Strength training program: +25% to strength for 2 months

Most men who go to the gym want one thing from their workouts - a big, muscular body that they can show off to their friends and family.
Often, in pursuit of huge muscles, athletes forget that in addition to size, there is another equally important indicator - strength. A big muscle is not always a strong muscle. Smaller-looking powerlifters lift weights that are beyond the strength of seasoned athletes. If going to the gym for you is not only a way to pump up muscle mass, but also a path to a strong body, then you need to figure out how strength exercises differ from the usual training for a bodybuilder.

How does training for strength differ from training for mass?

In order to understand the fundamental difference between training for strength and mass, you need to delve a little deeper into the theory. Strong athletes may have small muscles due to the fact that their training is aimed at producing myofibrillar hypertrophy. Most jocks gain impressive mass due to sarcoplasmic hypertrophy. Let's look at these two concepts in more detail.

Sarcoplasmic hypertrophy is the growth of muscle tissue due to an increase in the part of the muscles that is practically not involved in the act of contraction. The sarcoplasmic reticulum surrounding the contractile fibers grows due to an increase in the amount of non-contractile proteins and stores of glycogen, myoglobin, etc.

This result can be achieved by training with a large number of repetitions per set. This type of growth occurs when the load on the muscle lasts more than 30 seconds, glycogen stores are depleted, and micro-tears of the fiber occur, which will subsequently be repaired. Of course, this approach also increases strength, but to a much lesser extent than training powerlifters.

Myofibrillar hypertrophy is an increase in the number and volume of contractile muscle fibers, that is, myofibrils. Training with low numbers of repetitions per set when working with submaximal weights produces significant gains in strength, while muscle size increases to a lesser extent.

How to increase strength? A training method used by powerlifters. Minimum reps, maximum weight, more rest between sets. Next, we will analyze in detail all the nuances of such training.

From theory to practice

The strength training we propose will differ from the traditional training of powerlifters, which consists of almost nothing but squats and bench presses. The training will include all major muscle groups and will allow you to significantly improve your results in all basic and advanced strength exercises.

You don't have to train for strength all the time. After finishing the program, you can move on to training with a higher number of repetitions. This way you will get the perfect balance between an aesthetic physique and strong muscles.

Methods of developing strength will bear fruit very quickly and in the future will even help you gain noticeable mass. Your working weight will increase, which means you will not encounter the phenomenon of stagnation, when it seems that training is practically not producing results.

You can get used to a new type of training gradually. The proven method of increasing weight frequently over the years will help you start with 8-9 repetitions in the first week of the program with light weights and achieve sets of 2-3 repetitions with much heavier weights in the last week.

Strength training program

The described technique will show you how to develop strength by increasing your working weight by 25% in just 2 months of regular exercise. This result is difficult to achieve with the help of training used in bodybuilding, but this program is highly effective and is based on the following:

1. Testing ourselves . Testing your strength is an integral part of the program. They will be carried out three times to ensure that your training makes maximum progress. The first test must be taken before the start of classes, the second - in the middle of the cycle, the third - at its completion.

The essence of the test is to determine the maximum one-time weight in a particular exercise. It is calculated using a specially developed formula, the accuracy of which exceeds 97% if you do everything correctly:

(5RM: 0.454) x 1.1307 + 0.6998 = X x 0.454= 1RM

5RM is the maximum weight you can perform 5 reps with. Substitute the indicator obtained during the test and get your one-time maximum for this exercise.

In each test, determine the performance in the following exercises: bench press, barbell squats, standing barbell curls, narrow barbell bench press, dumbbell wrist curls, seated barbell press, bent-over rows, toe presses, shrugs.

1. We train with submaximal weights . How to increase muscle strength in the shortest possible time? Do the minimum number of repetitions with the maximum weight. You don't need to wear out your muscles with endless sets; squeeze everything out of them with a few hard reps.

As mentioned earlier, the transition from habitual training to low-repetition training will be gradual. Additionally, each time you will need to warm up by performing a couple of sets with a warm-up weight.

The goal of the program is to reach the point of performing basic exercises with a weight of 95% of the maximum for 2-3 repetitions by 7-8 weeks. Strength exercises that target large muscle groups are performed to failure with the same weight.

1. Explosive training . Every Friday and Saturday (except test weeks) will be blast days. Basic exercises will be performed in an explosive manner, that is, you should do them, accelerating the positive phase as much as possible, while maintaining the usual duration of the negative one. In simple words, you need to lift weights sharply, jerkily. This way your muscles will learn to contract at maximum speed.

