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Athlete Recovery & Regeneration: Monitoring Fatigue & Benchmarking Recovery – Part 2

Recently, several different sports have added more events to their competition calendars. This has placed increased demands upon athletes, not only from the competition itself but also from the associated burdens of travel, time zone changes and sleep disruption, which can easily lead to the rapid accumulation of fatigue. As a result, athlete recovery and regeneration is now playing an ever more important role in high performance sport.

Athlete fatigue can come from many different sources, including physical, neural, metabolic, psychological and emotional. For that reason, if athlete recovery strategies are going to be effective, it’s essential that we identify the stressors that athletes are being exposed to. In other words, for recovery protocols to be effective, it’s important that we know precisely what it is that the athlete is recovering from.

The previous article in this series analyzed the role that fatigue monitoring plays in the athlete recovery process. Here we will look in more detail at some of the tools and systems that can be used to benchmark athlete recovery and identify excessive fatigue, and explore how these tools can be applied as part of a systematic recovery assessment process.

Monitoring Tool 1: Physical Output in Training & Competition

Fatigue and under-recovery are associated with a deterioration in performance below that of normal levels. For that reason, it is essential that practitioners and performance analysts pay close attention to the physical outputs being produced by athletes, both in training and competition, and identifying any sudden instances of unexplained performance decline.

Heart Rate Response

One monitoring method which can be a useful indicator of fatigue is to evaluate the athlete’s heart rate response during exercise. The maximal heart rate of an over-trained athlete has been shown to be significantly reduced, whilst the rate of recovery from maximal exercise is slower. This may be due to a decline in the ability of fatigued muscles to utilize oxygen, therefore by monitoring heart rate responses during and after training, we may be able to identify the early stages of overtraining. One method of implementing this as a monitoring tool in an applied setting is to have athletes perform a short submaximal run as part of their warm-up routine. The run is completed over a set distance at a pace which is carefully controlled using pre-recorded bleeps on a speaker system. Athletes who exhibit unusually elevated heart rates during these runs may well be under-recovered, with studies showing heart rate response during submaximal fitness tests to be a reliable and valid indicator for monitoring an athlete’s physiological state.

RPE

A second useful analysis tool is to compare an athlete’s Rate of Perceived Exertion (RPE) with their training output. If an athlete’s interpretation of the effort required to train suddenly increases, but their running distance or work rate remains normal, or even declines (as measured using a GPS tracking system), this may be an indication of an increased stress response. In other words, the athlete is finding it harder to produce the same level of physical output, which may well be a marker of fatigue.

GPS Metrics

GPS systems themselves provide a vast array of data points which can be used to identify markers of possible fatigue. Exercise Induced Muscle Damage, or EIMD, is characterized by a reduction in the athlete’s force generating capacity, which in performance terms can transfer into a decline in power related activities, such as sprinting, jumping, explosive decelerations and agility actions. Therefore, by monitoring the physical outputs produced by the athlete in these metrics during training, we may be able to identify potential markers of fatigue. In an applied setting, coaches set physical training targets for each athlete based on their individual loading profile, and from these targets the training output produced during each session will then be judged. By reviewing the physical components of the session, staff can determine if the athlete has reached their performance target for that session. Any outliers or underperforming athletes may require further investigation into potential under-recovery.

Although reviewing training output allows a ‘real world’ assessment of athlete status to be made, the significant drawback with this method of analysis is that athletes with low training outputs may already be over-reaching. In addition, any athlete presenting with fatigue or under-recovery will have had the condition exacerbated by the additional training load involved with that session. A better use of physical output data would be to use it as a means of avoiding excessive fatigue in the first place, with one of the ways proposed to address this being to monitor the ratio between acute and chronic workload.

Monitoring Tool 2: Acute: Chronic Workload Ratio (ACWR)

The Acute: Chronic Workload Ratio (ACWR) was developed in an attempt to minimize the effects a sudden spike in training load can have on injury risk. In this model, chronic training load is described as the rolling average physical output from the previous six weeks of training, and acute training load is described as the physical outputs from a single week’s training.

