregately and collectively, the United States has won 77% of the gold medals, while two countries, Australia (23%) and France (15%) have won silver medals with eight countries winning at least one silver medal each to make up the remaining 62% of medal recipients; whereas two countries, Australia (23%) and Russia (15%) have won bronze medals with eight countries winning at least one bronze medal each to make up the remaining 62% of medal recipients. Table 11 highlights the United Sates in comparison to other teams.

Table 11 is as follows:

Women’s Olympic Gold Medals Since 1976 (N=13)

Table 11, according to (10), indicates the Soviet Union as only having received one gold medal since 1976. The United States Women’s Team has had ten (10) gold medals within this time. Table 12, however, highlights the silver medals where Australia had the highest number of silver medal at three (3). Table 12 is as follows:

Women’s Olympic Silver Medals Since 1976 (N=13)

Table 12, according to (10), shows several countries with only one silver medal. Some of those countries include China, Australia, South Korea, Spain, and others. Table 13 highlights those countries that have received bronze medals since 1976. Table 13 is as follows:

Women’s Olympic Bronze Medals Since 1976 (N=13)

Table 13, according to (10), indicates Australia with the highest number of bronze medals. Russia has received two (2) silver medals while several countries received one (1) bronze medal. What becomes evident is the consistency of the United States as the recipient of gold medals throughout the years. Australia is identified as the country that is next in terms of the medals received since this time. Competition matters.

Shared Implications on Context and Competition Matter: The NBA, WNBA, Olympics, and Globalization for Basketball

Context and competition have shared implications for globalization when considering the NBA, WNBA, and the Olympics. From historic Olympic, NBA, and WNBA games to the more recent Olympic, NBA, and WNBA games, it remains important to continuously consider the sociohistorical and current impact upon the globalization of the game of basketball. Both the NBA and WNBA markets are continuing to evolve into the vision first spoken by late NBA Commissioner, David Stern vision of globalization and during the WNBA’s first president, Val Ackerman, service as a U.S. representative to the International Basketball Federation (FIBA), to grow the game of basketball. Currently, as it stands in 2024, the economic, social, political, and technological changes that are taking place are evident as the game of basketball is part of the global sports industry, that is worth $484 Billion Dollars in 2023, according to The Business Research Company in April of 2024, with an expected market growth rate of 6.1% over the next five years from $484 Billion in 2023 to an estimated $862 Billion in 2028.(15) Such financial outcomes collectively shape the context and competition for professional basketball.

Furthermore, the Olympics Games of 2024 has provided a unique example of how much the game has grown ever since the 1992 Dream Team of NBA Players entered the competition. Through the vision of the late NBA Commissioner, David Stern, and the continued efforts of current NBA Commissioner, Adam Silver, the game and competition continued to improve. This year’s Olympic Game Gold Medal Games was another example of how far globalization has come as the United States of America competed in the Men’s and Women’s finals again the host country of France, with each of these games featuring players from not only globally, but from the NBA in the Men’s Gold Medal Game and from the WNBA in the Women’s Gold Medal Game.

To that end, from both context and competition stances, the game will continue to build upon the past success of this year’s Olympic Games as it was viewed globally by millions. With almost 400 million fans in 2024, basketball continues to expand across the globe. For example, this year’s Men’s Olympic Games gold medal game averaged 19.5 million viewers on NBC and Peacock, which according to the (3) in the New York Times (2024). According to LeBron James in that same article regarding the United States Olympic Games Gold Medal Game, “we got our moment…it’s a basketball world and everybody loves the game; we just hope that we continue to inspire people all over the world”. As one of the most recognizable figures in the game and the first active NBA billionaire player, LeBron James, along with Kevin Duran, Steph Curry and the 2024 Olympic Gold Media winning team of NBA superstars, the U.S. Team was able to capture the gold and continue in the legacy of past U.S. Olympics teams made up of NBA superstars.

Additionally, from an WNBA perspective, the U.S. Women’s Olympic Team, led by WNBA MVP, Aja Wilson of the Las Vegas Aces’ and her fellow WNBA and Olympic teammates was able to win the gold medal over France with “a peak viewership of 10.9 million for the final half hour of the one-point affair” (8). With the growth of women’s basketball on the collegiate level, through the emergence of budding stars, Caitlin Clark (Iowa) and Angel Reese (LSU), they are now in the WNBA, with Clark, with the Indiana Fever and Reese, now with the Chicago Sky and will potentially be in the 2028 Olympics to help extend their record eight straight goal medal streak started in 1996. As a result, the future is very bright with the new stars emerging in the NBA, WNBA and Olympic games, while the old guard passes the torch to the next generation. Therefore, as the past is cherished, the present is held and the future is embarked upon, basketball is changing because of the demographic makeup of National Basketball Association (NBA), Women’s National Basketball Association (WNBA) and Olympic team rosters in 2024 and beyond (12). Context and competition matter.

In closing, since the founding of basketball at Springfield College by Dr. James Naismith in 1891, for both men and women now, the pathways into the globalization of professional basketball has expanded from a small college to larger colleges and universities to professional leagues to countries from across the world. With there being no boundaries, the opportunities for globalization remain limitless. Thus, the success of individual teams led by those individual basketball players born outside of the United States has not only led to an increased fanbase, but also has allowed the Olympic game talent to become more talented. As “Table 1: Birthplace of non-U.S. Born NBA and ABA Players” and “Table 2: NBA Rosters from a Global Perspective, 2023-2024” show, the nationalities of players have grown exponentially, while at the same time, selection of MVP’s has grown as well. The cities of Houston, San Antonio, Dallas, Milwaukee, and Denver, which now boast NBA Finals MVP’s have all represented their counties well, along with those respectful induvial players.

When considering both context and competition, with the U.S. dominance in both Men’s and Women’s Gold Medal games, the next four years will offer interesting perspectives to consider as countries seek to close the talent gap between those teams that have and those two teams that have not. These are tremendous efforts, particularly since 2020/2021 during the pandemic when the teams of the NBA and WNBA, had to play in the bubble, the unintended yet, resulting, outcome has led to higher medical protocols and concerns for those participating then and even now. In effect, many will wonder how globalization will influence context and competition for the next four years. With the Olympics coming to Los Angeles in 2028, it will be critical that those involved in sports stay encouraged as the games continue to grow as the growth will foster itself as new markets come aboard. Moreover, as new forms of gaming enter the technical arena, having knowledge of the past histories allows one to be able to learn the necessities for current and future matters of context and competition, particularly given the rise of e-sports and related virtual gaming. By learning the game through e-sports and video games, participants can utilize their movements into today’s face to face games. Strategic planning and coaching sessions help to make today’s understanding of the globalized basketball game in a more reflective and projected manner. Within these types of sessions, learning about the world of gaming offers more engaging and relevant experiences. Such sessions create the platform for further advancing the globalized game of basketball for engaging professional and amateur worlds. With the popularity of the NBA and WNBA and the Olympics being at an all-time high, understanding the globalization of basketball, particularly given the implications and impact of context and competition, becomes important for how the future game of professional basketball is shaped for future generations

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George Minoso2024-12-03T15:53:49-06:00December 20th, 2024|Contemporary Sports Issues, General, Olympics, Research, Sports Exercise Science|Comments Off

The Predictive Ability of the Physical Skills Used at the NFL Combine to Predict Draft Status

Authors: Raymond Tucker ¹, Chang Lee ², Willie J. Black³

1 College of Education and Health Professions, University of Houston at Victoria, Victoria, TX, USA
2 College of Education and Health Professions, University of Houston at Victoria, Victoria, TX, USA
3 College of Education and Health Professions, University of Houston at Victoria, Victoria, TX, USA

Corresponding Author:

Raymond Tucker D.S.M., CFSC, CSCS * D, XPS, FMS, USATF, USAW
College of Education and Health Professions
University of Houston-Victoria
3007 N Ben Wilson St
[email protected]

Raymond Tucker, D.S.M., is an Associate Professor of Kinesiology at the University of Houston in Victoria, Texas. His research interests focus on leadership skills used by coaches in their daily interactions with athletes and various topics in strength and conditioning and sports performance.

Chang Lee, PhD, is an Associate Professor at the University of Houston at Victoria in Victoria, Texas. His research interest focuses on investigating the effects of resistance exercise and nutrition on skeletal muscle responses including lean mass and strength gains.

Willie J Black, EdD, Willie J. Black, Jr. Ed.D. is an Associate Professor of Kinesiology at the University of Houston in Victoria, Texas. His research interests are centering on leadership, physical education pedagogy, and social justice in physical education.

ABSTRACT
This study investigated the results of the six physical skills tests, 40-yard dash, vertical jump, bench press, broad jump, 3-cone drill, and 20-yard shuttle, used at the 2022 NFL Scouting Combine to predict draft placement in the upcoming 2022 NFL draft. Analyses of 324 potential draft prospects’ performance data showed no significant (p<0.05) difference between drafted and nondrafted players in any of the six physical skills tests (drafted vs. nondrafted; 40-yard dash: seconds, 4.70 ± 0.30 vs. 4.75 ± 0.31, p = 0.115; vertical jump: inches, 32.81 ± 4.58 vs. 31.96 ± 4.38, p = 0.173; bench press: reps, 21.83 ± 4.62 vs. 20.12 ± 4.59, p = 0.132; broad jump: inches, 118.15 ± 8.78 vs. 117.24 ± 8.70, p = 0.458; three-cone drill: seconds, 7.33 ± 0.41 vs. 7.44 ± 0.49, p = 0.247; 20-yard shuttle: seconds, 4.52 ± 0.25 vs. 4.54 ± 0.28, p = 0.598). Draft placement was correlated with broad jump performance (r_s= -0.221, p = 0.010) and 20-yard shuttle scores (r_s = 0.250, p = 0.043), but not associated with the other performance measures. The results indicate the physical skills tests used at the NFL Scouting Combine have little to no predictive ability in the draft status of prospective players. The findings will assist strength and conditioning coaches and head football and football position coaches at the collegiate level in preparing their football players for the upcoming NFL draft.

Keywords: football, performance testing, skills test, NFL combine results.

INTRODUCTION
The National Football League (NFL) Scouting Combine is held annually at Lucas Oil Stadium in Indianapolis, Indiana, providing personnel from the 32 NFL teams with an opportunity to evaluate prospective draft prospects in a range of physical skills tests, on-field position drills, and an extensive medical evaluation and player interviews. Seniors who have completed their senior year and underclassmen who have declared for the NFL draft that satisfy the National Collegiate Athletic Association (NCAA) and the NFL requirements and guidelines are eligible to participate in the NFL Combine. It is estimated that 335 football players participate in the NFL Scouting Combine annually.

However, it is unclear whether the physical skills tests used by the NFL Combine can accurately predict draft status in the NFL draft and assess if prospective draftees have the skills and abilities required to play in the NFL. Sierer et al. (10) indicated that testing performed at the combine might not take into account a player’s potential skill level during an actual game. Yet, coaches and scouts have used the test results from the NFL Combine to assess players’ physical abilities and skills as a determining factor of their success at the professional level. McGee and Burkett (8) state that the NFL Combine can be used to accurately predict the draft status of running backs, wide receivers, and defensive backs. The study by McGee and Burkett (8) supports the study by Kuzmits and Adams (6) that shows the 40-yard dash, 10-yard and 20-yard timed increments are highly correlated with running back performance in the NFL and should be used going forward when drafting running backs. However, a later study by Robbins (9) concluded that draft success is not significantly correlated with the results of the NFL Combine’s physical test battery, normalized or not. Normalized data were no more valid than raw data for predicting draft order based on the results of the eight physical skills tests comprising the battery of tests utilized at the NFL Combine. Robbins (9) added that performance measures used at the combine have only a weak correlation with draft success. The author emphasized that NFL teams are interested in only a few physical characteristics, such as straight sprint time and jumping ability. The study by Robbins (9) supports an earlier study by Kuzmitz and Adams (6) that found that only one third or less of the physical performance measures making up the NFL Combine test batteries correlated well with draft performance in the quarterback, running back and wide receiver positions. They suggested that other performance evaluations at the combine, such as field position specific drills, anthropometric measurements, interviews, aptitude testing, flexibility, injury evaluation, and illegal substance testing, may help better determine whether prospective football players will be selected in the upcoming NFL draft. According to Robbins (9), the findings of Kuzmitz and Adams (6) would imply that NFL teams do not rely heavily on physical performance data collected at the NFL Combine when making draft decisions. Furthermore, a former Tennessee Titans president stated that all that matters at the combine is medical evaluations and player interviews (4).

We have previously observed that the physical tests used at the NFL Combine are not a reliable predictor of draft placement in the NFL draft except possibly for the WR position (11). We found that the physical skills tests utilized at the NFL Combine are essential in differentiating between getting drafted into the NFL (11). To follow up on and reconfirm our previous findings, we designed the present study to conclusively investigate the issue by analyzing more recent NFL Scouting Combine performance data in 2022 for their predictive ability to draft status. We hypothesized that there would be no differences between drafted and nondrafted players in their physical skills tests, and the physical skills test scores would not have any predictive validity in the NFL draft.

METHODS
Participants
This research study included 324 football players who attended the 2022 NFL Scouting Combine: 15 Quarterbacks (QB); 36 Running backs (RB); 40 Wide Receivers (WR); 21 Tight Ends (TE); 58 Offensive Lineman (OL, including offensive guards (OG), offensive tackles (OT), and centers (C); 48 Defensive Lineman (DL, including defensive tackles (DT), nose tackles (NT), and defensive ends (DE, edge rushers); 36 Linebackers (LB); 61 (DB); and 9 Specialist (ST). The Committee for the Protection of Human Subjects (CPHS) at University of Houston-Victoria determined this study is exempt from Institutional review board approval because this study is a secondary analysis of publicly available data.

