Authors: Gillian Hotz1, Jacob R. Griffin2, Hengyi Ke3, Raymond Crittenden IV4, Abraham Chileuitt5
1Department of Neurosurgery, University of Miami Miller School of Medicine, Miami, FL, USA 2KiDZ Neuroscience Center, The Miami Project to Cure Paralysis, University of Miami Miller School of Medicine, Miami, FL, USA 3Department of Public Health, Division of Biostatistics, University of Miami Miller School of Medicine, Miami, FL, USA 4Department of Neurology, University of Miami Miller School of Medicine, Miami, FL
Gillian A. Hotz, PhD is a research professor at the University of Miami Miller School of Medicine and a nationally recognized behavioral neuroscientist and expert in pediatric and adult neurotrauma, concussion management, and neurorehabilitation. Dr. Hotz is the director of the KiDZ Neuroscience Center, WalkSafe, and BikeSafe programs.
Comparing Public vs. Private High School Sports-Related Concussions from a Countywide Concussion Injury Surveillance System
ABSTRACT
Purpose Largely, research on adolescent sports-related concussion (SRC) has focused on public school athletes. SRCs of private school athletes have been studied less and may differ due to differences between school types.
Methods SRCs between Miami-Dade County high school athletes at trained public (n = 1088), trained private (n = 272), and untrained private (n = 79) were compared. Outcomes included days between date of injury (DOI) and clinic date, days between DOI and post-injury ImPACT retest, days withheld, return to play (RTP), ImPACT baseline and post-injury retest completion, and academic accommodation status.
Results Trained public and trained private groups had similar days between DOI and clinic date, days withheld, and percentage who RTP. Differences between the trained public and untrained private groups existed for RTP but not for days between DOI and clinic date or days withheld. Private group athletes were more likely to receive academic accommodations.
Conclusions Public and private high schools trained on the same SRC protocol did not have significantly different outcomes. The untrained private schools, however, had worse outcomes compared to the public group.
Application In Sports SRC outcomes in both public and private high schools may benefit from SRC education, training, an established protocol, and use of a management system.
Each year, an estimated 1.6 to 3.8 million sports-related concussions (SRCs) occur in the United States (1). While the nearly 8 million high school athletes participating in sports annually benefit from the improved social, psychological, and physical health gained from playing sports (2, 3), there is also an ongoing risk of injury due to consistent athlete-exposure (4). SRCs are understandably a concern for high school aged athletes due to the short-term and potentially lifelong behavioral, cognitive, emotional, physical, and psychological effects they can produce (1, 5). These consequences can be particularly worrisome as this population is already experiencing their own ongoing physical and cognitive development changes that can negatively be affected by an SRC (6). Understanding risk factors contributing to adolescent SRCs and what may lead to differences in outcomes is therefore imperative for identifying those most at risk and ensuring the proper management and treatment resources are in place.
Thus far, an overwhelming majority of research on SRCs has focused on or included samples of public high school athletes as opposed to private high school athletes. One example is the High School Sports-Related Injury Surveillance Study, Reporting Information Online (RIO) (7). The High School RIO is an internet-based data collection tool that captures athletic exposures and injury events through athletic trainers (ATs) that report data. It is often used as a source of SRC data for research (4). In the most recent report, nearly 80% of the participating high schools were public with the rest being private (7). Additionally, other studies on SRC incidence and trends have included only athletes from public high schools (8.) The lack of private high school inclusion in adolescent SRC research is an important consideration because known distinctions between public and private high schools possibly lead to differences in SRC incidence and outcomes (4). These include differences in school size, support services and resources, student racial/ethnic backgrounds, rigorous academic programs, and socioeconomics (9).
While there has been recent research that details private high school athlete SRC experiences and reporting behavior (4, 10), there is still a need for continued research into private high school SRC outcomes. Specifically, it would be important to examine how SRC outcomes differ between public and private high schools. Therefore, the purpose of this study was to compare SRC outcomes between public high schools who received specific concussion training and education to private high schools who received the same training and private high schools who did not receive training on the same SRC protocol. The goal of using these three distinct groups was to examine whether differences in SRC outcomes would be a result of differences in SRC education, training, and protocol.
METHODS
Participants and Procedures
This study included Miami-Dade County (MDC) public and private high school athletes with an SRC that occurred in a practice or game between August 1st, 2012, and July 31st, 2022. All athletes were treated at the University of Miami Miller School of Medicine’s Concussion Clinic, UConcussion (UCC). Athletes that sustained an SRC outside of the study period were excluded as well as those with an SRC that did not occur during an MDC public or private high school practice or competition. If an athlete was treated at a provider other than the UCC, they were also excluded.
The UCC clinical team hosts an annual SRC training and educational workshop for MDC public high school ATs and athletic directors (ADs). In these workshops, ATs and ADs are trained on how to use the Six Steps to Play Safe protocol (11) and how to administer ImPACT(12) concussion tests. The UCC also makes available specialty concussion clinics where athletes with a suspected SRC can be referred to for management and treatment. The UCC similarly partners with and provides training and education to 8 private high schools within MDC. While athletes at other private high schools within MDC can still be referred to and receive treatment at the UCC, ATs and ADs at these high schools are not provided with the same educational workshops and training on the Six Steps to Play Safe protocol (11). In this study, there were 35 trained public, 8 trained private, and 29 untrained private high schools that were grouped as either “trained public,” “trained private,” or “untrained private,” respectively.
The Six Steps to Play Safe(11) is a standardized protocol that can be used to manage an athlete’s SRC and safe return to play (RTP) and return to school during recovery (Figure 1). Included in this protocol are, in order, pre-season ImPACT(12) baseline testing, AT sideline testing, post-injury ImPACT testing, SRC clinic follow-up, gradual RTP and return to learn protocols, and SRC injury surveillance form completion.
Variables Reported variables were collected during UCC visits and from surveillance reporting by ATs. Athlete information in the study included demographics and the sport played when the injury occurred. SRC specific information was also reported and included date of injury (DOI), days between DOI and first clinic date, days between DOI and post-injury ImPACT retest, RTP status (yes/no), and days between DOI and RTP (days withheld). To eliminate the few extreme outliers, athletes were only included in days between DOI and first clinic date as well as days withheld mean calculations if the value for these variables was < 120 days. For similar reasons, only athletes with days between DOI and post-injury ImPACT retest < 30 days were included in the calculation. Whether an athlete received academic accommodations was included as a variable because previous research (13) suggests that private high school students experience particularly high levels of stress due to concerns about academic performance and school requests, which potentially impacts whether academic accommodations are prescribed. The percentage of athletes who experienced loss of consciousness (LOC) was also reported because LOC indicates a potentially more severe SRC and is associated with longer recovery than SRCs without LOC (14). Athlete ImPACT (12) baseline testing and post-injury data from the ImPACT test online database was included and used to determine whether athletes had completed a baseline ImPACT test and/or a post-injury ImPACT retest. ImPACT testing comparisons were only included for the trained public and trained private high schools since untrained private high schools either did not use ImPACT or did not grant the UCC access to their records.
Data Analysis Data analysis was performed using R 4.2.2. Athletes sustaining an SRC from MDC public high schools were compared with athletes from private schools between 2012-2022. The eight private schools were particularly selected because they followed a similar protocol and received the same SRC education as the public schools. The other 29 private schools did not receive the training or follow the protocol. For continuous data in the normal distribution like “Age”, mean and standard deviation were reported. For categorical data, such as “Gender”, data was presented as frequency and percentage. For those variables with important clinical significance, such as “Days withheld”, data was reported as median and interquartile range. Propensity score matching was performed to match the public schools with the eight private schools who received similar SRC training. SRC outcomes were therefore compared between trained public and trained private schools before and after matching. This was done to confirm whether one hypothesis, that public and private schools trained on the same SRC protocol would not differ in SRC outcomes, would be true when baseline covariates were and were not controlled for between the groups. Sample T-test was used to detect the significant difference for quantitative data in the normal distribution. The Wilcoxon test was used for quantitative data in non-normal distribution. The Chi-Square test was used to detect significant differences in categorical data. Statistical significance was set at < 0.05.
RESULTS
Participant Demographics A total of 1,088 public, 272 trained private, and 79 untrained private athletes were treated at the UCC during the study period and are included in this study. The average age was similar for each group (16.5 and 16.2). While there were more male than female athletes in all three groups, the percentage of athletes that were female was greater in the trained (38.6%) and untrained (38.0%) private groups than the public group (25.9%). In both the trained and untrained private groups, a greater percentage of athletes were White (28.5% and 25.3%) or Hispanic (62.6% and 68.0%) compared to public athletes (8.0% White, 56.4% Hispanic). The public group instead had a greater percentage of Black athletes (30.9%) than the trained (24.7%) and untrained (6.7%) private groups. Across all three groups, football accounted for the greatest percentage of SRCs but was more prevalent in the public (58.3%) than both private groups (36.4% and 39.2%) (Table 1).