The working weight should be 60% of the one-time maximum. Do not think that such weight loss only slows down progress. Science has proven that the speed of muscle contraction directly affects the strength of the fiber.

Training Frequency for Muscle Growth: What the Data Says

There is a lot of debate about training frequency for muscle growth. See what the data really says.

After my article on training frequency for strength last week, many people wanted to know how beneficial even higher training frequencies would be for hypertrophy. I told them all that frequency probably doesn't matter for hypertrophy. In the end, the two factors that seemed to be most important in explaining the benefits of frequency for strength development (higher average repetition speed and increased motor performance capability) turn out to be less important for hypertrophy.

Linking a variety of studies to Schoenfeld's 2016 meta-analysis of training frequencies, which showed that frequencies of at least twice a week are better than frequencies of only once a week, we understand that these findings are absolutely insufficient to talk about the increase in hypertrophy with exercise. even higher frequency of training. I thought about it and realized that the only reason I wrote my last article was the recent renaissance in frequency research. So I went back to work to analyze the effect of frequency on hypertrophy.

From the very beginning I want to clarify my pre-existing bias. My assumption going into this article was that given equal training volume, higher frequencies would probably be beneficial for strength gains, but probably wouldn't make much of a difference for hypertrophy (beyond two or three times per week) . This bias arose from my observations of physical culture (many successful strength training traditions practice higher frequencies, but for athletes focused solely on hypertrophy lower frequencies are the norm), my non-quantitative assessment of research (several individual studies were found), significant results in strength when using higher frequencies, but very few have found increases in hypertrophy), and my lack of attention to this issue as a coach (I primarily train people for strength, hypertrophy is a universal side effect, and has not been a focus for me since my athletes). In all my other analyzes up to this point (periodization, sex differences, and the effect of frequency on strength gains), the results were more or less as expected. This time I was surprised. So let's dive into the process.

I started by searching several databases to find all relevant studies based on the four criteria.

The study was designed to examine the effects of training frequency based on volume and intensity per exercise or muscle group. The training intervention should last at least 6 weeks.

The study had to provide data on changes in either direct measures of hypertrophy (i.e. muscle thickness or cross-sectional area) or indirect measures of hypertrophy (i.e. muscle mass or circumference measurements), and provide sufficient information to calculate weekly training volume (sets) for a week).

Subjects must be healthy and not elderly (as age appears to influence the relationship between frequency and hypertrophy, as older people are slower to recover from training).

The research must be published in a peer-reviewed journal.

From each study, I extracted all relevant information, including the length of the training period, the number of parameters measured/assessed muscle size before and after training, and the total number of exercises performed per week. From these data, I calculated effect sizes ((post-pre)/(pooled pre-training SD)) and percent muscle growth ((post-pre)/pre) for each hypertrophy measure in each study. I also calculated the percentage of hypertrophy per week.

I analyzed these studies in several different ways. I began with a mixed-effects meta-analysis of effect sizes with frequency as a binary term (i.e., higher frequency versus lower frequency), including all measures from all studies, just direct measures of hypertrophy, and just indirect measures of hypertrophy. I also calculated the pooled weekly percent hypertrophy and between-group difference for all exercises across all studies as a more easily interpretable meta-analysis, since effect sizes can sometimes seem a bit abstract. I weighted the percentage analysis by the number of subjects in the study, adjusting for the number of subjects in each study. For example, if a study had 5% of the total number of subjects in the analysis and only one hypertrophy measure, then that single hypertrophy measure would receive a weight of 5%. If, on the other hand, a study had 5% of the total number of subjects in the analysis, but used five measures of hypertrophy, each of those measures would receive a weight of 1% (so that the overall study weight remains 5%).

I made two tables for further analysis: one table of weekly percentage hypertrophy for each frequency across all studies and one table of the difference in weekly percentage hypertrophy for each frequency. For example, in the second table, the frequency of three times a week was sometimes the high frequency condition and sometimes the low frequency condition; this allows a given frequency to be compared with all other frequencies (both higher and lower) to determine if there is a frequency "sweet spot" or frequency range that works best.

As an additional analysis, I did studies comparing frequencies of once or twice a week with frequencies of 3+ times a week, and studies comparing frequencies of 1-3 times a week with 4+ times a week using weekly percentage hypertrophy. As additional sub-analyses, I analyzed frequency as a binary term using percentage weekly hypertrophy in trained studies, untrained studies, upper body hypertrophy scores, lower body hypertrophy scores, direct measures of hypertrophy, indirect measures of hypertrophy, studies low training volume (<10 sets per week for a given muscle group or <60 sets per week) and high volume studies.

