Using sport science data in collegiate athletics: Coaches’ perspectives

Abstract

Limited research has examined American collegiate coaches’ perceptions of collecting data for informing training practices. The purpose of this study was to examine collegiate coaches’ perspectives and needs for collecting data from their athletes using a qualitative approach. Four focus groups were conducted with NCAA Division I coaches (N = 13) at a mid-sized liberal arts university. Coaches were asked how they could benefit from collecting data from their athletes, how they would use the data to answer questions about athletes’ performance, what data they would want to collect, and what concerns they had regarding data collection. Principles of thematic analysis were used to analyze the interviews. Most coaches (54%) felt that collecting data would provide evidence needed to support training methodologies, and they would benefit (i.e. make improvements to coaching and athlete training) from monitoring progress in their athletes (61%). Regarding performance questions, coaches were interested in utilizing a biomechanist to conduct movement analyses (23%) and assessing athletes’ mental and emotional states (23%). Coaches wanted to monitor athletes’ fatigue, recovery, mental health states, and health behaviors (i.e. sleep and diet; 15%). Coaches expressed concerns over finding an optimal time to test athletes (8%) and effective presentation of data to athletes (23%) while limiting body composition assessments due to athlete discomfort (15%). Findings from these focus groups suggest that coaches would like to collect data to learn more about athletes’ physical and mental states, but several logistical and practical concerns still exist regarding how to efficiently collect and utilize the data.

Keywords

Athlete monitoring,biomechanics,performance analysis,psychology

Introduction

Using data in a sport context is key for connecting coaches with primary evidence for effective, safe, and time-efficient practice techniques.¹ One of the primary goals of sport science is to collect data from athletes that allows coaches to make decisions that are based on evidence (i.e. data collected from athletes) to inform athletes’ training as a means of improving athletic performance. Although this goal exists, the collection and translation of sport science data to practice have been inadequate. Research indicates that sport scientists often fail to study issues that coaches find relevant and the findings from sport scientists are often difficult for coaches to apply within practice and training settings due to challenges around coaches understanding sport science data and how sport scientists present the data.²

The field of sport science is a broad term that often refers to the application of data to sport in which data are used to guide sport practice for the improvement of performance.¹ The sport scientist's role is to collect and interpret data as a means of analyzing performance and developing new concepts for improving coaching and training practices in sport. From the limited research available investigating coaches’ perceptions of sport science, coaches appear to have mixed views on the topic.^3–5 Martindale and Nash³ interviewed 58 coaches in the United Kingdom across novice, developmental, and elite sport levels, and found that coaches’ opinions on sport science had significant variation regarding its relevance and usefulness.³ Some coaches perceived sport science as being relevant, but only applicable to coaches and athletes at elite levels. These different views of sport science often create tension between coaches and sport scientists. Additionally, coaches felt that the average coach would not find sport science information to be very compelling.³ However, many coaches across the three sport levels viewed sport science as being useful and applicable to every level of sport.³ Coaches believed that some coaches simply do not have access to sport scientists to obtain sport science knowledge, while others showed interest in using sport science if it was applied in the correct manner.³ Regarding where coaches and sport scientists access their sport science knowledge, 125 registered Australian sport scientists indicated that they tend to use scientific articles, conference attendance, and networking to acquire new information around coaching and training practices.⁴ Conversely, 222 Australian coaches reported acquiring this knowledge from their own experience as athletes, through mentorship from other coaches, by gaining experience as a coach, by reflecting on their own coaching practices, and via formal coaching education. These findings indicate that sport scientists may obtain their knowledge about coaching and training advancements from different sources than coaches may be using. Coaches seldom attend the scientific conferences or read the scientific articles that sport scientists are typically using to advance their knowledge within the field.⁵

While it is imperative for sport scientists to stay up-to-date with advancements in the field, if coaches do not have the opportunity to stay informed of scientific advancements in the field, this becomes problematic. Additionally, coaches may lack the scientific training to properly understand the data they may receive from sport scientists. Coaches have also reported that sport scientists typically do not present data to them in terms that are easily understandable.^4,5 Specifically, research examining factors that influence the coach–biomechanist relationship within elite sprinting found that coaches reported an inconsistent understanding of biomechanics theory and the data a biomechanist could provide to them.⁶ This study also found that biomechanists need to improve how they communicate with coaches.⁶ Subsequently, if the scientific information is not quickly available and understandable to coaches, they may not be able to implement changes to their coaching or adjust their athletes’ training, thus making the data a challenge to utilize effectively and timely.

The current research assessing coaches’ perspectives of using sport science displays a significant variation in how coaches perceive the relevancy and utility of sport science. This variability may be attributed to coaches’ perceptions of the definition of sport science.³ It appears that coaches who have a greater understanding of what sport science is perceive it to be of great use. However, problems still exist regarding how coaches define sport science and how to effectively apply sport science to coaching and training methodologies.^2,3 This issue may be addressed through future efforts to educate coaches about the field of sport science and how sport scientists often specialize in specific areas of the field as well as the role of skill acquisition specialists which are separate from sport scientists.^7,8 Research suggests that coaches believe it is important for them to stay up-to-date with current findings within the sport science literature and coaches have emphasized efforts needing to be focused on improving coach education and professional development opportunities.⁵ Additionally, coaches often feel pressured to show that the changes they have made to their coaching or athletes’ training have led to improved performances by their athletes. However, sport scientists are often in an academic position at universities and the data collection, analysis, and interpretation process takes more time than is typically ideal for coaches. These sport scientists often work part-time as they may have a dual role within academia, which can also compromise their ability to provide timely data to coaches.