Comparing Trained Public and Trained Private High Schools SRCs Data from trained public and trained private high schools was compared to determine if there were any differences in outcomes between public and private high schools that were trained using the same protocol and program. There were no differences between the groups for days between DOI and first clinic date (P = 0.1), days withheld (P = 0.83), post-injury retest completion (P = 0.06), and RTP (P = 0.30). The average days between DOI and post-injury ImPACT retesting was smaller (P < 0.001) for the public (3 days) than trained private (6 days) group. The public group also had a greater percentage of athletes who completed ImPACT baseline testing (88.5% vs. 80.1%; P < 0.001). The trained private group had a significantly greater percentage of athletes who had academic accommodations (P < 0.001) and experienced LOC (P < 0.001) (Table 2).
After matching, groups had similar demographic characteristics for age, sex, race, grade, and sport (Table 3). Outcomes between the matched groups were also compared, and there were no differences for days between DOI and first clinic date, days withheld, percentage of athletes who completed ImPACT baseline testing and post-injury retesting, and RTP (Table 4). However, average days between DOI and post-injury ImPACT retest was smaller for the public group (4 vs. 6 days, P < 0.001). The public-school group was also more likely to have experienced LOC (P < 0.001) and not receive academic accommodations (P < 0.001).
Comparing Trained Public and Untrained Private High School SRCs Trained public and untrained private groups did not differ in average days between DOI and first clinic date (P = 0.40) or days withheld (P = 0.40). A significantly greater percentage of the public group did RTP (91.9% vs. 81.0%; P = 0.002). More of the athletes in the untrained private group received academic accommodations (P < 0.001) and experienced LOC (P < 0.001) than did the trained public group (Table 5).
Discussion
Understanding risk factors, whether demographical (e.g., sex, age) or injury event-related (e.g., sport, mechanism of injury), that are associated with differences in SRC outcomes are important for ensuring that those most at risk receive proper SRC treatment and resources. One potential risk factor that was explored in this study was whether an athlete was from a public or private high school. Historically, most research on SRC risk and outcomes has been conducted using public high school athletes (4). This study provides further insight into how SRC outcomes between high school athletes differ based on the type of school attended and if a dedicated SRC protocol and education can help mitigate any differences.
While football accounted for the greatest percentage of SRCs in all three groups, its contribution was roughly 20% percent more in the public group than both private groups. Other sports, including soccer, basketball, and volleyball, were more prevalent in both private school groups. The distribution of sport played during the SRC injury event likely differed between public and private groups because private schools offer a variety of sport options, like crew and sailing, that were not available at public schools. This availability may have impacted the popularity of sports and participation numbers as private school athletes had a greater number of sports to choose from.
To our knowledge, there is only one other study (15) that directly compares SRC experiences between public and private schools. In that study, private school athletes were twice as likely to report a history of SRC compared to public school athletes, but there was no difference in RTP timelines between athletes at the different types of school (15). While the current study did not compare history of SRC between school types, analysis was performed to compare rates of RTP. There was no significant difference between the trained public and trained private school groups for RTP percentage or days withheld (Table 2), similar to the other study that concluded no difference in RTP. After matching, there was still no difference in RTP percentage or days withheld between these groups (Table 4). The untrained private group, however, had significantly less athletes RTP than the trained public group (Table 5). The UCC is a specialized concussion program that provides comprehensive SRC management and treatment, but the program also provides continuing education and a standardized protocol to the trained public and private high schools to better identify, manage, and treat athletes with an SRC (11). Athletes at these participating trained high schools potentially benefited from the coordinated and structured care they receive as a result of these trainings and partnerships, which may have led to better RTP outcomes compared to the untrained private group. These results also suggest that SRC outcomes do not necessarily depend on school type and the systematic differences between public and private schools (4, 9), but instead on AT and AD SRC education and if an SRC protocol is in place and being followed. Additionally, these results also indicate the positive effect an available and established SRC program and protocol with clinicians trained on SRC management and treatment can have on SRC outcomes. Another finding was that the trained public and untrained private groups did not differ in average days between DOI and first clinic date (Table 5). Systematic differences in socioeconomics between public and private high schools (9) may explain why the trained public group did not have significantly fewer average days between DOI and first clinic date than the untrained private group, which was the initial hypothesized result. There is well established evidence (16) that supports a relationship between socioeconomics and access to healthcare, and socioeconomic differences between school type may have led to barriers, including transportation, time, and costs, that delayed public athletes from getting into the UCC (17). Yet, there was also no difference between trained public and trained private groups for average days between DOI and first clinic date in both unmatched and matched comparisons (Tables 2 and 4), suggesting that UCC’s partnership with these schools and the flexibility it provides by offering both on-site and virtual appointments may have alleviated any potential differences. These findings also indicate that educating ATs and ADs on the risks of SRCs leads to quicker identification and subsequent appointments.
The percentage of athletes who received academic accommodations after an SRC was significantly greater for both the trained (unmatched and matched) and untrained private school groups compared to the trained public school group. During recovery from an SRC, athletes may have post SRC symptoms that can interfere with their ability to participate and function in the classroom setting (18). Consequently, return to learn protocols and academic accommodations are often provided to the athlete to help reintegrate them into classes but also prevent worsening symptoms (19, 20). Previous research (13) shows that private school students face a particularly high level of academic pressure, potentially due to more rigorous academic programs (9), which could explain why a greater percentage of private groups in this study received more academic accommodations. These additional academic accommodations may have been provided to reduce the burden private group athletes felt about their academic responsibilities or at the request of academic advisors employed at these schools. However, it is important to ensure that all athletes with a sustained SRC receive any appropriate and necessary academic accommodation, regardless of school type attended, to prevent further symptom development.
Limitations This study is not without limitations. All participants in this study were athletes that attended a public or private high school in MDC. Results may not be generalizable to other playing levels, like youth, middle schools, and college, nor to public or private high schools in other counties. Additionally, while other counties may have their own SRC surveillance system, they may not have a program, such as the UConcussion program, that provides ATs with additional SRC training and encourages timely, accurate reporting. A larger sample population in all three groups would have also been beneficial and provided more evidence on the impact of SRC education and protocol on SRC outcomes in the high school setting.
CONCLUSIONS
Public and private high school groups trained on the same SRC protocol did not have significantly different SRC outcomes. The untrained private high school group, however, had worse SRC outcomes compared to the public school group, suggesting that SRC outcomes in the high school setting may benefit from education, training, and an established SRC protocol and program and not on whether the school is public or private.
Applications In Sport
An inherent risk of playing sports is injuries, and SRCs are a particularly concerning injury for high school athletes, especially those playing contact sports. Ensuring those responsible for helping to manage SRCs in high schools are educated about SRCs is important, and a collaborative approach to treating and managing SRCs has been recommended (20). As suggested by this study, all high school personnel involved with athletics should be offered SRC management training and education to help improve outcomes of those that sustain an SRC. Additionally, an SRC protocol, like the Six Steps to Play Safe (11), should be established and can include:
Pre-season baseline testing, using computer-based tests such as ImPACT (12)
Sideline testing after a potential SRC injury (SCAT5, Balance Error Scoring System (BESS), etc.)
Post-testing after a suspected SRC (to compare neurocognitive scores to pre-season baseline tests)
Clinic appointments with a healthcare professional trained in SRC who can evaluate tests and make recommendations
Gradual RTP and return to learn protocol after the athlete has been examined by a professional and is asymptomatic
Injury surveillance system reporting by ATs
ACKNOWLEDGEMENTS The authors would like to thank: Dr. Kaplan and the UHealth Sports Medicine Clinic and Staff, the Division of Athletics and Activities for the Miami-Dade County Public Schools, all Miami-Dade County High School Certified Athletic Trainers, previous UConcussion team members, Dr Kester Nedd who served as medical director of the program from 2012 to 2019, current medical director Dr. Abraham Chileuitt, and The Miami Dolphin Foundation for supporting countywide ImPACT testing and educational workshops. We also want to thank David Goldstein and the Goldstein Family for the development of the Countywide Concussion Care Program and their initial and continued support. The project was supported by the University of Miami Clinical and Translational Science Institute.
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George Minoso2024-03-18T11:04:24-05:00April 5th, 2024|General, Research, Sport Training|Comments Off on Comparing Public vs. Private High School Sports-Related Concussions from a Countywide Concussion Injury Surveillance System
1Department of Economics, San Diego State University, San Diego, CA
Corresponding Author:
Christiana Hilmer, PhD 5500 Campanile Drive San Diego, CA 92182-4485 chilmer@sdsu.edu 619-301-9388
Christiana E. Hilmer, PhD, is a Professor of Economics at San Diego State University in San Diego, CA. Her research interests include the economics of sports, applied econometrics, labor economics, and resource and environmental economics.