In selecting studies, we did not take into account any other factors: nutrition, intake of nutritional supplements or special sports nutrition, hormonal status, sleep and rest patterns, except the number of workouts. Naturally, all of these factors can be decisive - each of them. Our resource is dedicated, first of all, to sports nutrition and test boosters, but for the purity of the experiment we have omitted all these details.

Strength training program

Strength training will take place 5 days a week. Rest days are Thursday and Sunday. The first sets of 4-10 repetitions with medium weights for warming up. They will prepare the muscles for the main load.

Monday

We perform the bench press, incline dumbbell press and dumbbell flyes for the chest. We start with weights of 60% of 1 RM, by the 4th approach reaching 80-90% of the calculated one-time maximum.

Also on Monday we work the biceps with standing barbell raises, seated dumbbell raises with a regular grip and a hammer grip. Exercises for arm strength also include dumbbell wrist curls. They are performed with the progression of weights in sets described above.

Tuesday

We pump up our legs using squats with a barbell on the shoulders and chest, leg extensions and bends in the machine, and toe presses on the calves.

We finish the workout with triceps exercises. Perform 4 sets of close grip bench press and French press.

Wednesday

We train deltoids with seated military presses, seated dumbbell presses, and lateral dumbbell raises.

For the back, we perform bent-over rows, lat pull-downs, and bent-over dumbbell rows. We finish the workout with barbell shrugs. We remind you that all strength exercises are done with a progression of working weights from 60 to 90% of the one-time maximum.

Friday

Explosive training day. Following the above-described execution technique, we do: bench press, squats with a barbell, standing biceps curls, close-grip bench press, wrist curls with dumbbells.

Saturday

Second day of explosive training. We do seated military presses, bent-over rows, calf toe presses and shrugs.

Remember, the main guarantee of the effectiveness of this training method is the correct selection of working weights and the best exercises for developing strength. The program is designed for athletes who already have some experience and are ready for intense physical activity.

These are the exercises to develop strength that will give you results.
After completing all stages of this training, you will increase your strength by 25%. After which you can freely return to your usual workouts, which will become much more effective by increasing the working weights. Download WordPress Themes FreeDownload Best WordPress Themes Free DownloadDownload WordPress ThemesDownload WordPress Themes Freeonline free course

results

Thirteen studies with 305 subjects met the inclusion criteria, allowing for 40 comparisons. The average study duration was 8.3 weeks (range: 6–12 weeks) with 10.9 subjects per study group (range: 8–15). Four studies used untrained subjects, and nine used subjects with at least some previous training experience.

A random effects meta-analysis of all hypertrophy measures found that higher training frequencies were associated with significantly greater hypertrophy (p < 0.0001), although the overall effect was not significant ( d = 0.113; CI = 0.07–0.16). When analyzing only direct or indirect measures of hypertrophy, the story is very similar (d = 0.143; CI = 0.09-0.19; p < 0.0001 for direct and d = 0.097; CI = 0.03-0.16; p = 0.0098 for indirect).

Direct measures of hypertrophy are blue; indirect indicators of hypertrophy are orange. The general parameter for the scatter of results is gray.

On average, subjects in the lower frequency groups (N = 40 comparisons across 13 studies) experienced an increase in hypertrophy at a rate of 0.42% per week, whereas those in the higher frequency groups increased at a rate of 0.58% per week. The average difference in size gain between groups was 0.16% per week (range = 0.09-0.23%), meaning that the higher frequency groups grew on average about 38% faster (i.e. 0 .58% is 38% more than 0.42%). This could be classified as a small effect (d = 0.47; CI = 0.25–0.68), and the difference was significant (p < 0.0001).

Differences in size increase per week between higher and lower frequencies.

Positive values ​​(blue bars) represent greater gain for higher frequencies, while negative values ​​(red bars) represent greater gain for lower frequencies. The lighter bars are for indirect measures of hypertrophy and the darker bars are for direct measures of hypertrophy.

In this graph and all subsequent graphs like it, the blue dots above the black lines represent comparisons where the higher frequency group grew 10% faster than the lower frequency groups, the red dots below the black lines represent comparisons where the group with the lower frequencies grew >10% faster than the higher frequency group, and the yellow dots below the black lines represent comparisons in which the high and low frequency groups had approximately the same growth. Each point represents one measure from one study. For example, the point (0.5%, 0.75%) would represent a comparison in which the low-frequency group grew at a rate of 0.5% per week, while the high-frequency group grew at a rate of 0.75% per week.