Procedures
Players were grouped by position to perform on-field positional workouts and physical skills tests. Group 1: QB, WR, and TE; Group 2: OL, RB, and ST; Group 3: DL and LB; Group 4: DB. The data for this study was obtained from Pro Football Reference, a web-based public access domain (13). The physical skills tests used for the analyses in this study include the 40-yard dash, vertical jump, bench press, broad jump, three-cone drill, and 20-yard shuttle for offensive, defensive, and special team positions.

Positions	Tests	Drafted	N	Non-Drafted	N	P-Values
C	40-yard dash	5.10 ± 0.15	5	5.19 ± 0.76	3	0.302
	Vertical jump	29.25 ± 3.80	4	28.67 ± 0.58	3	0.807
	Bench press	25.00 ± 0.00	1	24.50 ± 0.71	2	0.667
	Broad jump	110.25 ± 6.85	4	110.33 ± 2.08	3	0.985
	3-cone drill	7.51 ± 0.22	3	7.51 ± 0.14	2	0.985
	20-yard shuttle	4.66 ± 0.25	3	4.58 ±0.12	2	0.687
CB	40-yard dash	4.44 ± 0.09	18	4.48 ± 0.10	13	0.250
	Vertical jump	36.75 ± 3.11	6	36.88 ± 2.14	4	0.946
	Bench press	16.50 ± 1.73	4	14.00 ± 0.00	1	0.287
	Broad jump	125.75 ±5.19	4	126.25 ± 4.03	4	0.884
	3-cone drill	N/A	0	6.48 ± 0.00	1	N/A
	20-yard shuttle	N/A	0	3.94 ± 0.00	1	N/A
DE	40-yard dash	4.76 ± 0.19	6	4.79 ± 0.03	2	0.846
	Vertical jump	32.92 ± 3.68	6	33.25 ± 6.01	2	0.925
	Bench press	20.50 ± 4.36	4	N/A	0	N/A
	Broad jump	118.00 ± 5.37	6	119.00 ±5.66	2	0.829
	3-cone drill	6.96 ± 0.27	3	N/A	0	N/A
	20-yard shuttle	4.30 ± 0.15	3	N/A	0	N/A
DT	40-yard dash	5.00 ± 0.22	9	5.33 ± 0.25	4	0.035
	Vertical jump	28.40 ± 3.66	10	27.50 ± 3.78	3	0.717
	Bench press	23.00 ± 6.00	3	N/A	0	N/A
	Broad jump	109.10 ± 6.12	10	103.00 ± 4.24	2	0.216
	3-cone drill	7.76 ± 0.45	5	N/A	0	N/A
	20-yard shuttle	4.66 ± 0.18	7	N/A	0	N/A
EDGE	40-yard dash	4.61 ± 0.14	11	5.08 ± 0.00	1	0.009
	Vertical jump	35.81 ± 2.66	13	26.50 ± 0.00	1	0.006
	Bench press	23.40 ± 2.61	5	21.00 ± 0.00	1	0.448
	Broad jump	122.62 ± 4.15	13	104.00 ± 0.00	1	<0.001
	3-cone drill	7.14 ± 0.10	2	7.20 ± 0.00	1	0.707
	20-yard shuttle	4.37 ± 0.08	6	4.24 ± 0.00	1	0.203
K	40-yard dash	N/A	0	N/A	0	N/A
	Vertical jump	N/A	0	N/A	0	N/A
	Bench press	12.00 ± 0.00	1	N/A	0	N/A
	Broad jump	N/A	0	N/A	0	N/A
	3-cone drill	N/A	0	N/A	0	N/A
	20-yard shuttle	N/A	0	N/A	0	N/A
LB	40-yard dash	4.57 ± 0.11	14	4.69 ± 0.13	9	0.033
	Vertical jump	37.00 ± 2.76	16	34.65 ± 2.65	10	0.042
	Bench press	23.75 ± 2.75	4	21.67 ± 2.08	3	0.326
	Broad jump	125.06 ± 4.30	16	120.40 ± 6.80	10	0.042
	3-cone drill	7.03 ± 0.09	4	7.19 ± 0.25	3	0.272
	20-yard shuttle	4.27 ± 0.02	2	4.44 ± 0.16	2	0.256
LS	40-yard dash	N/A	0	4.97 ± 0.00	1	N/A
	Vertical jump	N/A	0	29.50 ± 0.00	1	N/A
	Bench press	N/A	0	18.00 ± 0.00	1	N/A
	Broad jump	N/A	0	107.00 ± 0.00	1	N/A
	3-cone drill	N/A	0	7.53 ± 0.00	1	N/A
	20-yard shuttle	N/A	0	4.62 ± 0.00	1	N/A
OG	40-yard dash	5.18 ± 0.14	15	5.17 ± 0.16	7	0.872
	Vertical jump	27.14 ± 3.38	14	26.36 ± 3.29	7	0.618
	Bench press	26.50 ± 4.59	6	25.50 ± 4.12	4	0.735
	Broad jump	105.60 ± 4.47	15	105.71 ± 7.76	7	0.965
	3-cone drill	7.73 ± 0.20	11	7.88 ± 0.37	7	0.286
	20-yard shuttle	4.77 ± 0.19	13	4.79 ± 0.18	7	0.808
OT	40-yard dash	5.11 ± 0.18	10	5.10 ± 0.19	10	0.868
	Vertical jump	26.46 ± 2.39	11	27.17 ± 3.50	9	0.596
	Bench press	26.00 ± 3.46	3	22.50 ± 6.36	2	0.469
	Broad jump	106.27 ± 5.12	11	107.56 ± 4.48	9	0.563
	3-cone drill	7.71 ± 0.25	7	7.93 ± 0.44	6	0.284
	20-yard shuttle	4.69 ± 0.19	9	4.78 ± 0.26	7	0.433
P	40-yard dash	4.63 ± 0.06	3	N/A	0	N/A
	Vertical jump	32.00 ± 0.00	1	N/A	0	N/A
	Bench press	N/A	0	N/A	0	N/A
	Broad jump	121.00 ± 0.00	1	N/A	0	N/A
	3-cone drill	N/A	0	N/A	0	N/A
	20-yard shuttle	N/A	0	N/A	0	N/A
QB	40-yard dash	7.78 ± 0.16	5	7.77 ± 0.13	3	0.934
	Vertical jump	31.50 ± 3.43	5	31.38 ± 4.01	4	0.961
	Bench press	N/A	0	N/A	0	N/A
	Broad jump	117.25 ± 8.26	4	117.25 ± 5.32	4	1.000
	3-cone drill	7.14 ± 0.10	4	7.12 ± 0.39	3	0.956
	20-yard shuttle	4.34 ± 0.08	5	4.31 ± 0.11	3	0.648
RB	40-yard dash	4.48 ± 0.09	17	4.53 ± 0.10	10	0.217
	Vertical jump	33.11 ± 3.05	19	32.92 ± 2.57	12	0.860
	Bench press	23.50 ± 3.00	4	18.50 ± 2.12	2	0.109
	Broad jump	120.78 ± 3.84	18	119.83 ± 3.71	12	0.509
	3-cone drill	N/A	0	N/A	0	N/A
	20-yard shuttle	N/A	0	N/A	0	N/A
S	40-yard dash	4.45 ± 0.10	9	4.45 ± 0.08	6	0.973
	Vertical jump	36.11 ± 1.64	9	35.25 ± 2.66	6	0.448
	Bench press	18.67 ± 3.06	3	18.00 ± 3.23	6	0.775
	Broad jump	125.56 ± 4.48	9	122.63 ± 3.54	8	0.159
	3-cone drill	6.77 ± 0.18	5	6.95 ± 0.08	2	0.269
	20-yard shuttle	4.22 ± 0.10	5	4.46 ± 0.00	1	0.093
TE	40-yard dash	4.67 ± 0.09	8	4.86 ± 0.07	4	0.005
	Vertical jump	33.00 ± 2.85	8	32.70 ± 2.20	5	0.845
	Bench press	19.22 ± 3.03	9	19.00 ± 0.00	1	0.946
	Broad jump	120.40 ± 3.21	5	116.60 ± 3.58	5	0.115
	3-cone drill	7.05 ± 0.01	4	7.15 ± 0.20	4	0.337
	20-yard shuttle	4.46 ± 0.08	5	4.37 ± 0.16	5	0.276
WR	40-yard dash	4.43 ± 0.10	18	4.54 ± 0.09	14	0.002
	Vertical jump	35.34 ± 2.34	19	34.07 ± 3.77	15	0.235
	Bench press	N/A	0	15.00 ± 4.58	3	N/A
	Broad jump	124.37 ± 4.15	19	123.80 ± 7.50	15	0.795
	3-cone drill	7.10 ± 0.19	10	7.16 ± 0.32	4	0.642
	20-yard shuttle	4.31 ± 0.14	8	4.40 ± 0.16	5	0.307

Data are presented as mean ± SD. Units: seconds for 40-yard dash, inches for vertical jump, number of reps for bench press, inches for broad jump, seconds for 3-cone drill, seconds for 20-yard shuttle. C: center, CB: cornerback, DE: defensive end, DT: defensive tackle, EDGE: edge defender, K: kicker, LB: linebacker, LS: long snapper, OG: offensive guard, OT: offensive tackle, P: punter, QB: quarterback, RB: running back, S: safety, TE: tight end, WR: wide receiver.

Data Analyses
All statistical analyses were conducted using IBM SPSS Statistics software (version 28; IBM Corporation, Armonk, NY). The assumption of normal distribution was checked using Shapiro-Wilk test, and non-normal data were analyzed using non-parametric statistical procedures. Independent t-tests were performed to examine differences between two groups (e.g., drafted vs. nondrafted), and Spearman’s correlations were used to examine associations between physical skills tests and draft placement. P values of <0.05 were considered statistically significant, and data are presented as mean ± SD unless stated otherwise. RESULTS Differences between drafted and nondrafted players in performance measures. When participants were analyzed together, there was no difference between drafted and nondrafted prospective draft prospects in any of the six physical skills tests drafted vs. nondrafted; [40-yard dash: seconds, 4.69 ± 0.30 (n=148) vs. 4.75 ± 0.31 (n=87), p = 0.115; vertical jump: inches, 32.81 ± 4.58 (n=141) vs. 31.96 ± 4.38 (n=82), p = 0.173; bench press: number of reps, 21.83 ± 4.62 (n=47) vs. 20.12 ± 4.59 (n=26), p = 0.132; broad jump: inches, 118.15 ± 8.78 (n=135) vs. 117.24 ± 8.70 (n=83), p = 0.458; three-cone drill: seconds, 7.33 ± 0.41 (n=58) vs. 7.44 ± 0.49 (n=34), p = 0.247; 20-yard shuttle: seconds, 4.52 ± 0.25 (n=66) vs. 4.54 ± 0.28 (n=35), p = 0.598]. When the individual positions were analyzed separately, no differences were observed between drafted and nondrafted players in most of the positions’ physical skills tests with the exception of (DT)’s 40-yard dash, (EDGE) 40-yard dash, vertical jump, and broad jump, (LB) 40-yard dash, vertical jump, and broad jump; (TE) 40-yard dash; and (WR) 40-yard dash scores, where the drafted athletes showed better performances than the nondrafted athletes (Table 1). Correlations between performance measures and draft placement When all the participants were analyzed together, draft placement was weakly correlated with broad jump performance (rs = -0.221, p = 0.010) and 20-yard shuttle scores (rs = 0.250, p = 0.043), but not associated with the other performance measures (40-yard dash, vertical jump, bench press, and three-cone drill scores; p>0.05). When the individual positions were analyzed separately, draft placement showed a moderate to strong correlation with (DT)’s 40-yard dash (r_s = 0.753, p = 0.019) and offensive tackle (OT)’s 40-yard dash (r_s = 0.782, p = 0.008), but not associated with any other performance measures in any other positions (p>0.05).

DISCUSSION
The main finding of this study is that the physical skills tests used at the NFL Scouting Combine may not have predictive ability in determining the draft status of prospective draftees entering the 2022 NFL Draft. The performance differences between drafted and nondrafted players were minimal, and weak correlations between draft placement and physical test scores were observed in only a few tests or positions.

The first finding of this study indicates that when all of the offensive and defensive positions were analyzed together, the physical skills tests used at the NFL Combine to predict draft placement showed a weak correlation with broad jump performance (rs = -0.221, p = 0.010) and 20-yard shuttle scores (rs = 0.250, p = 0.043), but is not associated with the other performance measures 40-yard dash, vertical jump, bench press, and three-cone drill scores; p>0.05). The standing broad jump tests lower body strength and power. NFL players may have an advantage in a one on one situations if they can explode from a standing position while maintaining control and balance. Every player in the NFL will need a measure of lower body strength, balance, and explosiveness to jump, run, block, change direction, fight off an opponent in football, and prevent injury. The 20-yard shuttle tests a player’s ability to change direction. Every offensive and defensive position in football will need to have the ability to change direction to catch a pass or evade an opponent in football. The standing broad jump and the 20-yard shuttle showed a weak correlation, meaning that a farther broad jump and a faster 20-yard shuttle could influence draft placement; however, this finding is nonsignificant.
The second finding of this study indicated that when individual offensive and defensive positions were analyzed separately, draft placement showed a nonsignificant moderate to strong correlation with (DT) 40-yard dash (rs = 0.753, p = 0.019) and (OT) 40-yard dash (rs = 0.782, p = 0.008), but not associated with any other performance measures in any other positions; (p>0.05). The 40-yard dash tests a player’s ability to accelerate for 40 yards, which is a test of acceleration. Football players will start from a three point stance and sprint 40 yards. Times are recorded at the 10-yard, 20-yard, and 40-yard increments.

