An international conference was held in 2016, where athletic experts and researchers discussed their findings related to training load. A collective review discussed the pros and cons of key findings shared at the conference. Here, as well as in Part 1, we will review tools and measures commonly used to monitor athlete training loads.

Fitness-Fatigue Model

The fitness-fatigue model is used to analyze training load information (2). This method is used to advise training plans (8) and predict performance, fitness and fatigue levels (29, 30, 34, 37). The initial fitness-fatigue model suggests training loads give rise to fitness responses which increase performance and levels of fatigue (2). Increased levels of fatigue generally compute to decreased levels of performance (2). The model has been adjusted by various groups to better represent situations with variation in training load stimulus and increased fatigue levels (6, 7, 9, 10, 29). It is commonly used in the athletic community as a reliable measure for fatigue and fitness (29 30, 34, 37).

That being said, the fitness-fatigue model has been faulted to oversimplify complex relationships between training and performance (20, 24). As mentioned in Part 1, different factors and measures (e.g., psychological factors, training routines, health), can influence an athlete’s individual mental state and performance (2). As every athlete and training load is different, athletes’ progress and/or decline at different rates (2). Therefore, the simplification of the fitness-fatigue model has led to large variability in parameters and accuracy in performance predictions (20).

Acute:Chronic-Workload Ratio

The acute:chronic-workload ratio (ACWR) is used to evaluate the relationship between an athlete’s previous training load and what an athlete is prepared for (2, 11, 23). ACWR uses rolling averages to compare recently completed training load periods (generally ~5-10 days) with completed chronic training load periods (generally ~4-6 weeks) (11, 23).

To add, the ACWR method can also be used to identify risk of injury (4, 23, 31). When ACWR scores between 0.8 and 1.3, risk for injury is suggested to be low (2). An ACWR score greater than 1.5 generally shows an exponential increase in injury risk (Figure 1) (2, 3). However, rolling averages do not consider the effects of declining fitness and fatigue over time. Therefore, the validity of using ACWR to evaluate risk of injury is questioned (28, 35).

Internal:External-Load Ratio

The internal:external-load ratio estimates experienced psychophysiological stress during training in the context of the completed external training load. The internal:external-load ratio method can be used to interpret an athlete’s training status. You can find examples of internal and external loads in Table 1 from Part 1. (2)

For example, if an athlete experiences a reduction in heart rate (decrease internal load), they most likely are coping with training and/or gaining fitness (2).

This method can help advice upon the negative effects of training programs (32), identify fatigue in team-sport competition (1, 25), and identify changes in fitness and fatigue status (2, 5). However, this method can be difficult to utilize (2). Controlling and quantifying external loads, and managing the environment can be difficult. Therefore, this must be considered with care when using this method (2, 26).

Injury Prevention

There is high interest in knowing the optimal amount of training to ensure optimal performance but not overwork an athlete (2). Early studies suggest the harder an athlete works (the greater the training load), the greater their risk for injury (12, 16). For example, a 2012 study found when athletes increased amounts of high-speed running, they experienced greater risk for lower body, soft-tissue injuries (18).

However, when training load decreased, so did the presence of injury (13). That being said, recent studies have suggested intense chronic training could prevent injury in athletes (14, 17, 21-23, 31, 33). These studies suggest training load is like a “‘vehicle’ that drives athletes toward or away from injury” (2, 36).

For example, a 2014 study found cricket fast bowlers experienced a lower risk for injury when they bowled a greater number of balls in a 4-week period (chronic training load) compared to bowlers who did less (21).

The suggested “protective response” of training may result from the fact:

  1.  training load exposure allows the body to begin tolerating the load, and
  2. training allows the body to better develop physically, in turn reducing injury risk (15, 19, 27).

These studies suggest 3 approaches to protect against injury:

  1. high chronic training loads
  2. exposure to high chronic training loads to better tolerate high-intensity units in training
  3. association of ACWR to injury risk is better than acute or chronic load alone. (2)

So, How Do I Choose?

With new technologies, and analytical methods, there are a multitude of ways to monitor training loads of athletes. When choosing a method, how efficiently it can be implemented should be considered (2). Using more than one tool or method is also suggested (2). Methods able to count repetitions and/or compute a unit of measure are easy to interpret and then translate into an appropriate training plan (2).

The Sportavida method is a quick and easy tool to help quantify athlete fatigue, muscle stress, and other physiological processes. Implementation is convenient, as Sportavida sampling includes a simple saliva sample which can be done by anyone, anywhere, at any time. Once samples are collected, they are shipped and then assessed by professionals in the lab. An accurate and comprehensive report is delivered to the athlete or coach – providing information on how training load and competition is affecting the athlete’s body.

Consider your goals when deciding on methods and tools to use to monitor training load (2). What do you want to know? Is it:

How much faster is the athlete? Is this equipment improving their strength?

Is the new high-intensity routine fatiguing the athlete? Is the athlete experiencing overtraining?

Use of several methods and tools can add more complexity in interpretation but generally bring more insight to what is occurring (2). Studies suggest to use a consistent approach in a program over an extended period of time in order to get meaningful data about the efficacy of the program (2).

 

Thank you for reading! I hope you feel more informed. If you have any questions or comments, please feel free to leave a shout out!

 

 

 

 

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