While perceptions of sports science utilization by coaches in other countries have been examined, there has been limited investigation of coach perceptions of using sport science data within the U.S. In the U.S., sport science has typically been used at the elite or professional level to track both individual and team-level training and performance metrics. The frequency of sport science utilization in the collegiate setting is currently unknown. Only one study to date has been conducted to examine 127 NCAA Division I strength and conditioning coaches’ views regarding scientific research and training methodology.⁹ These coaches reported widely using professional resources such as peer-reviewed journal articles from respected journals in the field, other collegiate strength coaches, and their programs as important sources of knowledge to guide their program development and training methods.⁹ While this study is over 15 years old, it does provide evidence for the lack of sport science data collection and application that occurs within collegiate athletics. It is likely that with advancements in technology, collegiate programs are utilizing data to inform their athletes’ training for improved performance, but there is limited to no research about how universities in the U.S. are using sport science. In fact, no research to date has examined U.S. collegiate coaches’ beliefs and perspectives regarding the data collection process with their athletes, how these data may inform their training methodologies, and how to effectively develop a sport science model across all sports at a Division I institution. Thus, the purpose of this study was to examine collegiate coaches’ perspectives and needs for collecting data from their athletes using a qualitative approach.

Materials and methods

Recruitment and procedures

Approval to conduct this study was obtained from the university's human subjects review board. A member of the research team contacted every Division I coach or assistant coach at the university via email or phone call to determine their interest and availability for participating in the focus groups. Four focus groups were conducted with a total of 13 coaches. All focus groups were conducted in person.

Focus group questions were developed by the research team. Focus groups were led by a member of the research team and included five open-ended questions (Table 1) that were recorded using a digital voice recorder. A research assistant also attended the focus group interviews to take field notes. A script was followed to standardize the delivery of the questions and prompts were used as needed to elicit more information when the content discussion was limited. Demographic information was also obtained about participants’ age, sex, ethnicity, sport they coach, number of years they have coached that sport, and number of years they have coached that sport at the current institution.

Table 1.

Three most common themes per focus group question, frequency of responses, and example quotations.

Theme	N (%) of responses	Example quotation
Question 1: “Can you think of specific ways that your team would benefit from knowledge gained from collecting data?”
Evidence to support practice	12 (16.21)	“Data is always good for validation of coaching as it is difficult to have conversations if you are going off of qualitative things.”⁶
Monitoring/testing	12 (16.21)	“Tracking progress over time. I don't have a great way to compile this and have them reflect back on.”⁶
Recovery	7 (9.00)	“What's optimal of coming back…where they can be optimal, the best, playing, how much do I put on them and how much can they handle, being aware of that.”¹
Question 2: “Are there specific performance questions you would like answered when it comes to your team?”
Biomechanics	5 (14.70)	“Where you were doing well, or where there are deficiencies with your gait as you’re running.”⁷
Monitoring	4 (11.76)	“Data on how hard they are working.”¹⁰
Sport psychology	4 (11.76)	“I’d love having any information on anxiety and how players think when there is a pressure situation, and how we can help them in that.”¹
Question 3: “Have you heard of other university teams in your sport that have successfully used performance data? What measures or methods were used in these cases?”
Specialized consultation	13 (37.14)	“Most times the colleges will have a nutritionist and a sports psychologist that will talk to the teams and do one-on-one meetings with the student athletes.”⁷
Wearable monitoring	5 (14.28)	“They’re doing the GPS monitoring during the workouts. Some of the teams I have worked with before had just started to do heart rate, and they were thinking about trying to do the GPS tracking.”³
Biomechanical analysis	3 (8.57)	“If you look up biomechanics and feedback around golf, you’re going to find years of data and information and programs.”⁹
Question 4A: “If you were given an opportunity to collect data throughout the season, what specific questions you would want to see supported by the data?”*
Athlete monitoring	2 (8.69)	“For us, it would probably be overall, if there are a couple guys that are just really tired or fatigued or another guy that might be doing really well, there's probably another factor that is going into that.”¹²
Health behavior monitoring	2 (8.69)	“To have a general feel for, is the team getting enough rest, is the team overly fatigued and then maybe within that broken down individually so that you could see – these guys seem to be doing their job as far as getting sleep and eating right and these guys aren't.”¹⁰
Question 4B: “How do you think your team would use the data provided during the season?”
Training adjustments	6 (28.57)	“I think for the coaches, we would use data very effectively on loading and heart rates and intensity and fatigue to change what we’re doing in training, and that could have a big effect on performance.”⁵
Athlete buy-in	3 (14.28)	“And when you have those numbers that's going to be the bigger buy-in. When there's stuff there in front of them, they see them. Whoa, wait a minute, this actually makes a difference. Even though it can be the same thing you’ve been telling them for two years straight, when they finally see it in front of them, on a piece of paper or in the video, changes stuff up.”⁷
Process evaluation	2 (9.52)	“Once you’ve started, all this stuff becomes a habit. So now they know this is what you’re supposed to do. We need to start to tweak things here and there to make it better. But I think once you have that habit of reporting, and doing the things, and then them looking at those numbers.”⁸
Question 5A: “Are there any concerns to collecting data on your team?”*
Timing of tests	7 (15.55)	“Well, and each athlete is on a different training cycle, too. Some are more in pre-season. Some maybe are peaking. So even, in some ways, that adjusts the data.”⁵
Ineffective presentation of data	5 (11.11)	“Being able to present information where they can become aware, where they don't feel threatened, where they don't feel embarrassed about it.”²
Question 5B: “Would there be any assessments you would not want included?”*
Body composition	2 (66.66)	“Body composition, obviously you stay away from that. Anything with weights in general.”⁶
BMI	1 (33.33)	“If you just provide data, like body mass index, in my sport, they’re not going to care. They don't care.”⁹

