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What Coaches and Athletes Can Learn From the Lab: detecting meaningful changes in testing

Updated: Sep 19, 2022

by Alex Maycock

I have seen it common practice for athletes to complete cardiovascular performance testing on a regular basis planned by a coach, often at weekend training camps. When frequently done, I think it is essential to ask what the real purpose and benefit of the testing is. Is it to prove their training program is making athletes faster? Is it to simulate a race effort? Whether testing is a boost to the coach’s or athlete’s ego can be up for debate, but it certainly warrants consideration around what better testing practice could look like.

I'm aware of the common ski team testing examples, which include 3000 m and 1000 m time trials on outdoor running tracks, uphill maximal running tests, and roller ski times trials. Athletes will complete the tests every month or two, hoping to be faster than before. Although this practice is simple and easy, it has a number of issues which warrant consideration before jumping on the “frequent testing” bandwagon. The upcoming points may affect the reliability of the test and in finding any meaningful changes.

An initial consideration is that outdoor testing of this nature lacks any sense of environmental controls. Temperature, humidity, wind, and precipitation could all affect how an athlete performs from one day to the next. Bear with me as I use a running example, a more easily quantifiable sport compa

red with cross-country skiing, with my upcoming points.

Professor Andy Jones, a lead researcher in Eliud Kipchoge’s INEOS sub-2-hour marathon, explained the importance of waiting for the perfect environmental conditions on his sub-2 attempt day. Marathoners only get a few shots annually at earning a personal best, and this opportunity can be quickly kiboshed when the forecast has other ideas. The likelihood of Kipchoge accomplishing the major feat was dependent on numerous factors in almost lab-like conditions being executed perfectly; a pace car, ideal environmental conditions, pacers entering and exiting every 5 km in a chevron formation, and optimal drink feeds handed directly to him rather than dipping out to side tables along the route. These factors may be why 1:59:40 was accomplished in a controlled setting compared with his official outdoor marathon world record mark of 2:01:39. Although both are absolutely blistering paces, 2 minutes is a massive difference in performance at the world-class level.

Therefore, before conducting a mid-summer test on yourself or with your athletes, keep in mind that an individual's performance may depend on how well they are acclimatized to the hot summer conditions and not representative of their best possible execution of the task in a controlled setting.

Additionally, changes in pacing strategies simply from learning the cardiovascular test process (ex. learning a sustainable pace after blowing up the first time) may also result in a better performance irrespective of any actual physiological gains in aerobic fitness status.

At this point, I hope it can be seen why care should be taken when interpreting improvements in testing, and so should the athletes being tested. Younger athletes should see more pronounced improvements compared to mature athletes, simply as a result of growth and maturity, not necessarily from improving one’s VO2 uptake or lactate threshold.

What coaches and athletes can learn from sport scientists:

I really like this research/testing quote from researcher Louise Burke which states, “As in all robust research, the starting point is to control study conditions so that the intervention is the only variable that is changing, and to choose or practice a performance outcome to achieve high and known levels of reliability.” (Burke, 2017)

For this reason, individual comparisons should occur in a meaningful way. This is called intraindividual comparison. In the remainder of this post, I’ll explain why familiarization is essential to ensure an individual understands the test well and that subsequent test results are not simply an improvement resulting from a learning effect.

Human performance research most commonly includes running treadmills, and stationary cycles (Borg, 2018), which have been used to examine differences between experimental conditions in a controlled laboratory setting. However, research investigations depend on the task being highly reproducible amongst participants to detect small yet meaningful changes in performance (Borg, 2018). Further, when coaches or athletes hope to make a comparison between testing, such as pre and post training period or with and without a sport supplement, it is crucial that the individual does not experience a learning effect of the respective test piece.

While other labs have quantified the reproducibility of exercise tasks with a variety of individual backgrounds (Borg, 2018), to our Nipissing University physiology lab’s knowledge, no study has quantified the reliability of performance on a cross-country ski ergometer; a tool which has excellent laboratory control and is not dependent on cooperation from mother nature. Therefore, we studied the reliability of high-intensity sprint training on a cross-country ski ergometer with both experienced cross-country skiers compared to other endurance-trained athletes: runners and rowers.

Ultimately, the purpose of our study was to determine the adequate number of familiarisation sessions for both experienced cross-country skiers and other endurance trained athletes to generate substantially reliable high intensity sprints on a cross-country ski ergometer.


All 19 participants performed the same workout four times on four separate days within two weeks. The workout consisted of a 10-minute warm-up protocol, then the sprint workout (16 sprints; 4 sets of 4 x 30 second maximal sustainable sprints, interspersed with 15 seconds of passive rest, with 3 minutes active rest between the 4 sets) followed by a 10 minute cool-down all completed on the ski erg.


The findings from our study suggest that repeated ski sprint performance on a SkiErg is substantially reliable across all athletic populations; however, varsity level Nordic skiers demonstrate slightly higher estimates of reliability across all four interval sets compared to varsity level non-skier endurance athletes. The study also showed that one day of familiarization improved the reliability of the subsequent sessions; days 1-4 had a greater discrepancy and a larger mean average difference compared with days 2-4 which were closer to identical. This suggests that one familiarization session is essential to learn how to pace the task properly, irrespective of whether a sport-specific trained athlete is at the task or not!

For this reason, be careful assuming the following testing outcome from an athlete, especially younger or less experienced athletes, be a true representation of improvement when in actuality, it may be a result of learning optimal task pacing.

Practical Takeaways

  1. Allow athletes to practice pacing strategies before collecting results in an actual test piece. (This may include completing “test pace-specific” sessions or completing the session ahead of any official test). This should help improve reliability.

  2. Collect data in a controlled setting. Minimize external variables that could be controlled for indoors. Treadmills and ergometers are great testing tools for this reason.

  3. Consider who would benefit from testing- age, athlete maturity. If a sport supplement is being used, keep in mind this is considered a minute detail, potentially yielding exceptionally small gains compared to other factors (like practicing good athlete habits, including recovery with solid nutrition and sleep)- if the athlete is not maximizing their diet and recovery processes, individual experimentation with beetroot juice, creatine, or bicarbonate may not be the best first approach anyways. Intraindividual supplement testing should be restricted for select individuals already maximizing controllable factors like training well and recovering optimally.


Borg David N, Osborne John O, Stewart Ian B, Costello Joseph T, Sims Jesse NL, Minett Geoffrey M. (2018) The reproducibility of 10 and 20 km time trial cycling performance in recreational cyclists, runners and team sport athletes. Journal of Science and Medicine in Sport

Borg GA. Psychological bases of perceived exertion. Med Sci Sports Exerc 1982; 14(5):377-381.

Burke, L. M. (2017). Practical Issues in Evidence-Based Use of Performance Supplements: Supplement Interactions, Repeated Use and Individual Responses. Sports Medicine, 47(s1), 79–100.

Holmberg, H. C., Lindinger, S., Stöggl, T., Eitzlmair, E., & Müller, E. (2005). Biomechanical analysis of double poling in elite cross-country skiers. Medicine and Science in Sports and Exercise, 37(5), 807–818.

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