A comprehensive guide to physiological testing in endurance athletes

An article written by Sophie Herzog, Øyvind Sandbakk, Trond Nystad and Rune Talsnes

Regular testing should be an essential part of the training process, helping to ensure the quality of the training process by informing decisions and evaluating the effects of the training plan. By integrating tests, athletes and coaches can monitor overall performance and related key variables both in the lab and/or in the field. But testing is not only done to measure the overall performance, but can also be used as a monitoring tool to assess whether an athlete is adequately adapting to and recovering from periods of high training loads or if they are developing signs of overtraining or underperformance. This article will discuss a variety of physiological tests used in endurance sports and their practical implementation strategies.

Physiological testing can be conducted in the field, which is practical as it can be performed in the athlete’s specific training and competition environment, or in laboratories, which typically require more sophisticated equipment and trained staff. The feasibility characteristics usually determine the selection of the test methods. Various tests are utilized to measure different aspects of an athlete’s physiological capabilities. Table 1 lists a selection of these tests, their usual purpose, and some of their advantages and disadvantages.  

Table 1: A selection of well-known physiological tests. While anaerobic endurance can only be assessed through maximal performance testing, aerobic endurance tests can be maximal and sub-maximal, continuous or intermittent with fixed or incremental protocols. Note: to keep it simple(r), we have not included biomechanical or anthropometric tests in this overview.

Which test makes the most sense for you or your athletes depends on the specific demands of the sport, the training phase, the state of the athlete and the corresponding goals. For example, it can be useful to test a cyclist’s sprint power, but it makes very little sense to test just this one parameter, as in cycling a final sprint often takes place after several hours of racing. Therefore, combining multiple tests often provides a more comprehensive understanding of an athlete’s performance state, their strengths and weaknesses and it can help to outline or adjust the training process. A well-designed test protocol should be able to inform on whether the athlete’s performance has changed, and what the underlying causes are. Physiological testing should only be done if it can help make the right decisions in the training and development process.

“Testing should not be done simply to test, but to obtain data that can help optimize training, recovery and performance.”

Implementing Testing in the Real World

In practice, physiological testing should be integrated as seamlessly as possible into an athlete’s routine. These sessions should be repeatable, comparable and specific to ensure that one can use the outcome of the session to guide the training process. Testing frequency varies depending on the testing purpose, the training phase and the athlete's state. Typically, 2-6 tests per year are conducted to monitor long-term development, with additional submaximal tests or key training sessions carried out more frequently to monitor key performance indicators (e.g., lactate thresholds) or assess training intensity zones on a more regular basis. Some athletes also use standardized warm-ups as a form of testing to assess “readiness” and do adjustments to the training load of the subsequent session. Even doing a training session on the same segment (e.g., a climb, trail or road section) repeatedly over weeks, months or years creates a valuable “database” that provides answers to the athletes’ response to training in the shorter term and can monitor long-term performance development. When and how to test depends on the accessibility and financial resources allocated to testing. In cross-country skiing, it is common to perform a VO2max and/or threshold test in June, October, and March (at the end of the season). Additionally, submaximal tests are conducted more regularly, recording heart rate, lactate levels, and perceived exertion (RPE) for each stage. Sometimes, the heart rate recovery (i.e., the drop in heart rate during recovery) is also measured. These more feasible tests are performed every 4-5 weeks to monitor the athlete’s progress and can help the athletes to reduce anxiety around testing. If the test results are good or normal, the athlete will proceed with a regular intensity session afterward. Alongside these “official” tests that should be kept very standardized, athletes keep track of time, lactate, heart rate, and RPE during all intensity sessions, hence they could be seen as “tests” too. By combining the results from all major and minor tests, athletes and coaches gain a comprehensive overview of the athlete's state. These results act like a compass (or nowadays a GPS system), guiding the training direction and development process to optimize performance development.

Here's an example of how laboratory tests (T) could be distributed over a season for different endurance sports:

Figure 1: Typical annual season phases described by world-class coaches across Olympic endurance sports. A = altitude camp (2-4 weeks), T= laboratory  testing[i]. Colors indicate different season phases: Green = preparation period, red = competition period, yellow = transition period; ** indicates weeks of peak  performance during international championship or world tours.

