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There are a number of factors within a particular environment that can contribute to the performance outcome of an athlete’s effort. Weather is often an intractable and unpredictable variable in outdoor competitions. The event venue—such as World Championship or Olympic stages, as compared to local or regional events—can greatly affect both the mental and physical performances of the athlete, especially when comparing indoor to outdoor events. Wind resistance has a physical effect on running speed and metabolic cost, as does the altitude of the venue. These factors, as well as timing method, were investigated by Hollings, Hopkins, and Hume (2012) for their effect on elite male track athlete performance.

Timing and Venue

Human error is a major factor in the timing of events, and it led to the evolution of automatic timing systems. Stopwatch-timed sprint events are notoriously biased toward a 0.24-second faster time on average, due to the timer’s anticipation of the athlete’s finish (Hollings et al., 2012). Hand-timing in distance events is associated with delayed times of greater than 0.14s, again from timer bias. The 200-meter, 400-meter, 800-meter, and 1500-meter events are typically run slower indoors than outdoors, likely due to the tight turns of the track, and there being twice as many bends to run.

The standard of competition was found to affect performance based on the event distance, since there are varying outcome goals per respective race (Hollings et al., 2012). Sprint and hurdle events raced their fastest times at the highest stage venues, while middle- and long-distance events raced slower due to the tactical nature of the race on that level of competition. Similar findings occurred at altitude, where the sprinters performed much better due to less air resistance. Distance appeared to be a greater challenge, due to the reduced oxygen content of the air at altitude. The advantage of running sprints at altitude is greatly outweighed by the disadvantage in the distance events.

Weather

Heat exchange between an athlete and their environment is directly impacted by the ambient temperature of the environment, as well as its moisture density, or humidity. Effective evaporation is limited in heavy humid conditions due to increased sweat vaporization, and thus reduces heat loss in the athlete (Hayes, Castle, Ross, & Maxwell, 2014). In dry heat conditions, the evaporative requirement of the athlete cannot be matched by the environment’s evaporation potential. In either case, the athlete is at risk for hyperthermia and significant physiological performance stress.

Ideally, an athlete should train for the environment in which the performance will take place. Share on X

There was a comparison made between hot, humid environments and hot, dry environments for their respective conditional effects on intermittent-sprint exercise performance (Hayes et al., 2014). The conditions were matched for heat stress to create the most controlled and accurate analysis of the two experimental groups, in relation to the temperate environment control group. The proposed hypothesis was that hot, humid conditions would produce greater physiological strain than hot, dry conditions and result in impaired sprint performance.

The results of the study concluded that sprint performance was impaired, but not significantly more so in one condition over the other when heat stress was matched between the two. Ideally, an athlete should train for the environment in which the performance will take place. For example, training in dry heat would be optimal preparation for a championship event in Arizona. However, this is not always possible, so aiming to match the heat stress is a valid way to achieve similar gains in training. Preparing in Georgia heat and humidity for a dry heat Arizona competition may require training to be conducted in the early morning hours, when the humidity and temperatures are lower, to equilibrate the demands of GA and AZ running. As an example, training in 65 degrees and 40% humidity often feels equal to dry 80-degree training.

Another study specifically investigated the effects of dry and humid heat stress on heat loss capacity in different age categories (Larose et al., 2014). As age increases, sweat rate has been found to decrease, making it more difficult for older adults to effectively expend the heat retained during exercise. Heat loss capacity was measured by both direct (evaporative) and indirect (metabolic) calorimetry in 60 males, ages 20-70, in 35˚C and both 20% and 60% relative humidity.

The hot, humid conditions caused an attenuated heat loss capacity in all age categories. The relative core temperature, heart rate response, and perceived thermal discomfort level all increased with age. This corresponded with a decrease in heat-loss capacity in the middle-age and older populations. No age group differences were observed in dehydration status, percent change in body weight, or local sweat rate and blood flow (Larose et al., 2014). Participants aged 40-70 stored 60-85% [in dry heat] and 13-38% [in humid heat] more than the 20-30 year age group.

It’s important to consider the physiological effects of prolonged exercise in heat, especially for the lack of efficient thermal regulation in the older age populations. All in all, these findings are helpful for athletes to know and apply across multiple race performances, in order to gauge true comparisons in performance.

Since you’re here…
…we have a small favor to ask. More people are reading SimpliFaster than ever, and each week we bring you compelling content from coaches, sport scientists, and physiotherapists who are devoted to building better athletes. Please take a moment to share the articles on social media, engage the authors with questions and comments below, and link to articles when appropriate if you have a blog or participate on forums of related topics. — SF

References

1. Hayes, M., Castle, P. C., Ross, E. Z., & Maxwell, N. S. (2014). “The influence of hot humid and hot dry environments on intermittent-sprint exercise performance.” International Journal of Sports Physiology and Performance, 9: 387-396.
2. Hollings, S. C., Hopkins, W. G., & Hume, P. A. (2012). “Environmental and venue-related factors affecting the performance of elite male track athletes.” European Journal of Sport Sciences, 12(3): 201-206.
3. Larose, J., Boulay, P., Wright-Beatty, H. E., Sigal, R. J., Hardcastle, S., Kenny, G. P. (2014). “Age-related differences in heat loss capacity occur under both dry and humid heat stress conditions.” Journal of Applied Physiology, 117(1), 69-79.

Over the years, sports coaching and training has become much more scientific. Today, training decisions and process are expected to at least have some form of evidence base, and the expectation for coaches and support staff (and even athletes) to be scientifically literate has increased. The advent of the internet has also led to an increase in PubMed warriors (myself included), and there is an ever-increasing number of scientific papers out there that can be found and cited to support a person’s position.

Central to most scientific research is the idea of statistical significance. As part of my day job, I run education programs for fitness professionals from personal trainers to those in elite sports. When I’m presenting data, a common question will be, “Is it significant?” The unsaid assumption is that, if it is not statistically significant, the results are worthless.

Researchers determine statistical significance through the use of p-values, which you will have come across if you’ve read scientific papers. Typically, if the p-value is said to be less than or equal to 0.05 (represented as p≤0.05), then the effect is said to be statistically significant. If it’s greater than 0.05 (i.e., p>0.05), then it’s said not to be statistically significant.

The Problems With P-Values

There are a few problems with the p-value method, and these often lead to issues in understanding research that are common with sports science practitioners. This, in turn, can lead to the misinterpretation of research and, therefore, the misuse of research paper findings.

Let me illustrate this with an example. Let’s say I want to test the effects of caffeine on vertical jump height. What I would likely do is gather a group of athletes—let’s say 40—and get them to do two trials: one with caffeine, one without. I collect the data and then analyze it using a t-test, and I come up with the following conclusion:

Subjects jumped significantly higher (p<0.05) in the caffeine trial than the placebo trial.

From this, I can conclude that caffeine improves jump height. But what is the p-value really telling us? Have a think and come up with your own explanation of what the p-value actually is. Seriously, do it—I’m not going anywhere.

Thought about it? Great! I also asked this question on Facebook, and got answers from a number of coaches and support staff—people who I would consider scientifically literate. Far and away, the most common description of the p-value was that it tells us “whether the effect is down to chance or not.” So, in the caffeine example, a p-value of <0.05 tells us that there is a less than 5% chance of these results being down to chance. Why 5%? Well, it’s arbitrary, but it’s a nice round number that has caught on, so it gets used.

Here’s the problem: That explanation is not quite correct.

To explain why, I need to explain what really happens when most people do an experiment. The common method used in research is that of Null Hypothesis Significance Testing (NHST). This means that we have two hypotheses: the null hypothesis and the alternative hypothesis. So, in my caffeine example, my hypotheses are:

1. Caffeine improves vertical jump height (alternative hypothesis).
2. Caffeine does not improve vertical jump height (null hypothesis).

When I’m calculating the p-value, what I’m really doing is deciding whether or not I can reject the null hypothesis. Scientific research is set up to disprove the null hypothesis. If p≤0.05, I can reject it, if its >0.05, I can’t. Rejecting the null hypothesis means that there is a difference between the groups.

What the p-value actually tells us is the probability of getting a result as extreme as this, and the null hypothesis being correct. When p=0.05, this means there is a 5% chance of getting a result as extreme as this and the null hypothesis being correct. If p=0.01, there is a 1% chance of getting a result that extreme and the null hypothesis being correct. Essentially, we’re getting the probability of falsely rejecting the null hypothesis, which is a false positive, known as a Type-I error.

P-Values and the Size of the Effect

So far, perhaps we have been largely arguing about semantics. Let me introduce the next question for you. Returning to my caffeine trial, I add an additional group of athletes. The first group take 3mg/kg or placebo. The second group take 6mg/kg or placebo. Here is the main finding:

Subjects jumped significantly higher in both the 3mg/kg (p=0.04) and 6mg/kg (p=0.004) caffeine trials compared to placebo.

My question to you is this: Is 6mg/kg of caffeine more effective than 3mg/kg of caffeine at improving vertical jump height?

Again, when I asked this on Facebook, most people answered yes. The correct answer is: you can’t tell. This is the main issue with p-values and NHST; they don’t tell you the size (or, more correctly, the magnitude) of the effect. So, while we can be more confident about correctly rejecting the null hypothesis in the 6mg/kg trial, we can’t be more confident that the effect was greater.

The main issue with p-values and NHST is that they don’t tell you the magnitude of the effect. Share on X

To repeat, the p-value tells us nothing about the size of the effect. Something having greater significance does not necessarily have a greater effect. This is important when it comes to translating science into practice. Whilst 6mg/kg caffeine might significantly (p<0.05) improve vertical jump height, if the size of this effect is just 0.1cm, this might not have any real-world effect. For example, if you’re a high jumper, you can only move the bar higher in 1cm increments, so jumping 0.1cm higher has no real-world impact for you.

Similarly, I once read a research paper examining the use of a specific type of training on mood. Mood was determined by a questionnaire, with each person scoring themselves out of 10. The training significantly improved (p<0.05) mood, but the average improvement in the training group was 0.2. Given that the scale used was 1, 2, 3 … 10, an improvement of 0.2 means that you would need five subjects to get a real-world improvement of 1 (i.e., going from 1 to 2, or 9 to 10). So how effective is the training really?

The scientific community is starting to wake up to the issues with p-values and NHST, and I am certainly not the first person to notice it. The American Statistical Association released a statement on this last year. Sports scientist Martin Buchheit, from Paris Saint Germain Football Club, recently authored a great editorial on the subject. In recent years, the godfather of statistical analysis in sports science, Will Hopkins, has proposed the use of Magnitude Based Inferences (MBIs) to help practitioners understand the true size of the effect of an intervention, in order to determine whether it is useful or not. Journals are starting to slowly move away from just the reporting of p-values, requiring effect sizes to also be used.

All of this allows for the better use of science in sport. Right now, my concern is that athletes and coaches only look for statistical significance, and not real-world significance. An effect can be statistically significant due to a large sample size, but have no real-world effect. Conversely, an intervention can have no significant difference in terms of statistics (usually due to a small sample size), but have a large real-world effect. More pertinently, when comparing two different interventions, the difference in p-values between them doesn’t really tell us anything about the magnitude of these effects, which is more important.

