fbpx
22 December 2019

The Utility of Dynamic/Autoregulated Double Progression

by Brian Minor 0

Brian Minor, MS, CSCS Whether it be session to session, week to week, or block to block, gradual increases in the imposed training stress are necessary to account for the positive adaptations and increases in fitness that take place.  These adaptations occur as a result of performing enough work within a sufficient or specific proximity…

Brian Minor, MS, CSCS

Whether it be session to session, week to week, or block to block, gradual increases in the imposed training stress are necessary to account for the positive adaptations and increases in fitness that take place. 

These adaptations occur as a result of performing enough work within a sufficient or specific proximity of our maximal capabilities. In order for adaptations to continue, the training stress needs to “keep pace” as we adapt and fitness increases. In other words, over time, we need to perform better as we get better.

There are an abundance of progression strategies available to achieve the fundamental objectives of progressive overload. However, at their core, almost all progression strategies aim to progress the training stress via increasing intensity and/or volume in a structured manner. 

In this article I will discuss two of the most common progression strategies, single and double progression, and propose a more ‘pliable’ model of progression that respects, and accounts for, individual differences between lifter’s rates of adaptation and the often significant fluctuations in ‘readiness’ lifters may experience within a training cycle.

Let’s progress with this discussion…(#dadjoke)

Single Progression

Single progression involves the progression of only one programming variable, while keeping everything else the same. The most common and  intuitive form of single progression is adding weight from session to session. However, depending on the exercise, simply adding load may not be the most appropriate or feasible strategy. Adding 2.5 kg to the bar on squats each week can often make sense, especially in novices. However, adding 2.5 kg on a bicep curl or lateral raise each week is a much larger relative increase, even for advanced athletes. The larger the relative increase, the less likely sufficient adaptations have occurred to accommodate using the heavier weight. 

Double Progression

Double progression strategies can accommodate a more conservative increase in the training stress session to session.  As the name implies, it involves progressing two programming variables, with one usually occurring before the other.  Most often, it is when reps are progressed within a predetermined range each week, and load is increased after the top end of the rep range is hit. This method increases the training stress in a more gradual manner, and is often more appropriate than single load progression. Some examples include lighter isolation lifts as alluded to previously, but it can also  be used for heavier compound lifts as rates of adaptation slow with experience.

Traditional double progression models progress the variables in a predetermined, or static manner. Meaning, they often don’t take into account the rate at which the athlete is adapting or their ability to express performance at that moment in time (fancy term is “readiness”). It makes some assumptions, both in terms of readiness and that the magnitude of increase optimal. These assumptions can be a problem.

TRADITIONAL DOUBLE PROGRESSION
Example: 3 x 8-10
Wk 1 100 x 8,8,8,8
Wk 2 100 x 9,9,9,9
Wk 3 100 x 10,10,10,10 
Wk 4 105 x 8,8,8,8

For example, if an athlete has been prioritizing recovery, and is adapting exceptionally well, it may result in the application of a stimulus below what may be optimal for the athlete’s readiness in the next session.

Conversely, if the athlete’s recovery game is subpar, and little if any positive adaptation has occurred, the static nature of the model may result in an excessive stimulus being applied. In extreme cases, perhaps the athlete may not be able to complete the protocol at all.

One additional downside to the traditional double progression model (or any static model, to be honest), is it can be tricky to distinguish true progress from simply working harder from one week to the next. After all, progress and progression are not necessarily synonymous. Let’s say the first set in Wk 1 was 100 kg x 8 reps @  3 RIR, and then the first set in Wk 2 was 100 kg x 9 reps @ 2 RIR. Has the athlete made progress, or did the athlete just push harder and perform one more rep? 

Technically, it’s impossible to say with absolute certainty since acute and residual fatigue can mask the expression of adaptations, but it definiely makes identifying true progress less straightforward. 

Dynamic Double Progression – The DDP Method

“Dynamic” double progression works around many of the potential issues we encounter with static single and double progression models. 

