
Background on Training Variables: Frequency, Intensity, Time/Duration, and Type/Mode
Endurance athletes have a few key training variables that can be manipulated to optimize training adaptation and maximize race-day performance. These variables include the following:
Frequency
Intensity
Time/Duration
Type/Mode
These variables described above are the key characteristics of training prescription and are the key drivers of training adaptation. The planned manipulation of frequency, intensity, and duration over the course of days (microcycles), weeks (mesocycles), and months/years (macrocycles) is defined as periodization. However, there are a variety of ways that these training variables can be manipulated. Typically, training intensity and training volume (frequency x duration) are manipulated throughout a macrocycle to achieve an important performance goal. For example, training volume might be high and intensity low when an endurance athlete is months away from their main competition. As the athlete gets closer to their competition, training volume might decrease or remain the same while intensity increases so that they are physiologically prepared to perform at their best on the day of their competition.
When it comes to total training volume, typical training volumes among world-class endurance athletes is uniform with some variations depending on the individual athlete. It is well-established that, in general, a greater training volume will yield greater endurance adaptations if the athlete can handle it and recover well from it. This is not to say that there is a specific number of hours or miles that all endurance athletes should strive for, but rather that endurance athletes should strive to generally increase the amount of training volume they can perform and tolerate as this will likely lead to better overall performance.
For example, an amateur runner in their first year of dedicated training might be able to handle running 30 miles/week. As this runner improves, the volume of training required to continually maximize training adaptations might be greater. At the same time, this runner’s capacity to handle and recover from training stress will increase. During the third year of this amateur runner’s dedicated training, they may be able to perform 50 miles/week of running. Now, this runner will surely reach a threshold of running volume at which their performance no longer benefits, and their risk of injury and illness increases. It would be wise for the athlete to not cross that threshold of training volume as the risk is not worth the reward. Doing more volume, hence, is not always better. But there is a clear relationship between training volume and endurance performance broadly speaking. It is for this reason that world class endurance athletes all perform high training volumes (1,3).
When it comes to training intensity, however, there is some debate amongst coaches and researchers as to which type of training intensity distribution is best for endurance athletes. This is not to say that there is a debate as to whether doing more intense training sessions is beneficial or not, but rather the debate relates to how much time spent at various intensities yields the best results for endurance athletes. Before we can dive deeper into this debate, we need to first discuss what is training intensity and how is it measured.
A Background on Training Intensity
Training intensity is, in simple terms, how hard or easy an effort is. Training intensity can be monitored subjectively and objectively:
Subjective Training Intensity Monitoring
Objective Training Intensity Monitoring
There are upsides and downsides to each intensity monitoring tool, and there really is no such thing as one intensity monitoring tool that is “best”. Each mode of monitoring intensity tells us something that another doesn’t. For example, RPE is highly subjective and a higher RPE value can sometimes be assigned to objectively low exercise intensities when an athlete is under heavy fatigue. Combine RPE with HR and you start to see a more complete picture. That same athlete might indicate a high RPE during an objectively moderate exercise intensity with a HR of 120 bpm, indicating that they are fatigued. Add in other more objective metrics like pace, power, and/or lactate, and the picture becomes even more complete. Often, different metrics will be used under different circumstances as a way of prescribing specific training sessions and/or reviewing training-related data from a specific session. For an easy run, a coach might have an athlete rely solely on RPE. Yet, for a threshold run session wherein the athlete has access to a power meter, the coach might prescribe very precise power outputs for certain durations of time and have the athlete disregard RPE almost completely during the session.
This is only the briefest of introductions on training intensity monitoring. There are entire books written on the topic of training intensity, and it can be quite a complex topic as one dives deeper and deeper into certain intensity metrics. For this discussion, we all simply need to have a basic understanding of training intensity and to acknowledge that there are benefits of each method of training intensity monitoring.
Once we understand training intensity and how it is monitored, we can then begin to create different training “zones”. A training zone is simply a range of values that correlates with a different exercise intensity. Training zones are most often set with highly objective metrics, such as pace, power, and/or blood lactate. Then, HR values and RPE values are assigned to correlate with the different physiological zones. Keep in mind though, that training zones can be effectively setup and utilized based on just RPE and HR if that is all that an athlete has access to. The most basic training zone model is one comprised of three different training zones as seen in the graph directly below.