Something that has a greater significance does not necessarily have a greater effect. Share on X

Finally, to complicate things further, recent research has illustrated that there is a significant amount of inter-individual variation in response to an intervention, such that even if an intervention has no statistically significant effect for the average between groups, the effect can be huge for individuals within a group. As confusing as this might be, having a working knowledge of what a p-value is, and knowing the limitations of it, are crucial to successfully translate science into practice.

Recommended Reading:

The problem with p values: how significant are they, really?

Since you’re here…
…we have a small favor to ask. More people are reading SimpliFaster than ever, and each week we bring you compelling content from coaches, sport scientists, and physiotherapists who are devoted to building better athletes. Please take a moment to share the articles on social media, engage the authors with questions and comments below, and link to articles when appropriate if you have a blog or participate on forums of related topics. — SF

 

In an earlier blog entry, we discussed practical steps to take to enhance the accuracy and reliability of data collection in strength training, practice, recovery, and competition. The core concept of enhancing data reliability centers on the steps that coaches, trainers, practitioners, and sports scientists will take once the data is collected and organized, and primary analysis begins. With so many tools and methods available to collect data in sports, practice, and training, what can coaches and sports scientists actually do to start assessing and improving performance?

A practical starting point is assessing how data is being collected and organized in research conducted on sports performance. Popular technology such as global positioning systems (GPS), accelerometers, and heart rate monitors (HRM) are increasingly prevalent in research performed on team sports performance. However, the concepts used by researchers with these tools can be broadly applied to physical activities beyond competition and practice alone.

In 2014, Dellaserra et al., published a review of integrated technology (IT) use in team sports that highlighted opportunities, challenges, and future directions for their use in performance analysis [1]. Understanding the foundational methodology of data organization of both objective and subjective metrics is a key first step to effective performance analysis. As they organize all objective and subjective data, each practitioner will ultimately work to identify key performance indicators (KPIs) matching their program’s goals and philosophies. Forming KPIs is an essential portion of the sports science analysis process, and should be done on an individual process. The KPIs of one particular university, team, or facility may be totally different than the KPIs from another, yet each set will optimally serve each institution based upon their needs.

This second installment of the sports performance article series outlines and adapts the main points of the Dellaserra et al. review to provide useful steps as to how data can be organized once you and your staff have started collecting data on performance, training, recovery, or readiness. Consider the following elements once you start data collection: summarization, quantification, comparisons, and bioenergetic demands.

Summarization

After data is collected during activity, practitioners can begin organizing it into categories. This process may also be provided or supplemented by using the software accompanying the specific IT devices used. Data collected manually can be input to existing athlete management systems (AMS) or simple spreadsheets. Summarization can occur each day post-activity as data is uploaded via interfaces provided by each manufacturer of the tech devices used. Practitioners will then be able to produce summaries from the data collected during the activity of that day.

The basic descriptive summaries of totals, minimums and maximums, means, medians, and all other values of parameters measured can be classified by the following categories and subcategories:

Individual Parameters

1. By individual player: for example, player A, player B, etc.

Grouping Parameters

1. By position groups: such as all offensive linemen, freshman midfielders, or transfer point guards.
2. By depth chart standing: such as all first-string players, all second-string players.
3. By depth chart and position: such as all first-string guards, all redshirt pitchers.

Activity Parameters

1. By drill or practice sequence: such as Individual or Grouping parameters during a specific drill. For example: player A during 1-on-1 drills, first-string wide receivers during 7-on-7 drills, or all central defenders during set-piece drills.

Chronological Parameters

1. By day of the week: such as Monday practice, “game day minus 2,” walk-through session, summer conditioning, etc.
2. By week of the season: such as week 1 of pre-season camp, or week 3 of the season versus opponent “X,” or bye week.
3. By portion of the season: such as daily doubles or pre-season, post daily doubles preseason, in-season, post-season conference championship, playoffs, and bowl preparation.
4. By time of year: such as off-season training periods, off-season practice periods, pre-season camp, in-season.

Injury Status

1. By injury designation: such as pre- and post-injury, by rehab process or phase of treatment.

Quantification

Summarization of information can be applied to many parameters reported by IT devices or manual data collection in ways that produce discrete or continuous data. Remember, discrete data is data that can only occupy one distinct and separate value, like the number of pitches thrown (because you can’t throw half a pitch), number of repetitions completed in an exercise (because half reps are not counted in a certain test), or sleep quality rating on a scale (because you only offer a 5-point scale on sleep quality). Continuous data can be measured and take on any value on a scale possessing intervals between whole values, such as a bodyweight of 185.5lbs (because there are weight intervals between 185 and 186 pounds), or running a 40-yard dash in 4.44 seconds (because there are other time intervals between 4.40 and 4.50 seconds) [2,3].

Metric quantification has been part of strength & conditioning programs for decades. Share on X

The data points serve as quantifications of these parameters and are represented by numbers in the form of maximums, minimums, ranges, totals, and averages. As noted above, these quantifications can apply to both activity parameters and chronological parameters dealing with various individuals or groupings. Specific parameters may differ by software or methodology; however, several main themes include:

• Maximums – acceleration rate, speed, heart rate, heart rate recovery, heart rate variability, skin/core temperature, mechanical intensity, perceived exertion, jump height or distance, weight lifted for specific reps, and physiological intensity.
• Minimums – speed, heart rate, skin/core temperature, mechanical intensity, physiological intensity, sprint time, and training intensity.
• Ranges – heart rate, skin/core temperature, mechanical intensity, and physiological intensity.
• Totals – acceleration count, distance covered, distance covered within speed ranges, time spent within speed ranges, time spent within heart rate ranges, caloric expenditure, volume of weight lifted, mechanical load, physiological load, and training load.
• Averages – acceleration, speed, heart rate, heart rate recovery, heart rate variability, skin/core temperature, mechanical intensity, physiological intensity, and training intensity.

Keep in mind that metrics quantification has been part of strength and conditioning programs for decades. The quantifying method answers questions such as: How much weight was lifted? How fast was the agility test performed? How many repetitions were performed? Objectively quantifying workloads is an essential element of measuring progress in physical performance. As introduced in Part 1 of this blog series, there are times when more subjective data is collected. In this case, the same procedures apply to organizing subjective metrics such as surveys and RPE scales.

Comparisons

Quantifications allow the practitioner to create a framework of what occurred during the measured activity. As these figures are summarized, comparisons can be made to assess the importance and implications of the data. Practitioners can use various quantifications of the individual, grouping, activity, and chronological parameters to facilitate these comparisons, which may include:

Intra-Subject Comparisons

1. Using the quantification of individual parameters to compare session-to-session values of maximums, minimums, ranges, totals, and averages of various performance markers for an athlete.
2. Using quantifications of individual parameters of an athlete to compare performance prior to injury, leading up to injury, and during the rehabilitation and return to play protocols for an athlete.
3. Using quantifications of individual parameters to compare various chronological parameters, including values reached during the off-season, pre-season, and various portions of the competitive season.

Inter-Subject Comparisons

1. Using the quantification of individual parameters to compare like values of maximums, minimums, ranges, totals, and averages of various performance markers between two athletes. This may include one starter versus another starter of the same position, or one starter versus a non-starter of the same position. This could also compare athletes of different positions.
2. Using the quantification of grouping parameters to compare like values of maximums, minimums, ranges, totals, and averages of various performance markers between two groups, activities, or chronological parameters.
3. Using quantification of individual or grouping parameters to compare like values of performance markers achieved during training activities, practice activities, and competition.

Bioenergetic Demands

Quantified information of individual parameters of performance markers can allow practitioners to gain insight into the bioenergetic demands of the activities measured. Practitioners with a strong background in bioenergetics and exercise physiology will recognize the main energy system contributions to various types of activities. These may include anaerobic qualities such as alactic power and alactic capacity, or aerobic qualities such as aerobic capacity and aerobic power.

While understanding the various movement qualities and demands of each position, the practitioner may be able to gain insight from data on the distribution of workloads of the various bioenergetic systems. As information is gathered from training, practice, and competition settings, practitioners can compare workload distribution of each setting to determine if training and practice are preparing the athlete for the bioenergetic demands of the actual competition. When assessing the physiological or bioenergetic demands of an activity for an athlete, the practitioners may consider the following elements:

• Number of bouts: The number of repetitions during each training session, drill, or game taken by the athlete. This information is used to help establish volumes of training within specific intensity parameters with such movements as accelerations, speed, changes of direction, and other movement classifications that can be associated with specific bioenergetic demands.
• Duration of bouts: The length of time each repetition lasts during each training session, drill, or game. The information is used to further help establish volumes of training within specific intensity parameters. As more information is gathered from the number and duration of each bout, a clearer picture of the bioenergetic demands of the activity can be formed.
• Timing or frequency of bouts: The time interval between repetitions during each training session, drill, or game. Information on the timing and frequency of bouts during these activities can help further describe the intensity of the activity when other mechanical or physiological parameters are known. This is done by establishing the length of rest intervals between bouts, given the demands of each bout. The demands are further described by parameters of the activity that include speed, acceleration, or heart rate.

Criterion Performance

As bioenergetic concepts are used when monitoring changes and types of performance, practitioners must have data to serve as a reference point to make necessary comparisons. The establishment and use of criterion performances for individual athletes in each activity may assist the practitioner in this process. These criterion performances may deal with both generalized and specific data, such as maximums, minimums, ranges, and totals of physical performance markers.

Criterion performances can be established from daily best marks to monitor acute fatigue, while using all-time best marks might allow insight into states of chronic fatigue or overall physical preparedness levels. These criterion values may also be of importance during the rehabilitation process, for practitioners to use performance markers prior to injury to compare with the athlete’s current progress. Factors being assessed during training, practice, or competition will fall into one of the following categories:

Training

1. Warm-up periods and all related rehabilitative or restorative protocols (stretching, range of motion, submaximal corrective exercises).
2. Speed training and all variations surrounding sprinting, mechanics of sprinting, and drills related to the development of speed and agility during locomotion.
3. Plyometric training and all variations, including jumps in all planes of motion, the shock training method, medicine ball throwing variations, and any other exercise focusing on optimizing the amortization phase.
4. Resistance training and all variations, including strength training, power development, hypertrophy, and specialized endurance using free weights, machines, bands, chains, and any other added outside force on the body.
5. Conditioning and all variations, including all activities focusing on the development of the cardiac system and aerobic energy system.

Practice

1. All practice warm-up periods.
2. Specialized work periods such as kickoff in football, free throws in basketball, set pieces in soccer, etc.
3. Individual position-related drills, such as only running backs practicing hand-offs, or only goalies defending shots, or only point guards practicing ball handling.
4. Group drills, including 7-on-7 offense versus defense, 3-on-3 drills in basketball, small-sided games in soccer.
5. One-on-one competition periods, including centers versus centers in basketball, wide receivers versus corners in football, or counter attack defending in soccer.
6. Team activities featuring live action in various situations such as two-minute hurry-up offense in football, final-play simulation in basketball, or sudden death in hockey.
7. Non-situation-specific drills, including form tackling, free throws, rondo-passing, and other general skill development sessions.

Competition

1. Pregame warm-up periods.
2. Special-activity periods and specific designations such as kickoff or punt return, free throws or inbounds, set pieces, or power plays.
3. Offensive or defensive drives, possessions, or efforts.
4. Chronological considerations such as quarter or half, or specific time range of a game such as the last six minutes of competition in a half or game.