The present study showed a nonsignificant moderate to strong correlation between draft placement and the 40-yard dash for (DT) and (OL); however, a question should be asked whether either of these positions runs 40 yards during a single play in a football game. The answer to this question would be that they don’t. Rather, they run 5 and maybe 10 yards, depending on the blocking scheme for offensive linemen and defending the pass rush. It appears that NFL personnel are looking at the fastest 40-yard time, but in reality, they could be more interested in the start and the times in the 10-yard and 20-yard increments, which are more relevant to the offensive and defensive tackle positions. The only positions on the football field that start in a three-point stance are offensive and defensive linemen and perhaps a fullback. If this is the case, why is every position at the NFL combine starting in a three-point stance when timed in the 40-yard dash? It may be better to evaluate how quickly a player can accelerate in 10-yards, which is a better indicator of what occurs on any given play in a football game for offensive linemen and defensive tackles.

The third finding is that 324 players attended the 2022 NFL Combine, and only 262 players were drafted. The results of this study show that the physical skills tests do not have the predictive ability to determine draft status in any offensive and defensive positions except for the positions of DT and OT in the 2022 NFL draft. The authors indicate that if the 40-yard (36.6 m) dash is the heavily weighted performance test and can distinguish between drafted and undrafted players, then why do the results of this study not show a positive correlation between the 40-yard (36.6 m) dash and draft status in all of the offensive and defensive positions.

The validity of the performance metrics used at the NFL Scouting Combine has been investigated in several other studies, and the results were equivocal (5). Football coaches appear to share the assumption that combine performance indicators can forecast a football player’s overall ability to play the game, yet studies have identified few reliable indicators (1-5). The performance metrics utilized at the NFL Scouting Combine examine players’ athletic skills rather than their ability to play football. It is questionable whether those combine performances are directly related to the football playing ability of prospective draftees. According to Vincent et al. (12), the NFL should consider changing the National Scouting Combine (NSC) testing battery to position-specific tests. These include a 10-yard dash for linemen and change of direction drills that are similar to those needed to execute successful pass patterns for wide receivers.

Our findings support a study by Robbins (9), which suggests that the combine tests are not sufficiently specific and have little bearing on a player’s actual ability to play the game of football and consequently receive little attention from NFL personnel. The study by Robbins supports an earlier study by Kuzmits & Adams (6), suggesting various explanations as to why performance in a number of the combine tests is not strongly correlated with draft order. One may be the rigorous preparation invitees undertake before attending the combine. Research by Kuzmits and Adams (6) indicates that the abundance of prep courses and other learning resources available to help players prepare for the combine may be the reason for the lack of correlation between overall performance at the NFL Combine. Kuzmits and Adams (6) explain that the lack of correlation between NFL Combine performance and NFL performance is that combine exercises measure the athlete’s athletic skill and not the athlete’s actual ability to play football. Also, when drafting prospective draftees, there are a number of additional variables that can come into play. The team’s needs for the upcoming season, injuries, off the field issues, and performance during college or pre-draft workouts are examples of such factors. In the end, NFL teams consider numerous factors when selecting players, making it difficult to predict the draft status of the participating players using the NFL combine skills tests. The combine tests are used to determine if a football player has the necessary elite skills and physical abilities to play in the NFL and contribute to a team’s success. However, according to Lyons et al. (7), on-field performance in college is likely the strongest predictor of success in the NFL.

CONCLUSIONS
Although certain individual positions may have limited applicability for specific skills test scores due to their ability to reveal players’ overall elite athletic prowess, collegiate football players aiming to earn NFL drafts should devote the majority of their time to honing the positional technical and tactical proficiencies necessary for success at their respective offensive and defensive positions. Additionally, they should be wary of suppliers and performance centers who make false promises of improved outcomes and substantial compensation at the NFL combine, only to enrich themselves through excessive pricing. The NFL Combine appears to be a mere exhibition where the nation’s most talented collegiate football players convene for a week in an attempt to secure a drafting spot and realize a lifelong ambition of playing professionally. Over the years, more and more top-rated collegiate football players have opted out of attending the NFL combine for several reasons, one common reason being to avoid injury. The hype of the players performing well at the NFL Combine has opened the doors for private sports performance facilities to offer training services to improve a player’s performance on the physical skills tests utilized to enhance the chances of being drafted higher and receiving a payday. Robbins (9) suggested that the lack of a strong relationship between the performance measures and the draft may be because of the rigorous preparation invitees undertake before attending the combine. The study by Robbins (9) supports an earlier study by Kuzmits and Adams (6) that brings up a very interesting point other than marketing claims made by vendors themselves, there is no scientific evidence that their preparation improves NFL combine performance. The authors of this study agree with Robbins (9) and Kuzmitz and Adams (6) and suggest that the physical tests used at the NFL combine are used to measure a player’s physical skills and not their football playing ability.

APPLICATIONS IN SPORT
This study hypothesized that there would be no difference between drafted and nondrafted athletes in their performance measures, and the performance scores would not have any predictive validity in the NFL draft. 324 football players participated in the 2022 NFL Scouting Combine, and based on the results, our data suggest that NFL Scouting Combine test results have little to no effects on the participating players’ overall draft status and bear little predictive value. Some of those skills test scores might be of limited usage in a few individual positions because those can show players’ overall elite athletic physical capabilities. To conclude, collegiate football players with the goal of one day getting drafted into the national football league should spend most of their time improving the positional technical and tactical skills required to succeed in their various offensive and defensive positions. They should also be aware of vendors and performance centers promising better results at the NFL combine and big paydays only to fill their pockets with the high prices they charge. Finally, prospective NFL players should place more emphasis on further developing their overall football playing ability, such as mental aptitude, team attitude, and willingness to learn, rather than the physical characteristics evaluated at the NFL Scouting Combine.
REFERENCES

Berg K, Latin RW, Baechle T. Physical and performance characteristics of NCAA division I football players. Res Q Exerc Sport 61(4): 395-401, 1990.
Black W, Roundy E. Comparisons of size, strength, speed, and power in NCAA division 1-A football players. J Strength Cond Res 8(2): 80–85, 1994.
Burke EJ, Winslow E, Strube WV. Measures of body composition and performance in major college football players. J Sport Med Phys Fit 20(2): 173–180, 1980.
Diamond J. Why NFL Combine is tedious, expensive and overrated in the eyes of a team president. Sporting News February 27th, 2019.
Fry A, Kraemer W. Physical performance characteristics of American collegiate football players. J Strength Cond Res 5(3): 126–138, 1991.
Kuzmits FE, Adams AJ. The NFL Combine: does it predict performance in the National Football League? J Strength Cond Res 22(6): 1721–1727, 2008.
Lyons B, Hoffman B, Michel J, Williams K. On the predictive efficiency of past performance and physical ability: the case of the National Football League. Human Perform 24: 158–172, 2011.
McGee KJ, Burkett LN. The National Football League Combine: A reliable predictor of draft Status? J Strength Cond Res 17(1): 6-11, 2003.
Robbins DW. The National Football League (NFL) Combine: does normalized data better predict performance in the NFL draft? J Strength Cond Res 24(11): 2888–2899, 2010.
Sierer SP, Battaglini CL, Mihalik JP, Shields EW, Tomasini NT. The National Football League Combine: performance differences between drafted and nondrafted players entering the 2004 and 2005 drafts. J Strength Cond Res 22(1): 6–12, 2008.
Tucker R, Black W. The National Football League Combine: do performance measures predict draft status among NFL draftees. Sport J 24: November 5th, 2021.
Vincent LM, Blissmer BJ, Hatfield DL. National Scouting Combine scores as performance predictors in the National Football League. J Strength Cond Res 33(1): 104–111, 2019.
www.pro-football-reference.com

George Minoso2024-12-09T15:40:54-06:00December 6th, 2024|Research, Sports Exercise Science|Comments Off

Maximizing Youth Sports Engagement on Social Media: How Visual Impact and Message Appeal Shape Consumer Responses Online

Authors: Wan S. Jung1, Won Yong Jang2, and Soo Rhee3

¹Department of Professional Communications, Farmingdale State College, New York
²Department of Communication and Journalism, University of Wisconsin, Eau Claire, Wisconsin
³Department of Mass Communication, Towson University, Maryland

Corresponding Author:

Wan S. Jung, Ph.D
Knapp Hall 30
2350 Broadhollow Road, Farmingdale, NY 11735-1021
[email protected]
934-420-2276

Wan S. Jung, PhD is an Associate Professor of Professional Communications at Farmingdale State College, NY. His research interests focus on the credibility assessment process of digital information.

Won Yong Jang, PhD is a Professor at the University of Wisconsin, Eau Claire. He specializes in 1) international communication, 2) news media and society in East Asian countries, 3) climate change policy & communication, 4) public opinion on North Korea’s Nuclear Program, and 5) territorial disputes in the Asia-Pacific Region.

Soo Rhee, PhD is a Professor at Towson University, Maryland. Her research interests include luxury brand advertising, gender portrayals in advertising, dynamics of electronic word-of-mouth, cross-cultural studies in advertising and message strategies in health advertising.

ABSTRACT
An increasing number of people rely on the Internet as their primary information source and use it to share their opinions and thoughts with others. Generally, individuals adopt a systematic approach when processing sports information, evaluating its completeness and accuracy due to the serious consequences of incomplete or inaccurate information, such as monetary loss and negative impacts on child development. However, our study finds that the heuristics of online information, even with subtle changes in design features, generate more positive attitudinal and behavioral changes compared to central cues (i.e., informational posting). Our findings suggest a dissociation between involvement and the effects of heuristics. This study also provides an empirical framework for predicting how people process information in digital media environments. Additional findings and implications are discussed.

Key Words: youth sport communication, visual impact of social media posting, message appeal

INTRODUCTION
The youth sport market is a huge and fast-growing industry, ranging from organized sports leagues to recreational activities. The market for youth sports in the United States stood at 15.3 billion U.S. dollars in 2017 and grew to 19.2 billion U.S. dollars by 2019 (11). With a fast-growing trend (i.e., a growth rate of 25.4% from 2017 to 2019) with various options, parents became more active in searching for information. As social media are pervasive, rapidly evolving, and increasingly influencing parents’ daily life and their sport consumption, parents increasingly turn to the internet as a source of community, which helps them connect, communicate, and share information (18).

The rapid growth of online sports information production and dissemination through social media parenting communities (e.g., Facebook local groups and Nextdoor) raises important research questions about how individuals process online information provided by other consumers (i.e., experienced parents whose child(ren) have participated in your sport programs) in youth sport consumption decision making. Moreover, since sport consumers make decisions about whether or not to adopt online sports information based on their own judgement (e.g., attitudinal formation), how individuals evaluate online information is central to sports communication agendas.

Although the formation of attitudes toward information can be attributed to multiple aspects of that information (e.g., source credibility, information completeness), sport consumers using online resources are more reliant on how the information is presented than on the quality of the argument (10), and subtle graphical adjustments become relevant when online parenting community members share their own experiences with other members on social media platforms. In order to emphasize their own views, web users often create visual prominence using subtle design elements, such as capitalized subject lines, copy-and-paste text art (also called keyboard art, e.g., ≧◡≦), or bullet-point symbols. In addition to subtle design changes, the characteristics of the online posting can be varied based on the degree of informativeness (i.e., emotion-based versus information-based).

The purpose of the current study is twofold. First, it will explore the effect on attitudinal formation and behavioral intentions of the message appeals and subtle graphical adjustments of posts in online parenting communities in the youth sport consumption context. Second, the study will investigate whether the strength of the relationship between attitude and behavioral intentions varies based on message appeals. Overall, the study will seek to advance understanding of digital media by examining how small graphical changes and message appeals impact youth sport consumers’ attitudes and behaviors when searching for consumer-generated information (e.g., testimonials) in online communities.

LITERATURE REVIEW
Parent-to-Parent Online Information in Youth Sport Consumption
“It takes a village to raise a child” is a proverb to explain the role of and community support in parenting. As social aspect is one of the primary factors that drives parents and their children to be involved in sport program (1), the influence of other parents’ opinion and the role of parent community are even more prominent in youth sport consumer’s decision making process. Braunstein-Minkove & Metz (2019) noted in their research on the role of mothers in sport consumption that youth sport consumption might not always about the sport but the experience. Therefore, parents of youth rely on other parents’ opinion to obtain relevant and sufficient information and evaluate various youth sport program options available. In order to provide the best sporting and exercise experience for their children, parents of young children are willing to hear voices of other parents (i.e., testimonial) regarding the type of sports, sports programs, and sporting events their children would participate in.

With the modern technology and the advent of social media, the notion of the village (or supporting community) has been expanded from a physical village to a digital community. Social media platforms support a variety of user generated content to be disseminated to other users and allows users to participate in interactive discussions. Among the various types of social media platforms, Facebook have become the most prevalent web-based service in the world (21) and remaining the most popular site by far (12). Also, Facebook recently provides an option to mark the group type as parenting group, which gives parents new ways to discover and engage with their communities (5). Though the role of online community and the influence of information from other youth sport consumers (i.e., testimonials from other parents in such online community) in youth sport consumer’s decision-making process became more prominent, there is no previous research to explore the effects of the presentation of online information on consumers’ attitudinal and behavioral response in youth sport consumption context.

The Impact of Visual Prominence
Quick and low effort cognitive information processing has been investigated in the field of psychology since the 1970s (e.g., 9, 13), and the research indicates that impression formation is the result of the perceiver’s rapid response to selective or incomplete information. In other words, one’s appraisal of an event occurs without intention or conscious thought. Theories of impression formation in the context of digital communication have been developed by Fogg (2003) and Wathen and Burkell (2002), and their studies suggest that visual prominence—the visual salience that allows people to effortlessly notice the presence of graphic elements (e.g., bold vs. non-bold font)—is a primary driver of attitudinal formation, rather than information quality.

The impact of visual prominence can also be explained by individuals’ reliance, when making decisions, on transactive memory systems, which consist of two key elements: internal memory (e.g., personal experience) and external memory (e.g., another person’s expertise; 14). The presence of an external memory will activate a transactive memory system, and such a dependency on external memory increases efficiency and cognitive labor power (20). Thus, external sources of knowledge can have a significant impact on one’s perception of what to accept as true and how confidently to accept it.