The model states that an Acute: Chronic training target should be in a ratio of 0.8-1.3, in order to develop physical capacity without excessive risk of injury. However, if the ratio rises to 1.5 or above, the training load enters an injury danger zone, and the athlete is at increased risk of sustaining an injury associated with excessive training.

For example, if, during the previous 6 weeks of training, a soccer player consistently averages 1000m of high-speed running during each training week, their weekly training target for high-speed running should be set at 800m-1300m. This would ensure that they are receiving enough of a training stimulus to maintain or to improve their high-speed running performance, without being exposed to an excessive risk of sustaining an injury. However, if that player suddenly and unexpectedly produces 1500m of high-speed running during a single training week, the load would be considered excessive, and the player could be regarded as being at increased risk of injury. Practitioners and performance analysts can then use this data both to adjust future training content and to prescribe appropriate recovery protocols.

Outside of monitoring training outputs, a superior analysis tool would allow objective markers of fatigue and recovery to be identified before any significant decline in physical performance is apparent. One assessment tool which fulfils this criteria, and which is commonly used to evaluate fatigue and recovery in power related performance, is the Counter Movement Jump test.

Monitoring Tool 3: Muscle Function – Explosive Force Production

Following strenuous exercise, the ability of the muscles to produce explosive force declines, which is one of the characteristics of Exercise Induced Muscle Damage (EIMD). More specifically, due to the relationship between muscle force and muscle function, a reliable indicator of muscle damage following eccentric exercise is the athlete’s capability to generate muscle force. In other words, we can use measurements of muscle force production to assess the level of EIMD the athlete is experiencing. EIMD is particularly correlated with eccentric contractions, therefore the ability of the athlete to utilize stored elastic energy through the stretch shortening cycle, with its significant eccentric component, is strongly affected by structural damage to the muscle tissue.

Counter Movement Jump

One monitoring tool which is commonly used to assess this specific form of fatigue is the Counter Movement Jump (CMJ). By measuring the athletes jump height in the CMJ we are assessing their stretch shortening capability, making the CMJ an objective marker of muscle damage. Decreased CMJ height, when compared to an athlete’s baseline measure, may be an indicator of compromised muscle function, which can then be used to assess the fatigue-recovery status of the athlete. In an applied setting, average jump height over a number of jumps has been shown to be a more sensitive measure of recovery status than maximum jump height. For that reason, in the context of a fatigue-recovery assessment, the average score over three jump attempts is used.

Monitoring Tool 4: Muscle Function – Maximal Voluntary Force Production

A second method of using muscle function to determine recovery status is to assess an athlete’s maximal voluntary force production. This approach has been shown to be an appropriate measurement not only of muscle damage, but also fatigue in both the peripheral nervous system and the central nervous system. Fatigue of this nature results in a reduction of neural transmission rates in short term maximal contractions, such as those involved in explosive, ballistic or maximum strength movements. As with all methods of fatigue assessment, the outcome of these tests will allow us to prescribe specific and individualized recovery interventions for each athlete.

Isometric Mid-Thigh Pull

One assessment tool that is a valid indicator of muscle function is the isometric mid-thigh pull (IMTP), which measures maximum strength and the rate of force development (RFD) in the athlete. Significantly decreased performance in the IMTP, compared to established baseline measures specific to the athlete, may be indicative of a reduced capacity to produce strength, indicating potential under-recovery. Although the IMTP is a maximal test, it does not induce excessive fatigue, therefore it is an appropriate tool for fatigue-recovery assessment.

Static Vertical Jump

A second test we can use to assess EIMD is the static vertical jump, which also correlates strongly with muscular fatigue. Any athlete who demonstrates a reduced vertical jump in relation to their normal performance profile has a reduced capacity to generate voluntary force, and is therefore highly likely to be experiencing fatigue.