BMI: body mass index: GPS: global positioning system.

Note. * Indicates questions in which a number of themes were represented a small but equal percentage of the time so the top two themes are presented in the table or limited variety in responses only led to two salient themes. Each coach was given a number and superscript numbers after each example quote indicate the coach who provided each response. The first study author can be contacted to obtain the full results.

One of the future goals of this project is to develop a data science model for all teams at the university; the research team invited every sport at the university to participate instead of determining sample size based on data saturation.¹⁰ A coach from every sport at the university participated in the focus group interviews except for the coach of the men's and women's tennis teams, who were unable to attend due to scheduling issues. Each focus group lasted an average of 38.75 min.

We recognize that the field of sport science is broad and for the purpose of the current study, we defined sport science as the utilization and collection of data (i.e. mental health, nutrition, sleep, fatigue, and recovery) from athletes that can be used for making changes and improvements to athletes’ training and subsequent performance. This definition of sport science was provided to all coaches before the start of each focus group so that they clearly understood how we were referring to sport science.

Data analyses

SPSS (version 26.0) was used for data management and descriptive analyses of the study sample. Descriptive statistics were used to examine participant demographics. Each recorded focus group interview was sent to an external vendor (Rev; San Francisco, CA, USA) for transcription. A member of the research team reviewed each of the transcriptions in comparison to the original audio recordings to ensure all content had been transcribed accurately before analysis began. Principles of thematic analysis were used to analyze the focus group interview data.¹¹ Thematic analysis has been shown to be the most common approach to data analysis for qualitative data as it involves searching for common themes that emerge from both the group dynamics and open conversation that occurs among focus group participants.^12,13 Themes that emerge from qualitative analysis reflect a range of individual attitudes, opinions, and beliefs that are grouped based on similarity into a coding scheme developed by the research team.¹⁴ To achieve this goal, focus group interviews were coded collectively by the entire research team into themes. A thematic framework was utilized, whereby each response was coded and categorized into a higher-order theme. All coders (n = 5) discussed the thematic coding for every individual response to each interview question until 100% agreement was achieved. Each question resulted in a varying number of themes in which illustrative responses were identified for each of the higher-order themes.

Participants

The sport coaches that were represented in the current study include baseball, softball, women's rowing, women's volleyball, and the men's and women's teams for the following sports: basketball, soccer, cross country, track and field, golf, swimming. The head strength and conditioning coach for all teams also participated and this coach is included in the total sample of size of (N = 13) coaches who participated in the study. Coaches had a mean age of 40 years (standard deviation (SD) = 8.0), 77% of the coaches were male, and 84% were Caucasian (see Table 2). Coaches indicated that they had been coaching in their given sport for a mean of 15.1 years (SD = 5.8) and they had specifically been coaching at the current institution for a mean of 5.6 years (SD = 3.0). Table 2 provides complete demographic information for the sample.

Table 2.

Demographic characteristics of the entire sample (N = 13).

Variable	N	SD	%
Age	40.0	8.0
Sex
Male			76.9
Female			23.1
Ethnicity
Caucasian			84.6
Native Hawaiian/Pacific Islander			7.7
Asian			7.7
Years coaching	15.1	5.8
Years coaching at current institution	5.6	3.0

M: mean; SD: standard deviation.

Results

A description of the three most frequently discussed themes along with example quotations for each of the focus group questions can be found in Table 1. Across the five questions, the most frequent themes were identified from the responses from each coach. Once higher-order themes were identified for each question, the research team calculated the number of individual responses that were categorized within each higher-order theme. The sum for each theme was divided by the total number of responses for that question to identify the most commonly discussed themes for each question. In some instances (4A, 5A, and 5B), there was limited response variance or there were several themes discussed by a small number of coaches and, in those questions, only two higher-order themes were identified.