Practitioners must find the exact physical and physiological parameters to monitor for each individual during periods outlined above, before electing to establish a criterion performance for these activities. Practitioners should use applied knowledge of factors affecting performance of the activity to determine when an individual athlete has achieved a personal best in a meaningful activity. The establishment of these criterion performances also allows the practitioner to lay the framework for future analysis of relationships between physical and physiological markers with objective performance outcomes.

Pay considerable attention to the relevant performance markers within a specific training program. Share on X

Establishing individual criterion performances also allows practitioners to compare athletes within the same group during the same activities. These comparisons might lend insight into strengths and weaknesses of each athlete as they compare to others in the same position group. This information is useful when designing training programs with the understanding of the underlying physical and physiological mechanisms that contribute to the activity.

Considerable attention should be paid to the relevant markers of performance within a specific training program. Establishing KPIs also allows practitioners to focus on more-efficient data collection, rather than opening the floodgates to never-ending data streams. There is absolutely a time and a place for expanding performance analysis to include more data, but strengthening the fundamentals of your data collection process must take precedent. The creation of program-specific KPIs lies at the heart of sports science, but this presents a question at the heart of the matter:

What is an operational definition of sports science that captures its true effect on performance?

This definition fits well, and gives consideration to the measurement factors outlined above:

Sports Science: The discovery, interpretation, and communication of meaningful data affecting athletic performance.

Discovery: through measurement, assessment, and monitoring of athletes.

Interpretation: by field experts with content knowledge of the relevant subdomains of the sport, training, rehabilitation, nutrition, and psychology.

Meaningful: content knowledge supplied by field experts influencing the practice of “modeling” within the performance process for athletes.

While endless measurements, assessments, and monitoring of athletic performance can take place, much of the data is useless without context. This highlights the need for educated practitioners with a diverse knowledge base to help “connect the dots” of data across fields. As the data stream comes in from all areas, defining a method for analysis becomes paramount. The simple procedure of the Performance Analysis Progression will meet the needs of practitioners looking to establish a foundation for their analysis program:

Performance Analysis Progression

I developed this procedure during my time as the sports science coordinator at a Division I university. Many coaches, scientists, and researchers have their own customized approaches to looking at their data, and I developed it out of the need to look at multiple streams of data concurrently, within context.

There is a simplistic progression in the order of asking questions about the data you collect, which also highlights the importance of collecting, organizing, managing, and visualizing your data via an AMS system. Consider the following progression when looking at the data from your athletes and, based on the previous descriptions of each step, define what it is you are looking for from your data:

 

 

 

 

As multiple data streams are combined to analyze performance and a system is put in place for making inquiries, managing data streams by connecting data sources and endpoints will enable practitioners to streamline this process. This element highlights the importance of an AMS that allows for customization to meet the needs of the users and the organization.

In my own experience, which is shared by countless practitioners, I grew tired of spending more time in front of a computer than out with athletes. Many strength coaches can likely relate to the reality of juggling many responsibilities at once beyond our primary duties. This includes: collecting endless streams of questionnaires at the last minute, sifting through piles of workout sheets to find one or two particular numbers, and connecting Google documents and downloading data. This is in addition to attempting to manage countless other streams that may or may not offer clarity. Not only did this process drive the need to create program-specific KPIs, but it also highlighted the need to streamline and simplify the process to meet foundational needs of sports science.

Out of this chaotic experience, I designed my own AMS, Voyager. I was familiar with other methods of managing data streams at a very high level, as well as other athlete management systems serving a high level of functionality, but I needed a simplified system for foundational sports science methodology. As I have mentioned before, the “bells and whistles” are necessary at a certain point, but there is great power in establishing a firm foundation of connectivity between athletes, strength coaches, sports medicine, sports nutrition, sports psychology, team managers, and sports scientists alike.

Analyzing the effectiveness of a training program, treatment modality, recovery intervention, or nutritional plan is not an attack on the practitioner implementing the program, but rather, it is part of the pursuit of performance that is a necessary trait of an elite coach.

As we highlight the need for connectedness and a streamlined process made possible by athlete management systems, the practicality of the Performance Analysis Progression is revealed. Think of the take-home concepts from the Performance Analysis Progression: What are we looking at? Why are we looking at it? What is it saying? What should we do? Did what we do actually work? The last question is troubling for some, because it requires that we—as strength and conditioning coaches, sports medicine practitioners, and sports scientists—assess the methodology we implement on athletes.

Nearly every good coach I have worked or spoken with over the last 15 years assesses their own performance and will not hesitate to improve their own training process. The best coaches I have worked or spoken with are tireless in their assessment of the performance of their athletes, and embrace the need to continue to refine their abilities as a professional. Therefore, sports science, as defined above, is part of a natural process that allows for the advancement of athletic performance and coaching ability. Analyzing the effectiveness of a training program, treatment modality, recovery intervention, or nutritional plan is not an attack on the practitioner implementing the program, but rather, it is part of the pursuit of performance that is a necessary trait of an elite coach.

During this current offseason period, I employed the Performance Analysis Progression while utilizing Voyager to organize in-house KPIs, Omegawave data, and training and wellness data, in addition to custom sports medicine assessments. I should also mention we had the opportunity to utilize a Freelap timing system and received exceptional, timely support from Christopher Glaeser on how to maximize use of the system to meet our specific needs. This process helped connect me with a strength and conditioning staff, a sports medicine staff, remote coaches, and a group of NFL-draft hopefuls and NFL off-season athletes.

While employing a new system and methodology creates many challenges, the connectivity and streamlining of our process based on the methodology outlined in this article allowed our team of professionals to further examine our own process. Within two weeks, we were able to identify needs for athlete education, project future adjustments in training load, and visualize progress for our athletes and their agents, coaches, and staff. We placed a particular emphasis on maximizing our use of the Omegawave Coach system, a system I have used as both an athlete and a coach. There are many ways to apply information from Omegawave screenings, wellness questionnaires, and athlete interaction to inform the training process, which will be the focus of a final article in this sports science methodology series.

Since you’re here…
…we have a small favor to ask. More people are reading SimpliFaster than ever, and each week we bring you compelling content from coaches, sport scientists, and physiotherapists who are devoted to building better athletes. Please take a moment to share the articles on social media, engage the authors with questions and comments below, and link to articles when appropriate if you have a blog or participate on forums of related topics. — SF

 

References

1. Dellaserra, C.L., Yong, G., & Ransdell, L. (2014). “Use of integrated technology in team sports: a review of opportunities, challenges, and future directions for athletes.” Journal of Strength & Conditioning Research (Lippincott Williams & Wilkins), 28(2): 556-573. doi: 10.1519/JSC.0b013e3182a952fb.
2. “Discrete and continuous random variables.” (2017). Khan Academy. Retrieved 20 March 2017.
3. “CaSQ 3B – Numerical Data: What’s The Difference Between Discrete and Continuous?” (2017). Retrieved 20 March 2017.

Introduction, Central and Chronic Fatigue

Sentient organisms are capable of perceiving the status of their moment-to-moment existence. Humans have the ability to compare and contrast the present moment with past experiences, and to rate the quality of such experiences. Many people exist in a state referred to as “chronic fatigue syndrome,” where they are inescapably held in a condition of feeling reduced energy to perform tasks and receive no joy during consciousness.

Anyone who has exercised to the point where they are reaching towards the upper limits of physiology has perceived acute fatigue, which decreases the ability to maintain a specific intensity level of output. According to Taylor et al. (2016), fatigue is a biological warning that signals an organism to reduce physiological output and move towards a resting state. Fatigue can result in performing a task slower or with less coordination, or in the complete inability to perform a task. Fatigue is objectively known to be involved with the performance of a task when there is an increase in EMG readings associated with that task.

Subjectively, fatigue can be said to be present when the participant perceives muscle pain, overall discomfort, or increased effort to perform a task (Taylor et al., 2016). Taylor et al. (2006) stated that factors leading to reduced performance resulting from fatigue are present at every level of the brain-muscle pathway. Meeusen and De Meirleir (1995) reported that exercise clearly alters neurotransmission, and does so by changing the concentration of different neurotransmitters. Such a change in neurotransmission has a direct impact on fatigue.

Chaudhuri and Behan (2004) stated that mechanical work output is a dependent variable affected by many factors. Internal (limbic system) and external (incentives) sources of motivation; feedback from motor, sensory, and cognitive systems; and environmental factors (external…temperature, internal…homeostatic state), are the primary factors that influence work output. The ability to execute and maintain voluntary activity depends on the smooth flow of afferent, interneuron processing, and efferent nervous activity in the primary sensory and motor systems. Any subsystem involved with the relay of information can contribute to fatigue.

Individuals with normal levels of internal and external motivation, and proper sensory and motor functioning, may still have reductions in work output due to limitations such as endocrine abnormality or autonomic dysfunction. Those who display abnormal levels of exertional fatigue, muscular fatigue, and exercise intolerance are categorized as having chronic fatigue syndrome, and are most likely displaying symptoms of neurological disease that is the result of mutation within the mitochondrial DNA. Central fatigue and chronic fatigue syndromes share many common threads, and are often grouped together within the literature (Chaudhuri and Behan (2004). Chaudhuri and Behan (1998) reported that approximately 80% of patients with chronic fatigue had a previous infection that likely led to presentation. These individuals typically have very low levels of motivation, experience anhedonia, struggle with sleep (apnea and hypoxia may be factors), and suffer from depressive symptoms.

Central and chronic fatigue syndromes share many common threads, and are often grouped together. Share on X

According to Chaudhuri and Behan (2000), central fatigue syndrome presentation is the result of hypothalamic, pituitary, and diencephalon abnormalities. Barron, Noakes, Levy, and Smith (1985) reported that development of sudden and profound central fatigue in athletes due to overtraining involves hypothalamic and neuroendocrine factors. In hypothalamic-pituitary driven cases of central fatigue, changes in body weight and sleep pattern are typically present. Often, centralized fatigue syndromes are the result of diseases that affect the basal ganglia and connected circuitry of the amygdala, thalamus, and frontal cortex. Typically, the connection between the prefrontal cortex and the thalamus is disturbed in these conditions.

Bruno, Crenidge, and Fick (1998) reported that in post-viral central fatigue circumstances, damage will take place in dopaminergic pathways, the reticular activating system, the midbrain, the brainstem, lenticular nuclei, the basal ganglia, thalamus, hypothalamus, and cortical motor areas. Reductions in leptins, substance P, and prostaglandins are associated with hypothalamic-pituitary central fatigue. Fatigue levels can also be impacted by circulating proinflammatory cytokines. These cytokines can be activated when there is a decrease in corticotropin-releasing factor and decreased circulating cortisol.

According to Steinman (1993), acute stress seems to be helpful, based on the fact that there will a spike in cortcotropin-releasing factor, which has an antagonistic effect on the T-helper-1 cell response (a proinflammatory cytokine); however, prolonged chronic stress seems to downregulate this system. This system is downregulated in patients with chronic fatigue syndrome (Scott and Dinan, 1999), post-traumatic stress disorder (Yehuda, 2002), fibromyalgia (McEwan, 1998), and postpolyomyelitis (Bruno, Sapolsky, Zimmerman, 1995). According to Yehuda et al. (2002), low cortisol concentrations following significant psychological or physical trauma were predictive of post-traumatic stress disorder. Low cortisol levels ultimately could impact the glucocorticoid receptors within the hypothalamic-pituitary network by increasing binding sensitivity. Such a change in receptor sensitivity could heighten a state of constant vigilance and feed into a constant stress response.

