The LSCT: How To Monitor Fatigue and Predict Performance
The Lamberts and Lambert Sub-maximal Cycling Test (LSCT) is a short, structured test protocol that we use to assess the fatigue state and training readiness of cyclists and triathletes we work with, where the tests help us as coaches to make more informed decisions on:
how fatigued a cyclist is
whether a particular planned session or string of sessions are pitched at an appropriate load
when an athlete is ready to return to inducing a training stress within a recovery-focused week
to what extent key physiological markers are improving as a result of the training program.
For cyclists to adapt positively to a training program over the long-term, the right balance of training stress and recovery is needed for a supercompensatory response to occur. A large part of a coach’s (or indeed a self-coached athlete’s) role is adeptly monitoring fatigue state and ensuring that the shorter term training dose is appropriate in that context.
Whilst there are a number of ways to monitor fatigue state, from simple but effective methods like an honest daily assessment of mood (e.g. using the Profile of Mood State - POMS - questionnaire) or a rating of fatigue, up to more involved and data-heavier methods such as heart rate variability (HRV), the LCST provides a means of combining measures of internal stress and external workload/output that can be easily integrated into a training program without a negative impact on planned training or the ability to recover well.
Let’s first take a look at how to perform the LSCT, before discussing how the data from the tests can be interpreted and practically applied. Finally we’ll cover some tips and considerations to help improve the execution of the LSCT test protocol.
What’s the LSCT?
The LSCT is typically a 16-17 minute long test, which can be used as a warm-up and as a standalone session when training stress is intended to be kept low, i.e. in a recovery-focused microcycle or on a recovery day within a training microcycle.
As mentioned above, the test is designed to predict performance increases and assess training/fatigue status, and is helpful when specifically looking for signals of potential non-functional overreaching/overtraining with regards to the latter.
How To Perform The LSCT
Cyclists performing the test are required to ride at intensities which elicit certain percentages of their maximum heart rate (MaxHR) values, where it’s advised by Lamberts and Lambert, and the other original authors, that this MaxHR value is determined from a step-test to determine peak power output (PPO), though other accepted means of determining MaxHR will work well.
Throughout the test, power output, HR, cadence and RPE are recorded.
It’s also worth noting that pre-test dietary patterns, particularly the consumption of caffeine (which can increase HR) is controlled, where it is advised that no caffeine is consumed within 3 hours prior to the test.
The test itself is split into 4 distinct stages:
Stage 1: Cyclist rides at an intensity that elicits 60% of MaxHR for 6 minutes
Stage 2: Rides at an intensity that elicits 80% of MaxHR for 6 minutes
Stage 3: Rides at an intensity that elicits 90% of MaxHR for 3 minutes
Stage 4: Stops pedalling after the 3 minute effort above is complete, sits up, and allows the HR to drop, where Heart Rate Recovery (HRR) is measured.
In stages 1, 2 and 3, the performance data analysis is conducted from 1 minute into each stage, setting aside this initial 60 seconds where the power output is higher than would typically be associated with the target HR in order to raise the HR to the desired level quickly.
RPE is recorded for the final minute of stages 1, 2 and 3.
A file will look something like the following, where an initial effort of a higher power output is applied to speed up the HR increase in the first minute of each stage, before power output is then reduced to a level sufficient to maintain HR as close to target %MaxHR as possible:
How To Interpret LCST Data
As mentioned previously, performing this kind of test allows cyclists and coaches to better assess training status and make more informed decisions about the appropriateness of the training load of upcoming sessions.
After a series of tests, which are usually conducted on a weekly basis either on the same day each week or at the same stage of a microcycle that is shorter or longer than 7 days, the data can help coaches and athletes to better understand the performance and fatigue trajectories.
So what decisions can be made off the back of LSCT results and what criteria influence these decisions?
Whilst specific criteria should be adjusted slightly for each individual athlete, and some will be more pertinent than others in particular cases, criterion suggested in the literature include:
Looking at RPE during Stage 2 compared with previous tests to see if there has been an increase ≥1 unit
Inability to achieve the target HR of 90% MaxHR within first minute of Stage 3
Change in Heart Rate Recovery (HRR) of >2 beats/min (whether a faster or slower HRR)
In the concerned study, the athletes did not proceed with the planned high intensity training if two or more of the above criteria were met.
Of course, if the results are positive, they can be interpreted in the context of the wider training program to make a decision on whether to proceed as is already planned or indeed increase the training load further.