How the team can benefit from data collection. There were 74 responses for the first focus group question. Out of the 74 responses, 16.2% (n = 12 responses) of those responses were about the utility of collecting data to provide coaches with evidence to support the training methodologies and practices they implement with their athletes. Eight sport coaches out of the 13 (62%) discussed this theme across the focus group interviews. Another theme that was equally discussed (16.2% of responses; n = 12 responses) was that coaches felt they could benefit from data collection (i.e. aerobic capacity testing; biomechanical assessment; and mental and emotional states) as a means of monitoring and tracking progress in their athletes over time. Again, this theme was discussed across the majority (7 out of 13; 54%) of sport coaches. Recovery was the next most frequently discussed theme (9% of responses; n = 7 responses) with coaches (23%; 3 out of 13) indicating that collecting data from their athletes would provide them knowledge about their athletes’ recovery process and help them to create a more optimal recovery plan for their athletes.

Performance questions coaches want answered. When asked what performance questions coaches would want answered from collecting data with their athletes, 34 responses emerged. The most commonly discussed theme was that coaches wanted to understand the biomechanics and movements of their athletes (14.7% of responses; n = 5 responses). Three sport coaches (23% of coaches) discussed this theme across focus group interviews. Monitoring and sport psychology questions were also frequent themes discussed during the focus group interviews (11.8% of responses; n = 4 responses for both themes). Questions that coaches wanted answered in relation to monitoring focused on measuring heart rate and workload during training and competition. Sport psychology questions that coaches indicated they would want answered focused on athletes’ mental and emotional states during games, practices, and outside of sport.

Knowledge of other universities that are using performance data. Coaches provided 35 responses regarding their knowledge about teams from other universities in their sport using performance data. The most frequently discussed theme (37.1% of responses; n = 13 responses) was that coaches stated that other universities use specialized consultation such as individualized nutrition meetings for athletes and that some teams have a group of specialists such as a sports performance specialist, a strength specialist, and a nutrition specialist to collect and monitor athlete data. Across the different sports, four out of the 13 (31%) sports coaches discussed specialized consultation. The next most commonly discussed theme was around wearable monitoring (14.3% of responses; n = 5 responses) with coaches indicating that other university sports teams use performance data to track athletes’ heart rate, heart rate variability, acceleration, and global positioning. Coaches also discussed that other university sports teams conduct biomechanical analyses with athletes (8.6% of responses; n = 3 responses).

Question coaches want answered from data collection throughout the season. The coaches were asked to indicate what performance-based questions they would want answered if given the opportunity to collect data throughout the season. Coaches provided 23 responses with the two most frequent themes that emerged being that coaches would want this type of data for athlete monitoring (8.7% of responses; n = 2 responses) and health behavior monitoring (8.7% of responses; n = 2 responses). Coaches discussed that they would like to have data throughout the season that would allow them to gauge athlete recovery and how to tailor training for their athletes based on the data. Regarding health behavior monitoring, coaches expressed that it would be important to gain a more robust understanding of an athlete's health behaviors outside of training such as their sleep and dietary behaviors.

How coaches would use data collected during the season. As a follow-up to the previous question, coaches were asked how they would utilize data that were collected during the season. This question resulted in 21 responses, with the majority of coach responses focusing on using these data to inform training adjustments (28.6% of responses; n = 6 responses). Coaches discussed that being able to assess variables such as load, heart rate, intensity, and fatigue from training and competition would be key for making proper adjustments to training for improving their athletes’ performance. This theme was discussed by four of the 13 coaches (31%) who participated in the focus groups. The second most frequent theme discussed by coaches was using the data to obtain athlete buy-in (14.3% of responses; n = 3 responses). The coaches felt that sharing data with their athletes would allow athletes to see the connection between the data and their performance. The next most commonly discussed theme from coaches was using data for process evaluation purposes (9.5% of responses; n = 2 responses) so that coaches could learn which data are most informative for training and improving performance and to get athletes accustomed to the data collection process.

Concerns about collecting data from athletes. Forty-five responses emerged from this question with the most commonly discussed theme being about the amount of time required for athlete testing (15.5% of responses; n = 7 responses). Coaches were also concerned about finding an optimal time in the year for athletes to complete performance tests as their stage of training has clear implications on the test results as well as their ability to perform such tests. The second most frequent theme discussed by coaches was a concern about ineffective presentation of data (11.1% of responses; n = responses) and athletes’ perception of these data. Coaches discussed a variety of other concerns, but these concerns were not consistently brought up by coaches, and thus only two frequent themes emerged for this question.

Assessments to exclude. Coaches were asked to specifically discuss which assessments they would want to exclude from athlete testing. Three responses emerged from this question with only two frequent themes identified. The two frequent themes were that coaches would not want to assess athletes’ body composition (66.6% of responses; n = 2 responses) or athletes’ body mass index (BMI) (33.3% of responses; n = 1 response).