McCall Isometric Test

A third test which utilizes force production as a measure of fatigue and recovery is the McCall Isometric test. The McCall test assesses isometric hamstring force production, and was designed specifically for use in soccer due to the role played by fatigue as a risk factor in hamstring injury mechanisms, and the high incidence of hamstring injuries in the game. The purpose of the test is to track the recovery of force production in the hamstrings following a competitive game as a means of measuring muscle damage and assessing hamstring injury risk. Soccer practitioners using the McCall test have reported an 11-16% drop in force production immediately post-match, and have shown it to be a simple, reliable and sensitive test for benchmarking recovery.

Monitoring Tool 5: EIMD & DOMS – Flexibility

The inflammatory cascade that follows EIMD can induce secondary muscle damage in the form of the Delayed Onset of Muscle Soreness, or DOMS. DOMS is the discomfort in the muscles which is experienced by athletes 24 hours after strenuous training, and which reaches a peak 48-72 hours post exercise. This discomfort is caused by the micro-traumas and the chemical cascade which is associated with EIMD and the inflammatory response, and is characterized by pain, stiffness and swelling in the affected muscles. Collectively, this can negatively impact on athletic performance by causing a reduction in joint range of motion.

Sit & Reach Test and Overhead Squat Test

A simple test which can assess the extent of this muscle stiffness and reduced range of motion is the sit & reach test. The sit & reach test measures linear flexibility in the upper hamstrings and the lower back, and can provide important feedback regarding how significantly the symptoms of DOMS are affecting the athlete. One of the major drawbacks to this test is that it only involves a single movement action, therefore a more comprehensive assessment of range of motion would be to perform the overhead squat test. However, in a team sport environment which involves potentially large numbers of athletes, the sit & reach test is an appropriate method to measure the effects of DOMS.

Another form of recovery assessment which can indicate the extent of muscle damage is to measure certain hormonal and biochemical markers. Two markers which have been proposed as indicators of muscle damage and recovery are Creatine Kinase and IgA.

Monitoring Tool 6: EIMD – Biochemical Markers Creatine Kinase

A symptom of EIMD is an increased blood circulation of Creatine Kinase (CK). CK is an enzyme that is found within the muscle, where it functions to maintain ATP availability during muscular contractions. Unaccustomed strength training or high intensity movements encountered during outdoor training, specifically decelerating, changing direction, and landing following a jump, rely heavily on eccentric muscle contractions, causing mechanical muscle damage and an increased permeability of the sarcolemma (the cell membrane that surrounds a muscle fiber). This increased permeability causes a leakage of CK from the muscle into the blood, making blood CK concentration a useful test to assess muscle damage.

The timeframe of blood CK elevation is highly individualistic, but it generally follows a pattern whereby it increases slowly in the immediate post exercise period, before accelerating and becoming more pronounced 24-48 hours post exercise. For this reason, it is vital that practitioners create a comprehensive CK profile of each individual athlete, in order to develop reference ranges specific to that individual athlete’s training response. These will provide the framework for recovery indicators, and allow any unusual spikes in CK appearance to be quickly identified. Loss of CK from the muscle cell has implications for energy supply, and, by extension, the capacity of the muscle to produce force. For that reason, this is an important screening tool in the fatigue-recovery monitoring process.

IgA

One commonly reported physiological and psychological change associated with overtraining is recurrent infection caused by immunosuppression. This means that monitoring the condition of the athlete’s immune system could be an important factor in preventing under-recovery. IgA is an immunoglobin which has been proposed as being an indicator of the status of the immune system, with a depressed level of IgA resulting in an ‘immunocompromised’ window. The immune system is extremely sensitive to physiological and psychological stress, and therefore measurements of any change could be used as an index of reaction to training and competition. It is during this immunocompromised window that players develop the colds and flu-like symptoms often associated with under-recovery.
Low levels of salivary IgA have been reported in overtrained athletes and during periods of intensified training. In an applied setting, IgA levels can be monitored through analyzing saliva samples taken before training or competition, and again twenty-four hours later. A failure to recover to pre-exercise levels could be indicative of under-recovery, although an IgA level of below 1.9 mmol/l has also been proposed as a marker of overtraining syndrome.