Using direct measures of hypertrophy (N = 19 comparisons in 7 studies), hypertrophy of subjects in the lower frequency groups increased at a rate of 0.72% per week, while subjects in the higher frequency groups increased at a rate of 0.72% per week. 85% per week. The mean difference in growth between groups was 0.12% per week (CI = -0.01-0.26%), meaning that the higher frequency groups grew on average 17% faster. This would be classified as a small effect (d = 0.35; CI = -0.02–0.72) and the difference was not significant (p = 0.079).

Using proxy measures of hypertrophy (N = 21 comparisons across 9 studies), subjects in the lower frequency groups grew at a rate of 0.29% per week, whereas subjects in the higher frequency groups grew at a rate of 0.29% per week. 43% per week. The mean difference in hypertrophy magnitude gain between groups was 0.14% per week (CI = 0.06-0.22%), meaning that the higher frequency groups grew on average 49% faster. This was classified as a medium effect (d = 0.72; CI = 0.30–1.14), and the difference was significant (p = 0.0031).

On average, untrained subjects in the lower frequency groups (N = 16 comparisons across 4 studies) experienced growth at a rate of 0.39% per week, whereas those in the higher frequency groups experienced growth at a rate of 0.58% per week . The mean difference in magnitude gain between groups was 0.19% per week (CI = 0.09-0.28%), meaning that the higher frequency groups gained on average 47% faster. This was classified as a medium effect (d = 0.62; CI = 0.31–0.94) and the difference was significant (p = 0.0014).

On average, trained athletes in the lower frequency groups (N = 24 comparisons in 9 studies) gained a rate of 0.44% per week, while similar subjects in the higher frequency groups grew at a rate of 0.58 % in Week. The mean difference in hypertrophy magnitude gain between groups was 0.14% per week (CI = 0.04–0.25%), meaning that the higher frequency groups experienced an average of 32% greater growth. This was classified as a small effect (d = 0.38; CI = 0.09–0.67) and the difference was significant (p = 0.016).

On average, upper body hypertrophy was observed in the lower frequency groups (N = 17 comparisons in 8 studies) at a rate of 0.42% per week and in the higher frequency groups at a rate of 0.59% per week. The average difference in size gain between groups was 0.17% per week (CI = 0.03–0.31%), meaning that the upper body of the higher frequency groups grew about 40% faster, on average. This was classified as a medium effect (d = 0.50; CI = 0.09–0.91) and the difference was significant (p = 0.029).

On average, the rate of lower body hypertrophy was observed in the lower frequency groups (N = 14 comparisons in 6 studies) at a rate of 0.65% per week and in the higher frequency groups at a rate of 0.83% per week. The mean difference in increase in hypertrophy magnitude between groups was 0.18% per week (CI = 0.03–0.34%), meaning that the lower body of the higher frequency groups grew approximately 28% faster, on average. This was classified as a small effect (d = 0.41; CI = 0.06–0.76) and the difference was significant (p = 0.038).

Note: This graph looks fairly flat, however, seven points are from one study, and all comparisons in that study showed either a typical increase or an apparent large increase with a lower frequency. Everything is done taking into account statistical analysis in order to equalize the absolute values ​​in the studies

This version of the graph has only one data point per study (the average of all measures in that study); it's a little more reflective of what the statistical model "saw".

In lower volume studies (N = 16 comparisons in 7 studies), subjects in the lower frequency groups grew at an average rate of 0.32% per week, while subjects in the higher frequency groups grew at a rate of 0.32% per week. 57% per week. The average difference in size gain between groups was 0.25% per week (CI = 0.10-0.40% per week), meaning that the higher frequency groups experienced approximately 77% faster hypertrophy growth, on average. This was classified as a large effect (d = 0.82; CI = 0.34–1.30) and the difference was significant (p = 0.0046).

This comparison also included Ocha's study with 7 separate comparisons, so I've combined them again here. Note that there are 8 points instead of 7 because one study had both male and female groups and I have presented them separately in this chart.