The theoretical and empirical evidence for transactive memory systems is based on offline social interactions (e.g., interactions within family groups). However, recent studies suggest that online sources can also trigger transactive memory systems due to the similarity between the process of outsourcing cognitive tasks to other people and the process of outsourcing cognitive tasks to the Internet (6). This nonhuman transactive memory network is further fueled by the unique features of the Internet (e.g., accessibility, breadth, immediacy of information), but such features may distort one’s ability to calibrate personal knowledge because the boundary between internal and external memory becomes unclear. That is, individuals often mix up information obtained through the Internet with information stored in the brain, and this illusion inflates self-ratings of competence regarding personal knowledge and decision-making (17). Recent research on such illusions also suggests that people tend to believe they can solve problems even in unfamiliar domains and that their decision-making processes are often based on heuristics, such as visual prominence (7, 8); the impact of visual prominence would thus be greater in digital media environments.

Since online parenting community members can establish the visual prominence of their postings on social media platforms only with subtle graphical adjustments, the current study will investigate how subtle changes (e.g., capitalizing subject lines, use of text art) to posts in online youth sport communities influence individuals’ attitude formation and behavioral intentions. Given the exploratory nature of the topic of individual information judgment in digital media environments, the following hypotheses are proposed:
H1: Visually prominent postings in online youth sport communities form stronger attitudes than less prominent postings.
H2: Visually prominent postings in online youth sport communities form stronger behavioral intentions than less prominent postings.

The Impact of Involvement on Message Appeals
The persuasiveness and prevalence of various appeal types (e.g., emotional, informative) have been extensively examined in different contexts, such as brand familiarity (Rhee & Jung, 2019), cultural variability (Han & Shavitt, 1994), and involvement (Flora & Maibach, 1990). However, less is known about the differential effects of appeal types in the context of online youth sport communities, and the current study therefore presents an exploration of the question of which type of message appeal is most persuasive in such communities.
The elaboration likelihood model (ELM; 16) is one of the most prominent theoretical frameworks employed in the message appeal literature and is applied in various contexts, such as public health service announcements (Perse et al., 1996), crisis management (Lee & Atkinson, 2019), and advertising (Stafford & Day, 1995). Studies have also commonly found a moderating effect of involvement on message appeals, and according to the ELM, people tend to rely on argument quality (e.g., information completeness, comprehensiveness) when processing information under high involvement conditions, with persuasion less likely to occur through peripheral cues, such as peers’ emotional experiences. The converse is also true under low involvement conditions.

However, a recent study by Jung et al. (2017) found evidence that contradicts the prevailing literature on the role of involvement in digital media environments; the study claims that individuals often find it hard to motivate themselves to process information thoroughly, regardless of involvement levels, due to the nature of the Internet, which inundates them with massive amounts of non-verifiable information. Individuals therefore tend to compromise the accuracy of their decisions, which can require extensive cognitive effort, by relying on the heuristic aspects of information.

In addition, in the context of online youth sports communities, people tend to seek others’ prior experiences (e.g., a coach’s personality) and emotionally supportive messages because any objective information about a youth sports program (e.g., fees, coach’s experience, facilities) can be easily found through sources such as the program’s website. It can therefore be assumed that the moderating role of involvement in appeal types might be limited by the dominance of social media. Nevertheless, because there is still insufficient evidence for the limited role of involvement in the social media context, we propose the following research question:
RQ1: What effect does involvement have on the appeal types of posts in online youth sport communities?

The Moderating Impact of Involvement on the Attitude–Intention Relationship
Attitudes are among the most significant predictors of behavioral intentions in psychology. According to the theory of planned behavior (TPB), intention functions as an antecedent of behavior and is attributable to individual attitudes, together with subjective norms and perceived behavioral control (Ajzen, 1991). Although a number of studies have provided strong evidence for the relationship between intentions and the three causal variables of the TPB, a meta-analytic study by Cooke and Sheeran (2004) also noted that less than 42% of the variance in intentions can be explained by those variables.

Consequently, there have been numerous attempts to increase the predictive power of the TPB by exploring moderators of the relationship between intention and the TPB variables, such as attitudinal ambivalence (Armitage & Conner, 2000) and certainty (Bassili, 1996). In addition to these moderating variables, Petty et al. (1983) has offered theoretical and empirical evidence that the attitude–intention relationship is more consistent under high involvement conditions, because attitudes established by highly involved people are more stable than those of lowly involved people. Verplanken (1989) also examined whether involvement can explain additional variance in the attitude–intention relationship, although that study was in the context of nuclear energy.

Therefore, the current study will examine the moderating role of involvement in the attitude–intention relationship in the sport communication context.
H3: High involvement will be associated with greater attitude–intention consistency than low involvement.

METHOD
Subjects and Procedure
192 participants who had parenting experiences (male = 64%) from the United States between the ages of 20 and 55 completed the study through Amazon’s Mechanical Turk (MTurk). For participants’ ethnicity, the most common ethnicity was Caucasian (53.6%), followed by Asian (33.9%), African American (5.2%), Hispanic (3.6%), and other racial backgrounds (3.6%). To participate in the study, subjects were requested to provide electronic consent. And subjects were debriefed and compensated upon completion of the study.

Experimental Treatment Conditions
To investigate the effects of visual prominence (high vs. low prominence) and message appeals (emotional vs. informative message) on online youth sport program postings, four versions of online postings were created as stimuli, and the subjects were randomly assigned to one of the four experimental conditions: low prominence and emotional (n = 49), high prominence and emotional (n = 49), low prominence and informative (n = 49), and high prominence and informative (n = 45).

The postings contained an online community member-created message about a local youth soccer program. The community member-created posting consisted of either factual information about the soccer program (informative appeal) (i.e., up to 12 kids in one session with two coaches, all are CPR first aid and AED certified, and having an indoor field) or user experiences (emotional appeal) (i.e., it was such an amazing experience and my son loves his current coach). A youth soccer program was selected as the topic for this study because of popularity of the sport among young parents. The manipulation of visual prominence was carried out by differentiating graphic elements between high prominence and low prominence conditions. Since parent community members on social media platforms can emphasize their posting with subtle graphical alterations, the high prominence version was designed to help the study participants notice the key messages by capitalizing key words, using a bulleted list and line-breaks in order to increase readability, and using a text art. The low prominence version lacks those design features.

Dependent Measures
Attitude toward the online posting
The attitude toward the online youth program posting was measured using
three semantically differential items (i.e., good/bad, favorable/unfavorable, negative/positive) emerged from the literature on the scale (Lee & Hong, 2016). The scale was internally consistent (Cronbach’s  = .91, M = 4.70, SD = 1.81).

Behavioral Intentions
Subjects were also asked to answer their intentions to 1) recommend the youth soccer program on the posting you just read and 2) register for the soccer program in the future on 7-point Likert-type scales ranging from 1 (not at all) 7 (extremely). The items were averaged to create a behavioral intention scale (Cronbach’s  = .83, M = 4.33, SD = 1.73).

Independent Measure
Involvement
Involvement in sports activities may influence the attitudinal formation and behavioral intentions. Thus, this study measured personal involvement with sports activities by using three 7-point (1 = strongly disagree, 7 strongly agree) Likert-type scales, the participants reported on how much they agreed with the following three statements: “I enjoy playing sport,” “Sport plays a central role in my life,” and “Sport says a lot about who I am.” The three items were averaged to measure involvement (Cronbach’s  = .86, M = 5.38, SD = 1.35). This study used a median split to categorize high-involvement (N = 86) and low-involvement conditions (N = 83).

RESULTS
Manipulation Checks
The visual prominence manipulations were examined. Using two seven-point sematic differential items, the participants were asked to rate the extent to which they thought the format of the online posting they just read were “attractive/not attractive” and “likable/not likable” (Cronbach’s  = .83, M = 4.81, SD = 1.75). A t test between the two prominence conditions (low vs. high prominence) showed subjects felt that the youth sport program posting was more visually prominent when it included noticeable graphic elements (M = 5.60, SD = 1.23) than when it lacked the elements (M = 4.05, SD = 1.84), t (190) = 6.82, p < .001.

This study measured the degree of informativeness of online postings (emotional versus informative) by asking participants to rate the extent to which they though the posting they just read was “emotional” and “warmhearted” (Cronbach’s  = .80 M = 4.39, SD = 1.61). A t test between two message appeal conditions showed that the emotional appeal group (M = 4.94, SD = 1.27) perceived the posting to be significantly more emotional than the informative appeal group (M = 3.82, SD = 1.73), t (190) = 5.11, p < .001.
H1 and H2: Visual Prominence Main Effects

Multivariate analysis of variance (MANOVA) was conducted to determine the significant impacts of visual prominence, message appeal, and involvement on attitudes and behavioral intentions. H1 and H2 suggest that participants reading visually prominent postings would form stronger attitudes and behavioral intentions than did participants reading less prominent postings. Follow-up analysis of variance (ANOVA) tests were also performed the examine the effect of visual prominence for each of the dependent variables. Findings revealed that the effect of visual prominence was pronounced in relation to being able to determine consumers’ attitudes (M_High Prominence = 5.30, SD = 2.02 vs. M_Low Prominence = 4.14, SD = 1.38; F (1, 169) = 20.90, p < .001, partial η2 = .12) and behavioral intentions (M_High Prominence = 4.69, SD = 1.64 vs. M_Low Prominence = 4.01, SD = 1.73; F (1, 169) = 7.24, p < .01, partial η2 = .04). Thus, H1 and H2 were supported.

RQ1 and RQ2: Influence of Involvement on Visual Prominence and Message Appeals
The impact of consumers’ involvement on visual prominence and messages appeals were examined by 2 (visual prominence) X 2 (involvement) ANOVAs and 2 (message appeal) X 2 (involvement) ANOVAs with attitudes toward the online posting and behavioral intentions as dependent variables. The ANOVA results showed that that there were not significant interaction effects of the involvement-appeal relation and the involvement-visual prominence relation. The p values of the aforementioned relations were greater than .37. However, the impacts of visual prominence and message appeals were greater under both involvement conditions (see Figure 1 and 2).

H3: Moderating effect of involvement on the attitude-intention relation
This study anticipated that the attitude toward the online posting would form a stronger impact on the formation of behavioral intentions for high involvement conditions. Pearson’s correlation coefficient was used to examine whether involvement modifies the magnitude of the attitude-intention relation. Then, each correlation coefficient values for the high- and low-involvement conditions was converted into z scores by using Fisher’s r to z transformation. In order to compare the z scores for the two conditions, the following formula was implemented to determine the observed z score: Zobserved = (Z1−Z2) ∕ (square root of [1∕N1−3] + (1∕N2−3))

For the high involvement condition (n = 83), the correlation coefficient for the attitude-intention relation was .49 (p < .001). For the low involvement condition (n = 84), the correlation was .25 (p < .05). The test statistics, z = 1.78, p < .001 (one-tailed test), indicate that the correlation in the high involvement condition is significantly higher than it is in the low involvement condition. Therefore, Hypothesis 3 is supported.

DISCUSSION
Our findings suggest a lack of association between involvement and the effects of heuristics. The moderating role of involvement has been well established since the introduction of Petty et al.’s (1983) ELM and Chaiken’s (1987) heuristic-systematic model. According to those theories, involvement is a significant determinant in the selection of an information processing route (peripheral versus central). It is also commonly acknowledged in the sport communication field that individuals generally use a systematic mode (i.e., evaluating completeness/accuracy) when processing online sport information under high-involvement conditions in order to avoid the serious consequences of incomplete or inaccurate information (e.g., monetary loss, negative impacts on child development). However, our study found that the non-systematic mode is often activated for both high-involvement and low-involvement participants, and this finding thus contributes to the literature on individuals’ approaches to online information processing.

According to evidence-accumulation models (2), individuals reach a conclusion once there is enough evidence to support a particular case, but they can also alter the amount of evidence needed for coming to that decision. Although individuals generally want to make accurate decisions, Internet users often compromise the accuracy of their decisions by reducing the amount of evidence required to validate the information they are investigating. This tendency is attributable to online information overload, in which individuals experience difficulties in understanding the nature of a particular topic (Robin & Holmes, 2008). The tendency suggests a new general pattern of the speed–accuracy trade-off (SAT) in social media environments. In line with the SAT, there are two driving forces in the decision-making process (4); one emphasizes faster (or more efficient) decisions, while the other emphasizes higher accuracy. Although there are trade-offs between speed and accuracy, the two can be pursued independently, but they produce a wide spectrum of outcomes, from slower but more accurate decisions to quicker but less accurate decisions. In social media environments, individuals are motivated to engage in less-effortful information processing and are more likely to trade accuracy for speed in the decision-making process.

The current study also found another reason for further examining the role of involvement in social media environments. It has been assumed that persuasion is less likely to occur through emotional messages when an individual is highly involved in an issue because people tend to scrutinize issue-relevant information. However, our findings suggest that emotional messages can be more persuasive than informational messages regardless of the level of involvement, especially in the online youth sport community context, and these findings can be explained by the types of information individuals seek in online communities. Objective information about a youth program (e.g., fees, coaches’ experience, facilities) can be easily found through sources such as the youth program’s website, but people also tend to seek others’ prior experiences and emotionally supportive messages when joining online communities.
It is important to stress that the attitude–intention relationship varies with involvement levels. Our study shows that the attitudes of high-involvement participants are more predictive of the intention to perform a specific act (e.g., signing up a youth sport program) than the attitudes of low-involvement participants. Our findings regarding the attitude–intention relationship suggest that the moderating effect of involvement on that relationship is applicable to not only traditional media environments (e.g., Krosnick, 1988; Verplanken, 1989), but also to social media environments.