Discussion

This study examined NCAA Division I coaches’ perceptions and needs for collecting data from their athletes. A primary study finding that emerged throughout several questions was that coaches discussed the importance of collecting data as a mechanism for monitoring progress in their athletes over time and using that information to make the necessary adjustments to their training. Coaches specifically identified a need to assess their athletes’ fatigue, recovery, mental states during games, practices, and in their daily life, health behaviors (specifically sleep and diet), and biomechanical movements. Coaches also felt that collecting data from their athletes would provide support for their training methodologies. Finally, coaches felt it was necessary to consider the timing of testing athletes as well as strategies for effective presentation of data to improve their athletes’ understanding regarding data-driven training adjustments and potential suggested changes to their lifestyle behaviors. Several of the key findings warrant further discussion.

Athlete monitoring for making training adjustments was a commonly discussed theme that emerged repeatedly across four of the five questions asked in the focus groups, including how coaches felt their team could benefit from collecting data, what general performance questions they would want answered from collecting data, what performance questions they would want answered from data collection throughout the season, and how they would use data collected throughout the season. Athlete monitoring and subsequent adjustments to training are a clear priority for coaches when considering the data collection process. Improving athletes’ performance requires the implementation of an optimal training program that includes a balance of training volume, intensity, and rest periods.¹⁵ Athletic performance is a result of complex psychobiological adaptations which can make it difficult to predict fitness and fatigue in individual athletes.¹⁶ Thus, Coutts et al.¹⁶ recommend a multi-dimensional athlete monitoring system that enables coaches to quantify training load measures for each athlete and their fitness and fatigue responses to that training. To monitor these outcomes effectively, coaches must work with sport scientists to critically determine the fundamental components of an athlete monitoring system. A comprehensive and multi-dimensional athlete monitoring system should assess athletes’ training loads, fitness levels, fatigue, and additional biochemical markers (i.e. markers of muscle damage, hormonal and immune system functioning).¹⁶ In a collegiate setting, there may be limitations regarding available assessment tools that sport scientists have to monitor and track these outcomes. Therefore, it is imperative that sport scientists work with coaches to build an athlete monitoring system that is logistically feasible and meets coaches’ needs. This will allow coaches to have access to useful data that they can then use to make necessary adjustments to their athletes’ training.

In addition to monitoring athletes for performance gains, coaches discussed monitoring these outcomes as a tool they can use to minimize overtraining and injuries while also ensuring that their athletes are recovering from the physical demands of training. When training is prolonged and leads to excessive strain on athletes, it can lead to inadequate recovery and a reduction in the positive physiological adaptations of training, which can further lead to overtraining and performance decrements.^17,18 While coaches expressed a desire to assess their athletes’ workloads, it is important to note that challenges currently exist regarding the most effective methods for assessing athlete workload. Heart rate has historically been the most commonly used outcome for evaluating internal training loads^19,20 but heart rate monitoring has limitations during weight, interval, intermittent, and plyometric training.²⁰ With increased interest in monitoring athlete workload and the type of practice used within the workload from sport scientists and coaches, additional methods have also been used besides heart rate. These methods typically include lactate, VO₂, and power output to assess metabolic thresholds as an indicator of internal load. While these measures may eliminate some of the limitations of assessing internal load via heart rate, they typically require laboratory testing, which limits their ability to be useful in the field and often produces too much information, in too slow a time frame, to be optimally useful to coaches.²⁰ Due to some of the limitations around performance assessments such as VO₂ max and blood lactate, these assessments are often too hard to obtain consistently from athletes to monitor their weekly fatigue. Thus, there has been recent interest in using wearable sensors to provide high-resolution data of the external training load which may provide an opportunity for coaches to monitor athlete workload in the field, in real-time. Additionally, there has been an increased recognition that mental states, specifically stress and anxiety, play a role in sport performance and can be indicators of early signs of fatigue and overtraining. Subsequently, monitoring athletes’ mental states through validated questionnaires is a logistically feasible and effective method for diagnosing training stress in athletes and monitoring for changes in training stress and recovery to allow coaches to better understand which athletes may be experiencing greater levels of fatigue and early indicators of overtraining.^21–24 Since it is easier to obtain measures of collegiate athletes’ heart rate, heart rate variability, ratings of perceived efforts, and mental states on a regular basis, these internal load measures should be used in conjunction with measures of external load such as global positioning system (GPS) monitoring devices to determine overall load in athletes to help coaches make decisions about their training.

The last outcome that coaches discussed wanting to monitor in their athletes included the health behaviors of their athletes, primarily their sleep and dietary habits. While no research to date has examined coaches’ perspectives regarding the monitoring of health behaviors in their athletes, research has previously established the importance of maintaining proper sleep and nutrition behaviors so that athletes can optimize their performance and recovery, and prevent injuries.^25,26 Based on the discussions with coaches, sleep behaviors are not commonly monitored with collegiate athletes, but coaches recognized the importance of monitoring sleep duration as an indicator of recovery in their athletes. Research indicates that both sleep quality and quantity are important for athletes to recover appropriately from the high physical and mental stress imposed on them during training and competition.²⁶ Regular monitoring of sleep behavior in collegiate athletes appears to hold importance to coaches in relation to the recovery–stress response and assessing training parameters. However, there are challenges that exist regarding how to effectively measure athletes’ sleep behaviors and the potential hesitancy that might exist with collegiate athletes sharing their sleep data with their coaching staff. Similar challenges exist when it comes to monitoring athletes’ dietary behaviors. Heffner et al. found that a considerable number of the 303 surveyed NCAA coaches (women's basketball, swimming, and gymnastics) participate in some type of dietary monitoring or weight management behaviors with their athletes.²⁷ The results from this study also indicated that monitoring dietary behaviors allowed coaches to identify athletes who may be experiencing disordered eating and provide them with the proper resources on campus.²⁷ If coaches want to effectively monitor sleep and dietary behaviors in their collegiate athletes, they may want to consider hiring sleep and nutrition consultants to review such data rather than relying on sport scientists or themselves to provide feedback and appropriate recommendations about these behaviors to their athletes.