Further reported physiological changes associated with under-recovery include alterations to the athlete’s cardiac function. One tool which we can use to monitor this is Heart Rate Variability.

Monitoring Tool 7: Cardiac Function Heart Rate Variability

The beating of a healthy heart under resting conditions is irregular, with these beat-to-beat variations in heart rate being measured by Heart Rate Variability (HRV). HRV reflects the cardiovascular control being exerted by the autonomic nervous system. The autonomic nervous system is comprised of the parasympathetic nervous system, characterized by a slow heart rate, and the sympathetic nervous system, characterized by an accelerated heart rate, and dominance of one over the other can be used to evaluate the autonomic response of an athlete to acute exercise or training.

In a recovery context, HRV can be used to help detect the markers of fatigue and under-recovery, with measurements taken whilst the athlete is asleep being the most reliable reflection of recovery status. Studies have shown that stressed athletes can experience an altered sleeping HRV, with an increased sympathetic drive and decreased parasympathetic component during sleep. The parasympathetic system promotes growth, energy storage, and other regenerative processes, therefore athletes with a lower night-time parasympathetic response following training or competition may well be under-recovered, and therefore less prepared to engage in subsequent training sessions.

In simple terms, high nocturnal HRV values reflect an athlete in a well recovered state, and low nocturnal HRV values indicate stress and a low state of recovery. Using nocturnal HRV as a guide allows practitioners to select training loads and recovery interventions on an individualized basis, and this methodology has been shown to promote positive training adaptations.

Monitoring Tool 8: Psychological Profiling

The perception of an athlete’s readiness to perform is a critical element in determining their recovery status. Recovery and fatigue are significantly influenced by psychological factors, particularly after the athlete has performed mentally fatiguing or emotionally draining tasks.
For that reason, subjective assessments of athletes are an extremely important part of the overall monitoring process, with subjective measures of fatigue and recovery in the form of athlete self-reporting having been shown to be effective in identifying athlete recovery status. The advantage that these tools have over physiological assessments is that they provide information to the coaching staff more quickly. Athletes can complete and submit a self-assessment form remotely, meaning that practitioners have an understanding of the fatigue-recovery status of the athlete before they have even arrived at the training center.

Mood State Questionnaire

One method commonly used to assess post exercise fatigue is a mood state questionnaire, in the understanding that how the athlete feels is an accurate gauge of recovery status. The cumulative effect of training and competition can result in athletes developing mood disturbances or increased symptoms of stress, which can translate on mood state questionnaires in reduced scores for motivation and increasing scores for anxiety or fatigue. These mood changes may reflect underlying biochemical and hormonal changes in the body which accompany exercise induced fatigue. A Profile of Mood State (POMS) questionnaire has been shown to be an effective tool to monitor mood changes, sleep patterns, fatigue and general well-being in the athlete, and this can provide useful insights into the athlete’s recovery status.

RESTQ-Sport and DALDA

RESTQ-Sport (Recovery-Stress Questionnaire for Athletes) and DALDA (Daily Analysis of Life Demands for Athletes) are further subjective tools which have been designed specifically for use by athletes, and which have been shown to be sensitive to changes in the athlete throughout the training period.
The RESTQ-Sport systematically addresses the fatigue-recovery state of an athlete, providing details as to how physically and mentally stressed they are, and which individual strategies should be used for recovery. The tool consists of a 77-item questionnaire scored on a 0-6 scale, with 7 general stress categories, 5 general recovery categories, 3 sport-specific stress categories and 4 sport specific recovery categories. These subjective assessment tools have been shown to demonstrate high reliability and consistency in measuring athlete well-being, however, a 77-item questionnaire can be a tedious and time-consuming task for an athlete to complete, and this may lead to an under-reporting or over-reporting of fatigue. For this reason, customized mood state questionnaires which contain fewer questions are more commonly used in applied sport settings.