An analysis of the factors impacting win percentage and change in win percentage in women’s Division 1 college lacrosse
ABSTRACT
What factors in women’s NCAA Division 1 college lacrosse led to an increase in win percentage in a single season and a change in win percentage across two consecutive seasons? Do these factors differ between teams at the top and the bottom ends of the win distributions? Using data from the 2023 and 2022 lacrosse seasons, we find that goals, assists, unassisted goals, and participation in the NCAA Championship tournament have a positive impact on win percentage, while opponent’s goals and if the team was new in 2023 have a negative impact on win percentage. The most crucial factor that explains the change in win percentage between the 2022 and 2023 lacrosse seasons is an improvement in the change in total shots ratio, while changes in attacking efficiency and defending efficiency are also important, all together explaining 58% of the variation. Teams at the bottom of the distributions have similar characteristics for both win percentage and change in win percentage as those teams in the middle and the top of the distributions, although there are some slight differences in the magnitudes of the statistically significant variables. These results suggest that lacrosse players and coaches should focus on obtaining additional goals and assists while concurrently minimizing the opponent’s goals to increase win percentage and changes in win percentage.
Keywords: distributional impacts, quantile regression, women’s college lacrosse
INTRODUCTION
Since the advent of sabermetrics pioneered by Bill James and the popularity of Lewis’s (5) Moneyball, the use of statistics to analyze sports has exploded in popularity. Reep and Benjamin (7) applied statistical analysis to team-wide factors in soccer where they investigated how the passing skill and position of a player on the field impacts goals. When analyzing a team’s performance, it is essential to determine which factors lead to a team’s success. Most research in this field has focused on professional sports. Busca et al. (1) examine eleven high-stakes international soccer tournaments to determine where a penalty kick is most likely to be struck. Pelechrinis and Winston (6) develop a framework that is comprised of publicly available data to determine the expected contribution of an individual professional soccer player to the probability of his team winning the game. Alberti et. al. (1) examine goal-scoring patterns in four different professional soccer leagues and find that the majority of goals are scored in the second half of the game with the most goals being scored in the last fifteen minutes of play. Castellano et. al. (3) analyze professional soccer match statistics to determine which factors impact winning, drawing, and losing a game and find that shots, shots on goal, and ball possession are important on the offensive end of the field, while total shots received and shots on target received are important on the defensive end of the field. A notable departure from research that focuses on professional soccer is Joslyn et al. (4), who examines the factors that improve the change in win percentage in men’s Division 1 (D1) college soccer. They find that improving shots, attacking, and defending positively impact the change in win percentage between two consecutive seasons.
This research utilizes the tools found in the team-focused literature from soccer and extends it to lacrosse. Soccer and lacrosse have many similarities, especially regarding possession, assists, goals, and defense. There are also marked differences between the two sports in addition to the obvious one: in soccer the ball is kicked while in lacrosse the ball is played with a net attached to a stick. Lacrosse is a higher-scoring game due to the presence of a 90-second shot clock and defending a women’s lacrosse player is more difficult in lacrosse than it is in soccer. One reason for this is that in lacrosse it is a foul to “move into the path of an opponent without giving the opponent a chance to stop or change direction, and causing contact” (page 51, 2022 and 2023 NCAA Women’s Lacrosse Rules Book (6)), while there is no such rule in soccer. Another reason is due to a rule in women’s lacrosse called shooting space (page 54, NCAA 2022 and 2023 Women’s Lacrosse Rules Book (6)), which states that “with any part of one’s body, guarding the goal outside or inside the goal circle so as to obstruct the free space to goal, between the ball and the goal circle, which denies the attack the opportunity to shoot safely and encourages shooting at a player” while soccer does not have a comparable rule. According to NCAA Statistics (7), the average number of goals per game scored in D1 women’s college lacrosse in 2023 was 12, while the average number of goals per game scored in D1 women’s college soccer in 2023 was 1.39. Another notable difference between lacrosse and soccer is that the offside rules are very different. The offsides rule in lacrosse states that there must be at least five defenders behind their defensive restraining line and at least four offensive players behind their offensive restraining line (page 61, NCAA 2022 and 2023 Women’s Lacrosse Rules Book (6)). The offsides rule in soccer is much less stringent and it states that when in the opponent’s half of the field “the player is not closer to the opponent’s end line than at least two opponents” (page 52, NCAA 2022 and 2023 Soccer Rules Book (7)). These disparities between lacrosse and soccer may result in differences in which factors impact win percentages and changes in win percentages.
This research examines which factors lead to an increase in win percentage and change in win percentage for women’s Division 1 college lacrosse teams. We also seek to determine if these factors differ among teams in the 25th, 50th, and 75th percentiles for win percentage and the change in win percentage. Using data from the 2023 women’s D1 college lacrosse season, we explain 86% of the variation in win percentage. Goals, unassisted goals, and participation in the NCAA Championship tournament have a statistically significant positive impact on win percentage, while opponent’s goals and if the team was new in 2023 have a statistically significant negative impact on win percentage. The most crucial factor explaining the change in win percentage between the 2022 and 2023 lacrosse seasons is an improvement in the change in total shots ratio, while changes in attacking efficiency and defending efficiency are also statistically significant, all together explaining 58% of the variation. The variables that explain both win percentage in a single season and the change in win percentage between seasons are similar between the 25th, 50th, and 75th percentiles. This suggests that teams at the bottom of the distributions should focus on the same factors as those at the top when they seek to improve during a season and between seasons.
METHODS
Data Source Win percentage was collected from the National Collegiate Athletic Association (NCAA) archives for the 2023 and 2022 seasons. A win was awarded one point while a loss was awarded zero points. Offensive and defensive statistics for the 2023 and 2022 seasons were collected from each University’s women’s lacrosse website housed in the season’s cumulative statistics. It is important to note that these data are provided by individual institutions and therefore the statistical findings of this research is dependent on the accuracy of the information provided by each school. In addition to winning percentage, data was collected on goals, assists, shots, opponent’s goals, opponent’s shots, unassisted goals, ground balls, turnovers, caused turnovers, draw controls, whether the team was new to NCAA D1 lacrosse in the 2023 season, and if the team made the NCAA Championship tournament in 2023. Of the 126 D1 women’s lacrosse teams, 123 had information on every variable listed above.
Variables and Distributions
This analysis aims to determine what factors impact a single season winning percentage and which factors impact the change in win percentage across two consecutive seasons. Figure 1 is a histogram of win percentage for the 2023 women’s lacrosse season. The average win percentage was close to 50% at 48.27%; the minimum win percentage was 0 for the two teams that lost every game during the season, while the maximum win percentage was from a team that won 95.65% of their games. The team with the second-highest win percentage won the 2023 NCAA National Championship tournament.
Summary statistics for the 2023 D1 women’s lacrosse 2023 season are found in table 1. The average number of goals and opponent’s goals nearly offset each other at 211 and 210, respectively. There was an average of 495 shots with a large standard deviation of 105. Below half the goals were aided by an average of 92 assists, while over half of the goals resulted from an average of 119 unassisted goals. There were nearly twice as many turnovers as there were caused turnovers, 7% or a total of 8 teams were new D1 lacrosse teams in 2023, and 24% of the D1 lacrosse teams made the NCAA end-of-season tournament.
Figure 2 contains a histogram of win percentage change, which is constructed by taking the win percentage in the 2023 lacrosse season and subtracting the win percentage in the 2022 lacrosse season. There are fewer observations in the change in win percentage because the seven teams who were new in the 2023 season did not have any statistics for the 2022 season. On average, most teams had a similar win percentage in 2023 as they did in 2022, with an average change in the win percentage of .16. The team with the lowest change in win percentage between the two seasons of -51.47 had a win percentage of 75% in 2022, dropping to 24% in 2023. At the other end of the spectrum, the team with the highest change in win percentage won 12% of their games in 2022 and improved to winning 50% of their games in 2023.
Following Joyce et al. (4), we construct three measures of team success to explain the change in winning percentage: total shots ratio, attaching scoring efficiency, and defending scoring efficiency. The first measure, total shots ratio, is constructed as
The total shots ratio in both 2022 and 2023 is .5, which means, on average, teams are matching their opponent’s shots with their own shots with a range in values from .23 to .7 in 2023 and .3 to .63 in 2022. This finding for lacrosse compares favorably to what Joyce et al. (4) found for D1 college soccer, where the total shots ratio ranged from .24 to .69 in D1 men’s soccer.
The second measure of team success is attacking scoring efficiently or goals to shots ratio.
The average attaching scoring efficiency for 2023 and 2022 was .42. This measure had a relatively smaller variability than the total shots ratio, with a minimum of around .3 for both years and a maximum of .5 in 2023 to .58 in 2023. This maximum means that the teams with the highest attacking scoring efficiency earn an average of one goal for every two shots. Being able to convert shots into goals is an essential aspect of winning games. Lacrosse teams are much more likely to convert shots into goals, as Joyce et al. (4) found an average attacking scoring efficiency of .1 or 1 goal for every ten shots in D1 men’s soccer.