According to Buckwald, Herreld, and Ashton (2001), the concordance rate among monozygotic twins for the development of centralized fatigue syndrome symptoms was approximately 50%. This suggests that a genetic element, along with environmental factors, is at play in development of this condition. Therefore, certain individuals would be more at risk in terms of moving into a chronically fatigued state due to stress and other environmental influences (e.g., infection).

In susceptible individuals, environmental stressors will cause changes in the hypothalamic-pituitary-adrenal axis and the norepinephrine system. Shannon, Flattem, Jordan et al. (2000) reported that depleted norepinephrine levels, or decreased sensitivity of the receptor for norepinephrine, results in fatigue and depression in animals. Chaudhuri and Behan (2004) stated that organisms have opposing directional responses regarding development of fatigue with acute versus chronic stress experience, where chronic stress moves animals towards chronic fatigue syndromes.

Changes in synaptic receptor sensitivities to corticotropin-releasing factor, serotonin, and norepinephrine establish the nature and severity of the fatigue experience. In humans, prolactin is also secreted under stressful circumstances from the anterior hypothalamus. Dopamine is known to have an antagonistic effect on prolactin secretion. This has led some to believe that dopamine may have a role in combatting elements of the chronic fatigue response system (Chaudhuri and Behan, 2004).

Central Fatigue from an Acute Work Perspective, Examining Neurotransmitters

Newsholme et al. (1987) were the first to report on the notion of central fatigue within acute mechanical work circumstances. They stated that central fatigue was a serotonin-mediated phenomenon, where rising concentrations of serotonin led to an increased perception of lethargy, sleepiness, and reduced motivation. The subsequent investigation has led to mixed results in validating the serotonin-centric hypothesis of central fatigue. However, the consensus scientific perspective points to neurotransmitter concentrations and specific receptor binding activity in specific parts of the brain as being the driver of demonstrable organism fatigue resulting from central pathways. The following section will analyze the findings within the literature on the impact of serotonin, norepinephrine, and dopamine on central fatigue in acute work output.

Neurotransmitters are the chemical messengers that relay information from one neuron to the next within the central nervous system. In regards to acute central fatigue models, monoamine neurotransmitters, which include serotonin, norepinephrine, and dopamine, are believed to be the key players. According to the meta-analysis done by Taylor et al. (2016), the result of central fatigue is either decreased voluntary muscle force or maintenance of the same muscle force via a compensatory strategy somewhere in the neural system.

The primary factor leading to central fatigue is an exercise-induced alteration in monoamine neurotransmitter concentration in specific parts of the brain. The most difficult factor in determining the exact role of the monoamine neurotransmitters on fatigue is that each monoamine causes different responses depending on which region of the brain the binding to receptors is taking place in. To provide clarity on this topic, it becomes prudent to analyze each neurotransmitter and determine what the critical regions of the brain are for receptor binding on fatigue.

Serotonin

Perhaps the two most threatening environmental factors on survival of an organism are temperature and pH. Humans belong to the category of animals known as homeotherms, which have to maintain a relatively constant body temperature, often via internal heat production. Regarding monoamine neurotransmitters and internal heat production, Soares, Coimbra, and Marubayashi (2007) found that increased concentration of serotonin in the preoptic area is associated with greater heat production during exercise. Newsholme et al. (1987) first reported that central fatigue was a serotonin-based phenomenon. Newsholme, Blomstrand, and Ekblom (1992) claimed that the mechanism of central fatigue was elevated tryptophan levels that led to increased serotonin concentrations, and that serotonin precipitated feelings of lethargy and reduction of motivation.

Soares, Lima and Coimbra (2003), and Soares, Lima, and Coimbra (2004) found that increased hypothalamic tryptophan levels precipitated fatigue and were related to a rise in core temperature marked by increased internal heat production and decreased ability to dissipate heat to the environment. Gisolfi and Moura (2000) and Zhang et al. (1997) found that dissipation of heat from the body is more important for temperature regulation compared to heat production during exercise conditions. Nielsen et al. (1997), and Walters et al. (2000) reported that CNS drive towards exercise work output was reduced by elevated core temperature, and that hyperthermia led to subjective discomfort and lethargy. This decrease in CNS outflow and motivation was believed to be a safeguard against allowing dangerously high brain temperatures to occur. Rodrigues et al. (2003) showed that heat storage rates in rats was the main limiting factor in running performance with thermo-neutral and hot environments.

Coimbra and Migliarini (1986), Ferreira, Marubayashi, and Coimbra (1999), Lin et al. (1998), and Santos, Leite, and Coimbra (1991) all determined that the preoptic area and the anterior hypothalamus are the two parts of the brain most responsible for thermoregulation. These parts of the brain are also critical for evaluating and regulating external thermal inputs with metabolically produced heat. Lin et al. (1998) found that injecting serotonin into the preoptic area and hypothalamus of rats increased core body temperature. Soares, Coimbra, and Marubayashi (2007) reported that rats injected with tryptophan into the right cerebral ventricle showed decreased running performance along with increased core temperature and increased concentrations of serotonin in the preoptic area and hypothalamus, compared to rats injected with saline (control condition).

Furthermore, Soares, Coimbra, and Marubayashi (2007) showed that serotonin concentrations were also increased in the hippocampus of rats injected with tryptophan, compared to control. Running time to fatigue was directly correlated with serotonin concentrations in the hippocampus, through a mechanism that seemed to have nothing to do with hyperthermia. Overall, a fatiguing mechanistic cascade appears to exist between tryptophan levels in the brain, which act as a precursor to serotonin, which binds to the preoptic area and the hypothalamus for a heat production element inducing fatigue, as well as a separate serotonin effect on the hippocampus, which has some other fatigue-inducing response. Serotonin concentrations in these areas appear to have a linear relationship with the onset of fatigue.

Serotonin concentrations in these areas appear to have a linear relationship with fatigue onset. Share on X

Regarding the mechanism by which serotonin concentrations in the hippocampus impact fatigue, conclusive evidence still remains elusive. Meeusen et al. (1996), Takahashi et al. (2000), and Wilson and Marsden (1996) found a relationship between serotonin levels in the hippocampus and locomotion. Serotonergic neurons that descend from the hindbrain to the spinal cord appear to be involved in central pattern generator (CPG) neural activity controlling locomotion. Without serotonin being present in these neurons, locomotion capabilities are lost.

Soares, Coimbra, and Marubayashi (2007) found that rising concentrations of serotonin in hippocampal neurons lead to a linear increase of fatigue in running rats, and reported that mechanisms need further elaboration. Soares, Coimbra, and Marubayashi (2007) reported that their findings call into question which neurons associated with the serotonergic system are responsible for fatigue. Perhaps there is interplay between multiple systems; perhaps only one set is truly responsible. Consideration of the fact that other neurotransmitters in other parts of the brain may be modifying these effects as well must be considered.

Sharples, Koblinger, Humphreys, and Whelan (2014) reported that monoamines promote locomotion and influence the rhythmicity of locomotion. This influence occurs via binding to the corticospinal tract as well as hind brain regions, and motoneurons. Cotel, Exley, Cragg, and Perrier (2013) found that serotonin contributes to fatigue primarily through binding to motoneurons. According to Johnson et al. (2004), and Perrier, Rasmussen, Christensen, and Petersen (2013), synapses from descending tracts of serotonergic neurons are adjacent to the dendrites and cell bodies of motoneurons. Serotonin binds to the 5HT2 and 5HT1A receptors in the motoneuron system. 5HT2 receptors are excitatory and appear to be the receptor that allows serotonin to be involved with promoting locomotion. When serotonin levels reach very high levels, a spillover effect will be seen, and serotonin will begin binding to 5HT1A receptors (which are known to be inhibitory) and will prevent motoneuron firing.

When examining the effects of serotonin on fatigue from the perspective of the motoneuron, it appears as though there are two distinct ways in which this occurs. Fornal, Martin-Cora, and Jacobs (2006) showed that, in cats, there is an eventual decrease in concentrations of serotonin with prolonged exercise (removal of the excitatory stimulus at the dendritic binding site). Wei, Glaser, and Deng (2014), through indirect measures with humans, found that serotonin release increases in concentration as the force of muscular contraction increases in exercise (addition of the inhibitory axonal binding site). No studies on humans have directly measured serotonin concentrations in the brain; however, 5HT1A receptors are known to exist in humans, and D’Amico et al. (2015) showed that motoneuron excitability in humans can be reduced via 5HT1A agonist drugs administration.

Dopamine

The original hypothesis on central fatigue related primarily to the effects exerted by serotonin on the system; however, researchers also began to understand that other monoamines were powerful players in regards to fatigue. In 1972, Borg et. al, showed that administration of amphetamines improved performance during exercise. Bailey et al. (1993) demonstrated the importance of increased concentrations and binding of dopamine during exercise. Fatigue in rats was correlated with increased serotonin and reduced dopamine in the brain stem and midbrain. Davis and Bailey (1997) showed that the interaction between serotonin and dopamine influenced central nervous system fatigue. A low ratio of serotonin to dopamine favors improved performance and a high ratio decreases motivation and promotes lethargy, resulting in decreased performance (Davis & Bailey, 1997).

Researchers began to understand that other monoamines were powerful players in regards to fatigue. Share on X

Early studies where researchers administered amphetamines showed significant increases in performance in both animals (Gerald, 1978; Heyes et al., 1985) and humans (Wyndham et al., 1971; Borg, 1972). Watson et al. (2005) investigated the effects of bupropion, a dual dopamine and norepinephrine reuptake inhibitor, during cycling at 18 and 30.1 degrees Celsius. At 18 degrees Celsius, no difference was found between the placebo and bupropion trial. When subjects cycled at 30.1 degrees Celsius, the bupropion group performed 9% faster. Roelands, Hasegawa, Watson et al. (2008) applied the same cycling and temperature protocol and administered methylphenidate to our subjects. At 18 degrees Celsius, no difference in performance was observed between conditions. Methylphenidate administration improved cycling time trial performance in 30 degrees Celsius by 16% compared to placebo. The subjects receiving methylphenidate were able to reach significantly higher core temperatures compared to controls (40.1 vs 39.1 respectively).

Despite reaching significantly higher core temperatures, the experimental subjects reported the same subjective perception of thermal sensation and rating of perceived exertion (RPE) as control subjects. The researchers concluded that the increase in dopamine concentration has an effect on the internal safety switch of the brain regarding thermoregulation. The increased dopamine led to a state where the subjects ignored the potentially harmful effects of increased temperature as well as enhanced power production.

Foley and Fleshner (2008) stated that the reason that you’ll see improved performance in hot environments versus no change in ambient temperatures with dopamine administration is that enhanced dopamine levels will provide an increase in psychological motivation to work harder in a more stressful environment. Increased dopamine levels will offset the negative effects on motivation that are brought on by the stress of heat exposure (Del Arco & Mora, 2009). The mechanism of the ergogenic effect of increased dopamine concentrations is believed to be the result of stimulation of the ventral tegmental area. According to Burgess et al. (1991), rats that received stimulation to the ventral tegmental area demonstrated increased motivation to run on a treadmill compared to rats receiving an electric shock.