Interpretation of tests

A thorough understanding and interpretation of physiological test results are crucial for training adjustments and managing the training process. Having a “database” of many tests is like an “insurance” for when the athlete is not performing as well as expected. For example, a lower-than-normal heart rate at a given workload could indicate improved efficiency or potential fatigue. Therefore, knowing the athlete’s baseline from previous tests and including the athlete in the discussion is essential. Coaches should actively “interview” athletes about their feelings and experiences during tests and compare these with the measurements. The goal is not always to achieve the best values, but to gain insights to make informed decisions. For example, an athlete’s rate of perceived exertion can provide contextual information to interpret the lower heart rate from the example above - indicating whether it is more likely due to improved aerobic fitness or fatigue. The table below shows multiple scenarios and interpretations of physiological responses based on objective and subjective measures of internal intensity at the same external intensity during a submaximal test. These interpretations, especially when complemented with a subsequent incremental test to exhaustion (i.e., performance test) provide quite a holistic picture of the training effect and the athlete’s training status and form the basis for decision support. It is important to note that one must look at all parameters as one, and not just single out one individual value. An example: An athlete has taken a test where the lactate is a bit higher than normal, but heart rate and rate of perceived exertion is lower than normal, and the result was better than the last test (i.e., the athlete completed more stages of the test). It is human to look for “negative” indicators or faults, hence it would be tempting to just focus on the higher lactate levels and conclude that the athlete is not responding well to training. However, the better (and probably more correct) conclusion would be that the athlete has responded well to the training performed and is in a good state, and that the higher lactate levels might be due to a greater carbohydrate availability.

Table 2: An example of a decision-support framework using a traffic light system, whereby green-yellow indicates good training status (“good to go”) and yellow-red light reminds you to be careful, potentially indicating an imbalance and requiring training load adjustments.

Reliability and Validity in Physiological Testing

In addition to the (at times overwhelming) variety of physiological tests and the complexity of their evaluation, there is also the difficulty of carrying out reliable and precise tests. To ensure the reliability of test results, it is crucial to standardize testing conditions as much as possible. This includes using the same lab/equipment, well-calibrated instruments (also the speed and incline of a treadmill must be calibrated daily), standardized protocols, consistent pre-test and test conditions (e.g., training in the days before the test, nutritional intake, caffeine intake, environmental conditions), and conducting tests at similar points in the training cycle (and for females ideally in the same phase of the menstrual cycle). A standardized/calibrated test is crucial for obtaining valid results. If the quality of the test and test routines cannot be guaranteed, it is better to not test in the laboratory at all, as the results can show extreme variability and hence the results cannot be trusted or used in guiding the training process. Consistency helps differentiate between normal biological variation and significant changes in performance. Nonetheless, it is beneficial to know the expected normal variation and being able to distinguish this from a significant change (i.e., the smallest significant change that can be measured). What constitutes the smallest significant change can be debated, but it is reasonable to argue that a significant change for an athlete must be greater than the typical variation, often measured as standard error (SE) or coefficient of variation (CV). To provide you with an example, we can have a look at the normal variation resulting from 4 lactate profiles of an amateur runner, conducted over the time frame of a week. Within the short time period of only a week, there is little expected impact from training and the results can therefore be used to indicate what the normal variation of different intensity measures is [1]. Here, for example, heart rate from test to test has a variation of 1.7 beats per minute (1.1%), while lactate shows a variation of 0.23 mmol/l (10%).

Table 3: Overview of the natural variation of different variables during 4 lactate profiles conducted over the time frame of a week for an amateur runner. SE = Standard error; CV = Coefficient of variation; Range = Span from lowest to highest value.

Conclusion

The principle of quality assurance is a fundamental feature of elite sport. Regular physiological testing to control the training process is an invaluable tool to determine whether athletes adapt to the training, observe individual responses, monitor fatigue and recovery and therefore guide athletes toward optimal performance and preventing negative “side effects” such as underperformance, illness and injury. By systematically measuring and interpreting physiological responses, coaches and athletes can learn a lot about their individual physiology, make informed decisions about training adjustments, ensuring the training plan is tailored to the athletes’ state. This individualization is crucial for sustainable development and optimal performance outcomes while maintaining health and well-being. Effective testing should be kept simple, repeatable and comparable to foster a deeper understanding of training impacts, leading to more confident and capable athletes.

[1] It is important to note that measurement accuracy depends not only on the intensity measure (e.g., heart rate versus lactate) itself but also on the specific measurement device used. For instance, different lactate analyzers require varying sample volumes (e.g., the amount of capillary blood in microliters), which can result in different error ranges.

[i] Øyvind Sandbakk, Espen Tønnessen, Silvana Bucher Sandbakk, Thomas Losnegard, Stephen Seiler, Thomas Haugen. Best-practice Training Characteristics as described by World-class Norwegian Coaches in Endurance Sports. Sports Medicine. In revision.