The third measure of team success is the defending scoring efficiency, which is contracted as
This final measure determines if teams can prevent opponents from turning shots into goals. The average values for defending scoring efficiency are slightly higher than attaching scoring efficiency, with an average of .43 in 2023 and .44 in 2022. The variability is higher for defending scoring efficiency than attacking scoring efficiency, with a minimum of .31 in 2023 and .34 in 2022 and a maximum of .66 in 2023 and .77 in 2022. Teams that are better at preventing shots from being converted into goals typically have a higher win percentage.
Regression Model The first step in our regression analysis is to empirically estimate the degree to which offensive and defensive statistics impact the win percentage for the 2023 lacrosse season. The win percentage regression model takes the form:
where is the error term and i is the individual women’s lacrosse team. This model is estimated using ordinary least squares to obtain the average marginal impact of each of the 11 variables, as well as using quantile regression at the 50th, 25th, and the 75th percentiles of the win percentage. Quantile regression is a statistical method that estimates the association between the explanatory variables for a conditional quantile of the dependent variable, see Walmann (8) for a more detailed explanation. In this application, we use quantile regression to determine if teams at the lower end of the win percentage distributions display different characteristics than those at the median and the top end of the distributions.
The second part of the analysis follows Joyce et. al. (4) to determine what factors impact the change in win percentage between the 2023 and 2022 lacrosse seasons. The regression model is as follows
where ε_i is the error term and i is the individual women’s lacrosse team. As with the individual season analysis, this model is estimated using ordinary linear regression and quantile regression at the 50th, 25th, and 75th percentiles.
RESULTS
Table 3 contains the results for the estimation of equation (4) from the 2023 lacrosse season with robust standard errors in parentheses. Looking first at the results from the ordinary least squares model, 86% of the variation in win percentage is explained by the 11 independent variables. Turning to the variables that are statistically significant, each additional goal results in an increase of .18 in win percentage, while each opponent’s goal results in a decrease of .2 in win percentage, with goals and opponent’s goals nearly offsetting each other. On average, one additional unassisted goal results in an increase of .13 in win percentage. Being a new D1 women’s lacrosse team in 2023 results in a 9 point marginally statistically significant decrease in win percentage relative to teams that have been in the league in previous years. This result suggests that new D1 teams have a difficult time navigating their first year likely due to players and coaches lacking experience and chemistry, making obtaining wins more difficult. Women’s lacrosse teams who participated in the 2023 NCAA Championship Tournament have a statistically significant almost 5 point higher win percentage than those who did not participate in the tournament. This finding is not surprising given that the two ways to get a team into the tournament are to either receive an automatic bid by winning their conference tournament or earn an at-large bid by having a compelling enough record during the regular season and conference playoffs.
The last three columns of table 3 contain quantile regression results at the 50th, 25th, and 75th percentiles of the win percentage distribution. Opponent’s goals are the only statistically significant factor to explain wins across all three percentiles. The magnitude of opponent’s goals is largest at the 25th percentile at -.24 and is -.20 for both the 50th and 75th percentile. Teams at the 25th and 50th percentiles of the win percentage distribution that participates in the NCAA end-of-season tournament has a statistically significant 7 point and 6 point higher win percentage, respectively, relative to those who did not participate, while this variable is not statistically significant at the 75th percentile. This may be because most, 73%, of the tournament participants come from the teams at the top 25% of the win percentage distribution, while most teams at the middle and bottom of the distribution did not participate in the tournament. Aside from this difference, the results are similar between the models at the three points in the win percentage distribution.
Table 4 contains the second part of the regression analysis which estimates equation (5) that attempts to determine what factors impact the change in win percentage between the 2023 and 2022 seasons. The variables contained in this analysis mimic those in Joyce et. al. (4) for men’s D1 college soccer. Looking at the OLS results, teams that had a one unit increase in the change in total shots ratio between the two seasons had a 2.4 increase in the change in win percentage. Teams with a 1 unit increase in the change in attacking efficiency had a 1 unit increase in the change in win percentage, and teams with a one unit increase in the change in defending efficiency decreased the change in win percentage by 1.2 points. The statistical significance between these lacrosse results and those found for soccer by Joslyn et al. (4) are identical, suggesting that even though there are many differences between the two sports, the same factors are important in explaining the change in win percentage between consecutive years. Comparing magnitudes between the two applications is not possible because the estimation methods differed. The statistical significance of the variables included in the quantile regression evaluated at the 50th, 25th, and 75th percentiles were the same as in the OLS regression. The quantile regression performed at the 25th percentile of the change in win percentage had the highest impact for the change in total shots ratio and the change in attacking efficiency, while the change in defending efficiency had the smallest impact. The change in total shots ratio and the change in attacking efficiency had the smallest impact for those teams at the 75th percentile, while the change in defending efficiency had the largest impact for those teams at the 50th percentile. These results suggest that the factors that impact the change in win percentage are similar across teams at the bottom and the top of the change in win percentage distribution, although the marginal impacts differed slightly between the percentiles.
Discussion
It is not surprising that additional goals led to an increase in win percentage and an increase in opponent’s goals led to a decrease in win percentage. However, it was unanticipated that many of the other offensive and defensive statistics included in the regression were not statistically significant. It is likely that these other factors either lead to the team’s ability to score goals, such as shots, ground balls, and caused turnovers, or lead to the opponent’s goals, such as turnovers. One drawback of this research is that it does not investigate how these other factors impact goals and opponent’s goals. One adage in lacrosse is “win the draw, win the game.” Even though draw controls are not statistically significant in explaining win percentage, there was no information contained in the box scores on how many goals were obtained when the team won the draw control or how many goals were conceded when the team lost the draw control. More detailed information would be needed to investigate this relationship further. Other factors that likely explain win percentage and changes in win percentage such as team chemistry, the presence of a star player, the experience of the players and the coaches, and how different game management strategies, such as the usage of substitutes and quickness of play, are not included because they are difficult to measure, not included in the box scores, or both.
For a lacrosse coach or lacrosse player who is looking to improve win percentage between seasons, it is comforting to note that focusing on improving the changes in total shots ratio, attacking scoring efficiency, and becoming better at defending by decreasing the opponent’s goal-to-shot ratio will lead to an increase in the change in win percentage. One major drawback of this research is that it does not point to the factors that cause improvements in these variables and how they feed into additional goals or fewer conceded goals.
CONCLUSIONS
This study is the first to analyze which factors impact win percentage and changes in win percentage for NCAA D1 women’s lacrosse. The regression results suggest that goals, unassisted goals, and those who competed in the NCAA tournament had a positive impact on win percentage, while opponent’s goals and teams that were new in 2023 had a negative impact on win percentage. These factors were similar across the distribution of win percentage at the 25th, 50th, and 75th percentiles. Changes in win percentage between the 2023 and 2022 seasons are positively impacted by the change in the total shots ratio and attacking scoring efficiency and negatively impacted by the change in defending scoring efficiency. Even though there are many differences between lacrosse and soccer, the findings of this research and those of Joyce et. al. (4) that focus on college soccer suggest that the factors that explain changes in win percentage are similar between the two sports. These results also suggest that the statistics that explain win percentage and change in win percentage are similar between teams at the bottom, at the middle, and at the top of the distributions.
Applications In Sport
Women’s lacrosse programs at the collegiate level as well as at the national level can use these results to determine which factors to focus on when attempting to improve their win percentage within a specific year or over the course of several years. This research suggests that teams should emphasize their efforts in practice and in games on factors that increase goals as well as those factors that prevent goals. The lack of empirical analysis at the collegiate level, especially for women’s sports, can be rectified using available data. Additional publicly available information would make individual game analysis more informative such as how winning a draw control impacts goals as well as how focusing on specific factors such as caused turnovers or increasing assists increases goals and therefore positively impacts a team’s chances of winning.
REFERENCES
(1) Alberti, G., Iaia, F. M., Arcelli, E., Cavaggioni, L., Rampinini, E. (2013). Goal scoring patterns in major European soccer leagues. Sport Sciences for Heath, 9(3), 151-153.
(2) Buscà, B., Hileno, R., Nadal, B., & Serna, J. (2022). Prediction of the penalty kick direction in men’s soccer. International Journal of Performance Analysis in Sport, 22(4), 571–582.
(3) Castellano, J., Casamichana, D., Penas, C. (2012). The use of match statistics that discriminate between successful and unsuccessful soccer teams, Journal of Hunan Kinetics, 31, 137-147.
(4) Joslyn, M.R., Joslyn, N. J. & Joslyn, M. R. (2017). What delivers an improved season in men’s college soccer? The relative effects of shots, attacking and defending scoring efficiency on year-to-year change in season win percentage. The Sport Journal, 24, 1-12.
(5) Lewis, M. (2004). Moneyball: The art of winning an unfair game. WW Norton & Company.