Coaches also expressed a need for collecting data that allowed them to better understand how their athletes are moving from a biomechanical perspective. Sport scientists and biomechanists can work together to use technology and video equipment to measure and analyze athletes’ movements and then provide feedback to both coaches and athletes.²⁸ To conduct a practical performance analysis that is useful for both coaches and athletes, it is imperative that the sport scientist and biomechanist choose the appropriate performance indicators based on the sport of interest.²⁸ This process should also allow for coaches to identify good and bad performances of an individual or a team member and facilitate comparative analysis of individuals, teams, and players.²⁸ Biomechanists can complete biomechanical analyses of athletes’ movements to identify injurious techniques and work with coaches and motor control and learning specialists to help athletes develop proper movement techniques to reduce their risk of injury.²⁸ In a large survey study of level 3 swim coaches affiliated with the American Swim Coaches Associations, coaches believed that biomechanics was the most important sport science outcome to assess with 70% of coaches using video-based methods of analysis with their athletes at least monthly.²⁹ However, coaches in this study did recognize common barriers that exist around using biomechanical analysis with their athletes such as lack of finances, time restrictions, and accessibility to suitable testing equipment.²⁹ As discussed previously, research suggests that some coaches do not understand biomechanical knowledge and that biomechanists need to improve their communication with coaches which also creates barriers around utilizing biomechanical data with athletes.⁶ The findings from these studies suggest that coaches want to assess their athletes’ biomechanics, but effective measurement depends on having access to the resources and a biomechanist that can interpret the data and communicate clearly to coaches.

The most frequent theme that emerged when coaches were asked how their team could benefit from collecting data from their athletes was that they would use the data to provide support for the primary training methodologies they use with their athletes. It appears that coaches want the data to provide them with the evidence they need to validate the training strategies and approaches they are using. The limited research available regarding coaching and evidence-based practice has focused more specifically on coaching techniques and the use of research to improve coaching performance rather than using sport science data to support the training that coaches are implementing.³⁰ This novel finding provides further evidence for the need for sport scientists to provide data to coaches in a user-friendly format. Additionally, coaches need better access to up-to-date research on sport science and education around how to apply sport science findings to their coaching and training with their athletes. While not all collegiate athletic programs will have the resources to have a full-time sport scientist on staff to enable coaches to apply research findings to their practice, it is important for coaches to have a basic understanding of sport science that could be provided through educational coaching courses that many coaches attend. Athletic programs could also consider working with a kinesiology department on campus to conduct athlete testing and monitoring and provide them with an interpretation of their athletes’ data. Without a sport scientist on staff or education for coaches about the field of sport science, this could lead to an increased risk for injury and poor performance in athletes since coaches may lack the ability to monitor their athletes’ physical and mental states. Thus, if possible coaches should have continued monitoring and up-to-date data about their athletes to understand if the adjustments they made to training based on data from their athletes are positively impacting their athletes’ performances.

Coaches most commonly discussed their concerns about collecting body composition data from athletes. Coaches are aware that assessing athletes’ body composition and providing athletes with data about their body composition can lead to body image dissatisfaction and subsequent negative behaviors such as extreme dieting and excessive exercise. In some sports, particularly those that are more weight sensitive (i.e. running, gymnastics, figure skating, wrestling, cycling, and rowing), body composition is often viewed as a key performance variable. However, providing athletes in these types of sports with feedback about their body composition can increase the likelihood of frequent weight fluctuations, extreme dieting, eating disorders, insufficient bone density and body fat, and menstrual dysfunction in females as they attempt to conform to the anthropometric demands of their sport.³¹ Research indicates that even medical staff, including sports physicians, nutritionists, and exercise scientists, experience challenges in handling the issues of optimum body composition, dieting, and eating disorders in athletes.^32,33 Therefore, providing coaches and athletes with body composition data is not recommended since health care professionals struggle with how to handle these issues with athletes and the negative influence that body composition can have on athletes’ confidence and perceptions of their body. Based on the data from the current study, coaches recognize that body composition assessments are not the most important variables to assess in athletes when compared to other outcomes (i.e. heart rate, workload, and fatigue) that are better indicators of performance.