In higher volume studies (N = 24 comparisons in 9 studies), subjects in the lower frequency groups experienced an average increase in hypertrophy of 0.46% per week, while subjects in the higher frequency groups experienced an average rate of 0.46% per week. .58% per week. The mean difference in hypertrophy magnitude gain between groups was 0.12% per week (CI = 0.03-0.21% per week), meaning that the higher frequency groups grew on average 27% faster. This was classified as a small effect (d = 0.34; CI = 0.08–0.60) and the difference was significant (p = 0.017).

Because I combined low-volume studies when plotting, I also combined high-volume studies to ensure consistency.

Simply looking at the average hypertrophy reported with each frequency across all studies, there does not appear to be a significant relationship between frequency and hypertrophy. When performing simple linear regression, the correlation coefficient is basically zero (r = -0.04).

Note: This is the most common general approach to data analysis like this, but I feel it is wrong.

However, as explained in a previous article on the relationship between increasing frequency and strength, simply comparing the average hypertrophy observed at different frequencies does nothing to eliminate the differences in hypertrophy observed between studies. Imagine you have three studies. One compares a frequency of once a week with a frequency of four times a week, a second compares a frequency of three times a week with a frequency of four times a week, and a third compares a frequency of once a week with a frequency of three times a week. In the first study, the low frequency group (1x) grows by 2% and the high frequency group (4x) grows by 4%. In the second study, the low frequency group (3x) grows by 4% and the high frequency group (4x) grows by 6%. In the third study, the low frequency group (1x) grows by 8%, while the high frequency group (3x) grows by 10%. Just averaging the size gain, you're looking at a 5% increase once a week [(2% + 8%)/2], a 7% increase three times a week [(4% + 10%)/2], and an increase of 5% [(4% + 6%) / 2] four times a week. It appears that 1x/week and 4x/week result in similar growth, while 3x/week results in the most growth; however, these conclusions are based on differences between studies rather than frequencies. In a direct comparison, on the other hand, 1x is worse than 3x and 4x by 2%, 3x is worse than 1x by 2% and 4x by 2% (average 0%), and 4x is worse than 1x and 3x by 2%. This more accurately represents the results in this imagined trio of studies because it does a better job of accounting for the variability of results between studies.

I believe that direct comparisons (orange dots) better reflect the results of these imaginary studies than simple averages (green dots).

When the frequency of once per week (N = 25 comparisons from 10 studies) was directly compared with other frequencies, it was slightly inferior in direct comparisons by 0.079% per week. The frequency of twice a week (N = 17 comparisons from 7 studies) is not significant in direct comparisons at 0.080% per week. The frequency of three times per week (N = 21 comparisons from 7 studies) was generally performed at par in direct comparisons (minimum lead of 0.009% per week). The frequency of four times per week (N = 9 comparisons from 2 studies) was slightly higher than 0.087% per week. The frequency of five times per week (N = 7 comparisons from 2 studies) was greater than 0.310% per week. Finally, a frequency of six times per week was greater than 0.194% per week, but one study only had one measurement examining such frequency. Because there are fewer studies examining higher frequencies greater than three times per week, we again pool results from studies using frequencies of 4+ times per week (N = 17 comparisons from 5 studies), finding that they were superior to direct comparisons by 0.185% in Week. Higher frequencies were associated with greater hypertrophy in direct comparisons (r = 0.32, p = 0.0036).

Given the linear relationship between frequency and hypertrophic overperformance in direct comparisons, I examined the results of studies comparing frequencies of once or twice per week with frequencies of 3+ times per week, and studies comparing frequencies of 1-3 times per week with frequencies of 4+ times per week to check the results of the regression analysis. Twenty-four measures from eight studies were included in the first comparison, and 17 measures from five studies were included in the second comparison. In both comparisons, the higher frequency groups experienced significantly faster hypertrophy. The effect size was small (d = 0.33) when comparing frequencies 1-2 versus 3+ and medium (d = 0.51) when comparing frequencies 1-3 versus 4+

Since there appears to be an approximately linear relationship between frequency and hypertrophy, we can analyze the slopes again to see how much additional hypertrophy we can expect as frequency increases. Each additional day of frequency increased weekly hypertrophy by 0.11% (CI = 0.05-0.16% per week). The average hypertrophy rate across all frequencies across all studies was 0.50% per week, meaning each additional day of frequency resulted in an average of 22% hypertrophy. This slope was significantly different from zero (p = 0.0004).

Each blue line represents the slope of the frequency/gain relationship in one study. The red line is the mean slope, and the black lines are the top and bottom of the 95 percent confidence interval. A positive slope means more hypertrophy at a higher frequency, while a negative slope means more hypertrophy at a lower frequency.