(6) NCAA 2022 and 2023 Women’s Lacrosse Rule Book. https://www.usalacrosse.com/sites/default/files/documents/Rules/WLC23.pdf
(7) NCAA 2022 and 2022 Soccer Rules Book. https://www.ncaapublications.com/productdownloads/SO23.pdf
(8) NCAA Statistics, Women’s Lacrosse and Women’s Soccer http://stats.ncaa.org/rankings/conference_trends
(9) Pelechrinis, K., & Winston, W. (2021). A Skellam regression model for quantifying positional value in soccer. Journal of Quantitative Analysis in Sports, 17(3), 187–201.
(10) Reep, C., & Benjamin, B. (1968). Skill and chance in association football. Journal of the Royal Statistical Society. Series A (General), 131(4), 581-585.
(11) Waldmann E. (2018). Quantile regression: A short story on how and why. Statistical Modelling. 18(3-4): 203-218.
George Minoso2024-04-01T07:01:38-05:00March 22nd, 2024|General, Research, Sport Training, Sports Management|Comments Off on An analysis of the factors impacting win percentage and change in win percentage in women’s Division 1 college lacrosse
1K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing,
Corresponding Author:
K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway, PB 8905, N-7491 Trondheim, Norway karsten.ovretveit@ntnu.no
Karsten Øvretveit, MSc3, is a physiologist and PhD candidate at the Norwegian University of Science and Technology (NTNU). His research areas include genetic disease risk, physical performance, motivational dynamics, and human nutrition.
Can there be two speeds in a clean peloton? Performance strategies in modern road cycling
ABSTRACT
In the history of professional cycling, riders have always sought competitive advantages. Throughout 20th century, many relied on performance-enhancing drugs (PEDs) which gave rise to a phenomenon called “two-speed cycling”. Throughout its modern era, professional cycling has seen anti-doping efforts repeatedly intensify on the heels of several large doping scandals. Over the past decade, the sport appears to have transitioned away from large-scale systematic doping and towards novel, legal performance-enhancing strategies, facilitated by a close relationship with scientific, technological, and engineering communities. The tools and technologies available to assess the demands of the sport, the capabilities of the riders, and the role of environmental factors such as wind resistance, altitude, and heat are more refined and comprehensive than ever. Teams and riders are now able to leverage these to improve training, recovery, equipment, race tactics and more, often from a very early age. This review explores several key developments in road cycling and their implications for the modern professional peloton.
Key Words: professional cycling; performance-enhancing drugs; marginal gains; performance analysis
INTRODUCTION
The main pack of riders navigating the road in a cycling race, known as the peloton, comprises a wide range of physiological, anthropometrical, technical, and strategical attributes. The role of each rider in a given race is typically based on strengths, weaknesses, and objectives, and can be modified by injuries, fitness level, personal goals, and unexpected in-race developments. The concept of “cycling at two speeds”, cyclisme à deux vitesses, has historically been used to distinguish between chemically enhanced riders and those who ride clean (134). However, despite increasingly stringent doping controls in professional cycling along with a clear shift in doping culture, the concept of two-speed cycling remains. Given the well-documented benefits of performance-enhancing drugs (PEDs), there is an expectation that the intensification of anti-doping measures in professional cycling leads to more homogeneous performance levels in the peloton by reducing the number of artificially enhanced riders. Although this may be a reasonable assumption, it discounts the many substantial advances made in training, nutrition, technology, and strategy, as well as the growing talent pool of potential professionals and the early age at which they begin to seriously structure their training, racing, and recovery. These factors can differ greatly between teams and individual riders and thus help maintain the two-speed phenomenon. This review provides a brief history of the PED culture and use in professional cycling, followed by an examination of some of the key developments in the sport that has helped preserve the two-speed phenomenon in a peloton riding within an increasingly strict anti-doping framework.
The performance-enhanced past of the peloton
Drugs have been used to enhance athletic performance for millennia, stretching back to at least the ancient Olympic Games (16). Cycling as a profession emerged among working-class men who likened endurance sports to physically demanding jobs where the use of drugs to aid performance was considered the right thing to do (58). Indeed, doping has been pervasive in professional cycling for over 150 years, throughout most of which it was either legal or not subject to testing (34). For decades, riders doped to simply be able to do the job – faire le métier (33). Then, athlete health became a concern and a major driving force to regulate, if not outright ban the use of certain substances. Drug testing in the Tour de France (TdF), the most prestigious event on the race calendar, began in 1966. Despite this, amphetamines, cortisone, and steroids remained widespread in the professional peloton. It was also around this time that rumors about the use of blood transfusions in athletes began (60). The year after Raymond Poulidor underwent the first drug test in the TdF, Tom Simpson collapsed on the ascent of Mount Ventoux and later passed away due to an unfortunate combination of alcohol, amphetamines, intense heat, and extreme physical exertion. Although this event brought more attention to the use of stimulants and other drugs in cycling and in sports in general (69), doping would persist for decades to follow. Based on interviews with riders on a professional cycling team at the turn of the millennium, psychiatrist Jean-Christophe Seznec (115) asserted that professional cyclists are not only prone to develop an addiction to PEDs, but also recreational drugs, noting the importance of explicitly acknowledging this risk in order to mitigate it.
When professional cycling entered the 90s, the banned yet at that time undetectable erythropoiesis-stimulating agent (ESA) recombinant human erythropoietin (rHuEPO) arrived in the peloton (101), and performances hit a new level. Increasing circulating erythropoietin (EPO) by illegal means has been perceived by some riders and coaches to give an estimated performance boost, without the term “performance” being strictly defined, of 3% to 20% (31, 100, 134, 138). Interestingly, despite its popularity in the peloton, the research literature on the effects of ESAs such as rHuEPO on endurance performance is equivocal. Its effects on hematological values like hemoglobin concentration ([Hb]) and clinical measurements of power and maximal oxygen uptake (V̇O2max) are well-established, but the real-world benefits are not always clear (116, 123).
There are several aspects of professional cycling that are difficult to account for in experimental studies on exogenous EPO, such as the extremely high fitness level of a peaked professional cyclist and the physiological impact of training and racing on parameters such as Hb. A recent randomized controlled trial found no apparent benefit of EPO on relevant performance markers has sometimes been cited to shed doubt on the true effects of the drug (47). However, this study was done in cyclists with an average V̇O2max of 55.6 mL/kg/min, which is substantially lower than their professional counterparts (124). By his own account, former professional Michael Rasmussen saw his hematocrit (Hct) drop from 41% to 36% following the 2002 Giro d’Italia (98), illustrating how blood composition can be severely perturbed by training and racing. Similar values have been observed in other professionals following participation in Grand Tours (17, 89). Using Rasmussen as an example, using rHuEPO to bring this up to 49%, just below the old 50% limit, would represent a relative Hct increase of 36% and result in improved ability to maintain a much higher intensity in training and racing, and consequently greater exercise-induced adaptations.
Throughout the 90s, Grand Tour riders with supraphysiological Hct would traverse France, Italy, and Spain at impressive speeds until it all seemingly came to an end in 1998. Three days before the start of the 85th edition of the TdF, a Festina team car carrying various PEDs was stopped by customs agents at the French-Belgian border. This event marked the start of what later became known as the Festina affair, a major catalyst in cycling’s transition to a cleaner sport. The wake of this scandal saw an increasing number of calls to action against doping, including by the driver of the Festina car (132), with claims of the sport dying unless drastic action is taken. Subsequent large-scale doping cases such as Operación Puerto and the contents of the USADA’s Reasoned Decision Report (10) served as reminders that PEDs were still present in the peloton and strengthened the resolve of those fighting for a cleaner sport. Although riders are often blamed for the pervasive drug use in cycling, most entered a sport with a lack of top-down anti-doping efforts, leaving them with the difficult choice of either conforming to the culture or competing on unequal terms. One of the most crucial steps towards a cleaner sport is a change in culture among teams and riders. Much, if not most, of the credit should go to the riders themselves, many of which have actively pushed against the use of PEDs for years (46, 50, 59, 85, 130). Today, most doping cases in cycling are among semi-professional riders, whereas the number of riders testing positive at the highest level is approaching zero (88).
Although absence of evidence is not evidence of absence, fewer doping cases at the highest level of cycling suggests that overt, systematic drug use is a thing of the past. Given professional cycling’s checkered history, it would be naïve to think that doping has been eliminated entirely, but the sport does appear to have evolved beyond doping being perceived as all but necessary to gain entry into the professional peloton. Generational shifts not only among riders, but also among governing bodies and team leadership have contributed to an overall firmer stance against doping, removing potentially significant contributors to anti-doping violations (6). There is also indications that the post-Armstrong generation, especially those who started their careers young, are less likely to use PEDs (5), although the evidence is equivocal (64). Additionally, anti-doping technology continues to improve, with recent advances such as gene expression analysis being able to extend the detection window of blood manipulations (28, 133).
