Wednesday, September 25, 2013

Intensity-Effort Table for Strength training

Intensity-Effort Table for Strength training

Continuing on my rant on three parameters of intensity in strength training I decided to update my Percent-Repetition Chart from August, 2012 that seems to be quite popular (I have seen it in couple of blogs and some recent books – I don’t mind – au contraire – I feel pride).

I have modified and updated this table over the last year mainly using ideas and work of others like Dan Baker, Michael Tuchscherer, Joe Kenn and Donnell Boucher.  

The table features Intensity zones (% of 1RM) and Effort zones (proximity to failure; see Intensiveness). Effort zones could be based on Tuchscherer’s RPE levels, but for this table I have chosen Dan Baker effort zones (which he presented in is Wave-cycle approach to In-season training at this year’s NSCA conference).

The table is read starting with Intensity level and then you choose Effort level. This way you get amount of reps that should be done in a given set. 

Training cycles can progress in couple of ways and one can use this table in most of them (at least for compound movements, not for Olympic lifts and power/ballistic movements). 

Just for the sake of example I will present couple of different progression schemes over a cycle. Some of the variations can be called intensification, accumulation, “effortification” (my word  ), depending on what are you progressing and what are you trying to keep same. All of these represent Level Three – Programming in Tool of Three Levels™ approach.  

Increasing intensity and effort over cycles, while keeping the same reps and volumes (written in brackets)
Week 1: 80% x 3 reps x 6 sets (18) [HE]
Week 2: 82.5% x 3 reps x 6 sets (18) [HE]
Week 3: 85% x 3 reps x 6 sets (18) [NME]
Week 4: 87.5% x 3 reps x 6 sets (18) [NME]

Increasing number of reps and effort over cycles, while keeping the same intensity
Week 1: 80% x 3 reps x 6 sets (18) [HE]
Week 2: 80% x 4 reps x 6 sets (24) [HE]
Week 3: 80% x 5 reps x 6 sets (30) [NME]
Week 4: 80% x 6 reps x 6 sets (36) [NME]

Increasing the volume (number of sets) while keeping everything else the same
Week 1: 80% x 3 reps x 4 sets (12) [HE]
Week 2: 80% x 3 reps x 5 sets (15) [HE]
Week 3: 80% x 3 reps x 6 sets (18) [HE]
Week 4: 80% x 3 reps x 7 sets (21) [HE]

Increasing the intensity while keeping effort the same by decreasing number of reps. Keeping the volume pretty same
Week 1: 75% x 5 reps x 5 sets (25) [HE]
Week 2: 80% x 3 reps x 7 sets (21) [HE]
Week 3: 85% x 2 reps x 9 sets (18) [HE]
Week 4: 90% x 1 reps x 12 sets (12) [HE]

One could probably come up with dozen versions utilizing different combos, rep and set schemes, etc. 

The point of this table is using it to understand certain progressions in certain programs, to allow us easier progression and to see how much we are pushing it in certain cycles. Use Prilepin table as a guideline for volume, but keep in mind that this table is used in Olympic lifting, so it could be a bit ramped up with general strength goals and it could be ramped up a lot with hypertrophy goals.  

If you are interested in velocity-based approach modification of this table please refer HERE

I wish to thank everyone who have used it in their blogs, books and work. That keeps me motivated to share and contribute more to this field. 

Intensity-Effort Table with rep ranges

Intensity-Effort Table with exact number of reps for easier reading

Click HERE for Excel workbook. 


Andrew McGunagle asked a good question in the comments and I wanted to address it in the article since I planned covering it. 

If athletes are getting stronger from week-to-week and the percentages are becoming slightly less-accurate, would the prescribed effort levels begin to take precedence for weight selection?

The table above is useful for shorter cycles (up to 6 weeks IMO) without adjusting either percentages or 1RM. 

With shorter cycles (4 weeks), last week might be something 6x3 w/85%, while in longer cycles (12 weeks) it might look like 6x3 w/95% because 1RM improved during that longer cycle.  This again depends on the duration of the cycle and "expected" improvement in 1RM (which depends on the level of the lifter). 

So, ones needs to either adjust 1RM used in planning the weights or adjust the percentages for the long cycles. 

This is pretty similar to work by Jim Wendler and his 2x5/3/1 plus unload week (7 week cycles). 

Between each 5/3/1 cycle, Jim Wendler recommends  adjusting (increasing) your 1RM for 1,25-2,5kg for upper body and 2,5 to 5kg for lower body (make sure to remember that he recommends starting 5/3/1 with 90% of 1RM). 