To keep this piece of the discussion very brief, this is a classic 3-Zone Training Intensity Model depicted with lactate and HR. Lactate is perhaps one of the most precise ways of determining different training intensity cutoffs in an athlete. The only cutoffs that really matter for endurance athletes are the first and second lactate turn-points (LT1 and LT2). LT1 indicates the cutoff for an athlete’s low-intensity training zone, whereby anything below LT1 is considered a low-intensity effort. LT1 through to LT2 indicates an athlete’s moderate-intensity zone. And LT2 is the cutoff for an athlete’s high-intensity training zone, whereby anything above LT2 is considered a hard effort. LT1 corresponds to the exercise intensity at which lactate begins to rise noticeably in the blood above resting values. LT2 corresponds to the exercise intensity at which lactate accumulates in the blood exponentially. LT2 is also known as one’s “lactate threshold” or “functional threshold power/pace”.
These 3 training zones can be setup and based off lactate, power, or pace. Lactate is the most precise way of monitoring intensity, but power and pace can be very precise as well if proper testing is done. What matters here is that we understand that training intensity zones, at their most basic level, are comprised of low-intensity (Zone 1), moderate-intensity (Zone 2), and high-intensity (Zone 3). For those used to a more common 5-zone model, Zones 1-2 fall into Zone 1, Zone 3 falls into Zone 2, and Zones 4-5 fall into Zone 3 when translating them over to the 3-zone model.
Now, the debate amongst researchers and coaches relates to how much time endurance athletes should be spending at various exercise intensities to maximize performance. This is the research we will take a closer look at next!
What’s Better: Polarized or Pyramidal?
Two of the more common training intensity distribution (TID) approaches that endurance athletes follow are the polarized and pyramidal models. Polarized training consists of spending most of one’s time in Zone 1, a very small time in Zone 2, and a bit more time in Zone 3. Pyramidal training consists of spending most of one’s time in Zone 1, a bit of time in Zone 2, and a very small amount of time in Zone 3. See the figure below for a comparison of typical intensity distribution breakdowns for each of these models.

There is a consensus that most of an endurance athlete’s time should be spent at low intensities in Zone 1 (75-80% of total training volume) as this has been documented to be associated with superior endurance performance (1,3). The debate comes into play regarding how much time should be spent in Zones 2 and 3. There is published research to suggest that both TID models are effective (2,4,5,6). So more recently, researchers have tried comparing the two different TID models head-to-head. For example, Filipas and colleagues (2) published a paper in 2021 comparing four groups of well-trained runners completing 16 weeks of training following a different TID plan. The groups were as follows:
Group 1
Group 2
Group 3
Group 4
The total training volume across all groups was equal so that training volume was not a confounding factor. Runners were tested at baseline, mid-point, and post-intervention for a range of factors, including VO2peak, running velocity at blood lactate 2mmol/L, running velocity at blood lactate 4 mmol/L, and 5km time trial performance. All groups saw improvements across all outcomes mentioned above, but the group that performed PYR > POL saw the greatest improvements in the outcomes tested.
So, does this mean that a periodization plan that follows a PYR > POL is the most effective design for all endurance athletes? Not necessarily. It is important to consider the athlete, their goal event, and their fitness when choosing a TID approach. The study mentioned previously had testing outcomes that likely favored the physiological adaptations that would occur from switching to a polarized TID for the last 8 weeks leading into the post-intervention tests. A 5km time trial is performed well above threshold, and a polarized TID has athletes training more often above threshold in Zone 3. Now, the velocity that runners could achieve at LT1 and LT2 improved, indicating improved running economy. We know that training at very high intensities can improve running economy at higher and lower intensities, which is included if one’s training with a polarized approach. It is interesting that the 16-week polarized TID group did not show any superior outcomes when compared to the 16-week pyramidal TID group. So, there is something that was more effective in transitioning between TID approaches in this study.