Norepinephrine

Roelands et al. (2013) reported that different neurotransmitter concentrations in the brain can lead to different pacing strategies during cycling time trial performance. Subjects with higher concentrations of dopamine in the brain demonstrated higher power output throughout time trial performance compared to control. Conversely, increased serotonin and norepinephrine led to decreased power output during time trial performance. The researchers stated that with increased serotonin, subjects were unable to end the time trial with an extra surge of power output (a kick). This led the researchers to speculate that serotonin may cut off access to some type of reserve capacity of substrate or perhaps decreases the motivation to increase power output (Roelands et al., 2013).

Serotonin, dopamine, and norepinephrine-dominated neuronal tracts innervate different areas of the hypothalamus, including the preoptic and anterior hypothalamus, which are considered the most critical regions of the brain for thermoregulation monitoring and control responses. Quan et al. (1991, 1992) have shown administering norepinephrine into the preoptic area of conscious guinea pigs decreased core temperature via reduced metabolic rate. Roelands et al. (2008) showed that subjects cycled 20% longer after given reboxitane, a norepinephrine reuptake inhibitor, to complete the same amount of work in comparison with the placebo trial. Subjects reported feeling colder before and during exercise under the reboxitane condition, and core temperature tended to be lower during exercise.

When studying the effects of norepinephrine on fatigue, part of the difficulty in the process relates to the fact that administration of drugs, such as reboxitane, exerts simultaneous central (brain) and peripheral (heart and vasculature) effects. Such combined effects can lead to confounds in elucidating the exact central role that norepinephrine plays (increased heart rate could expedite the experience of fatigue). Klass, Roelends, Levenez et al. (2012), Piacentini, Meeusen, Buyse et al. (2002), and Roelends, Goekint, Heyman et al. (2008) have all reported that norepinephrine reuptake inhibitor drugs have shown no effect or negative effect on reducing fatigue during exercise conditions with humans.

The negative effect on performance associated with pharmacologically increased norepinephrine levels is unexpected because of the positive associations between norepinephrine and levels of arousal and sensations of reward (Montgomery, 1997; Meeusen et al., 2006). Actions of norepinephrine on neurons alters serotonergic activity via binding to excitatory a1-adrenoceptors. Activation of the a1-adrenoceptors in the locus coeruleus causes action potentials in the serotonergic neurons in the brain stem and dorsal raphe (Szabo & Blier, 2001). Based on these interactions, the negative effects of norepinephrine on fatigue may be modulated through the serotonergic system of the brain.

Conclusions

Fatigue is a perceived experience that is unpleasant and is associated with decreased performance in physical tasks. Fatigue is induced by situations that are associated with a heightened stress experience. Elevated stress experiences that are short term stimulate organisms and have the ability to improve underlying physiology, and resiliency to future stressors. Stress experiences that are prolonged have deleterious effects on physiological systems. When animals exist in ceaseless stressful environments, they have the potential to develop chronic fatigue syndrome that has a stereotypical subjective component associated with lethargy and the inability to experience joy, as well as a chemical profile objectively linked to altered glucocorticoid levels and receptor abnormalities.

Exercise presents a specific environmental condition wherein the participant moves into an acutely fatigued state that results in the inability to sustain an absolute level of mechanical work output. Chronic and acute physiological state differences present themselves in the examination of many different systems, and are often extremely divergent from one another in terms of desirability on the impact of the overall status of an organism. Despite such differences, some of the mechanisms that lead to an overall state, such as fatigue, whether it be chronic or acute in nature, may find a common denominator.

From a reductionist perspective, central fatigue, whether chronic or acute, appears to involve specific neuronal circuitry, which is impacted by the concentration of specific neurotransmitters in the synapse as well as the binding sensitivity with receptors. While it is extremely early in the examination of the impact of neurotransmitters on fatigue, there appears to be a relationship with monoamine concentrations and perception of fatigue. Maintaining a situation where dopamine concentrations are protected and do not drop to diminished levels appears to be an effective strategy for preventing the movement towards a fatigued state.

Short-term stimulatory activity has the potential to increase dopamine levels. Dopamine appears to have a neuroprotective role against creating an unfavorable glucocorticoid level and aberrant receptor activity situation. Furthermore, dopamine acts in a rewarding manner, and reinforces the behavior that resulted in the initial secretion, thus making it likely that the behavior will be executed again. While this relationship of fatigue resistance and dopamine concentrations appears to be emerging based on the current body of literature, patience and skepticism should guide the overall thought-process regarding causative roles. Behavioral outcomes from neuronal activity driven through neurotransmitter communication systems are modulated by the interaction of many neurotransmitters working together in a concert-like fashion.

We are in the age of the brain in the body of knowledge of exercise physiology. However, this age is in its infancy, and our understanding is both superficial and lacking an overall integrated framework to guide our perspective on individual study findings. Future findings will be transformative in the way that we view chronic and acute states of fatigue, and new methods for manipulating the system will likely present themselves that lead to breakthroughs in physiological output.

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Strength and conditioning coach, Daniel Martinez, recently talked to a roundtable of seven coaches and trainers from four different countries about several sports science topics. This is the sixth and final post in this series of Sports Science Roundtable articles.

Daniel Martinez: Can you give an example of a dialogue or training process that has made a difference in the performance of either a specific team or individual?

Cory Innes: Being in the training environment and the IAPs gives the perfect opportunity for this. An example would be an athlete whose long sprint performance was limited by their speed. Biomechanical analysis showed force production was compromised by an inability to get into a certain position and redirect force. Testing showed a weakness in over-yielding and lack of eccentric force applied appropriately, so between an eccentric-focused block and technical training around this position, we improved speed significantly, which coincided with an increase in long sprint performance. There are many examples of this easily obtained by being in the field and not guessing at what you are trying to improve.

Cory Kennedy: In sport, the outcomes are so complex that I cringe when we try to imply too much impact from a final result. We have been fortunate to help impact some great performances, but even though we don’t like to admit it, likely the same amount of disappointments. With that said, I believe that the system we have built in-house to collect and analyze data (CMJ, IMTP, and various sport specific tests) has had an immense impact on how we do our job.

Being able to toggle between acute (daily and weekly) and long-term changes (month by month over years, in some cases) gives us great perspective on achieving proper tapers or adjusting training if we are in an extended period of stagnation. Being able to reflect on our training regularly with objective measures is humbling, but extremely important for us. We are very transparent with the athletes on this data, so as we do achieve personal bests and the taper lines up, there is a large impact on their confidence as well. This might be more important than the physiology; we just don’t know it yet.

An example could lie in the development of a speed-based athlete (maybe field sports). Looking closely at the progression of splits on timing gates, jump height/distance, underlying reactive qualities inside a jump, and overall strength parameters, allows us to tease out our training direction. If speed is stagnating or slowing its progress and strength is decreasing, we can likely use more strength-speed focused methods to continue our work. If strength is high, and speed is lagging, we can be very specific with mostly unloaded high-velocity movements.

Some people might read this and say it sounds obvious, but how often do you overlay a year’s worth of data for an athlete on these various physical qualities to see how they are interacting? This is the basis of our process, which we believe informs our best decision-making.

Devan McConnell: The biggest example of significant influence was several years ago, as we were just beginning to utilize an HR system. I had a hunch that the way we structured our week, and especially the day before games, was not conducive to high readiness on game day. In a nutshell, the “traditional approach” seemed to result in slow, lethargic starts. However, when we occasionally broke ranks and deviated from this path, our players seemed to respond positively.

Without data, the idea I had put forth didn’t hold much water, and certainly didn’t result in any long-term changes to strategic planning. However, once I could show objective data regarding workloads, readiness scores, and wins/losses relative to the two approaches to structuring practice throughout the week, we made an immediate change to our approach. Not only did this result in performance improvements, but it was the catalyst to really getting great buy-in from the coaching staff, as there was now direct relevance between my data and what they really cared about.

Mike Boykin: While it’s rarely just one specific conversation that leads to continuous long-term improvement, we take reflective conversations, or debriefs, seriously. All the athletes here have a fairly extensive training age, and with that comes a certain set of epigenetic factors that have to be taken into account. In conjunction with their training history, each athlete has had numerous coaches, various beliefs about how they should train (whether these assertions are correct, incorrect, or somewhere in the grey scale between, is beside the point here), and certain lenses through which they view the world around them.

Upon arrival, or at the start of each year, lead coaches and the athletes they work with sit down and review previous years’ performances, conduct personal and environmental assessments, and build strategies to obtain success moving forward. These are usually (although not with every athlete) multi-layered analyses with simple, yet difficult, questions. Clear communication between the coach and athlete, as well as communal objectives, are crucial for long-term success. These initial conversations are followed up with more targeted and specific debriefs as the year goes on, to help clarify micro-objectives and review current training and lifestyle factors.

With our indoor season finishing up, the past month’s competitions have served as a useful barometer for where each athlete is on the actualization of certain abilities. For one athlete, our general goals throughout fall and winter were to stabilize overall health, build communication levels, and learn to love the sport again. From a training-specific standpoint, returning to previous form in training (the past couple of years had seen a drop-off in certain abilities) was a priority before specific performance metrics became the sole focus.

Consistent debriefs, use of the daily monitoring app, blood work, and days missed due to injury all showed that many of our health and wellness factors were progressing steadily in the right direction. However, we had yet to see performance improvements to go with these. After a careful examination of loading parameters for certain abilities critical in the 200m and 400m, we made an adjustment in the volume, intensity, and density of speed, speed endurance, special endurance, and intensive tempo in the training. While there is still plenty of work to do, the improvement within the last three weeks has been promising.

If you listen to the athlete long enough, they will eventually give you the answer. Share on X

Art Horne, a close friend and mentor of mine, told me years ago that, if you listen to the athlete long enough, they will eventually give you the answer. The past three years of my career have shown this to be true time and time again.

Nate Brookreson: The relationship that exists between our strength and conditioning staff and our swimming and diving staff has made a tremendous difference in the success of that team. They place absolute trust in our training process because it is constantly shared, justified, and rationalized, and it is results driven. The swim and dive staff has a detailed macro/meso/micro cycle process that they detail to our staff, which we then complement in training.

We monitor neuromuscular fatigue through the testing of countermovement vertical jumps and look at decrement over the course of the season and how it matches up to more demanding training cycles. We will then monitor bar speeds in Olympic lifts, ground contact times on depth jumps, and vertical jump characteristics, and we enter late-season strength-speed and speed-strength blocks and provide this information to the staff so they can make changes as they see fit in the pool. We then meet daily as we enter our peaking phases for championship events, to discuss our key performers in detail and make sure we are seeing similar results in the pool and in training.

Patrick Ward: I think good examples here probably circle back to some of the wearable tracking technologies and their utilization during return to play processes. I work closely with our team physical therapist to build out training drills that impose certain physiological loads on the players returning from injury, so that we are more certain that we are preparing them for the demands that they will face in practice and during the game. Building positional and player profiles that are specific to ergonomic needs and demands has helped with a lot of this planning, and has made a positive impact in the process.