Just like a traditional double progression model, you still operate within a specified rep range with the intent to progress reps and load over the course of weeks. However, the key difference between traditional double progression and DDP is that with the DDP method of progression, your aim is to prioritise and maintain the same relative intensity (RPE or RIR) across every set. This is in contrast to the traditional model which focuses on adding reps, and then load in a sequential, predetermined/static manner. We know that for hypertrophy outcomes, meeting a requisite level of relative effort, while performing a sufficient volume (number of sets per muscle group) is most important and the exact number of reps or weight lifted is far less of a concern (1). Thus, by maintaining a sufficient degree of relative intensity, the DDP method increases the likelihood of providing the ‘optimal’ degree of stimulus for the day, while allowing adaptations and readiness to dictate when increases in reps/load should be made. Thus, progression will come to you as your fitness and readiness increase, provided the relative intensity (effort per set) and total set volume is sufficient. 

Once you reach the top end of the rep range for a given set, you increase the weight for that specific set in the following week/session. Example shown below:

DYNAMIC DOUBLE PROGRESSION
Example: 3 x 8-10 @ 2 RIR

Wk 1
100 x 10 @ 2 RIR
100 x 8 @ 2 RIR
95 x 9 @ 2 RIR

Wk 2
105 x 8 @ 2 RIR
100 x 9 @ 2 RIR
95 x 10 @ 2 RIR

Wk 3
105 x 9 @ 2 RIR
100 x 10 @ 2 RIR
100 x 8 @ 2 RIR

Wk 4
105 x 10 @ 2 RIR
105 x 8 @ 2 RIR
100 x 9 @ 2 RIR

This method is more pliable than the traditional double progression model. Firstly, it shifts the focus in training from the ‘numbers’ (reps/load) to effort within a rep range. This allows for real time adjustments to be made to either reps and/or load from set to set – provided the RPE/RIR is met and reps performed remains within the specified range. 

A scheme like this that uses relative intensity is dynamic/autoregulated in nature (dynamic sounds way cooler), and accounts for the athlete’s ability to perform (readiness) on a given day. Another way to think of this is that the overall stimulus is progressed at the rate the athlete adapts, while also accounting for their ability to express those adaptations. In doing so, it can prevent a lifter from digging an unnecessary recovery hole by training beyond their current capabilities when their readiness is lower than expected. While grit is commendable, insisting on beating the log book can, at times, be a bad idea.

On the flip side, the model accommodates pushing things a bit more when readiness is higher. As an example, let’s say  the athlete from the earlier example is well recovered and looks at their log book and sees they performed 100 kg x 10 reps @ 2 RIR in Wk 1. Since they hit the top end of the rep range the week prior, they increase weight the next week to 102.5 kg for that first set, but maybe they end up hitting 10 reps @ 2 RIR again! In this case, the model has allowed them to really capitalize on the additional recovery and greater degree of readiness. (It also brings up a caveat to the “rules” which I will discuss momentarily) 

There will most likely have days where the model accommodates a bit both ways. Regardless, the aforementioned scenarios are both common occurrences which can’t be accounted for when predetermined/linear increases in training stress are applied dogmatically. 

In addition to providing a nice framework for managing and progressing the stimulus, DDP offers valuable insight into the effectiveness of the existing strategy. Observed progress at a fixed RIR tells us the existing protocol/overall volume within the prior microcycle is likely providing an overload stimulus and producing the positive adaptations we are after. This is especially true as the weeks go on and training fatigue is likely increasing. As alluded to earlier, fatigue can sometimes create the illusion that a program isn’t working as well as it actually is. However,  in cases like this, it may be working even better than your performance indicates since progress is being expressed even while perhaps being masked a bit.  As weeks roll by, you can keep tabs on performance and manage your volume accordingly (a hyooge topic of discussion in itself). The point is, the DDP method serves as a good diagnostic tool as much as it does a progression scheme.

Another vastly overlooked benefit of this method is it gives more autonomy to the athlete and helps them become more comfortable with gauging and applying relative intensity scales; something that admittedly takes some practice. The use of subjective ratings of effort ultimately dictates the reps performed with each load, which in turn, drives the planned load increases. This is a powerful paradigm shift in ‘control’ over the execution of the program as now the lifter is in the driver’s seat when actioning out the program, with their own readiness determining what loads/reps will best suit the set/session at hand. It takes the athlete out of the mentality of chasing an arbitrary number of reps, and shifts the focus to moving each rep as explosively as they can until they reach the prescribed relative intensity. From there,  the protocol unfolds based on the reps performed and whether or not the athlete believes they need to reduce the load to maintain the rep range.