Conceptual approaches to legal performance development
It could be argued that the extraordinary performances regularly being on display by the current generation of riders suggest that the dismantling of systematic doping practices has led to progression rather than regression of the sport of cycling. The transition away from prevalent PED use has forced teams and riders to seek out other areas of improvement, some with barely measurable effects, to keep up. Although seeking improvements in many areas is not a new phenomenon in professional cycling, it has received increasing attention over the past decade with the success of Team Sky, now INEOS Grenadiers, and team director, Dave Brailsford, who called this concept “marginal gains”. Brailsford and his team set out to win the TdF within five years with a clean British rider (29). To achieve this, he brought with him the approach he used as a performance director for British Cycling, which had led to considerable success in track cycling. Team Sky was established on the back of British dominance in the Laoshan velodrome during the 2008 Beijing Olympics, where they took home seven gold medals. As he transitioned from the track to the road, Brailsford brought the idea that compiling enough marginal gains could provide a greater performance advantage than PEDs (87).
Although the marginal gain concept came to prominence with Team Sky during one of professional cycling’s most recent avowed shift from banned to legal performance-enhancing strategies, it has been practiced by cyclists since at least the mid-1900s. Italian Fausto Coppi, who rode to multiple victories in the TdF and Giro d’Italia, as well as in one-day classics throughout the 40s and early 50s, was an early adopter of novel diet and training approaches. After World War II, the sport of cycling was anything but advanced and Coppi set out to change that. He worked with Bianchi to develop bikes and other equipment; he adapted his diet to better fuel his riding – not only its contents, but also the timing and amount; and he explored strategies for how to best race as a team (37). Some of these developments would later influence other greats, such as Eddie Merckx, who, among other things, was obsessed with proper bike fit (38). Current director of the French national team, Cyrille Guimard, has also long been known for his application of cutting-edge technology and training methods. One of his former riders, Laurent Fignon, described him as being “right up-to-date. He had files for everything. He was interested in all the lates training methods. Where his protégés were concerned, he would look at the very last detail and even the slightest defect would be corrected. He knew how to ensure everyone had the very best equipment that was on the market: made-to-measure bikes, the newest gadgets.” (32, p. 56).
The notion that modern riders can surpass past performances solely through legal performance strategies rests on the assumption that these strategies, particularly when combined, are highly effective. Furthermore, a larger pool of athletes and an earlier onset of structured athletic development might amplify these effects. The following section explores the degree of improvement that can be made in the areas of training, nutrition, and technology.
There is not a single anthropometric or physiological characteristic that is completely uniform across high-level cyclists (65, 111). Those with elite potential tend to have stand-out absolute measurements of aerobic fitness and power, but these are attributes that can also be found in cyclists of lower caliber. Elite riders also possess very high power-to-weigh ratios, typically expressed as watts per kilogram (W/kg). An emerging concept that may also distinguish riders of different caliber is durability, i.e., the point and degree of physiological decline during extended exercise (66, 79, 80). Laboratory measurements of key performance determinants such as power-to-weigh ratio, V̇O2max, cycling economy, critical power, and peak power output provide a detailed physiological profile of each individual rider but cannot accurately predict real-life performance.
Training Strategies
Aided by technology, experience, and insights from a growing body of research, training is more refined, structured, and supervised than before, with most, if not all, training sessions serving a specific purpose. Each rider typically follows an individualized training plan that is carried out under comprehensive monitoring of variables such as heart rate, power output, climate, and terrain. These data, along with laboratory measurements, race outcomes, and even psychological variables, are used to adjust volume, frequency, intensity, and/or modality throughout the season. This allows each rider to absorb as much recoverable training volume as possible to optimize physiological adaptations and peak repeatedly for competition while avoiding overtraining. Whereas virtually every single pedal stroke of the modern rider is quantified and analyzed to guide training, racing, and recovery, riders of the past relied more on “feel”, often opting for subjective rather than objective measurements of output. During the 1987 TdF, Laurent Fignon declared his legs to be “functioning again, more or less”, but did not see the value in monitoring his heart rate, explaining that “I lost my temper with those blasted pulse monitors: I handed mine back so that it wouldn’t tell me anything anymore” (32, p. 182).
Although W/kg is often favored as an indicator of riding capacity and a way to quantify cycling performances, a large V̇O2max has long been considered a basic requirement of entry into the professional peloton. Values reported for GC contenders are generally comparable between generations, with the lowest value found in the most dominant TdF rider of all time, albeit with an asterisk (table 1). There are a few caveats to these numbers, such as the validity of the actual measurement, most of which are not described in the research literature but rather in media. Moreover, oxygen uptake does not increase in proportion to body mass and scaling V̇O2max to whole body mass is thus not appropriate when comparing athletes of different body sizes (71). Although some of these values may be exacerbated by PED use, both the baseline level and plasticity of V̇O2max are under considerable genetic influence (15, 86, 135), and WorldTour levels can be reached without doping in those with sufficient genetic predisposition and appropriate stimulus.
Interestingly, there seems to be a physiological trade-off between efficiency and power, where adaptations towards the latter may attenuate the former (72, 113). This phenomenon was observed in Norwegian cyclist, Oskar Svendsen, who once had the highest V̇O2max ever recorded. Svendsen showed promise early by becoming junior time trial champion with less than three years of training and placing high in Tour de l’Avenir. However, despite an incredible V̇O2max of 96.7 ml/kg/min at 18 years of age, Svendsen never became a WorldTour rider. Although his early retirement at age 20 left his potential at the elite level largely unexplored, the reduction in cycling economy he experienced with increased training load could have been resolved as he matured as a rider, as cyclists appear to become more efficient over the span of their careers with little change in V̇O2max (112). If he remained active, Svendsen may eventually have been able to exploit his incredible baseline to reach the proverbial second speed in the modern peloton without chemical assistance. These insights into Svendsen’s physiological profile not only reveal some of the physiological complexities involved in high-level endurance performance, but also serve as an example of the scientific resources available to modern teams and riders that allows for a level of detail in the assessment and follow-up of athletes never seen before at that level of the sport.
Among the many training-related advances in the modern era is a more systematic approach to altitude training. Altitude-mediated erythropoiesis has long been recognized as an exposure that can produce adaptations that improves performance at sea level, as well as acclimatize athletes to sustain performance in hypobaric conditions. There are several ways to approach altitude training and care should be taken to avoid carrying the detrimental effects of prolonged hypoxic exposure, such as reduced cardiac output (Q̇) due to hypovolemia (117), into competition. Today, professional cycling teams rely on both experience as well as past and emerging research to use altitude as an important preparatory measure in various parts of the season. As the individual responses to hypoxic conditions can vary greatly (93), a large hematological response following real or simulated altitude exposure is an important attribute in modern riders. If done properly, altitude training can induce comparable hematological changes to rHuEPO use (table 2), making it a crucial performance-enhancing strategy in the modern peloton. Increasing [Hb] not only improves V̇O2max by improving the oxygen-carrying capacity of blood (43), it also enables sustained work at a higher fraction of maximal capacity (40) and faster V̇O2 kinetics (18), which can be hugely influential in a peloton with limited interindividual difference in V̇O2max.
A more recent strategy to legally induce hematological adaptations is heat acclimation. Prolonged exposure to heat is associated with both increased plasma volume, which can improve stroke volume and consequently Q̇ and V̇O2max, as well as an expansion of total hemoglobin mass (Hbmass) (91). In fact, light exercise in a heated environment five times per week has been shown to increase Hbmass by 3% – 11% in endurance athletes (90, 103, 107). Due to the logistical challenges and cost related to with altitude camp designs such as live high-train low, heat acclimation training may offer a more accessible strategy for riders and teams with less resources, or an additional stimulus to regular stays at altitude. The mechanistic similarities between synthetic and natural causes of erythropoiesis makes it physiologically possible to harness the benefits of EPO without doping. Voet (132) recounts that pre-scandal Festina riders did not even bring EPO to altitude camps because it was going to be “useless”. Describing his first stay at altitude, formerly enhanced rider, Thomas Dekker, wrote that “[t]he altitude works its magic: the thin air jolts my body into producing extra red blood cells and the Swiss Tour is the first race in ages where I can stay with the pace on the climbs” (25, p. 135), expressing relief that he could hang with the peloton without PEDs. Michele Ferrari, Lance Armstrong’s coach during the height of his career, argues that the effects of EPO on hemoglobin concentration can be achieved through proper altitude training alone (31).
Every rider in the professional peloton possesses rare abilities as cyclists. Given that the sport selects for individuals with above average baseline values of [Hb] and Hct, it may not take much stimulus to maintain a high level. However, compared to simply administering rHuEPO, strategies such as altitude training and heat acclimation are more complex undertakings, partly because of potential drawbacks with that must be accounted for, such as transiently reduced Q̇ and altered dietary requirements. The financial cost associated with prolonged exposure to altitude and/or heat for a professional team is also a considerable barrier, as the finances of teams can differ greatly. In some cases, PED use might simply just be more practical than legal strategies, and not necessarily more powerful.