Since you’re here…
…we have a small favor to ask. More people are reading SimpliFaster than ever, and each week we bring you compelling content from coaches, sport scientists, and physiotherapists who are devoted to building better athletes. Please take a moment to share the articles on social media, engage the authors with questions and comments below, and link to articles when appropriate if you have a blog or participate on forums of related topics. — SF

Strength and conditioning coach, Daniel Martinez, recently talked to a roundtable of seven coaches and trainers from four different countries about several sports science topics. This is the fifth in this series of Sports Science Roundtable articles.

Daniel Martinez: What are some important steps you have taken to impact buy-in from other staff and coaches?

Cory Innes: Get into the field and know your sport inside out; visit them often in their sport environment. This not only shows them you really care about them, but will increase your knowledge and allow deeper, more meaningful conversations about performance with the coach. You need to have the ability to communicate on a deep level with the athlete and coach about their sport, as well as see them in their daily training environment, or you will lose their confidence. You also need to be honest, genuinely caring, and knowledgeable, as well as constantly seeking answers.

Another important step is to be open-minded and allow input from coach and athlete into the training process. Help educate them about what you do and invite them into the gym regularly. These ideas go for fellow staff members, too. Take time to really understand what they do and how they contribute. Let them tell you and don’t assume that you know.

Cory Kennedy: There are many different elements that affect buy-in with coaches, so I will outline a few. First, our training philosophy is built on understanding the athlete’s well-being, and working within that understanding to reach our training objectives. You can’t just say you care—you must show daily that you care about the athlete’s health and overall enjoyment of the process. This comes from robust monitoring, and frequent conversations with athletes and coaches, with the monitoring often just serving as the jump-off point for the conversation.

The second element is regular reporting on workload data or other observations. We try to sit down weekly with most teams, often without a fixed agenda, to update on anything pertinent. There should also be a physical or digital report that goes with it. Finally, be very clear with training objectives when you can. Sometimes you are after subjective qualities that are difficult to measure, and that is OK. Other times, when you have a measurable outcome, state it and stand by it. Then update everyone involved on progress. If you are chasing strength, how much exactly? If speed, how fast? Being very clear with outcomes and results buys a lot of trust.

Devan McConnell: The only thing that I have consciously done to create buy-in is to continuously educate both the staff and the players. I think it is absolutely crucial that I bring the info to them in a way that they can understand, and that is non-threatening. A person in my role must never forget that we are the support for the coaches and athletes; we are here to serve. My job is to inform them of the appropriate information and my interpretation of that, and make it clear that moving forward, whatever the ultimate decision is (speaking specifically of the coaching staff), I will be on board regardless of whether that decision is in line with what my data says. This, in itself, creates buy-in: It might look like a big step backwards from time to time when a coach “just doesn’t get it,” but by remembering that it is ultimately his team, and not mine, it usually ends up being one step back, and two steps forward with regard to the overall buy-in and my ability to have significant influence.

Jonas Dodoo: Education towards high performance. Provide transparency and show vulnerability. Love and patience.

Mike Boykin: We are fortunate at ALTIS that the performance model and details described above are embraced by our staff, including the track and field coaches, strength and conditioning coaches, and therapists. Having interned with multiple S&C coaches in university settings and assisted in the development of a variety of Olympic sports, the common denominator among support staff that receives the greatest buy-in from other staff and coaches is the ability to speak a common language. The better you understand what the lead coach is looking to accomplish and the methods they will use to do so, the clearer you can portray your message in a way that is meaningful to them.

The common denominator among support staff that receives the greatest buy-in from other staff and coaches is the ability to speak a common language. ~Mike Byokin

Nate Brookreson: I have been deliberate with my communication and kept ego out of the way. I have always kept conversations focused on the well-being of the athlete so that we avoid agendas that are divisive and opinionated. With regard to staff, I think of it less as buy-in and more as “how are we going to provide the best service for our student-athlete and provide a galvanized message to the sport coach?” I make sure that we address specific topics centered on creating a robust and proficient athlete, and what our roles and responsibilities are in this process. With athletic training, that might be how we can better screen and gather information on the athlete up front and over time, how we can complement each other in terms of corrective/exercise selection, and how to periodize the use of recovery strategies and modalities. With nutrition, it is centered on optimizing blood profiles, educating the athlete on food choices that maximize their training adaptations, and teaching them to create and maintain good nutritional strategies.

Buy-in from sport coaches revolves around asking them to articulate what questions they might have about their athletes and how we can answer those questions using data from practice, competitions, or training; providing a detailed analysis of the yearly plan and our rationale behind our choices in training; and being honest with them regarding practice planning. Buy-in is earned by making sure that their athletes are ready to meet the challenges that they present to them in training, which requires conversation about their goals, training philosophy, and important competitions. No matter how much is going right, concerns will always arise as a season passes. It’s my job to make sure they understand the long-term training goals.

Patrick Ward: We create reports that take the analysis and put pieces of it into a more consumable form for staff and coaches. Presenting information in meetings has been helpful to provide deeper context around what they observe in the basic reports. It also allows for discussions on which players may need more assistance from staff to maintain health and well-being while going through a grueling season.

The next installment of this Sports Science Roundtable series is: “Making a Difference in Athletic Performance.”

Since you’re here…
…we have a small favor to ask. More people are reading SimpliFaster than ever, and each week we bring you compelling content from coaches, sport scientists, and physiotherapists who are devoted to building better athletes. Please take a moment to share the articles on social media, engage the authors with questions and comments below, and link to articles when appropriate if you have a blog or participate on forums of related topics. — SF

Strength and conditioning coach, Daniel Martinez, recently talked to a roundtable of seven coaches and trainers from four different countries about several sports science topics. This is the fourth in this series of Sports Science Roundtable articles.

Daniel Martinez: What type of monitoring do you and your staff implement and how does this either inform or alter your process?

Cory Innes: We use an athlete management system (AMS) developed by the Australian Institute of Sport. This tends to be shifted towards being more physiotherapy- and physiology-driven and monitored than S&C for training measures, although a more specific strength and conditioning monitoring system is planned to be released shortly. In the meantime, I utilize Excel for load monitoring in gym exercises, as well as tracking neuromuscular measures.

I also developed a comprehensive monitoring system for badminton, incorporating training load, S&C load, tournament load, and wellness measures. However, any of these measures are only as useful as the compliance from the athletes, as well as “reporting fatigue”—i.e., the athlete’s propensity to return to a standard feedback option—as to whether you can gain true meaningful data. This is the reason we have moved back to basic communication on different training measures, as well as fatigue measures (neuromuscular) and athlete daily feedback as more effective tools to alter training sessions.

Cory Kennedy: For monitoring, we use a few different strategies, and each team will look slightly different. Most athletes fill out a questionnaire (usually Hooper-Mackinnon), and track training load using sessional RPE. This is usually collected daily, but analyzed weekly. Then we use a countermovement jump (typically three to five times a week) with most athletes for an objective performance measure. We have built a fairly robust system that takes into account each athlete’s individual variability, to allow us to view the performance through a clear lens. Finally, we have a variety of tests we collect monthly that usually have a component specific to the sport (time trials, etc.), and we use them as a reference point for the rest of our collected data.

As for process, there needs to be a general decision-making framework, and we discuss this regularly. First, we try to be fluid in our daily choices to meet the athletes where they are. Then we review where we are in the year and how much fatigue we can afford to collect. Finally, we regularly review the long-term view of our physical qualities to see if we are actually making a lasting change, or returning to square one every year.

Devan McConnell: We use a number of tools to monitor and assess fatigue/readiness and development. Subjective wellness questionnaires, HRV, and RSI via drop jump constitute our “front end” analytics. This combination is utilized to have a better indication of where our athletes are at before we begin on any given day, and what the latent cost of previous work was. The “back end” is used to inform our staff and players what we did—what the immediate cost of training was—so that we have a better idea of what needs to be done moving forward. This consists of various internal workload metrics via heart rate, sRPE, and, of course, a host of physical development parameters. These include several jump metrics, strength, and power measurements via tonnage, as well as velocity, on ice speed, and conditioning testing, etc.

Jonas Dodoo: In track, we perform CMJ (countermovement jump testing) weekly in normal phases, and drop jump and CMJ two to three times a week in high CNS stress phases. In all cycles, we will run fast at least to 30 meters through Optojump with a speed gun at least once every three to four weeks, but this can increase to once every 10 days in pre-comp phases. Jumps are mainly for performance monitoring, as opposed to fatigue. We see drops in performance values when we expect athletes to be fatigued. Drops rarely come from a significant reduction in height or stride length, but from an increase in contraction time (eccentric phase) and ground contact time.

We have used sRPE questionnaires in the past a lot, but we get so much more pertinent information verbally from the athletes on a daily basis that the questionnaires seemed like a box ticking exercise. Athletes get on the therapy table with a physio or osteo at least twice a week and this is where a lot of information is collected verbally, as well as through muscle testing, movement analysis, groin squeeze of different lengths, single leg hop or drop jump, and Nordbord.

We get much more pertinent information verbally from the athletes daily than from questionnaires. Share on X

The information can vary depending on the therapist, but is always extremely valuable for letting us know where the athlete is now compared to their norms. Athlete reports and medical reports greatly influence my decision-making around session content. Sometimes a hard day becomes Plan B or Plan C; sometimes active recovery day can actually become a second day of stress. We are constantly learning about the way athletes respond to training, and we are flexible with our microcycles to get the best out of the athletes while keeping them healthy.

These tools are all used in team sports as well. The difference is the flexibility around training content. The good managers listen to their staff and adjust.

Mike Boykin: The idea of simply observing athletes as they go about normal activities (walking into practice, interacting with teammates, etc.) and train was first introduced to me by Jim Snider at the University of Wisconsin-Madison. As the strength and conditioning coach for the men’s and women’s hockey teams, Jim is especially attuned to athlete mood and overall energy during pre-season and competitive season, when physical and emotional loads are highest. Central to his philosophy is ensuring that what he does in the weight room is a beneficial stressor versus one that simply adds more load.

This “active observation” of athletes during all activities is our first metric at ALTIS when it comes to daily monitoring. How vocal (or not) an athlete is, the amount of eye contact they make, their posture, their weight shifts, the amount they laugh—it can all be placed on a sliding scale and compared to their normal range to help create a global picture of their well-being.

Because we work in track and field, the training itself keeps tabs on how individuals are progressing simply by timing, measuring, or weighing. While it is not as simple as seeing fly 30 times decrease over the course of the season, observing the change and interaction of various menu items and different bio-motor abilities helps to create a multi-layered understanding of where someone may be adapting versus maladapting.

The final piece—and how many people will want this question answered—involves a daily monitoring questionnaire from Athletigen through their Iris application. The questions asked and information gleaned from the application is similar to the Hooper-Mackinnon or Profile of Mood States (POMS) questionnaires. Having access to objective data from subjective markers helps us to avoid heuristics and biases that can skew perception from reality. Daniel Kahneman’s book, Thinking, Fast and Slow, is particularly interesting material to read on this topic.

What Athletigen has done particularly well on this front is ensure that the information presented to coaches separates acute and chronic trends from simply noise, or daily fluctuations, which can be expected from a dynamic system. While there certainly may be daily prescriptions that are altered based upon the data from the questionnaire, this will always go hand in hand with a conversation to gain a deeper understanding of why certain acute changes are occurring. The chronic information gleaned from the app allows us to examine weekly, cycle, and long-term trends as they relate to individual athletes.