In addition to the theoretical implications of this study, understanding parents’ information processing in assessing youth sport program is an integral part of the sport communication landscape. With the growing importance of (local) parenting community groups on social media and the impact of user generated message, this study will help youth sport service providers understand the effective way of crafting online information. This study will shed lights on communication strategies for youth sport providers when they try to utilize a form of testimonial in introducing their services to the market. This study will also lead how social influencer marketing would be employed in delivering and disseminating the promotional messages to the consumers.

This study has some limitations. All its subjects were recruited through Amazon’s Mechanical Turk (MTurk). Although MTurk respondents tend to be more diverse than student samples in terms of demographic, psychographic, and geographic characteristics, some reliability issues (e.g., the work ethic of MTurk respondents) are unavoidable (3). Another limitation is that this study was conducted with samples of people who had parenting experiences because the study used a youth soccer program to develop the experimental stimuli, and the context of parenting might amplify reactions to emotional messages. We therefore recommend that future studies be conducted with more diverse samples and more popular sports topics (e.g., local sports events) in order to exclude the specific study topic and characteristics of the sample as potentially confounding factors.

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George Minoso2024-11-04T18:10:35-06:00November 22nd, 2024|Contemporary Sports Issues, General, Research, Sports Studies, Sports Studies and Sports Psychology|Comments Off

Title: The effects of COVID-19 infection on athletic performance: A systematic review

Authors: ¹Marisella Villano, MS, CFT, CES and ²Frank Spaniol, PhD

Department of Kinesiology, Texas A & M University – Corpus Christi

Corresponding Author:

Marisella Villano, MS, CFT, CCES

Marisella Villano recently graduated with a Master’s degree in Kinesiology from Texas A & M – Corpus Christi and has previously earned a Master’s degree in Gerontology from Long Island University. Additionally, she is a certified fitness trainer and corrective exercise specialist and is the founder and owner of MARVIL FIT, an indoor cycling, fitness and personal training studio in the Hamptons.

Frank Spaniol, PhD is a professor of sport and exercise science and also the program coordinator in the Kinesiology department at Texas A & M University – Corpus Christi. His
research interests include: sport performance, strength and conditioning, visual skills training, and sport technology.

Abstract
Purpose: This systematic review investigated the effects of COVID-19 infection on athletic performance. Methods: Using guidelines for a systematic search review, a comprehensive literature review was conducted utilizing the computer databases Google Scholar, PubMed and the Mary and Jeff Bell Library at Texas A&M University-Corpus Christi. Results: Incidence of cardiac abnormalities is low among athletes with COVID-19 infection, but cardiopulmonary deficiencies like shortness of breath have been shown to affect aerobic capacity which can impair performance. A premature switch to anaerobic metabolism at higher intensities was observed during cardiopulmonary exercise testing (CPET). Increased exercise heart rate (HR) and blood pressure (BP) were also observed in some athletes during CPET. Finally, the effects of COVID-19 appear to be multisystemic as decrements were also observed in balance, sleep and high intensity performance. Conclusion: COVID-19 infection primarily affects the cardiorespiratory system, but other multisystemic disturbances to athletic performance may occur which can negatively affect performance. Applications to Sport: Athletes recovered from COVID-19 illness continue to experience shortness of breath which may decrease recoverability after high intensity exertions and increase fatigability during competition. Proper screening beginning with CPET and planned RTP protocols based on the individual needs of athletes are necessary for seamless return to sport and attainment of performance levels prior to infection.

Keywords
Return to play, cardiorespiratory, cardiopulmonary exercise test, cardiac magnetic resonance, heart rate, VO2max, aerobic threshold, anaerobic threshold, ventilation, ventilatory efficiency, ventilatory inefficiency, long covid

Introduction
The COVID-19 pandemic spared no one, including athletes, and became a significant worldwide problem that appeared to primarily cause respiratory and cardiovascular illness (29). While clinical manifestations of COVID-19 in athletes are generally mild, persisting symptoms like cough, fatigue and tachycardia are similar to individuals in the general public (25). Individuals affected with mild or moderate COVID-19 illness also have the possibility of experiencing persistent symptoms post infection called Long-Covid (LC) and asymptomatic infection can introduce symptoms once a person has recovered from the primary infection (32). Persistent symptoms lasting more than 28 days are defined as LC and generally include fatigue and shortness of breath (6, 34).

Aside from the common symptoms of COVID-19 which include cardiorespiratory and cardiovascular disturbances, multisystemic disturbances have been observed in the central and peripheral nervous systems, gastrointestinal system, hematological system, liver, skeletal muscle, and kidneys (11, 16, 29). Furthermore, post infection sequelae causing imbalances of the autonomic system have also been observed (15). To sum up, the virus responsible for COVID-19 attacks the immune system of its host and creates a systemic inflammatory response by activating a large number of cytokines, which induces inflammation and can affect multiple organ systems that could potentially contribute to their failure in severe cases (1).
Multiorgan damage by COVID-19 infection is caused by penetration of the virus through angiotensin-converting enzyme-2 (ACE2) receptors found on the surface of the cell (21). Further, large concentrations of ACE2 receptors are found in pulmonary and cardiac tissue, which may explain symptoms of shortness of breath and cardiac complications in recovered individuals (21). Additionally, COVID-19 complications have been observed to last longer than 30 days and up to 6 months (28). Even though the athletic population appears to develop mild to moderate COVID-19 infection, are not at high risk for severe illness and are quick to recover, they may experience lingering post infection sequelae from COVID-19 like myocarditis, exertional dyspnea, tachycardia, muscle pain, joint pain and fatigue (even with asymptomatic and mild infection) (9, 15, 25). Lastly, estimations of LC in athletes are between 3 and 17% (34).
First time symptoms of COVID-19 illness can occur once the primary infection has subsided (32). Because athletes exert demanding loads compared to the average population, understanding the long-term effects of COVID-19 is not only important to help maintain maximal performance levels, but should also be a concern for their safety (2, 6, 32). While athletes appear to fully recover after COVID-19 infection, cardiopulmonary exercise testing (CPET) post infection has aided medical professionals to uncover potentially detrimental symptomatology during exertional activities (5).

Fortunately, current research has demonstrated that the chance for cardiac abnormalities among athletes recovering from asymptomatic to moderate COVID-19 illness is very rare (3, 14, 16, 19). In a study by Maestrini et. al. (2023), 6% of the participants exhibited cardiac abnormalities post COVID-19 cardiovascular evaluations. Also, of 1597 athletes in Big Ten American Football Conference, 37 athletes (2.3%) exhibited clinical or subclinical signs of myocarditis (10). Of interest, some cardiac issues uncovered during CPET and cardiovascular testing while undergoing return to play (RTP) protocols after infection had no relationship to COVID-19 and appeared to result from preexisting conditions (3, 24, 32). This emphasizes the need for regular CPET (which has been used as a standard test to determine the cardiorespiratory and pulmonary health of individuals post infection) and cardiovascular screening for all athletes (3, 24, 32).

While most athletes will have mild or no symptoms during acute COVID-19 infection, 3-17% will be affected by continuing symptoms, like fatigue, that can have negative effects, to optimal performance (33). Unfortunately, the recommended forced rest of 14 days for elite and competitive athletes can be detrimental to power and maximal oxygen consumption (VO2 max), cardiac output and stroke volume (21). Information regarding the long-term effects of COVID-19 continues to evolve and only necessitates the importance of research and investigation, especially in athletes because their success relies on their physical capabilities (31). Additionally, little research is available on the consequences of any potential musculoskeletal cellular interruptions through the ACE2 receptors primarily occurring in pulmonary and cardiac tissue (31).
Although many athletes have a significantly reduced risk of severe COVID-19 illness, they are not immune to contracting the disease and its lingering effects (9,33). Further, compared to other acute respiratory viruses, the proportion of athletes who have not fully recovered from COVID-19 is significantly higher (34). The purpose of this review is to evaluate the effects of COVID-19 infection on the performance of athletes.

List of Abbreviations
Cardiopulmonary Exercise Test (CPET), Cardiovascular Magnetic Resonance (CMR), Heart Rate (HR), Maximal Heart Rate (MHR), Ventilation (VE), Ventilatory Efficiency (VEf), Ventilatory Inefficiency (ViE), Long Covid (LC), Maximal Oxygen Consumption (VO2max), peak oxygen uptake (VO2 peak), Beats Per Minute (bpm), Blood Lactate (BL), Oxygen (O2), Carbon Dioxide (CO2), Repetition Maximum (RM), Respiratory Compensation Point (RC), Ventilatory Aerobic Threshold (VAT), Beat per Minute (BPM), VE/CO2 Slope (pulmonary ventilation to CO2 production), Partial Pressure of CO2 (PETCO2), Forced Expiratory Volume in the First Second (FEV1), Second Forced Expiratory Volume (FEV2)

Methods
Using guidelines for a systematic search review, a comprehensive literature review was conducted from January 2020 to November 2023 using the computer databases Google Scholar, PubMed and the Mary and Jeff Bell Library at Texas A&M University-Corpus Christi. Several search terms were used and include; covid and athlete; covid infection and athlete and performance and CPET; covid infection and athletes and power and performance and VO2max and cardiorespiratory; covid infection and CPET and anaerobic and athlete; covid infection and athletes and power and performance and VO2max and cardiorespiratory; covid infection and athletes and power and performance and VO2max and cardiopulmonary and sport. Larger search terms to narrow results were necessary when using Google Scholar as the use of two search terms like covid infection and athlete resulted in over 22,000 results. All search titles were carefully filtered to include athletic performance inferences and COVID-19 infection.

Once searches were filtered, article content was reviewed to determine relevance of the investigation as mentioned above. Research journal articles were selected along with 2 case studies due to lack of information in this newly emerged topic. 947 articles were retrieved using Google Scholar with search terms covid infection and athletes and power and performance and VO2max and cardiopulmonary and sport. Of the 947 articles, 10 were relevant to the research parameters. A second search on Google Scholar was conducted using the search terms covid infection and CPET and anaerobic and athlete with 899 results. Of the 889 resulting articles, 17 were relevant to the research parameters. Two separate searches were conducted in PubMed for the terms (1) covid infection and athlete and performance and CPET and (2) COVID infection and athlete and performance and CPET and anaerobic. The first search resulted in 122 outcomes with 18 relevant articles and the second search resulted in 7 outcomes with 5 relevant items. Larger search terms were used because using only the terms covid infection and athlete together resulted in almost 3,000 results. Lastly, the Mary and Jeff Bell Library was used in the review search using fewer search terms since using the larger terms resulted in an extreme narrowing of results. The search terms COVID and athlete were used and resulted in 237 articles. Using the option to include the search terms in the subject heading, the search was further narrowed to 88 where 7 of these search outcomes were selected based on the criteria. 6 articles were extracted from the final selection of articles that did not meet the search requirements and all results were compared for duplicates. In total, 32 articles were retrieved from the search. Additionally, a few articles were extracted from the articles obtained in the search for further investigation of research evidence.

Babity et al. (2022) observed a 10% decrease in VO2max in athletes recovered from COVID-19 infection when comparing their CPET values before illness. Also, post infection CPET times were longer among athletes recovered from COVID-19 infection (p=.003). Further, increased heart rate (HR) was observed in athletes previously infected with COVID-19 during testing. However, once adjustments for age were calculated, no statistically significant changes were evident. Additionally, 13% of elite athletes who participated in the study had asymptomatic infections and a small group appeared to have cardiac irregularities. Despite these differences, no difference was observed between COVID-19 athletes and the control group in ventilation (VE,) carbon dioxide (CO2) removal, blood lactate (BL) levels and percentage of time spent during the anaerobic phase. Vollrath et al. (2022) observed that athletes recovered from COVID-19 infection with persistent symptoms had lower ventilatory efficiency (VEf) than athletes who were symptom free and may indicate a slow recuperation of VEf for symptomatic individuals. Three months later, these persistent symptoms experienced by the athletes were reduced but still present in about 60% of the subjects.

Ventilatory inefficiency (ViE) was observed in competitive athletes that tested positive for COVID-19 by Komici et al. (2023) but was not observed to limit their exercise capacity. These athletes were tested after an RTP program of about 2 weeks. When comparing post infection sequelae, a study by Rinaldo et al. (2021), observed that nonathletic individuals exhibited similar symptoms at rest and at work whereas athletes did not appear to express symptomatology at rest. The exercise decrements observed between both groups in CPET included early AT, early termination of testing, lower peak oxygen (O2) pulse, lower work and a decreased slope relationship between O2 uptake and rate of work. Decreased capacity of exercise was not observed in athletes by Komici et al. 2021, however a trend was observed in the decrease of forced expiratory volume in the first second (FEV1) among the recovered athletes.
Similarly, Keller et al. also observed 4% lower peak values of VO2max in athletes recuperated from COVID-19 (p=.01) when compared to athletes who did not contract the virus. Along with reduced VO2max, Keller et al. (2023) observed an increased chance for exercise hypertension during CPET testing within this group which can be indicative of intolerance to exercise. Additionally, the authors noted that incidences of shortness of breath and chest pain were more prevalent with older athletes in the study group. Reduced peak oxygen uptake (VO2 peak) and increased BP among athletes recovered from COVID-19 illness were observed during CPET, but not at rest.

CPET values among COVID-19 recovered athletes with mild to moderate illness reached AT faster (p=.05) and also had lower measurements for minute ventilation (Ve) than the control group in an investigation by Anastasio et al. (2022). However, differences in maintaining CPET parameters between the two groups were not significant. Additionally, differences at maximal effort only differed by HR, with the COVID-19 group demonstrating higher HR values, but performance during testing was not altered. Finally, one month post COVID-19 infection athletes demonstrate a premature shift to anaerobic metabolism when compared to the control group.