Using absolute 'jumps' instead of percentages work better because it adjusts for the level of the lifter automatically. This means that beginner will improve more from phase to phase in terms of percentage, than advanced lifter (e.g. 2.5% compared to 1.25%). If you put this to numbers, hypothetical beginner squatting 100kg gets improvement of 100x2.5% = 2.5kg, and advanced lifter get 200x1.25% = 2.5kg. Hence, if someone uses 1RM 'jumps' it is better to use absolute weight than percentage. If I have used same percent jump, the advanced lifter (since he is using more weight) will get unrealistic jump in 1RM.

"Better" option might be to test 1RM using open sets in the last part of the cycle and adjust 1RM accordingly (see Juggernaut method). In the example above (6x3 @85%) this might take a form of 5x3 @85% and 1x3+ @85%, where one tries to perform more than 3 reps on the last set. If one uses 2 reps in buffer (i.e. 5RM) and the athlete performs 8 reps, then 1RM needs to be adjusted for the next cycle. 

One could also use 'subjective approach' and use RPE levels (effort levels) as Andrew pointed out to adjust loading. This is how Mike Tuchscherer autoregulates his training. 

Third and novel option might be to use velocity based approach, since velocity is most stable from cycle to cycle and doesn't demands re-testing. I have wrote about this extensively - just check the Velocity-based strength tab.



Monday, September 23, 2013

Three I’s of intensity in strength training

Three I’s of intensity in strength training

This is a short rant regarding the confusion that exist regarding the topic of intensity in strength training. Without going into too much of details (I have spoken about this problem before HERE and HERE) my opinion is that Intensity (with the big “I”) has THREE interrelated components:

INTENSITY – This is weight on the bar [absolute], usually expressed as percentage of your maximum lift [% 1RM] or expressed as weight with which you can do certain number of maximum reps [5RM, 10RM, etc]. Example might be squat with 150kg, or bench with 80% 1RM or press with 10RM weight which might be 50kg [10RM = 50kg]. 

INTENT – Is lifters’ [well duh] intent to lift each rep with maximum acceleration and speed. For example, using 80% 1RM one athlete might use maximum intent and lift it with 0.4 ms-1 mean velocity or he might use sub-max intent and lift it with 0.2 ms-1. With the same intensity [% 1RM] using different levels of intent will yield different levels of force, power, velocity & acceleration and TUT (Time Under Tension). Sometimes this takes form of Tempo prescription.

INTENSIVENESS -  This is how close to a failure [RM; repetition maximum] you are. If the intensity is 80% 1RM one might perform 3 reps [pretty away from failure] or perform 7 to 8 reps [which is point of failure]. There are couple of ways of controlling and prescribing intensiveness. One is to prescribe intensity with nRM [e.g. 5RM weight, or 10RM] and prescribe reps with that weight, something along these lines 8[10], which means do 8 reps with the weight you could use to do 10 reps. In other words reps in the tank, in this case 2. You can also prescribe reps in the tank for a given intensity (e.g. lift this weight until you have two left in the tank). Another way is using RPE (Rate of Perceived Exertion/Exhaustion) which is another way to quantify/quality reps left in the tank. One novel way of controlling and prescribing intensiveness is by monitoring velocity of the lifts (especially the stop velocity), taking into account that intent in every rep is maximal. 

Coaches, and especially researchers should take into account all three parts of prescribing and quantifying Intensity (Intensity together with Volume provide LOAD; but I will leave different ways of quantifying Volume for another rant) to avoid confusion and provide precision. This could be done with monitoring velocity of the lifts as well and I urge researchers reading this to start using velocity data to supplement usual statistics reported (like 1RM, 5RM, % 1RM, etc). 

One thing to consider also is that all these three “components” are related not only to kinetic and kinematic performance [external], but also to MU recruitment, fatigue, etc. Here is a short summary:

INTENSITY – Highly related to force output (both mean and peak) and MU recruitment. Inversely related with velocity taking into account maximum intent.  

INTENT – Related to peak force output (not sure about average force), acceleration and velocity along with MU recruitment

INTENSIVENESS – Related to end velocity (taking maximum intent into account) and MU recruitment. Highly related to fatigue, both metabolic and NMF. Related to volume parameters as well. 
The tricky part is the complexity of their interaction at both micro (single set and sets for an exercise) to mezo (single workout to a single week) to macro (couple of weeks to couple of months) training effects and training prescriptions. Another complexity is that we still don’t know what drives adaptation (gain in strength, hypetrophy) regarding these parameters (i.e. mean/peak force, MU recruitment, volume, velocity…).

Hence the importance of acknowledging these three components, prescribing it and reporting it with studies. 