Nate Brookreson: Because of the relationships that exist within our department, different monitoring strategies are utilized among S&C and their respective sports. For swimming, we examine subjective RPEs and countermovement vertical jumps all year, and look more closely at bar velocities relative to load in the strength-speed, speed-strength, and peaking phases. We also examine ground contact time and vertical jump height with our depth and drop jumps. In the pool, the coaches track starts from the blocks and push times with set loads on power racks, and speed decrement over 25/50s almost weekly to determine progress.

Typically, the information is provided to create context and open dialogue. If we see negative trends regarding our tracking and performance outcomes in dual meets, we sit and have more detailed meetings. This might include ATCs to talk about visits to the training room and nutritionists to discuss most recent body fat testing or blood biomarkers. We try to address the low-hanging fruit first (statistically significant changes in objective/subjective markers, increased visits to trainer, blood/body fat changes). If unclear, we will look at long-term trends in sRPE training loads and vertical jump, along with performance outcomes in the pool, to determine a course of action. Most of the time, issues are caught early because of the consistent communication and fluidity of how both S&C and swim and dive operate.

Patrick Ward: The three main things we utilize are morning wellness questionnaires, GPS/Accelerometer during training, and sRPE post training. This information allows us to quantify the long-term impact of training/competition on the players (wellness questionnaire), as well as what they physically did during practice (GPS/accelerometer) and how hard they perceived the session to be (sRPE). This gets fed through some analysis that allows us to flag players when things don’t look right (i.e., when things are different then we predicted them to be). Doing this allows us to have more specific conversations with the player and plan an intervention strategy, if necessary, to try and get them back on the right track.

The next installment of this Sports Science Roundtable series is: “The Best Ways to Get Buy-In.”

Since you’re here…
…we have a small favor to ask. More people are reading SimpliFaster than ever, and each week we bring you compelling content from coaches, sport scientists, and physiotherapists who are devoted to building better athletes. Please take a moment to share the articles on social media, engage the authors with questions and comments below, and link to articles when appropriate if you have a blog or participate on forums of related topics. — SF

Strength and conditioning coach, Daniel Martinez, recently talked to a roundtable of seven coaches and trainers from four different countries about several sports science topics. This is the third in this series of Sports Science Roundtable articles.

Daniel Martinez: What is your view on periodization and its relevance to your team’s needs?

Cory Innes: A well-rounded knowledge of basic periodization structure and the detraining effect of the various bio-motor qualities is crucial. This knowledge should be so well understood that the practitioner can adjust and adapt training both within the wider plan and daily. (For instance, being able to stick to the periodization structure of what you are trying to achieve but being flexible within that process because, in the real world, perfect concentrated loaded periods and deloading periods don’t occur on a constant 3:1 macrocycle.)

There also needs to be reflection on what you expect to see, what you are seeing, what the difference is, and why there is a difference. This helps you understand an athlete at an individual level. There should also be a greater emphasis on skill development so that exercises performed are performed with perfect mechanics for what you have programmed. The “how” is more important than the “what,” and you need a vision of what you want to see in what time period, and what skill progressions you may need to achieve that.

Cory Kennedy: I think periodization is a very important starting point with every group you work with, but it is not final. There are definitely key periods of the year that are pre-defined with a specific type of training, which is probably the case for most people in our field. Early off-season, with GPP (General Physical Preparation), happens close to universally, although what that means can change from sport to sport. After that, we definitely employ a blend of block training with fluid periodization. We typically establish specific objectives for the athlete and the two to three qualities we need to build in the next cycle. Then, using the different monitoring tools at our disposal, we try to adjust our daily choices based on the state of the athlete. There are many roads that lead to Rome, so as long as our destination remains clear, our daily choices can be somewhat adaptable.

’Sport science’ informs the direction that the necessary ebbs and flows of training, practicing, competing, and all other stressors must take relative to the original periodization model. ~ Devan McConnell

Devan McConnell: Periodization lays the general framework for how I structure our training, both on a micro and macro level. I find great usefulness and success in the long-term planning of training, despite this being recently out of fashion. That being said, I don’t think that it is appropriate to consider any periodized plan as “gospel.” The entire point of tools such as subjective wellness questionnaires, sRPE, internal and external load monitoring, and CNS and ANS assessments is to provide relevant, immediate feedback on an athlete’s ability to adapt to stress. Ignoring this information blindly because it does not fit with the pre-ordained, periodized model would be foolish. Therefore, “sport science” informs the direction that the necessary ebbs and flows of training, practicing, competing, and all other stressors must take relative to the original periodization model.

Jonas Dodoo: I have always been a believer in training all components throughout the year in a “complex hierarchy,” where you essentially list all your training components and their objectives. You also list which ones will have primary, secondary, tertiary, quaternary (and so on) priority when planning learning objectives, training focus, training time, training stress, etc. It’s always easy to address your primary priority within each phase/cycle, but the problem I encountered early in my career is that it’s easy to overshoot your tertiary and quaternary priorities. This can become a problem, as these priorities can demand more adaptation reserve than planned and lead to over-training or dilution of training. It’s just as easy to undershoot these components, which may have detrimental long-term implications.

Mike Boykin: Periodization, or the structured and systematic implementation of a plan, is obviously exceptionally important, although perhaps not in the classical sense of a coach having all training-related details laid out until the “peak” competition. For our staff and athletes, periodization is more practically applied to ensure that the people involved in an athlete’s preparation understand what the goal(s) is/are for a certain period of time and which objective or subjective metrics need to be monitored most carefully.

This is always dynamic, and it shifts depending on numerous factors including, but not limited to: an athlete’s health (physical and emotional), technical progress, and physical development, as well as time of year. To give a fairly straightforward example, take an athlete who is coming off a chronic injury that has caused numerous compensatory strategies and limited consistent training. Until this athlete has stabilized health factors and mechanics, performance markers (such as times during practice or weight lifted in the gym) are not a priority. Unless the entire coaching/therapy staff is on the same page with this, an athlete will consistently receive mixed messages on what they should be focusing on.

Nate Brookreson: I believe that the planning of a yearly training block is one of the most important processes a coach can go through. It creates communication with sport coaches in determining the most important competitions to plan for, allows you to stratify programming between different levels of athletes, permits you to have meaningful conversations with athletes about how you are going to achieve success and what markers you will use to determine this, and serves as a road map for other coaches who might be assisting you with your team to see your thought process and rationale. I don’t feel that a periodized plan needs to be at the level of individual exercises because I think these will be influenced by what team you are working with and your exercise preferences with them.

I believe in creating a plan based on your training goals (e.g., strength endurance, strength, strength speed, etc.) and then filling in exercises, sets/reps, and percentages based on these goals. I try to be as scripted with the training in the off-season as possible, as there are times when I am trying to create fatigue to target specific adaptations, although within reason. However, when we reach our in-season phase, there are specific competitions at which my objective is to attenuate fatigue, and I am more sensitive to getting feedback from the athletes to manage the training loads and make changes in programming as necessary.

Patrick Ward: Periodization comes down to logical, structured planning. In team sport, I look at it in two main ways—mesocycle and microcycle. The mesocycle is going to be dependent on the phase of the season (e.g., training camp, in-season quarter 1, etc.), while the microcycle is specific to what we do that week in preparation for the upcoming competition. The microcycle layout is critical in team sport, given the frequent competitions and how one week flows into the next. Understanding that weekly structure and preparation is something I strongly believe in. Then, how subsequent weeks feed into a block of time—a mesocycle—helps you take a longer term look at things.

I left macrocycle off the list only because looking at programming/planning from year to year isn’t as critical for us, given that a pro sports team turns over a lot of players each year. There are also coaching changes, and these athlete and coach changes alter the training context each season. There isn’t as much consistency from year to year, like there might have been before the times of free agency.

The next installment of this Sports Science Roundtable series is: “The Effect of Monitoring on the Training Process.”

Since you’re here…
…we have a small favor to ask. More people are reading SimpliFaster than ever, and each week we bring you compelling content from coaches, sport scientists, and physiotherapists who are devoted to building better athletes. Please take a moment to share the articles on social media, engage the authors with questions and comments below, and link to articles when appropriate if you have a blog or participate on forums of related topics. — SF

Strength and conditioning coach, Daniel Martinez, recently talked to a roundtable of seven coaches and trainers from four different countries about several sports science topics. This is the second in this series of Sports Science Roundtable articles.

Daniel Martinez: What are the challenges of your current work environment?

Cory Innes: The challenges of my work environment tend to revolve around funding and, therefore, athlete access. The result of working within a government system is that funding is limited, so servicing needs to cover a wide range of athletes. There have been recent moves to decrease athlete-to-staff ratios to provide greater in-depth performance, but this then leaves the developing or non-performing athlete vulnerable to being cut off from access to servicing. So, there is constantly a trade-off between who needs help and how/if they can be serviced. Additionally, relationship building is a key requirement of the position and one of the biggest challenges lies in communication with the coach, other service providers, and athletes.

“Relationship building is a key requirement… and one of the biggest challenges lies in communication.”

Cory Kennedy: Personally, I like to think of advantages over challenges, but I don’t fault you for asking. I would say the largest challenge we face is the allocation of resources. Since most of our funding comes through the federal government, there is a comprehensive process that determines each sport’s level of support from year to year. This means that some sports that have more success will reap the rewards of a higher budget. So, while Olympic hopeful athletes from a variety of sports share the same space, training side by side on a daily basis, our level of involvement is dictated by the allocated resources. Each athlete has a drive to reach the podium, and we like to offer each athlete their best chance to reach those dreams. Unfortunately, we can’t always spend the same amount of time with each of them.

Devan McConnell: I am a one-man show. My primary responsibility is the physical training of the team, but all other aspects of the position still fall on my shoulders. These other duties are often the sole responsibility of other individuals within a larger or more well-funded organization. Specifically, on the sport science side, I find it always a challenge (although a well-appreciated one) to “sell” the usefulness of the data to the head coach. And I would be remiss if I didn’t mention the complete lack of understanding of my role and/or its significance to the program by administrative-level individuals.

Jonas Dodoo: At Speed Works, the challenge is that we are a registered charity in an amateur sport during a time when sponsors are put off due to the financial climate and the controversies that consistently occur within our sport. So, we are balling on a budget.

High Performance Advisor connects vision and reality for young developing players who are often paid more than staff members. As a result, these athletes have traditionally had more power to decide how they train.

Mike Boykin: At ALTIS, we face similar challenges to what most relatively new companies encounter. Resources are appropriately allotted in order to maintain a high level of coaching and therapy expertise on-site to best serve the athlete population. This means that there are fewer (read: no) individuals here in Phoenix who are 100% dedicated to what most practitioners think of as “classical sports science.”

However, this “issue” is mitigated greatly by the fact that John Godina hired coaches (initially Dan Pfaff, Stuart McMillan, and Andreas Behm) who have a wealth of knowledge and a high level of understanding in areas that are often saved for a specialist. This is why the paradigm of sports science as hooking up a GPS (just to pick one example) should instead be viewed more holistically as the “science of sport,” where the coach is a fantastic generalist with a broad educational background in an environment where they can continue to grow.