Improving oxygen delivery and utilization have been main training targets for cyclists throughout most of its history, while resistance training (RT) has been largely neglected. As the impact of both power output and oxygen consumption on cycling performance is intrinsically related to rider weight, maintaining a low body mass has been, and still is, imperative. However, RT with an emphasis on neural adaptations can substantially improve force-generating capacity and reduce the oxygen cost of exercise in athletes without adding unnecessary bulk (51-53, 140). It also helps maintain bone mineral density, which elite cyclists are prone to lose (48, 110). A recent study found that RT with traditional movements and individualized load improved bone mineral density and endurance performance in professional cyclists (126). Moreover, it appeared to improve strength, power, and body composition to a greater degree than short sprint training, a more traditional power training modality for cyclists, supporting the role of structured RT as a part of a professional cyclists overall training program. Indeed, evidence for the benefit of RT on cycling performance has been mounting over the past years (table 3) (62, 102, 104-106, 108, 109, 120, 131, 141). This has contributed to changing the way RT is perceived and applied in the.
An elite physiology is easier to perturb than improve. At the highest level of cycling, large adaptations to training are unlikely to occur in the short term. The full, natural potential of a rider can only be reached via the cumulative effects of proper training and recovery, both of which are highly dependent on proper fueling. Nutrition, body composition, and supplementation
In Jørgen Leth’s classic documentary, “A Sunday in Hell”, Roger De Vlaeminck can be seen consuming a plate of meat with his team before setting out to defend his multiple Paris–Roubaix victories from the previous years in the 1976 edition, with the narrator explaining that “a rare steak is a good breakfast for what lies ahead” (67). This is in stark contrast to the low-residue diet often consumed by riders in the modern peloton (39). A low-residue diet is characterized by a very low fiber content, which can reduce rider weight and consequently improve race performance (36). This diet is usually combined with a very high carbohydrate intake throughout a race to ensure constant glucose availability, and the reduced satiety that can be associated with low-residue diets may even help a rider maintain energy intake during a race. The exact amount differs between riders, with numbers around 100 g of carbohydrate per hour being a rough estimate that may be exceeded considerably on hard days. The recognition of the added performance benefit of increased carbohydrate intake has given rise to the concept of gut training for athletes (56, 78). Racing hard for hours on end for multiple consecutive days with limited glucose availability is guaranteed to hamper performance compared to a well-fueled athlete; as red blood cells do not convert to adenosine triphosphate; blood doping cannot replace bioenergetic fuel.
There are some examples of riders that leveraged nutrition to increase their performance throughout history, such as Fausto Coppi (37), but in the modern era, all riders pay attention and have access to both nutritionists and chefs, both of which are roles that have become integral parts of professional teams. Riders also have access to more knowledge and tools, such as food apps powered by machine learning (121). The days of training hard during the day following by alcohol consumption in the evening and racing on the weekends are gone, but were reportedly common until fairly recently (25, 54). The culmination of evidence- and experience-based diets in professional cycling has led to better fueling strategies and lower body mass in the peloton and perhaps especially among the best riders.
Although described as “thin as rakes” (132, p. 63), the riders of the 90s were heavy by today’s standard. Laurent Fignon (32) explains that the importance of power-to-weight ratio did not become known among the riders before the mid-80s and that he, until that point, paid little attention to diet. Looking at the top 10 finishers of the TdF for the past four decades, starting with the latest edition, suggest that it is becoming more and more of a requirement for the overall GC placing (table 4). Notably, between 1992 and 2022, the average BMI of the top 10 decreased by 8.1%. This trend seems to generally hold across all Grand Tours for the past decades (118).
Supplements such as creatine and beta-alanine have been shown to improve endurance performance, including in cycling (7, 12, 21, 49, 127, 128). Creatine was introduced to the peloton in the mid-90s but was very expensive at the time. Riders who had access to it could consume up to 30 g the day before a long time trial or a mountain stage in hopes of a performance boost (132). Creatine and beta-alanine are now both affordable and widely used, alongside other supplements such as caffeine, electrolytes, nitrates, various vitamins, and minerals, as well as macronutrient supplements such as protein and carbohydrate.
In recent years, a lot of attention has been devoted to exogenous ketones. It is a contentious supplement that has been embraced some of the strongest teams while being recommended against by the Union Cycliste Internationale (UCI) and the Movement for Credible Cycling (MPCC). Ketones, or ketone bodies, are acetyl-CoA-derived metabolites that are produced by the liver under conditions with reduced glucose availability, such as low-carbohydrate diets, fasting, and during or after hard exercise. Ketone bodies such as β-hydroxybutyrate can spare glycogen by inhibiting glycolysis and acting as an alternative fuel in oxidative phosphorylation, which in turn can improve endurance (19). As with the research on other legal and illegal enhancement strategies, the degree to which exogenous ketones translates to improved exercise performance remains to be fully elucidated (24, 92, 94, 96, 125, 139). Although there may be potential drawbacks with isolated ketone supplementation (82), in conjunction with sodium bicarbonate, which is a weak base that has been used for some time in endurance sports (45), ketone supplementation has been shown to improve power output towards the end of a race simulation by 5% (95), although this effect may be unreliable and warrants further study (97).
Much of the hype surrounding some of the proposed effect of ketones as an energy substrate appears unwarranted, but emerging evidence suggest that it may have intriguing properties as a signaling molecule. A few years ago, it was shown that infusion of ketone bodies increased circulating EPO levels in healthy adults (63). The impact of ketones on EPO is supported by the observation that adherence to a ketogenic diet can increase [Hb] and Hct by ~3%, with the caveat this effect is within the biological variation of these markers (83). Recently, Evans et al. (30) found that ingestion of ketone monoester after cycling exercise increased serum EPO concentration, providing further evidence that it may be the signaling effects rather than nutritional value of ketone supplements confers the greatest performance benefit for professional cyclists.
Technology and equipment Science tends to be reductionistic by necessity, whereas a cycling race is much more open-ended. There is, however, a certain cycling event that is performed in highly controlled conditions and relies heavily on technological advances that can serves as a good example of marginal gains in modern road cycling: the hour record. In 1972, Eddy Merckx, perhaps the greatest cyclist of all time, rode a distance of 49.431 km to set a new hour record for the first time since the 1950s. Twelve years later, Francesco Moser breached 50 km with an effort totaling 51.151 km, aided by disc wheels and a skin suit. The following years would see various innovative approaches by riders such as Graeme Obree and Chris Boardman, until the UCI decided to revise the rules in 1994 and again in 2014 (table 5). To set his records, Boardman worked closely with Brailsford’s predecessor in British Cycling, Peter Keen, and then later with Brailsford himself after his retirement, on what would be the beginning of British riders’ marginal gains on the track and later in the peloton (14).
From Voigt’s first attempt to Ganna’s latest, the modern hour record has been improved by over 11%. Although Ganna is a multiple World Time Trial champion and likely one of the most suitable riders to attempt the record, the last person to hold the record before him was Daniel Bigham, the only rider on the list that was never a WorldTour rider. Although an accomplished cyclist in his own right, Bigham’s record is a prime example of how far and fast you can get by maximizing the margins, with his record being set at an average power output approximately 100 watts less than Wiggins. Bigham himself puts his performance down to 50% physiology and 50% equipment (137). One of the main aspects Bigham exploited was aerodynamics; his coefficient of aerodynamic drag (CdA) was ~0.15, which is considerably below what is commonly seen in cyclists, including professionals (41).
Aerodynamics is not only relevant when riding fast around a velodrome for an hour, but also one of the most important things to consider when trying to ride fast on a bike in general. At a riding speed of about 54 km/h, close to the average on a flat TdF stage, approximately 90% of the total resistance is aerodynamic resistance (13, 44). Most of the resistance is caused by the rider himself, with common estimates ranging from 60-82% (74), and the rest by other factors such as equipment (22, 73, 77). The importance of minimizing CdA underlies much of the development of modern bike frames, wheels, handlebars, helmets, clothing, and more. In recent years, there has been less emphasis from manufacturers on getting their bikes down to the UCI weight limit of 6.8 kg in favor of more aerodynamic optimizations. This approach is supported by findings showing that simply opting for aerodynamic rather than light wheels will reduce climbing time on 3% – 6% grade hills (57). Steeper hills favor lighter wheels and WorldTour riders often make specific selections of wheelset, gear ratio, and even frameset based on race or stage profile. Some teams take it a step further, such as Jumbo-Visma, who use a portable aero sensor to measure exact wind conditions on race day and make equipment selections accordingly (81).