Tuesday, September 17, 2013

UPDATE: Percent-based to velocity-based converter 2.0

I have updated Percent-based to velocity-based converter to include conversion from velocity-based to percent-based approach using load-velocity profile and %1RM-max reps profile. This is important since it allows coaches to get easier 'grip' on velocity-based approach and how it could be used and converted.

Here is the screen shot

You can download the new version HERE. Please refer to video on this page on how to use it.

Tuesday, September 3, 2013

Percent-based to velocity-based converter

Percent-based to velocity-based converter

“Nothing Is More Practical Than A Good Theory” – Kurt Lewin[1]

In the following video I am explaining how to use Excel converter to convert percent-based programs to velocity-based programs based on lifters load-velocity profile for a given movement.

I am covering some important ‘rules’ and relationships of velocity-based approach to strength training, like load-velocity profiles, minimal-velocity threshold, “reps-in-tank velocity relationship” (not sure if I should patent this one?) – So before watching the following video please refresh your understanding by reading the following posts:

Here is the Excel converter I used in this video [DOWNLOAD].

[1] In the video I stated that Volta said this, but I cannot find it anywhere online. Apparently Kurt Lewin said it. 

Monday, September 2, 2013

GymAware user stories: how to track 1RM without actually testing it

GymAware user stories: how to track 1RM without actually testing it


There are two main methods for estimating 1RM of an exercise: (1) to build up to true 1RM lift and (2) to estimate 1RM from reps-to-(technical)-failure [RtTF] with sub-max weight using various formulas and tables.

One simple formula to be used with reps-to-(technical)-failure [RtTF] is the following:

For example, if I squatted 140kg for 5 reps (6th rep would be impossible or technically flawed) I can estimate my 1RM using the above formula:

The problem with these two approaches is that they demand time and energy to be done. Some lifters following Bulgarian ideology lift to daily 1RM by ramping up the weight from set to set in the main movements and finish-up with couple of sub-max sets. RtTF could also be applied somewhere in the training cycle by performing one open set at the end of the prescribed sets (e.g. after doing 2x5 reps with 80%, try to do 3rd one with as-much-reps-as-possible).

Both of them are viable options for occasional testing days. What we are looking for is a way to estimate 1RMs DAILY and without negatively affecting the normal training process. This is important because regular monitoring could help us individualize training load, durations of the training blocks and tapering, especially if it is combined with a measure of workload (like tonnage, relative volume or what have you)[1].

Testing days are a bit left behind us because, excluding the strength sports (but even there),  athletes nowadays cannot afford a whole day for testing and doing it occasionally to be useful – especially in team sports. What do we need is continuous monitoring of both training loads and training effects without negatively affecting the normal training process. This would give us a feedback and it is up to us then to manage emerging information and to modify the overall training process based on them (without relying too much on predefined set/rep schemes and block distributions and durations).

One quick way to do this is to use ISO pulls. Yet for that we need specialize equipment (like force plates or force gauges). Plus we are not sure how force expression at certain joint angle relates to the dynamic movement for a certain individual. Although this might be used as an indicator of improvement/regression, it is not a best way to estimate 1RM for a dynamic movement.

I am about the present you the most simple and quickest way to do just this by using nothing more than your warm-up sets.

Estimating 1RMs using load-velocity regression

I have wrote previously on the method for estimating 1RM using load-velocity relationship. This could be considered new, or the third way to estimate 1RM (two of them being true 1RM test and reps-to-(technical)-failure as explained). What I would love to do now is to tweak it a little bit and make it applicable for daily monitoring instead for occasional full session testing.

Performing either true 1RM or RtTF testing session with velocity analysis should still be the gold standard and it should be performed occasionally at specific check marks or competitions. Here is why – you need to know your “minimal velocity threshold” (MVT) or in plain English the velocity of your 1RM repetition. 

Interestingly enough, the “minimal velocity threshold” (MVT) is the very similar for 1RM lift and for the last rep in RtTF tests[2].  In other words, the mean velocity of the 1RM repetition will be not be (statistically) significantly different than the mean velocity of the last repetition in the 5RM test.

Hence, to use load-velocity regression one needs to know his MVT for the exercises he wants to monitor. In the following table there are MVTs for bench press and squat movement that one could use as a starting point before estimating his own (or of his athletes) MVT.

To perform 1RM estimation one needs at least 3 data points (more and heavier is better; a.k.a. more reliable) that involve weight used and velocity attained. If you perform multiple reps (is what we all usually do in warm-up sets) then take the best rep. The estimation is very easily done in MS Excel. Here is the example calculus:

Using =TREND function one can easily estimate the weight at 0.3 ms-1 in the squat, which is 164kg in this case. Standard Error of Estimate (SEE)[3] is the measure of the accuracy of predictions. We should aim to minimize this by performing all the sets with same technique (depth, pause at the bottom, etc). Sometimes SEE might be a bit higher on certain days, which might also be indicator of performance in some way (if take into consideration that the weight in the warm-up sets are the same across monitoring period) or just plain proof for lack of focus.