The challenges of being a start-up have forced us to adapt. Therefore, many of our partnerships are formed around creating better athlete support systems. One example is the work we do with Athletigen in providing genetic and environmental data to our coaches and athletes. If there’s something we cannot adequately do, there is someone within our network who can assist.

Nate Brookreson: As silly as this might sound, I try to not view anything about my role as a “challenge” anymore. I think early in my career, I definitely had this mentality regarding things like communication between support staff, the lack of understanding with my sport coaches when it came to physiology, and the difficulty in articulating my role in the competition performance of athletes in mixed sports. I am now at a point in my career where I try to be solution-oriented.

I have forcibly increased communication with support staff through frequent meetings that have a specific agenda. I have increased the information I share with sport coaches and attempt to educate regarding weekly practice structure and peaking protocols. I also understand the limitations in trying to explain all performance outcomes, but share the information that I can reliably collect and track using research (whether others or my own) to pick validated indicators of performance. Maybe the only legitimate challenge I still face is time management (knowing when to walk away from certain projects).

Patrick Ward: The challenges are the challenges faced anywhere and are not specific to professional sport. Anytime you have information that challenges antiquity or dogma, you will meet with some resistance. It takes a lot of time to help people understand where you are coming from or maybe even to change their thinking on things. Sometimes it isn’t even about changing the thinking as much as it is getting people to look at things from a different angle and conceptualize things in a different way. So, being patient can sometimes be a challenge, as things never move as fast as you want them to. As they say, it takes a long time to make a right turn on the Titanic.

The next installment of this Sports Science Roundtable series is: “The Relevance of Periodization.”

Since you’re here…
…we have a small favor to ask. More people are reading SimpliFaster than ever, and each week we bring you compelling content from coaches, sport scientists, and physiotherapists who are devoted to building better athletes. Please take a moment to share the articles on social media, engage the authors with questions and comments below, and link to articles when appropriate if you have a blog or participate on forums of related topics. — SF

Cory Innes (Victorian Institute of Sport – Lead S&C T&F/Badminton)
Cory is the Lead Strength and Conditioning Coach for Track and Field and Badminton at the Victorian Institute of Sport in Melbourne, Australia. He provides strength and conditioning support to nationally identified athletes in these sports, and develops programs for training camps and education to national junior squads. Additionally, he operates as the National Sport Science and Medicine Manager for Badminton and sits on the High-Performance Committee, which involves the development of a national structure and framework around strength and conditioning and medical support.

Cory Kennedy (Institut National du Sport du Québec – Head of S&C)
Cory is the Head of Strength and Conditioning at Institut National du Sport du Québec. This role includes being the lead for certain training groups, as well as managing the delivery of strength and conditioning as a whole within the Institut. This means helping to guide other team members in their journey in strength and conditioning, as well as managing the logistics and equipment within the training space.

Devan McConnell (UMass Lowell – Head of Hockey Performance)
Devan serves as the Head of Hockey Performance at UMass Lowell. His role is essentially to oversee everything that goes into development off the ice. This includes strength and conditioning, recovery and regeneration, nutrition, sport science data collection and interpretation, and continuing education for the staff and players.

Jonas Dodoo (Speed Works – Head Coach of Athletics and High Performance Consultant)
Jonas is the Head Coach of Speed Works, a track group based in London. He is also a high-performance advisor to professional sports teams (mainly rugby and soccer).

Mike Boykin (ALTIS – Sprints & Hurdles Coach/Sports Science Lead)
Mike is currently a Sprints and Hurdles Coach at ALTIS, overseeing the development of a group of 200m and 400m sprinters, and 400m hurdlers. He also serves as the sports science lead on The ALTIS performance team.

Nate Brookreson (NC State University – Director of Olympic Sports)
Nate is currently the Director of Olympic Sports at North Carolina State University, where his primary team responsibilities are with women’s basketball, swimming, and men and women’s golf. As a coach, his job is athlete management, which consists of the planning and implementation of training programs; the review of the plans through observation of performance qualities to determine if they are producing expected outcomes; and making changes based on testing, monitoring and performance results. As a supervisor, he assists staff in the: creation of needs analyses for the respective sports; centralization and management of performance and monitoring data; dissemination of information to improve the staff’s knowledge and programming; and creation of opportunities for the staff to complete departmental projects to positively impact the Pack Performance unit.

Patrick Ward (Sports Science Analyst at Seattle Seahawks)
Patrick is a Sport Scientist for the Seattle Seahawks and was formerly with Nike’s SPARQ Division in Portland.

Strength and conditioning coach, Daniel Martinez, recently talked to a roundtable of coaches and trainers from four different countries about several sports science topics. We will be presenting these questions, and their answers, in a series of Sports Science Roundtable articles, starting with this one on the definition of success.

Daniel Martinez: How do you define success for your team and your role?

Cory Innes: Success is defined by performance. If the sport performance is not improving, then
we are not doing all we can to help facilitate that. My role involves helping create individual performance plans (IPPs), in consultation with the coaches, national sport organizations (NSOs), and a wider support team (sport science, physiotherapy, psychology, nutrition, etc.), which focus on identifying areas of improvement within the athlete’s performance and then developing ways of measuring improvement in each area.

This is an integrated approach with accountability from each contributing team member, and these are reviewed and adjusted as required. This allows us to see specifically where or if we have been successful in our contribution to performance. In my role, I look at specific measures that identify whether my contribution is successful at a strength and conditioning level, but also whether this improvement transferred to the sports performance.

Cory Kennedy: Success as a strength and conditioning staff member (or a sport scientist) is difficult to define, as some colleagues regularly remind us. So, we look at success in a few different areas. Approval and trust from an athlete can sometimes be the low-hanging fruit, but it is essential. You need their trust, and they need yours. Matching each other’s expectations is so important. Secondly, you need to have the coaches’ approval. Sometimes we think the coaches are wrong, and vice versa. Yet, we have to trust each other and get along.

Lastly, are we offering something to the sport that they never had before? Is there a legacy that we are providing? We tirelessly shake every tree for research and innovation opportunities, because we are learning new things about different sports, training methods, equipment, and human beings. This means that there will always be opportunities to improve on processes. This could be the way coaches view training and practice, or tests used to identify or track talent, or they could be validating equipment that enters the marketplace.

If we can publish reviews or original research, this is a huge success. Even if it’s not published, if the sport assimilates it into their way of doing things, that is a big win for us. Within those principles, we have an Integrated Support Team (IST) around each sport (think of the different specialists), and we do our best to really get on the same page, collaborate on projects, and share similar perspectives, so we can offer a sport a well-functioning team.

Devan McConnell: Success, in a general sense for our team, comes from the basic premise of wins/losses, just as with any other athletic organization. At the end of the day, our staff and program are judged by how we finish within our league, and if and how we earn an opportunity to compete in the NCAA tournament. On a more specific level to my position, in addition to our team success, the success of my role is reflected by our “man games lost” statistic, or what our injury ratio is. I am also judged, from an athletic development perspective, by how many of our players move on to play professional hockey after their college career.

Finally, in addition to all this, I personally view success as how “successful” my athletes are once they are done being athletes…. Do they leave us as a better version of themselves? I measure their success by how much more mature, worldly, and prepared they are to be productive members of our society; and by the depth of the relationships they have formed along the way.

I personally view success as how ‘successful’ my athletes are once they are done being athletes. Share on X

Jonas Dodoo: Success is always measured by the progression of performance. Running fast and winning games are essentially what stake holders will measure players, athletes, teams, and coaches by. But, within our team, we measure our success by progression towards high performance. Some may talk about this being culture and some may just call this being professional. Either way, we identify the behaviors, processes, and benchmarks of high performance, then work on bridging the gap between where we want to be and where we are now. If we are doing everything in our power to close this gap, then we expect to see more wins, faster times, and healthy athletes.

Mike Boykin: When we sat down as a performance team in September, which was the start of our 2016-2017 training season, the No. 1 goal for this year was international level success of our athletes. While success in this context can be defined numerous ways, in track and field and in our situation, it was simply having athletes performing their best in meets, with a long-term focus on premier competitions, while staying healthy.

There are multiple ways to achieve this and certain landmarks must be hit along the way, as it requires doing things correctly when it comes to supporting the athlete group. Many people have written and spoken about this before and Good to Great by Jim Collins is a fantastic reference on the topic, but it begins with the people involved. ALTIS’ infrastructure was built on high-level coaches and therapists working together with the athlete, in what Dan Pfaff and Gerry Ramogida have aptly termed the “Coach-Athlete-Therapist Triad.”

The keystone to success in this model is the ability of all three members to communicate openly with each other and put ego aside to best serve the athlete and their goals. All other support services are just that—support. Things that are classically defined as “sports science,” whether it be some sort of physiological, biomechanical, psychological, nutritional, etc. information, must inform the coach and therapist, and, where appropriate, the athlete. These support services are present to give the team increased access to a wealth of information that they theoretically would not have due to lack of expertise in a particular area.

Anything that aids in best practice must be put in a framework that the coach and therapist can apply (or at least file away for a later date), rather than an isolated factoid that simply feeds that athlete with additional information.

Nate Brookreson: Success in my role is multifaceted. In the role of support staff to a sport coach, my primary responsibility is to optimize the development of our student-athletes to be able to compete for conference and national championships. While this topic has been discussed in detail in recent months, my success in this role is related to athlete availability and measurable performance improvement. Athlete availability is quantified in missed practices and competitions, as well as missed training opportunities in the off-season. Measurable performance diagnostics are separated into orthopedic, strength, power, speed, and fitness categories, and further subcategorized from there.

Developmental emphasis is placed in certain categories depending on the sport, time of year (i.e., basketball movement/orthopedic early off-season, strength, power, and fitness late off-season), and developmental stage of the athlete. All performance testing is evaluated based on the work of Will Hopkins and his magnitude-based inferential statistics to determine meaningful performance changes. We then compile this information into detailed performance profiles for our athletes that we can share with sport coaches and administrators.

Patrick Ward: Defining success in any support role is always challenging in team sport. It isn’t like individual endurance sports where, as a physiologist/coach/strength coach, there may be a more direct link between what you do and how it impacts successful performances. Team sport is inherently “noisy” because success, in the form of winning games, is dependent on a variety of factors that can often be outside your control.

For myself, I think success is more defined by my contributions back to the four main departments in a pro sports team: Management/Scouting, Coaching, Strength Coach, and Medical/ATC. I look at the role of a sport science department as an information services role (to steal from the business world), whereby you are helping people in those departments answer relevant questions that may aid them in making decisions. If I am able to listen to people in those departments, understand what is relevant and important to them, and then use a scientific approach to answer questions for them and set up analysis that may explain some sort of phenomenon or uncover information that is not directly observable to the human eye that allows them to take action, then I feel pretty successful.

The next installment of this Sports Science Roundtable series is: “The Challenges of the Work Environment for Coaches and Trainers.”

Since you’re here…
…we have a small favor to ask. More people are reading SimpliFaster than ever, and each week we bring you compelling content from coaches, sport scientists, and physiotherapists who are devoted to building better athletes. Please take a moment to share the articles on social media, engage the authors with questions and comments below, and link to articles when appropriate if you have a blog or participate on forums of related topics. — SF