Coaches’ primary concerns about collecting data from their athletes were around the timing of testing. Coaches discussed the challenges around finding an optimal time to conduct performance testing in their athletes. Some coaches felt that obtaining pre-season assessments could be helpful to gauge their athletes’ fitness levels, but they would want to conduct additional follow-up testing to examine these outcomes within the context of the season. However, coaches expressed concerns about the added strain that performance testing might place on athletes during the season as performance assessments are highly fatiguing. Based on these concerns and the research literature around performance testing in athletes, these tests should not add excess burden to the athlete and should be incorporated into athlete monitoring.³⁴ Athletes need to be fully recovered from one test before moving on to another, which may limit the ability to obtain the primary data points coaches suggested they would want (i.e. power output and maximal oxygen consumption) on the same day.³⁴ These findings continue to provide a strong rationale for the need for coaches and sport scientists to work more effectively together to develop an athlete monitoring system that would include these performance tests at the appropriate times as identified by the coaches of each sport.

Coaches also expressed their concerns about the effective presentation of the data. It is imperative that coaches and sport scientists communicate effectively to bridge the gap that currently exists between both parties.³⁵ As discussed previously, coaches typically lack the scientific training to properly understand the data being presented to them and how those data inform the changes they should consider making to their athletes’ training.³ Additionally, sport scientists may not be able to share their knowledge in lay terms that coaches can easily understand. The data becomes ineffective if it is not presented to coaches in terms that are easily understandable so that they can use that data as a mechanism for improving their athletes’ performance as well as reducing their risk of overtraining and injury. Coaches also wanted to ensure that the data were presented to the team effectively so that they could achieve buy-in regarding any training adjustments, rest, or behavioral feedback they provide to their athletes. To date, no research has examined how athlete buy-in may influence the efficacy of using sport science data, but it is logical for coaches to want their athletes to understand how and why they are using data as a training tool. Therefore, the data must be presented in such a way that it is meaningful to both coaches and athletes.

The current study provides detailed perspectives from coaches about the utilization of sport science data in collegiate sports, what their current needs are for collecting data with their athletes, and how a university may be able to develop a comprehensive sport science model. This study is the first to our knowledge to examine U.S. collegiate coaches’ beliefs regarding the utilization of sport science data across an entire athletics department. Despite these study strengths, there were some limitations. While we did include all available coaches at a Division I institution, we were limited to the sports that this institution offers which do not include sports commonly offered at other universities (e.g. football, ice hockey, field hockey, gymnastics, or wrestling). Additionally, the coaches that participated in the study were largely homogenous in ethnicity and gender (i.e. Caucasian males). Thus, the findings from this study may not be generalizable to all coaches at Division I universities in the U.S. Future research should examine coaches’ beliefs and needs around sport science and data collection from other institutions across all collegiate sport divisions (i.e. NCAA Divisions I, II, and III; National Association of Intercollegiate Athletics) to gain more diverse perspectives. Lastly, moderator bias could have occurred during the focus group interviews. The research team followed a script to minimize bias and prevent the researchers from using leading questions, but participants may have felt pressured to respond to questions a certain way.

As the field of sport science continues to grow, it is imperative that coaches receive education about sport science and how to apply sport science data to their coaching and training practices. It is also important for coaches to be informed regarding the latest findings and developments from research within the sport science field through organized seminars and workshops that also focus on current trends in coaching. At the collegiate level, coaches recognize the importance of monitoring athlete outcomes that play a role in their performance, recovery, and injury prevention. While there are still barriers that exist regarding how to best monitor these outcomes, our study findings support the need for the development of a multi-dimensional athlete monitoring system that meets each team's needs and is feasible given the available resources. Performance tests should also be used that are appropriate to each sport and conducted at times that each sport believes to be most beneficial for their athletes and their needs. These performance tests should be included within the multi-dimensional monitoring system. Finally, coaches and sport scientists will need to work together using an appropriate language they can both easily understand so that an effective multi-dimensional monitoring system can be developed that provides coaches and athletes with data and feedback that is practical and useful for optimizing each team's performance and recovery.

Footnotes

Acknowledgements

The research team would like to acknowledge Jacob Kysar for his assistance in collecting and analyzing data.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Erica L Rauff

References

Bishop

Burnett

Farrow

, et al. Sports-science roundtable: Does sport-science research influence practice. Int J Sport Physiol 2006; 1: 161–168.

Bishop

. An applied research model for the sport sciences. Sports Med 2008; 38: 253–263.

Martindale

Nash

. Sport science relevance and application: Perceptions of UK coaches. J Sports Sci 2013; 31: 807–819.

Williams

Kendall

. Perceptions of elite coaches and sports scientists of the research needs for elite coaching practice. J Sports Sci 2007; 25: 1577–1586.

Kubayi

Coopoo

Toriola

. Analysis of sports science perceptions and research needs among South African coaches. S Afr J Sports Med 2018; 30: 1–4.

Waters

Phillips

Panchuk

, et al. The coach-scientist relationship in high performance sport: Biomechanics and sprint coaches. Int J Sports Sci Coach 2019; 4: 617–628.

Steel

Harris

Baxter

, et al.

Skill acquisition specialists, coaches and athletes: the current state of play?

J Sport Behav 2013; 36: 291–305.