Practitioners who employ psychological profiling tools such as these must be mindful that the phase of the competitive season will have an influence on how effective they might be. For example, wellness data doesn’t correlate well with loading markers during pre-season, when athlete’s fitness levels are typically low. This doesn’t mean that they shouldn’t be used during pre-season, but that the data they provide should be analyzed alongside the outcome of other monitoring tools, such as HRV, sit and reach, and counter movement jumps. Collectively, this would account for the multifaceted nature of athlete fatigue, and provide an integrated approach to monitoring athlete regeneration and benchmarking recovery.

Summary

One of the central pillars of an effective recovery strategy is to have a comprehensive monitoring system in place, one which is designed to assess an athlete’s level of fatigue and ensure an appropriate balance between stress and recovery. If we can establish the recovery status of an athlete, it means that we can then plan our subsequent training program for that athlete with a higher degree of accuracy.

Fatigue is multifaceted and can come from multiple different sources, which presents a significant challenge to the fatigue-recovery monitoring process. A single test, performed in isolation, will only assess one particular aspect of recovery and fatigue. For that reason a multivariate approach needs to be adopted, using a number of different tests, with each one designed to monitor a specific category of fatigue and recovery. But this then creates a further problem: if we are going to apply all of these tests, what are we going to do with the data we get from them, and how can we use it to create an accurate athlete recovery profile?

Apollo Makes Sense of Your Recovery Data

Practitioners working within sports teams will use a vast number of tools to help establish an athlete’s recovery status. Sports scientists, S&C coaches and medical staff will collect data on sleep quality, HRV, jump height, isometric force production, subjective wellness, muscle soreness, hydration, biochemical markers and flexibility on a daily basis. However, if the outcome from all of these different tests is stored on multiple separate systems, how can we be expected to make sense of it? Unless recovery data is assimilated quickly and presented to coaches and players in a way that they can understand, it’s unlikely to make any difference to the training program – therefore what is the point in collecting it in the first place?

Apollo’s solution to this is the ‘Recovery Dashboard’. Our API’s pull data from the multiple tools and systems that different practitioners operating within the support staff are using. Then, powered by our specific AI models, we bring it all together in a centralized report quickly enough to identify the recovery levels of each individual athlete. This gives coaches the information that they need to make informed training decisions – crucially, in enough time for them to adapt their sessions whenever necessary.

Where Apollo Makes A Real Difference

ApolloV2 is not a traditional ‘one size fits all’ athlete management system. Instead, we are a highly adaptable platform which can create customized dashboards specifically tailored to each team’s individual needs and unique way of working. Our system equips teams with the ability to generate custom-made data visualizations without software code. We have more API’s than any other system, which allows us to collect data from all of the multiple different tools and systems staff are using, and then bring it all together quickly enough to allow coaches to make informed decisions with their players. Crucially, we have Power BI and Tableau integrated into our ecosystem, which enables us to build bespoke best-in-class data reports designed to meet specific requirements and ensure that coaches receive the data driven insights they need to inform decision making and influence positive change.

To learn more about using Apollo for performance enhancement, visit www.apollov2.com or email info@apollov2.com.

Written by Adrian Lamb, ApolloV2 Sports Scientist

Email Adrian

WHAT APOLLO CAN DO FOR YOU

Our system equips teams with the ability to generate custom-made data visualizations without software code. We have more API’s than any other system, which allows us to collect data from the multiple tools and systems staff are using, and then combine it efficiently to allow coaches to make informed decisions with their players.

We have Power Bi and Tableau integrated into our ecosystem, which enables us to build bespoke, best-in-class data reports designed to meet specific requirements and ensure that coaches receive the data driven insights they need, to inform decision making and influence positive change.

To learn more about using ApolloV2 for performance enhancement, email – alamb@apollov2.com.