Significant differences were not observed by Babity et al. (2022) when analyzing CPET values of elite athletes before and 3 months after COVID-19 infection. It is important to note that athletes in this study also underwent post COVID-19 retraining protocols where significant increases were observed in average exercise times (p=.003), time to achieve VO2max, respiration rate (p=.008), and HR achieved at AT (p=.004). Also, findings during examination uncovered arrhythmias or hypertension in asymptomatic athletes, and additional non-COVID-19 related to cardiac abnormalities. Moreover, Parpa & Michaelides (2022) observed significantly lower VO2max (p=.01) and decreased VO2max (p=.05) in 21 soccer players recovered from COVID-19. Significantly higher HR at ventilatory threshold (VT) (p=.01) and respiratory compensation point (RC) (p=.01) were also detected. Lastly, decreases in running speed during testing were only observed at VO2max (p=.05) and lower running times (p=.01) were observed.

In a study by Milovancev et al. (2021) of professional volleyball players recovered from COVID-19 infection with about 20 days of retraining, CPET values appeared to show fairly normal pulmonary function. After analyzing data from other studies of healthy athletes, the authors observed lower VO2max and second ventilatory threshold (VT2) in the participants of their study but contributed the deficits to detraining. Lastly, no cardiac disturbances were detected during testing. Similarly, testing results of athletes recovered from COVID-19 showed no statistically significant difference before and after COVID-19 in a study by Taralov et al. (2021) regardless of continued fatigue symptomatology. Due to the study’s small sample size, the authors looked at individual results and were able to see that one participant’s total CPET time was 30 seconds shorter post infection from 18 minutes to 17:30 minutes. Further, AT was reached earlier after acute infection. Additionally, maximal heart rates (MHR) were similar during testing before and after infection which suggests that the similar effort post infection resulted in decreased testing capacity. Another test subject had differing recovery HR 2 minutes into recovery from 141 beats per minute (bpm) before COVID-19 infection to 156 bpm after COVID-19 infection, which is an indication of diminished recovery capacity.

Wezenbeek et al. (2023) showed decreased aerobic performance after COVID-19 infection in elite soccer players about 2 months post infection. Statistically significant higher (MHR) percentages were observed 6 minutes into a Yo-Yo Intermittent Recovery Test (YYIR) (p=.006). When compared to non-infected team members, the MHR percentages were 6-11% greater in the players recovered from COVID-19. After a retest 4-5 months post recovery, these decreases dissipated to normal values. Lastly, the authors also investigated the effects of the viral infection on jumping, strength and sprinting capabilities and no significant differences were observed before and after infection.

A comparative study by Stavrou et al. (2023) between athletes that tested positive for COVID-19 and healthy athletes which never contracted COVID-19 demonstrated statistically significant differences during CPET even with non-significant differences in testing performance. First, the post-COVID-19 group had lower HR at maximal exertions than their healthy counterparts, 191.6 ±7.8 bpm and 196.6 ± 8.6 bpm respectively (p=.041). Mean arterial pressures were similar between both groups. Also, O2 consumption showed no significant difference between the groups. Second, BL levels in the post- COVID -19 group were significantly higher at rest (p=.001), during CPET and during recovery than the healthy group. Third, both groups achieved similar VO2max values, but the post-COVID-19 group did have greater exertional symptoms like increased VE. Fourth, increases in VE were observed in post-COVID-19 group even with non-significant performance differences in CPET between the two groups. Lastly, the post-COVID-19 group also had greater sleep disturbances based on study questionnaires (p=.001). Interestingly, no significant differences in O2 consumption were present between the groups, yet VE was higher at greater workloads in the post-COVID-19 group.
Another comparative study by Śliż et al. (2021) with endurance athletes before and after COVID-19 noted significant changes in CPET parameters after illness. These changes include aggravations to VO2 at AT (p=.00001), VO2 at RC (p=.00001), HR to RC (p=.00011) and VO2max (p=.00011). Additionally, lowered VO2max and early accumulation of lactate were observed during CPET.

Similar findings to ViE and decreased aerobic capacity in elite and highly trained recovered athletes were observed by Brito et al. (2023) with CPET 6-22 weeks after onset of illness. Further, statistically significant decrements were observed in both symptomatic and asymptomatic participants recovered from COVID-19 illness. Additionally, over 50% of all test subjects exhibited significant dysfunctional breathing (p=.023) and over 60% presented significant evidence of ViE (p=.001). Also, a statistically significant percentage of abnormalities were more prevalent among symptomatic individuals, specifically VE/CO2 slope (p<.001), PETCO2 rest (p=.007) and PETCO2 max (p=.008). Statistically significantly higher abnormalities of expiratory air flow/tidal volume were apparent with asymptomatic individuals (p=.012). Lastly, no changes in running economy were apparent in either group. Bruzzese et al. (2021) also noted statistically significant changes to oxygen uptake at second ventilatory threshold (VO2VT2) (p=.28), MHR (p=.04) and respiratory exchange ratio (RER) (p=.02).
In a case study by Barker-Davies et al. (2023) an elite runner recovering from COVID-19 experienced reduced work capacity and O2 uptake at AT 5 months after infection and occurred more rapidly than a previous CPET conducted 15 months earlier. Also, a decrease in workload by 27 watts (W) and a reduction of O2 uptake by 13% was also observed. When reviewing calorimetry, a 21% decrease in fat metabolism was observed and may explain the early onset to AT. Despite the decrements in performance, the absolute values of the CPET fell within normal range but the athlete complained of fatigue and difficulty generating power.

An investigation by Rajpal et al. (2021) which focused on cardiovascular magnetic resonance imaging (CMR) found incidence of current myocarditis or prior injury to the myocardium in almost 50% of 26 athletes recovered from COVID-19 (22). In another investigation by Maestrini et al. (2023), 2% of cardiac abnormalities were observed in 219 asymptomatic or mildly symptomatic athletes by Maestrini et al. (2023). Moreover, 3.3% of study participants demonstrated cardiac disturbances that included pericarditis and myopericarditis by Cavigli and colleagues. Juhász et al. (2023) also provided evidence that about 3% of recovered athletes had evidence of myocarditis or pericardial effusion. The authors also mentioned that persistent symptoms of COVID-19, like fatigue and chest pain, were factors that restricted players from RTP. Further, the disturbances seemed to be prevalent only among female athletes who had mild symptomatic COVID-19 infection. Additionally, these cardiac disturbances were determined during CPET testing and ECG monitoring. Biomarkers for cardiac disturbances, arrhythmias and structural abnormalities in the heart were also very low in the study by Sridi-Cheniti et al. (2022). Lastly, Cavigli et al. (2021) also observed that no athletes with asymptomatic COVID-19 infection demonstrated any cardiac complications.

Conversely, all athletes participating in an investigation by Fikenzer et al., (2021) had fluid accumulation in the pericardium (pericardial effusion) and magnetic resonance imaging (MRI) with high T1- and T2- values had a reduced maximal load, maximal O2 uptake, a higher HR at comparable exertion, and a significantly reduced O2 pulse when compared to previous testing. The changes to cardiac muscle in HR and O2 pulse were visible at moderate intensities, while the cardiopulmonary effects became apparent during higher intensities. Additionally, the respiratory minute volume which is used as a constraint of pulmonary function was considerably reduced. Malek and colleagues noted that 28 Olympic athletes recovered from COVID-19 infection did not appear to have any acute myocarditis findings after MRI testing. However, 5 of the subjects did show cardiac abnormalities. These individuals were all able to fully recover and RTP safely. Lastly, a case study by Nedeljkovic et al. (2021) observing native CMR images of an athlete recovered from asymptomatic COVID-19 infection demonstrated no signs of inflammation to the cardiac tissue. However, after contrast application, the indication of focal myocarditis became apparent where the athlete was advised to cease training for 3 months. Further, this individual continued to present with signs of myocarditis and decreased functional ability at a 3 month follow up visit.

Individuals like National Football League player Myles Garrett, National Basketball Association player Jayson Tatum and Major League Baseball player Yoan Moncada all experienced symptoms of fatigability (33). Because of this, Walker et al. (2023) compared the mean Pro Football Focus (PFF) game scores before and after a COVID-19 infection in players to examine performance. When analyzed by position before and after infection, statistically significant decreases in the numbers of snaps per game were observed in Defensive Backs (p=.03) and statistically significant decreases were further observed for mean scores in Defensive Linemen (p=.03). Additionally, similar findings were observed by Savicevic et al. (2021) in professional soccer players that were recovered from COVID-19 infection and completed RTP protocols where players demonstrated a decrease occurrence of high intensity accelerations and decelerations in game performance (p=.04).

Neuromuscular disturbances affecting balance may be another complication arising from COVID-19 as observed by Fernández-Rodríguez et al. (2023) which evaluated six handball players 1 month post infection and demonstrated degradation to static balance. Mild sleep disturbances were observed to affect 31% of individuals testing positive for COVID-19 by Śliż et al. (2023) and the sleep disturbances appear to influenced endurance athletes while performing CPET. Endurance athletes that experienced decreased sleep times experienced significant parameter changes in breath rate, pulmonary VE and BL concentration at AT. The study further observed several CPET correlations in athletes with sleep disturbances and performance and include (1) disturbances in HR and RC, (2) higher pulmonary VE at AT, (3) maximum power output and maximal HR and (4) individual habit which including methods to cope with sleep disturbances. Of interest, Vollrath et al. (2022) observed that sleep disturbances increased during the course of their investigation. Lastly, the authors further described that the most persistent symptoms observed in athletes included insomnia, fatigue and neurocognitive disorders, which can cause impairments to memory, learning and decision making.
Probing the influence of COVID-19 strains on athletic performance, Stojmenovic et. al. (2023) demonstrated that athletes infected with the Omicron variant, the latest virus strain, had higher VO2 max when compared to athletes infected with the older variants, Wuhan and Delta. Athletes affected by the Omicron variant had better VE and higher O2/HR values when compared to the two previous strains, Wuhan and Delta. Further, O2 transport to skeletal muscle was also greater with the Omicron variant. No statistical difference was observed with MHR at the completion of CPET and during the 3-minute recovery. Of further interest, the early transition of aerobic to anaerobic metabolism, which has been observed in several studies with the Wuhan and Delta variants, was not present for the Omicron variant (29).

Stojmenovic et. al. and colleagues further observed values of HR at ventilatory anaerobic threshold (VAT) and RC that were much higher in the athletes who contracted the Omicron strain versus the groups of athletes which contracted the Wuhan or Delta strain (p=.01). Additionally, higher HR values at the VAT were observed with the Wuhan and Delta variants when compared to the Omicron variant (p=.001). The RER at lower intensities was greater among the Wuhan and Delta group (p=.001) which demonstrates a greater dependence toward carbohydrate as a fuel rather than fat and further indicating an inability to utilize O2 for energy production. The efficiency of O2 delivery was the greatest for athletes with the Omicron variant. Moreover, VEf, although within normal limits for all three strains, was the best for individuals recovered from Omicron which further highlights more effective O2 transport to the skeletal muscle. Also, this study demonstrated meaningful decreases in aerobic capacity for all COVID-19 strains. Deng et al. (2023) investigated the neuromuscular performance of the upper body and mental health in a group of vaccinated kayakers recovered from the Omicron variant. No decrements were evident in 1RM bench press about 22 days post infection. Mental health appeared to be intact.

In an investigation by Jafarnezhadgero et al. (2022) recreational female runners that were hospitalized for COVID-19 were able to maintain steady state running with similar HR as the control group but ran at slower paces than the control group (p=.0001). Further, running test in COVID-19 recovered female runners terminated early (p=.0001). Also, these individuals had longer foot contact time (p=.002), peak propulsion forces (p=.0004) and reductions in loading rate (p=.04). Another study by Toresdahl and colleagues explored a potential link to COVID-19 infection and increased chances for injury in recovered runners due to systemic inflammation. While the investigation relied on self-reported questionaries, the outcome presented finding that about 20% of 1947 study participants, which included both males and females, experienced injury after a positive COVID-19 infection that prevented them from running for at least one week.

Juhász, et al. (2023) also noted that females, when compared to men, were more likely to suffer from short term prolonged symptoms of COVID-19 infection (34% vs. 19%, p = 0.005). However, females conveyed information through study surveys which indicated that they were able to regain peak form and maximal training strength faster than their male counterparts (3 vs. 4 weeks, p = 0.01). Further, LC was statistically significant with age groups in the study, with older age groups experiencing LC and severe symptoms more than their younger counterparts (p= .02%).

Gattoni et al. (2022) noted significantly lower performance outcomes among soccer players recovered from COVID-19 infection (p<.01). Additionally, no cardiopulmonary or cardiovascular abnormalities were present among test subjects. Also, while no statistical significance was observed for cardiopulmonary abnormalities, individual impairments were noted.
Of 26 elite athletes and 20 physically trained individuals (average age 30) participating in a study by Brito and authors, 65% of them continued to have persisting symptoms approximately 2-3 weeks after COVID-19 diagnosis, with the most frequent symptom being dyspnea (or shortness of breath). Additionally, participants with symptomatic illness showed statistically significant impairment to minute ventilation/CO2 production (VE/VCO2) slope (p < 0.001), partial pressure of CO2 (PETCO2) rest (p = 0.007), and PETCO2 max (p = 0.009) when compared to asymptomatic individuals. However, expiratory air flow/tidal volume occurred more often among asymptomatic individuals (p = 0.012). Lastly, impairments during CPET did not differ between symptomatic and asymptomatic individuals.

Discussion
With increased research regarding the influence of COVID-19 infection to athletic performance, new information is emerging, and prior implications of significant cardiac involvement have been quelled. The concern for myocarditis and sport related cardiac complications lies in fears of sudden cardiac death due to high intensity workloads, but these complications in athletes who are typically healthy and young with asymptomatic or mild symptoms COVID-19 infection are low, yet the risk does exist (7, 23). Occurrences of myocarditis, pericarditis, intolerance to exercise, fatigue and shortness of breath in athletes presented the need for more regular medical examinations and screening post infection not only to conserve athletic capabilities, but to also prevent the possibility of sudden cardiac death (SCD) (29). Further, some of the cardiac issues uncovered with CPET and cardiovascular testing with RTP protocol may have been preexisting conditions in athletes which had no relationship to COVID-19 (3). For this reason alone, CPET testing and cardiovascular screening is recommended for all athletes (3). To complicate matters, changes to the heart muscle can occur in athletes due to adaptations resulting from exercise quantity and intensities that are necessary to maintain athletic performance and may make testing athletes at resting conditions to be counterproductive (22, 32).