Steel

Harris

Baxter

, et al. Coaches, athletes, skill acquisition specialists: A case of misrecognition. Int J Sport Sci Coach 2014; 9: 368–378.

Durell

Pujol

Barnes

. A survey of the scientific data and training methods utilized by collegiate strength and conditioning coaches. J Strength Cond Res 2003; 17: 368–373.

10.

Guest

Bunce

Johnson

. How many interviews are enough? An experiment with data saturation. Field Methods 2005; 18: 59–82.

11.

Green

Browne

. Analysing qualitative data. In: Black

Raine

Green

Browne (eds.) Principles of social research. New York: McGraw-Hill, 2005, pp. 79–80.

12.

Massey

. A proposed model for the analysis and interpretation of focus groups in evaluation research. Eval Program Plann 2011; 34: 21–28.

13.

Wiggins

. The analysis of focus groups in published research articles. Can J Program Eval 2004; 19: 143–164.

14.

Kamberelis

Dimitriadis

. Focus groups: strategic articulations of pedagogy, politics, and inquiry. In Denzin

Linconl

(eds) Collecting and interpreting qualitative materials. Thousand Oaks: Sage Publications, 2008, pp. 375–402.

15.

Elloumi

Makni

Moalla

, et al. Monitoring training load and fatigue in rugby sevens players. Asian J Sports Med 2012; 3: 175–184.

16.

Coutts

Crowcroft

Kempton

. Developing athlete monitoring systems. In: Kellman

Beckmann

(eds). Sport, recovery, and performance: interdisciplinary insights. Abingdon, UK and New York, NY: Routledge, 2017, pp. 19–33.

17.

Meeusen

Nederhof

Buyse

, et al. Diagnosing overtraining in athletes using the two-bout exercise protocol. Br J Sports Med 2010; 44: 642–648.

18.

Armstrong

VanHeest

. The unknown mechanism of the overtraining syndrome: Clues from depression and psychoneuroimmunology. Sports Med 2002; 32: 185–209.

19.

Bangsbo

Mohr

Poulsen

, et al. Training and testing the elite athlete. J Exerc Sci Fit 2006; 4: 1–14.

20.

Foster

Florhaug

Franklin

, et al. A new approach to monitoring exercise training. J Strength Cond Res 2001; 15: 109–115.

21.

Kellmann

. Preventing overtraining in athletes in high-intensity sports and stress/recovery monitoring. Scand J Med Sci Sports 2010; 20: 95–102.

22.

Chatard

Atlaoui

Pichot

, et al. Training follow up by questionnaire fatigue, hormones and heart rate variability measurements. Sci Sport 2003; 18: 302–304.

23.

Coutts

Reaburn

. Monitoring changes in rugby league players’ perceived stress and recovery during intensified training. Percept Mot Skill 2008; 106: 904–916.

24.

Elloumi

Ben Ounis

Tabka

, et al. Psychoendocrine and physical performance responses in male Tunisian rugby players during an international competitive season. Aggress Behav 2008; 34: 623–632.

25.

Thomas

Erdman

Burke

. Position of the academy of nutrition and dietetics, dietitians of Canada, and the American college of sports medicine: nutrition and athletic performance. J Acad Nutr Diet 2016; 116: 501–528.

26.

Kölling

Duffield

Erlacher

, et al. Sleep-related issues for recovery and performance in athletes. Int J Sport Physiol 2019; 14: 144–148.

27.

Heffner

Ogles

Gold

, et al. Nutrition and eating in female college athletes: A survey of coaches. Eat Disord 2003; 11: 209–220.

28.

Bartlett

. Performance analysis: Can bringing together biomechanics and notational analysis benefit coaches? Int J Perf Anal Sport 2001; 1: 122–126.

29.

Mooney

Corley

Godfrey

, et al. Analysis of swimming performance: perceptions and practices of US-based swimming coaches. J Sports Sci 2016; 34: 997–1005.

30.

Stober

Wildflower

Drake

. Evidence-based practice: A potential approach for effective coaching. IJEBCM 2006; 4: 1–8.

31.

Sundgot-Borgen

Meyer

Lohman

, et al. How to minimise the health risks to athletes who compete in weight-sensitive sports review and position statement on behalf of the ad hoc research working group on body composition, health and performance, under the auspices of the IOC medical commission. Br J Sports Med 2013; 47: 1012–1022.

32.

Currie

Crosland

. Responding to eating disorders in sports—UK guidelines. Nutr Food Sci 2009; 39: 619–626.

33.

Meyer

Sundgot-Borgen

Lohman

, et al. Body composition for health and performance: A survey of body composition assessment practice carried out by the ad hoc research working group on body composition, health and performance under the auspices of the IOC medical commission. Br J Sports Med 2013; 47: 1044–1053.

34.

McGuigan

Hassmén

Rosic

, et al. Training monitoring methods used in the field by coaches and practitioners: A systematic review. Int J Sports Sci Coach 2020; 15: 439–451.

35.

Bolger

Lyons

Harrison

, et al. Coaching sprinting: expert coaches’ perception of resistance-based training. Int J Sports Sci Coach 2016; 11: 746–754.