On a simplified level, the relationship between power output and HR is quick to analyse and of particular interest, since increases in power output for a given HR can indicate an increase in performance capacity and vice versa. RPE also serves to supports the ‘picture’ generated from each test and combines with the HR data to provide a strong assessment of internal stress.
On output data alone, power production in the 3rd stage is particularly important to examine, as this has been shown to correlate closely with improvements in various accepted performance measures like PPO (peak power output) and time-trial performance.
The HRR (Stage 4) element of the testing in another insightful step that is packed into this compact test protocol. Differences in the extent to which HR drops immediately after the 3 minute effort @ 90% MaxHR is also indicative of training status.
Rather counterintuitively, a faster HRR (drop in HR) can in some cases indicate fatigue, which is worth noting given that a “quicker recovery” would often be seen as a positive adaptive response and demonstrates that this measure should be considered with the additional measures discussed above, rather than drawing any conclusions from the HRR measure alone.
The mechanisms behind faster HRR are not well understood, but may be related to increased parasympathetic activity (Mann, T. N. et al., 2015).
LCST Tips
In the original study by Lamberts et al. (2010), in our own experience with athletes, and anecdotal experience from other coaches using the LCST, the test does not disrupt usual training practices or compromise recovery when used ~1x per microcycle.
Being sub-maximal and short in duration, the LSCT does not cause excess fatigue or take away significant amounts of training time.
On the contrary, the test can be used as a warm up for higher intensity sessions, but one which offers insights useful to the coaching process rather than simply preparing the athletes’ skeletal and cardiovascular systems for intensive training.
Since the test relies on mediating intensity to maintain specific HR values, making subtle adjustments in intensity in real-time can be challenging for some cyclists, and therefore it may take a few familiarisations to develop this skill to a level which produces accurate results.
As mentioned, the test can and perhaps should be performed on a weekly basis, and under the same conditions each week (i.e. before/after a certain type of session with a certain load), so that results from tests over time can be accurately compared.
Summary
As is illustrated here, this relatively short 16-17 minute test packs in a lot of measures which can be used to interpret the cyclist’s current fatigue state and give coaches and athlete’s themselves a very time and energy efficient means of gathering several useful data points for the purpose of fatigue and training readiness monitoring.
The extent to which certain markers truly indicate fatigue and the impact that performance markers will have on the ability for the athlete to perform a certain session needs to be assessed on an individual basis over time and after multiple high quality tests.
It’s worth mentioning that this test method demonstrates how HR and RPE, which are sometimes seen as rudimentary and outdated tools, remain important metrics to monitor and assess.
It is also important to note that the test cannot tell us where fatigue/overreaching is coming from, and it is important that coaches work closely with athletes to determine if the training dose is too high or too low and what extra-training factors may be impacting fatigue and the ability to train and perform optimally.
For more good information, visit http://www.scienceandcycling.com/ and see the references below.
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References
Capostagno, B., Lambert, M. I., & Lamberts, R. P. (2016). A systematic review of submaximal cycle tests to predict, monitor, and optimize cycling performance. International journal of sports physiology and performance, 11(6), 707-714.
Decroix, L., Lamberts, R. P., & Meeusen, R. (2018). Can the lamberts and lambert submaximal cycle test reflect overreaching in professional cyclists?. International journal of sports physiology and performance, 13(1), 23-28.
Hammes, D., Skorski, S., Schwindling, S., Ferrauti, A., Pfeiffer, M., Kellmann, M., & Meyer, T. (2016). Can the Lamberts and Lambert Submaximal Cycle Test indicate fatigue and recovery in trained cyclists?. International journal of sports physiology and performance, 11(3), 328-336.
Lamberts, R. P., Rietjens, G. J., Tijdink, H. H., Noakes, T. D., & Lambert, M. I. (2010). Measuring submaximal performance parameters to monitor fatigue and predict cycling performance: a case study of a world-class cyclo-cross cyclist. European journal of applied physiology, 108(1), 183-190.
Lamberts, R. P. (2014). Predicting cycling performance in trained to elite male and female cyclists. International journal of sports physiology and performance, 9(4), 610-614.
Mann, T. N., Platt, C. E., Lamberts, R. P., & Lambert, M. I. (2015). Faster heart rate recovery with increased RPE: Paradoxical responses after an 87-km ultramarathon. The Journal of Strength & Conditioning Research, 29(12), 3343-3352.