One way to use SEE is to provide confidence intervals for the 1RM estimate. For 90% level of confidence[4] that means multiplying SEE with 1.645. For the example above we are 90% certain that 1RM lies within:

 If you plan graphing your scores you can use confidence intervals as error bars on the graphs.

On the following table is an example of the training program for squat and tracking of the warm-up sets for estimating daily 1RM. The numbers come from my self-experiment with higher frequency lifting

On the following picture is a visual representation of daily estimated 1RMs with 90% CI (error bars), cycle 1RM (dotted horizontal line) with its SWC[5] and tonnage (vertical bars) over the duration of the cycle

As you can see from the graph of the daily 1RM is how often it is above/below pre-cycle 1RM (160kg in this case). This is pretty usual variability of the daily readiness and it should be taken into account.

One solution might be to utilize RPE scales alongside rep ranges to prescribe for intensities taking into account daily variability in readiness. One example of such a system is the one by Mike Tuchscherer

Another solution might be to “correct” pre-cycle 1RM by using estimates from the warm-up. In the example above, I had real problems finishing work-out on April 18th because my daily 1RM was 87% of pre-cycle 1RM. Since I planned performing 7x3x80% of 160kg (which is 130kg) I have performed 7x3 with around 90% (130kg / 138kg taking into account large SEE). After that workout I had some really bad knee soreness/pain that lasted for couple of weeks. Dumb decision definitely. What should I have done instead is to use daily 1RM to prescribe percent based training.

Third option to self-regulate would be to completely ditch the percentages and weights to prescribe intensity and rather prescribe training in form of velocities. This is completely novel approach that might yield some potential benefit besides auto-regulation. One of those benefits might be usage of the immediate feedback using GymAware which might yield higher and more reliable effort and hence adaptation stimulus. One aspect of velocity-based approach might involve prescribing the velocity of first rep (e.g. first rep at 0.5ms-1) and velocity threshold (e.g. perform reps until reaching 0.4ms-1) for a certain amount of time with prescribed rest periods.

Velocity-based approach is of great interest of mine. Unfortunately, there are not much of information on such an approach.

One aspect of utilizing daily 1RM estimate might be to allow certain drop during concentrated training block and decide on the duration of such a block and duration of the taper. Knowing how one lifter reacts to certain training load[6] allows for individualization of the training planning and programming, instead of relying on pre-made solutions.

With the above examples in Excel it is quite easy to start estimating daily 1RMs using warm-up sets within your training or with your athletes. Information like this gives you precious feedback to modify and individualize training prescription.

I have provided the simple Excel workbook HERE  that I have used to calculate and graph daily estimated 1RMs.

[1] Interested readers might look forward into Banister’s impulse-response model. Great read on the mathematical modeling of athletic training and performance is a paper by David Clark and Philip Skiba.

Clarke DC, Skiba PF. Rationale and resources for teaching the mathematical modeling of athletic training and performance. Adv Physiol Educ 37: 134–152, 2013

[2] Izquierdo M, Gonzalez-Badillo JJ, Häkkinen K, Ibañez J, Kraemer WJ, Altadill A, Eslava J, Gorostiaga EM. Effect of loading on unintentional lifting velocity declines during single sets of repetitions to failure during upper and lower extremity muscle actions. International Journal of Sports Medicine. Int J Sports Med ; 27: 718–724, 2006. [Pubmed Abstract]

[3] Read more on SEE here and here

[4] Level of confidence is used to describe the percentage of instances in which we will capture the true value. In the case of 90% that means we are 90% confident that the true value resides within the confidence interval. See more in Statistics in Kinesiology and Understanding the New Statistics.

[5] SWC stands for Smallest Worthwhile Change and for this example I have took 0.3 x standard deviation of daily estimated 1RMs over the duration of the cycle (although it should be data from competition). Using SWC and TE (typical error, in this case SEE) one could assess the individual and interpret changes in performance. Read more on these concept by statistics wizard Will Hopkins here, here and here.

[6] The problem in estimating impulse with Banister impulse-response model might be in deciding what represents it. Should one keep track of all tonnage for specific lifts, relative volume, or relative intensity? It is up for coaches to figure out what type of workload statistic gives the best predictions in 1RM response. See referenced paper by Clarke and Skiba on mathematical modeling.