Cardiac abnormality involvement in athletes recovered from COVID-19 is inconsistent (18). Clinical cardiac events in elite and high-level athletes after mild or asymptomatic infection are very low even after resuming high-level training (27). Because of the low prevalence of cardiac complications associated with COVID-19 infection, the use of resonance CMR has been suggested to be reserved as a screening tool for athletes that may be at risk for cardiovascular abnormalities, although cardiac screening in athletes was suggested to be performed at least once to help detect underlying heart abnormalities (3, 17).

COVID-19 seems to affect the cardiorespiratory system more than the cardiovascular system (19). Several studies have observed an early switch to anaerobic metabolism during CPET. The greater recruitment of anaerobic metabolism at a specific workload can help to explain the inability of athletes to develop a significant power output during exertion, most probably due to fatiguability (4). Further, a study by Ajaz et al., observed decreased cellular respiration in hospitalized COVID-19 patients when the glucose pathway for energy was blocked. Additionally, Stavrou et al. (2023) also emphasized this to be a deficiency in the aerobic pathway for energy production as ventilation increased during physical exertion. Keller and colleagues suggested that the limitations to performance are directly related to delivery of O2 to muscles tissue rather than occurring from cardiac complications. Also, Jafarnezhadgero et al. (2022) determined that decreased performance during running tests were caused by deficits in O2 transport rather than fatigue, and they did not affect running mechanics in the study participants which recovered from COVID-19. Finally, these ideas are further supported by Wezenbeek and colleagues, who believe that COVID-19 infection can cause disruption to capillary blood flow, thus limiting the uptake of O2.

Of interest, a study by Ajaz et al. (2021) observed decreased cellular respiration in hospitalized COVID-19 patients when the glucose pathway for energy was blocked. Additionally, cellular respiration in the healthy control group and a separate group with various chest infections not related to COVID-19 did not exhibit any augmentation to cellular respiration. Also, in all three groups, no changes were present when other energy pathways with glutamine and long chain fatty acids were blocked. Further, Ajaz and authors believe the dependency on glucose may explain the early shift from aerobic to anaerobic metabolism observed in some athletes post COVID-19 infection. Moreover, the authors consider that mitochondrial dysfunction from COVID-19 infection is responsible for the preference of cells to utilize the process of glycolysis for cellular respiration and energy production. Lastly, greater metabolism of carbohydrates may have more negative implications in female athletes since females are more reliant on fat metabolism than men (4).

Although testing parameters in a study by Taralov et al. (2021) demonstrated no statistical significance in CPET and blood testing before and after COVID-19 infection in athletes, many continued to complain of persisting fatigue for several months. By examining the individual differences among the small sample group, the authors were able to detect small changes in performance. For example, a 30 second shorter CPET time post infection with time with similar MHR and intensity values before infection may be indicative of fatigue. Additionally, another test subject exhibited higher recovery HR parameters post infection which can be indicative of a reduced capacity for recovery. Further, AT was reached earlier after acute infection. Taralov and authors further emphasized that these findings can be significant during competition. While these changes seem small when comparing test results, these small differences can make large differences during competition by increasing fatigability and decreased recovery capacity that can have a negative impact to performance.

Recovery from persistent COVID-19 infection sequelae can take several months. Parpa & Michaelides (2022) concluded that 2 months of recovery post infection may not be sufficient for athletes, especially since some symptoms are not detectable at rest. Subsequently, post COVID-19 infection can cause reduced VO2 peak during exercise testing and increases in blood pressure during exercise despite presenting normal findings at rest reinforces the need for return to play testing in athletes (14). Additionally, even mild illness in athletes who have non-significant differences in VO2max when compared to non-infected individuals will experience aerobic burdens, which will display strains in performance and respiration (28). Lastly, the authors recommended that factors like VT, RC and HR and running speed should be observed during VO2max and respiratory threshold (RT).

One of the primary reasons for performance decrement may be due to detraining from COVID-19 infection and the necessary forced rest (19). Declines in VO2max with detraining have been observed in as little as 12 days and are caused by decreased stroke volume and arteriovenous gas exchange due to decreased volume of plasma from decreased exercise exertion (19). In addition, decreases in mitochondrial density have been observed after three weeks of exercise with no changes in muscle capillarization (19). Finally, cessation of exercise in 42-85 days has been noted to change the oxidative capacity of intermediate type IIa muscle fibers toward type IIb muscle fibers (19).

Moreover, an increase in VE/VCO2 slope is suggestive of intolerance to exercise along with cardiovascular or cardiopulmonary disease (15). Komici et al., (2023) did not believe that deconditioning was associated with ViE from their ventilatory parameters because the slope of VE/VCO2 appeared similar within all groups of athletes recovered from COVID-19 in their study. However, a perceived inverse correlation among ventilatory efficiency slope (VCO2/VE) maximum and ventilatory equivalents for O2 (VO2/VE) maximum among test subjects was suggestive of a perfusion mismatching in ventilation which is indicative to ViE (15). While the mechanisms involved in their ViE were not clearly understood, an inverse relation was observed between maximum volume of CO2 during ventilatory exchange and the volume of max O2 during ventilatory exchange and may have implications to a mismatching of O2 (24). Moreover, cardiorespiratory deficits have been attributed to muscle deconditioning in patients, not athletes, when decreased ventilatory response and early AT was observed in post COVID-19 patients (24). Athletes recovered from COVID-19 infection may demonstrate shortness of breath but can also have reduced pulmonary capacity and cardiac symptoms only detectable during sub-maximal conditions which can result in reduced physical capacity (10,15, 25). Moreover, increases in HR at VT and RC may be a response in the cardiovascular system resulting from hypoxemia, which has been observed as a mismatching of gas exchange in several studies (21). To conclude, understanding how to assist athletes with regaining pre-COVID-19 infection performance is not only important for a safe return to play, but for performance too.

Sleep is important for the body to function properly, and can affect attitude, breathing, pulmonary VE, memory impairment, stress tolerance, BL concentrations, glycogen recovery, metabolic processes and immune function (26). In addition, reaction times, accuracy, perceptual abilities, skill performance, strength, power, endurance and overall athletic performance can be affected by sleep disturbances and may not allow adequate recovery from physical exertion (26, 28). Finally, lack of sleep and decreased ability for recovery may increase injury risk because of slower reaction times and decreased perceptual abilities (28).

Also, Jafarnezhadgero et al. (2022) suggested that COVID-19 infection may also alter rates of perceived exertion which can possibly affect running biomechanics. Further, Toresdahl et al. (2022) observed a potential cellular musculoskeletal deterioration from systemic inflammation of COVID-19 in a group of endurance runners. Since this investigation used only questionnaires, more research is necessary to confirm if the outcomes were a result of cellular musculoskeletal deterioration or if they were a result of deconditioning due to forced rest associated with illness which could be responsible for developing muscle weakness or neuromuscular control.

With the emergence of COVID-19 strains, understanding the symptomatology before and after disease is important for the determination of athletic integrity among individuals in sports (28). Fortunately, the emergence of new COVID-19 variants appears to have diluted pathologies or symptomatologies (8, 29). However, the authors emphasized that all athletes affected with the COVID-19 variants exhibited decreased collected values in VO2max. Stojmenovic and authors examined the effects of COVID-19 virus variants when compared to healthy athletes which never tested positive for COVID-19. Furthermore, testing was conducted during the athletic season where athletic capacity should be optimal. Additionally, Stojmenovic et. al. (2023) observed an adequate supply of O2 to the muscle in all three groups during testing and speculate an inefficiency with mitochondrial or cellular respiration caused by COVID-19 infection. Finally, Bruzzese and colleagues noted that although significant performance differences during CPET were observed in athletes pre and post COVID-19 infection, significant work intensities were attained.

Static balance is a skill for all sports and may help increase strength, power and speed (9). Fernández-Rodríguez and colleagues suggested that decrements to static balance may be due to the neurological impairment of sensory processing that may occur with COVID-19 infection. Moreover, sensory processing in sports is important for the cognitive control of decision making, planning of movement, organization of movement, thought planning and actual execution of performance (9). Lastly, other reasons for balance decrement can include mental health issues like depression, anxiety, inability to make decisions, fatigue and lack of sleep, cardiorespiratory impairments, or simply the forced break after infection with limited physical activity (9).

Bruzzese et al. (2023) suggested that a decrease in volume of O2 at second forced expiratory volume (FEV2) in evaluated athletes was a result of detraining from forced rest and isolation due to a positive COVID-19 diagnosis. Additionally, a case study by Barker-Davies et al. (2023) suggested that deconditioning due to imposed rest was a potential reason that might explain performance decrements. However, the individuals observed presented with normal stroke volume and cardiac output and values did not decrease as they would in a deconditioned individual. The authors further hypothesized that decreases in performance may also be a result of mitochondrial dysfunction, which has been observed with COVID-19 infection. Mitochondrial dysfunction is the result of the cells possessing an increased dependence of glucose rather than fat metabolism (4). Further, the authors explain that after calorimetry data review, the larger ratio of the metabolism of anaerobic to aerobic pathways may be another possible explanation for perceived decreases in power output. Finally, women appear to be more dependent on fat metabolism than men, thus reductions in aerobic pathways will probably have a greater impact on women (4).

Unfortunately, RTP for some athletes may not be an option because of persistent sequelae due to COVID-19 illness (12). Organizations like the National Strength and Conditioning Association and the Collegiate Strength and Conditioning Coaches Association Joint committee have recommended a gradual RTP which involves low intensity exercise once symptoms have subsided (12). From current studies, persisting sequalae among athletes post COVID-19 infection appear to resolve in 3-4 months and incidences of LC lasting more than three months was very low (3, 17, 23). Because the physical long-term health implications of COVID-19 to athletes are not fully understood and research is limited, an ambivalence for RTS protocols exists (11).
Currently, RTP protocols, which assist athletes to fully recover from illness, ranges from 1-4 weeks depending on severity of COVID-19 and generally have not included exercise stress (17, 25). Exercise should not be continued among symptomatic players that continue to experience persistent fever, dyspnea at rest, cough, chest pain, or palpitations, since high intensity exercise may increase inflammation and advance the rate of viral replication therefore negatively impacting immunity to exacerbate or even lengthen duration of illness (7, 19). Conversely, moderate exercise intensity has been noted to have positive effects on immunity (19).

Performance can be limiting as some athletes, specifically those with cardiac symptomatology, will require several months to clear symptoms and can lead to deconditioning, specifically to power and VO2max(5). Savicevic et al. (2021) noted absences resulting from COVID-19 infection ranged from 7-91 days and can have implications to detraining. Unfortunately, forced breaks in training due to COVID-19 illness may be the reason for decreases in mitochondrial functioning, which will decrease the oxidative capacity of the muscle and capabilities (12). Further, the lack of energy supply, coupled with possible decreases in oxygen transport, suggested to be a common consequence of COVID-19 infection, may contribute to fatigue during performances in sports (12). Additionally, voluntary skeletal muscle function and activation can also be compromised under circumstances of fatigue and can further precipitate early onset of fatigue and alter biomechanics of movement (12). However, the effects of detraining among elite athletes lasting less than 28 days have been observed to have non-significant effects on neuromuscular functioning (8).

Even with decrements in VO2max from COVID-19 infection, different sports have varying uses for aerobic capacity (21). For instance, sports like basketball and tennis rely primarily on anaerobic energy pathways, but rely on aerobic fitness for recovery, and resynthesis of phosphocreatine for the ATP-PC (21). Conversely, a sport like soccer will rely heavily on aerobic fitness with total distances covered by players in a game can range between 9-14 kilometers (21). Further, distance covered in a 90-minute soccer game is dependent on VO2max and lactate threshold and metabolite removal/recoverability (21). Additionally, with reference to team sports, Savicevic et al. stressed the fact that a decline in the performance of one team player could affect the performance of the entire team. Lastly, using CPET can be beneficial to observe athlete responses to high intensity demands and help distinguish between the effects of detraining or cardiorespiratory inefficiency from illness (21).

Conclusion
To conclude, COVID-19 infection does appear to affect athletes adversely and may last for several months. Although small, these differences could affect team success or individual success in sports. Additionally, some athletes recovered from acute COVID-19 infection continue to feel fatigued under physical exertions even when medical screening, physical fitness tests and power output results were within normal limits and may cause limitations during athletic performance. Individuals experiencing these symptoms of fatigue after a short-forced rest may be a result of viral infiltration resulting in mitochondrial dysfunction, while longer forced rest times may be contributed to deconditioning along with metabolic deficiencies. Fortunately, these issues appear to be reversible as observed with Babity et. al. (2022), where athletes were observes to have better CPET values post infection with a rigorous retraining protocol. Lastly, further research on decrements during competitive performance is necessary to fully understand the true effects of the virus infiltration among athletes since laboratory conditions cannot replicate the actual competitive environment.

Applications to Sport
Due to the complicated nature of COVID-19 and slow recovery associated with persistent fatigue which may be a result from a possible disconnect to pulmonary efficiency, capillary perfusion or mitochondrial function, screening for exertional stressors during athletic performance is highly recommended with CPET and spirometry. Further, the problematic physical circumstances of COVID-19 illness can prevent athletes from returning to sport at physically competitive levels. Individualized gradual RTP is recommended to acclimatize athletes to the high intensity demands of sports since small decrements to performance can produce negative consequential outcomes during play in competitive sports.