Practical Considerations

I personally lean heavily on the dynamic model for most of the accessories, and variants of main lifts that I program. I will even occasionally use it for a main lift but it’s usually in a volume/development focused block. With that said, the more structurally, and systemically taxing the movement, the more I suggest favoring the slightly lower relative intensities (~3-5 RIR range as opposed to ~1-2 RIR). Since gauging RIR becomes more difficult the further away you are from failure (2), I would make sure you or the athlete is confident in their ability to do so, or perhaps pick a different strategy for those lifts. It doesn’t need to be absolutely perfect, but it should be in the ballpark with consistent effort set to set.

Remember how I mentioned a caveat to the progression structure earlier (“increase weight only after hitting top of rep range”)? If you  increase weight and hit the top end of the rep range again (or very close to the top) you may consider keeping that same weight for one or more of the following sets as well, even if you didn’t hit the top end of the rep range on those sets the week prior. Ultimately, so long as you’re confident you can still stay within the rep range on a subsequent set(s), then maintaining the same load is usually fine, at least for that week.

Example  3 x 8-10 @ 2 RIR
Wk 1 100 x 10 @ 2 RIR
100 x 8 @ 2 RIR (tentatively planning to stay at 100 lbs the next week)
95 x 9 @ 2 RIR (tentatively planning to stay at 95 lbs the next week)
Wk 2 105 x 10 @ 2 RIR (to athlete’s surprise, they hit 10 reps again)
105 x 8 @ 2 RIR (athlete audibled to 105 lbs, but maintained range)
95 x 10 @ 2 RIR

This doesn’t happen all that frequently but there are certainly situations where it can. A couple potential examples are:

  • You are introducing a new exercise and experiencing rapid increases in technical proficiency.
  • You are coming off a lay-off and are a bit detrained. 

In both cases you will gain/makeup ground in a hurry. This is also a good time to remind ourselves how static models may be suboptimal in these cases.

From a planning perspective, when selecting the size of your rep range, be sure to take into account the exercise being programmed. Sometimes a minimal increase in load will throw you below even the bottom end of the range you had in mind. If training for hypertrophy, I just recommend keeping the bottom of the range at least 6 reps. The rationale for that stems from a review that demonstrated that number of hard sets can be a practical way to track/plan volume for hypertrophy when the sets performed are between 6-20 reps (3).

In closing, dynamic/autoregulated double progression can serve a valuable role in practice by progressing the stimulus based on current levels of preparedness and in assessing the efficacy of an existing training stress. The result can be mean more efficient progress, and increased motivation knowing the progression scheme is heavily driven by actual adaptations.

References

  1. Schoenfeld, B., Grgic, J., Ogborn, D., Krieger, J., 2017. Strength and hypertrophy adaptations between low- versus high-load resistance training: A systematic review and meta-analysis. Journal of strength and conditioning research. https://doi.org/10.1519/JSC.0000000000002200
  2. Zourdos, M.C., Goldsmith, J.A., Helms, E.R., Trepeck, C., Halle, J.L., Mendez, K.M., Cooke, D.M., Haischer, M.H., Sousa, C.A., Klemp, A., Byrnes, R.K., 2019. Proximity to Failure and Total Repetitions Performed in a Set Influences Accuracy of Intraset Repetitions in Reserve-Based Rating of Perceived Exertion. J Strength Cond Res. https://doi.org/10.1519/JSC.0000000000002995
  3. Baz-Valle, E., Fontes-Villalba, M., Santos-Concejero, J., 2018. Total Number of Sets as a Training Volume Quantification Method for Muscle Hypertrophy: A Systematic Review. J Strength Cond Res. https://doi.org/10.1519/JSC.0000000000002776

Your email address will not be published. Required fields are marked *

Send this to a friend