Since the inception of professional cycling there have been numerous technological advances and there is still a steady flow of innovations reaching the peloton. Some of these become widely adopted, such as aero-optimized gear; some are providing new alternatives without replacing old ones, such as tubeless tires (riders still use a variety of tubed, tubeless, and tubular tires); and others are replacing without immediately improving a function, such as disc brakes. Technology has also enabled more extensive monitoring of athletes, both on and more recently off the bike. For instance, several teams are now measuring body temperature and hydration status, and by analyzing the individual sodium composition sweat, can select the appropriate supplementary amount of sodium for each rider. During very hot days, riders are often seen wearing cooling gear to keep body temperature down. This can not only keep the riders comfortable, but may also benefit their performance in the race by lowering thermal strain (75).
Although professional cycling continues to benefit from science, technology, and engineering, the UCI have rules and regulations in place that ensures that cycling does not, for better or worse, stray too far away from its origins. Although these are subject to change based on new developments, they sometimes can become more restrictive, such as the recent ban on handlebars narrower than 350mm. Riders with the ability and resources to combine effective performance strategies from training, nutrition, recovery, and technology – perhaps especially strategies with small effects that are more likely to be ignored by others – may find themselves able to ride at a different speed than the rest of the peloton.
Merging the margins
Imagine a gifted and durable athlete with an exceptional ability to consume oxygen across all intensity domains, maintain a low body mass, effectively utilize lactate, absorb and recover from a high training load without injury or illness, handle training and race nutrition, thermoregulate in various climates, and respond well to altitude and heat exposure finding his or her way into cycling early in life. Suppose this young cyclist learns to maintain an aerodynamic position on the bike, pedal with an efficient cadence, move seamlessly through the peloton, avoid accidents, calmly handle the pressure of competition, and execute winning moves. Professional cycling selects for individuals with supraphysiological potential from environments that have allowed this potential to be expressed. Then, it awards those who have made it to the starting line and are able make as many performance determinants as possible come together on race day.
Increased professionalism at the highest level of the sport trickles down to the amateur and junior ranks, exposing up-and-coming cyclists to favorable conditions at an earlier age, leading to greater improvements in physiology, psychology, and race craft. Some riders may show incredible promise in some aspects of racing and struggle with others. Oskar Svendsen, V̇O2max world record holder, undoubtedly had one of the greatest physiological potentials ever seen in a rider. However, he admittedly also had technical and tactical challenges: “Cycling is a monotonous sport, yet so complex and driven by tactics that you won’t win races unless you deliver on all those qualities. I came into the sport with good physical qualities, but I struggled most with the tactics and patterns. I did learn a lot in my senior years on Team Joker though, even if I still had a long way to go. Descending down hills was also something I struggled a lot with, and it sapped much of my energy in races.” (99) Svendsen’s career serves as an example of how cycling is not only a physiological sport, but also technical, tactical, and psychological. Recently retired rider, Richie Porte, described former TdF GC winners Chris Froome and Tadej Pogačar as “psychological beasts” and noted that cycling has become increasingly scientific, which does not suit all riders (35). Modern riders are more methodical, data driven, and regimented than before. This reduces the human element of the sport, to the dismay of those claiming that this will increase predictability. Some researchers in the field have also warned against measuring just for the sake of measuring, and advise that rider data should serve a specific purpose (55).
The widely established routine of constant fueling during training and racing not only acutely increase work capacity but also improves subsequent recovery by preventing the rider from becoming completely depleted. This is in stark contrast to the days when reaching for your bottle during a hard training ride, even if it only contained water, was considered a weakness. Paul Köchli, former coach of riders such as Bernard Hinault and Greg Lemond, once said that the art of cycling is to do the right thing at the right moment (27). This is true not only in the context of a race, but indeed for the professional cyclist’s career as a whole. The effects of proper training, nutrition, and recovery accumulate not only throughout a season, but a whole career, benefitting those who consistently do the right things from early on.
Conclusion and future perspectives
In some ways, modern approaches to improving cycling performance represent a first principles approach to cycling and a fundamental challenge of conventions, within the rules and regulations of UCI. It seems to have restored some of the faith in the sport that was once lost with various doping scandals. Given the measurable impacts of legal performance-enhancing strategies, many of which were previously unknown or overlooked, it could be argued that combining these effects can bring a clean rider’s performance close to, or even surpass, that of an enhanced cyclist, assuming a gifted baseline and sufficient degree of adaptability.
Suggesting that it is possible to win at the highest level in cycling without the use of PEDs is not the same as claiming that the sport is completely clean. As others have pointed out, periods that have previously been perceived as clean have later been shown to be anything but (26). This paper covers some of the key legal advances in road cycling that has contributed to elite performances in the modern peloton, while at the same time acknowledging that illegal strategies may still be present.
Much of what was once considered “marginal gains” have now become common in all professional cycling teams. This represents a shift from a culture of doping to a culture of exhaustive continuous improvement, a lot of which is kept under wraps and some that may even be considered a grey area. Effective anti-doping measures contribute to a more level playing field, but not entirely level. The teams with the most resources often get the most talented riders, allowing them to combine the greatest potential with the best strategies. And even still, there are some who favor optimizing riders and their equipment for weight rather than aerodynamics, ignoring the latter to the extent that it becomes a considerable detriment. In an era of professional cycling where individual performances are influenced by a multitude of human and nonhuman factors, which in combination can have profound effects, the existence of two-speed cycling in a clean peloton is not only logical – it should be expected.
Acknowledgments
This work was supported by the Norwegian University of Science and Technology (NTNU). The author would like to thank Dr. Endre T. Nesse and Dr. Fabio G. Laginestra for their comments and feedback on the manuscript.
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Authors: Dr. James A. Reid1, Todd Schaneville2, and Trey Schaneville3
1Assistant Professor of Physical Education, Tuskegee University, Tuskegee, AL, USA 2Physical Educator and Coach, Brevard Public Schools, Viera, FL, USA 3Graduate Student-Athlete, Appalachian State University, Boone, NC, USA
Corresponding Author:
James A. Reid, DA, NSCA, CSCS and CPT 509 Greentree Ter Auburn, Alabama 36832 jreid@tuskegee.edu 256-690-3581
University. Dr. Reid has been teaching exercise science and physical education in higher education since 2001. Dr. Reid was a place-kicker and punter at Tulane University and Auburn University. He played three years of semi-professional football as well. While serving as Assistant Professor in the Department of Health and Human Performance at the University of Tennessee at Martin, he served as a volunteer kicking coach for the football team. Dr. Reid also has worked as a kicking coach with Feely Kicking School in Tampa, Florida.
Strength and Conditioning Practices among NCAA Place-Kickers
ABSTRACT
The purpose of this study was to examine the strength and conditioning practices of NCAA Division I and II starting place-kickers. The hope is that this information will be valuable to football coaches and strength and conditioning professionals who oversee the offseason regiments of kickers. The researchers investigated the strength and conditioning practices over nine different categories of exercises. The instrumentation used was a survey, and the subjects were fifteen starting NCAA place-kickers at the Division I and II levels. The survey format was divided into nine sections, and respondents were asked to indicate any exercise from a list that the athlete performs regularly during off-season training. The findings from this research study show that there are a few exercise categories that seem to be used more frequently than others and that certain exercises provide greater benefits to a place-kicker’s performance. One hundred percent of respondents reported that they utilize the following exercise categories: core strength and endurance, assistance strength and endurance, power lifts, speed and agility, and flexibility. However, for place-kickers, flexibility and plyometric exercises seem to be the most beneficial for this specific type of athlete. This is most likely due to their need for explosive strength and power, as well as improved range of motion during kicking.
Authors: Joni M. Boyd, Ashley M. Andrews, Janet R. Wojcik, & Charles J. Bowers
Corresponding Author:
Joni M. Boyd, PhD
Winthrop University
216L West Center
Rock Hill, SC 29733
boydj@winthrop.edu
803-323-4936
Joni Boyd is an Assistant Professor of Exercise Science in the Department of Physical Education, Sport, and Human Performance at Winthrop University in Rock Hill, South Carolina.
ABSTRACT
Understanding the beliefs and attitudes of student athletes (at all levels) in regards to their perception of their strength and conditioning programs is pivotal to an effective program. Therefore, the purpose of this study was to determine the perceptions regarding the impact of strength training of student athletes at a mid-major Division I university. This study employed a cross-sectional descriptive design using a volunteer sample of 123 college student athletes from a Division I university. Surveys measured student athletes’ perceptions on the importance of strength training in relation to sport-specific training. Results showed no significant differences in perceptions of strength training between genders or class rank. Significant differences were evident between the sports surveyed, specifically noting that some sports (baseball, track and field) felt their strength training program was more beneficial to their performance than other sports (softball, men’s soccer). These results show the differences in some athletes’ beliefs and perceptions regarding their strength training program, which could ultimately hinder results. The strength and conditioning professional can use this information to educate and monitor certain athletes or sports that may not feel their strength program is effective to enhancing performance.