Limitations
There were several limitations to this review. First, many of the studies conducted had small sample sizes. Second, most of the testing was conducted with male athletes. Third, limited data was available from CPET and cardiac screening before infection among test subjects which did not allow for comparative investigations. Also, since COVID-19 is a relatively new epidemic and disease, limited data is available, especially among the athletic population and vaccinated individuals. Additionally, data varies with respect to recovery times and physical conditioning as some testing was conducted after RTP or during the competitive season. Lastly, very limited data investigating strength and power was available and is of interest since many decrements to performance were observed during high intensity exercises in a few investigations.

Acknowledgements
Special thanks to Drs. Frank Spaniol and Dr. Donald Melrose for all their support and advice.

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George Minoso2024-11-26T09:43:24-06:00November 15th, 2024|COVID-19, Research, Sports Exercise Science, Sports Health & Fitness|Comments Off

Cupping Therapy Treatment on Range of Motion

Authors:¹Rachele E. Warken, ²Erik Reid, & ³Christopher M. Harp

¹Northern Kentucky University, Highland Heights, Kentucky, USA

Corresponding Author:

Rachele E. Warken, PhD, ATC

Northern Kentucky University

100 Nunn Drive, Highland Heights, KY 41099

859-572-5623

[email protected]

Rachele Warken is an associate professor and the director of the graduate Athletic Training Program at Northern Kentucky University. She is also a certified athletic trainer. Rachele has a bachelor’s degree from Northern Kentucky University and a master’s and doctoral degree from the University of Hawaii, Manoa.

Abstract

Purpose:The purpose of this study was to assess the effects of cupping therapy and passive stretching on shoulder internal and external rotation in healthy male high school athletes. Methods: Participants included nine high school male football players recruited from a local private high school. An eight minute cupping therapy treatment was completed on one arm, while passive shoulder stretching was completed on the other. Pre and post intervention measurements were taken for shoulder internal and external rotation and analyzed. Results: Analysis revealed that shoulder internal rotation range of motion post intervention were significantly higher than at pre intervention (p = 0.003), but there was no significant difference between shoulder internal rotation between the cupping therapy group and passive stretching group (p = 0.879). Similarly, shoulder external rotation range of motion post intervention was significantly higher than at pre intervention (p=0.021), but there was no significant difference between the cupping therapy group and passive stretching group (p = 0.621). Conclusions: The results of this study conclude that a cupping therapy treatment was as effective as a passive stretching treatment at increasing shoulder internal and external rotation in healthy high school males. Application in Sports: Cupping therapy is widely used by clinicians and athletes for a variety of reasons. Although this study this study did not find that cupping therapy is superior to passive stretching in healthy high school aged males, it did demonstrate that this intervention is as effective as passive stretching and provides the clinician with an additional method of treatment.

Key Words: Passive Stretching, Myofascial Decompression, Rehabilitation

Introduction

Injuries to the shoulder and elbow are very common among athletes, especially in sports that require forceful overhead activities. Range of motion deficits, specifically in shoulder internal and external rotation, have been linked to both shoulder and elbow injury. Previous research has indicated that athletes with a passive shoulder internal rotation deficit greater than 25° in their dominant shoulder compared to their non-dominant shoulder were at four to five times greater risk of upper extremity injury than those with less than a 25° deficit (10). Additionally, a total range of motion (shoulder internal rotation plus external rotation) of less than 160° also resulted in an increased the risk of upper extremity injury (2). As a result, clinicians and athletes consistently work to improve shoulder rotation range of motion with the goal of decreasing shoulder and elbow injuries.

Common methods to increase shoulder rotation include passive stretching and self-stretching. These stretches place slow and controlled tension on the soft tissue and have been shown to increase range of motion, improve flexibility, reduce the risk of injury, and improve blood circulation (1). Recently, the use of cupping therapy has gained popularity, especially in the athletic population as a result of prominent athletes advocating its use. Cupping therapy is an ancient Chinese technique that utilizes either glass or plastic cups along with fire or a vacuum pump to create negative pressure, drawing the skin and underlying tissue into the cup during treatment (9). The negative pressure developed during the treatment is thought to help reduce pain and inflammation, improve blood flow, facilitate the healing process and strengthen the immune system (6 ,8, 9).

Cupping therapy or myofascial decompression as it is commonly known in Western medicine is often used in sports medicine settings to increase range of motion. It is thought that the increase in blood flow to the muscle during a cupping therapy treatment increases tissue temperature causing tissues to become more elastic, resulting in greater range of motion (3). Although commonly used, there is currently limited research demonstrating the effectiveness of cupping therapy on improving range of motion. Previous research analyzing the effectiveness of cupping therapy on improving spine range of motion found that the cupping therapy intervention increased cervical and lumbar spine flexion range of motion following treatment (7, 11, 14). When cupping therapy was applied to other areas of the body differing results were found. When a cupping therapy treatment was applied to the gastrocnemius, an increase in dorsiflexion range of motion was identified (4). When cupping therapy was applied to the hamstring muscle group, researchers found that the cupping therapy treatment provided similar improvements in range of motions as more standard methods such as passive stretching (5, 8, 12) or found no improvement in range of motion (9, 13). To our knowledge, there is no previous research available that assess the effectiveness of cupping therapy on the upper extremity. Therefore, the purpose of this study was to assess the effects of cupping therapy and passive stretching on shoulder internal and external rotation in healthy male high school athletes. It was hypothesized that cupping therapy will result in greater shoulder internal and external range of motion values than the passive stretching technique.

Methods

Study Design

This study utilized a cross-sectional design, and all data were collected in the athletic training clinic of a local boy’s private high school. The dependent variables include internal and external shoulder range of motion. The independent variables include the treatment types (cupping therapy and passive stretching) and the time the measurements were taken (pre-intervention and post-intervention). This study was approved by University’s Institutional Review Board.

Participants

Participants in this study included male high school football athletes recruited from a local boy’s private high school. A total of nine participants completed the study. Participant demographic information including age, height and weight are listed in Table 1. The inclusionary criteria for this study were healthy male high school athletes who were cleared for full athletic participation. The exclusionary criteria for this study included those who did not have full medical clearance for athletic participation, had shoulder surgery within the past year, or currently have shoulder pain.

INSERT Table 1. Participant demographics.

Table 1
Participant demographics (mean ± SD)
	N	Mean	±	SD
Age (yrs)	9	15.89	±	0.60
Height (in)	9	70.00	±	2.35
Weight (lbs)	9	188.89	±	39.43

Instrumentation

A standard twelve inch goniometer was used to measure internal and external rotation range of motion of the shoulder prior to and following the interventions. For the cupping therapy intervention, five plastic cups and pumping handle were used (Hansol Cupping Therapy Equipment Set, Hansol Medical Equipment, Seoul Korea).

Procedures

All testing occurred in the athletic training room at the local all boy’s private high school. Each participant (and their parent/guardian) completed the informed consent and assent forms prior to testing. During testing, age, height, weight, dominant arm, and previous shoulder injury information were collected. Each participant completed both the cupping therapy intervention and passive stretching intervention, one on each arm. The interventions were randomly assigned to each arm (dominant/non-dominant).

Prior to any intervention, passive shoulder internal and external rotation range of motion were assessed in both shoulders with a goniometer while the participant was lying supine, with their shoulder abducted to 90°,their elbow flexed to 90° and their shoulder in neutral rotation. Two measurements in each direction were taken and the values were averaged and used in the statistical analysis.

Following the pre intervention measurements, the cupping therapy intervention was performed with the patient lying prone. Lotion was applied to the posterior shoulder, scapula, and upper back to act as a lubricant for the cups. Five cups, each two inches in diameter were then applied to the muscle bellies of the posterior and lateral deltoid, infraspinatus, the middle portion of the trapezius and the rhomboid major and given three pumps each. The cups remained in place for eight minutes and then removed. Following removal of the cups, shoulder internal and external rotation range of motion was measured again with a goniometer.

Prior to the stretching intervention, the participant was asked to perform a warm-up of the arm being stretched. The warm-up consisted of passive self-stretching into flexion, extension, internal and external rotation, and completing rows with an elastic band. Following the warm-up, the researcher manually stretched the shoulder in both internal and external rotation with the participant in the supine position. The researcher held each stretch for 30 seconds, switching between stretching internal and external rotation for a total of three stretches in each direction. Following the stretching treatment, shoulder internal and external rotation range of motion were measured with a goniometer.

Statistical Analysis

A two-way analysis of variance was used to assess the differences between interventions (cupping therapy and passive stretching) and time period (pre-intervention and post-intervention) was completed for each dependent variable (shoulder internal rotation and shoulder external rotation). A priori alpha levels were set at p < 0.05 for statistical significance. All statistical analyses were performed using SPSS Version 28 (SPSS, Inc, Chicago, IL).

Results

A total of nine male high school athletes participated in this study. The demographic information is included in Table 1. The two-way analysis of variance revealed that shoulder internal rotation range of motion post intervention were significantly higher than at pre intervention (p = 0.003). There was no significant difference between shoulder internal rotation between the cupping therapy group and passive stretching group (p = 0.879), nor was there a significant interaction (F(1, 32) = 0.094, p = 0.761) (Table 2). Similarly, the two-way analysis of variance for shoulder external rotation range of motion post intervention was significantly higher than at pre intervention (p=0.021). There was no significant difference between the cupping therapy group and passive stretching group (p = 0.621), nor was there a significant interaction (F(1, 32) = 0.061, p = 0.806) (Table 3).

Table 2
Shoulder Internal Rotation Range of Motion (deg, mean ± SD)
	Pre-Intervention			Post-Intervention
Cupping Therapy	65.33	±	4.85	73.67	±	6.78
Passive Stretching	64.00	±	11.60	74.11	±	9.91

Table 3
Shoulder External Rotation Range of Motion (deg, mean ± SD)
	Pre-Intervention			Post-Intervention
Cupping Therapy	80.78	±	9.20	88.11	±	9.73
Passive Stretching	78.22	±	9.23	87.22	±	11.95

Discussion

The purpose of this study was to examine the effectiveness of a cupping therapy treatment on increasing shoulder internal and external rotation. The results of this study found that both the cupping therapy intervention and the passive stretching intervention significantly increased shoulder rotation, however there was no difference between the interventions. To our knowledge, this was the first study to examine the use of cupping therapy to increase range of motion at the shoulder. Previous authors examined different areas of the body and found differing results.

Markowski et al. (7) conducted a study analyzing the effects of cupping therapy on lumbar flexion in participants with chronic low back pain. They found that one cupping therapy treatment significantly improved lumbar flexion range of motion. This study did not include a control group, so it is not clear if a cupping therapy treatment is superior to more standard ways of increasing range of motion such as passive stretching of the low back. Similarly, a study by Yim et al. (14) examined the difference between a cupping therapy treatment and McKenzie stretching exercises on cervical spine range of motion in healthy participants. They found that that the cupping treatment increased cervical spine range of motion to greater degree than the McKenzie stretching exercises indicating that cupping therapy applied to the cervical spine region was a superior to other standard stretching techniques.

A study by Hammons and McCullough (4) examined the effects of a cupping therapy treatment on dorsiflexion range of motion in individuals with delayed onset muscle soreness (DOMS) in their gastrocnemius muscle. They found that cupping therapy significantly increased dorsiflexion range of motion in individuals with DOMS compared to a control group. Although a control group was used in this study, this group did not receive any treatment, so although cupping therapy increased dorsiflexion, it is not clear if a cupping therapy treatment is superior to other methods of increasing range of motion.

Several studies have examined the effectiveness of cupping therapy in the hamstring muscle group. Kim et al. (5) compared cupping therapy to passive stretching in the hamstring group. They found that both interventions significantly increased hamstring range of motion, however there was no difference between groups. Murray et al. (8) found that cupping therapy significantly increased hamstring range of motion, but similar to other studies, they did not use a control group so it is unclear if the increased observed following the cupping therapy treatment was superior to other methods of increasing range of motion. Warren et al. (12) conducted a study on hamstring flexibility and compared a cupping therapy treatment to a self-mobilization treatment using a foam roller, in individuals with tight hamstrings. Similar to others, they also found that both groups had significant improvements in range of motion, but the individual treatments were not significantly different.

Finally, a study by Williams et al. (13) also looked at the effect of cupping therapy compared to a control group on hamstring flexibility. The control group did not receive any treatment. Unlike other previous research, they found that a cupping therapy treatment did not increase hamstring range of motion. Similarly, a study by Schafer et al. (9) compared hamstring flexibility in a cupping therapy group, a sham group and a control group and found that none of the groups significantly increased hamstring range of motion following treatment.

Conclusion

This is the first study to specifically examine the effects of cupping therapy on increasing shoulder internal and external rotation. The results of this study found that cupping therapy increased both shoulder internal and external rotation, but was not superior to passive stretching. Cupping therapy is a common practice among clinicians and athletes and is used for a variety of reasons. This study adds to the previous literature that indicates that cupping therapy could be a useful tool, among others to increase shoulder internal and external rotation. Future research could focus on individuals with shoulder rotation deficits, functional limitations and pain. In this population, it is possible that cupping therapy could be a superior method for increasing range of motion and function as well as decreasing pain.

Applications in Sport

Cupping therapy is widely used by clinicians and athletes for a variety of reasons. This study concludes that the use of cupping therapy is one possible method for increasing shoulder internal and external rotation. Although the results indicated that cupping therapy is not superior to passive stretching for increasing shoulder range of motion in healthy, high school aged male athletes, it is one tool that could be used. Although not analyzed in this study, cupping therapy has been shown to help with pain and inflammation. In theory, in an athlete suffering from a shoulder pain and decreased range of motion, a clinician may choose cupping therapy over passive stretching, because cupping therapy may increase shoulder range of motion, and it may also help with pain.

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George Minoso2024-11-04T11:58:48-06:00November 4th, 2024|Research, Sports Exercise Science, Sports Medicine|Comments Off