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The Science of Performance |
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The Effect of Training Frequency on Recovery Perhaps the most frequent protest that I hear against a high quality, low volume training approach is that “elites run high mileage, thus proving that high mileage is the best training method”. I agree that elites train using high volume. For many, that is proof enough that high volume is the best training method. However, the path from “all elites train with high volume” to “therefore, it’s the best training method for everyone” is not as short or straightforward as you might think. Is high mileage necessary in order to maximize performance? Should we all follow the example of the elites and strive to run the maximum mileage we are capable of? These are the questions we will be exploring today. Let’s take a look at a particularly interesting research study and see what we can discover. The Normal Distribution Curve Before delving into our research study though we will need to review something you probably learned about back in high school – the normal distribution curve, or more commonly known as the bell curve. Scientists know that humans are born with varying levels of genetic capabilities. A few are born with high levels of genetic talent, a few are born with low levels of genetic talent, and most are born with average genetic talent. The terms “normal distribution curve” and “bell curve” are used to describe this phenomenon of varying levels of genetic talent. If you took a large group of people, measured a physical characteristic, height for example, and then graphed the results, you would end up with a graph in the shape of an inverted U or a bell (hence the name, the bell curve). This graph would show that a few people are very short, a few people are very tall, and that the vast majority fall in the middle between the two extremes. The normal distribution curve applies to any variable physical characteristic you could measure - height, weight, intelligence, speed, endurance, strength, power, agility, jumping height, etc. It also holds true for the amount of time it takes to recover from a workout. Here are some examples of the normal distribution curve.
Two parts of the normal distribution curve pertinent to our discussion today are the mean and the standard deviation. Without going into all the details of their meaning, the important thing to know is that mean and standard deviation are ways of expressing the measured data. If you drew a vertical line down the middle of the curve, your line would divide the curve into two equal parts. Your line would represent the mean, or average. Half of the scores would be to the right of the line and half would be to the left. The mean is represented by the line labeled 0 in the picture below. The mean is the average of whatever you are measuring.
Standard deviation is a measure of the variance of the data - it is simply how close or wide the data is from the mean. For our purposes today the important thing to know is that 96% of the population falls between the lines labeled -2 and 2 on the normal distribution curve – meaning that 96% of the population falls within 2 standard deviations of the mean. Now that we have reviewed the normal distribution curve, let’s take a look at our research study. Recovery Research One of the questions asked by exercise physiologists is how long does it take to recover from a workout? A group of researchers from the Universite Saint-Etienne in France wanted to answer this same question (1). Specifically they wanted to know whether an increase in training frequency would cause a progressive increase in recovery time. They recruited six previously untrained subjects and put them through a 15 week training program. The 15 weeks were divided into four training periods: 1) 8 weeks with 3 training sessions per week 2) 1 week of no training 3) 4 weeks of 5 training sessions per week 4) 2 weeks of no training Each training day during the 8 weeks of 3 training session per week the subjects first performed a five minute test on a cycle ergometer to measure their maximum performance. After a 15 minute rest, the subjects then trained on the ergometer using intermittent exercise of five minutes of work interspersed with three minutes of rest. They repeated this process four times for a total work time of 25 minutes (5 minute test and 4 work sessions of 5 minutes each). The intensity of work was set to equal 85% of their last measured performance, which would be considered to equal about a moderate level of intensity. This same training protocol was repeated on Mondays, Wednesdays, and Fridays during the 4 week period of 5 training sessions per week. On Tuesdays and Thursdays the subjects did not perform the initial test to measure performance, instead repeating the training session five times. During the non-training weeks the subjects were tested for maximum performance several times, but performed no other exercise. The purpose of testing performance with such frequency throughout the entire study period was so that the researchers could determine how long it took each subject to recover from a previous training session. Recover was defined as the ability to duplicate the most previous performance level. Results What were the results of this research? Not surprisingly, the subjects enjoyed a significant improvement in performance throughout the entire study period. However, the researchers noted some really interesting things as the study progressed. During the initial 8 week training period when the subjects were training just 3 days per week it took an average of .9 of a day for the subjects to recover. The standard deviation for recovery time was +/- 2.1 days though. When the subjects increased training frequency to 5 days per week – an increase in training frequency but no increase in training intensity – recovery time changed significantly. Recovery time increased to 3.6 days on average during the 5 days of training per week period, with a standard deviation of +/- 2.0 days. Additionally, the increase in performance from each training session was decreased during the 5 days of training per week period. The subjects continued to improve while training 5 days per week, but improved at a slower rate than during the 3 days per week training period. Discussion The first thing of note in this study is that there is a large difference in recovery times for the subjects. When training was conducted 3 days per week, the mean recovery time (or average recovery time) was .9 of a day or about 22 hours. Recall from our discussion of normal distribution that this means that half of all subjects would recover in less than .9 of a day and half would recover in more than .9 of a day. For 5 training days per week the mean recovery time was 3.6 days. When training 5 days a week while following the same training as these subjects, half of the population will recover in less than 3.6 days and half will recover in more than 3.6 days. Whether the training was conducted 3 or 5 days per week, the standard deviation between the fastest recovery time and the slowest recovery time was about 2 days. Remember that 96% of the population falls within 2 standard deviations of the mean. So what does this mean? Basically it means that some will recover very, very fast – in a few hours – and others will recover much slower - taking up to 7 days to recover. Recovery time for 96% of the population following this training protocol will be between several hours and 7 days. The bottom line is that this study clearly shows that rate of recovery varies amongst individuals and with changes in the training stimulus. This brings up the question of frequency of training. How frequently should you train if it takes you 3 or more days to recover from a workout? How frequently should you train if it takes you less than 1 day to recover from a workout? If you recover in 1 day, should you wait 3 days between training sessions? If it takes you 3 days to recover, should you train every day? Should training frequency be based on recovery speed? I think so and therefore, I recommend that you train only as often as your recovery rate allows. It doesn’t matter how fast someone else recovers – it only matters how fast you recovery. What if you ignore my advice and decide to train before fully recovering from each workout? The second significant finding of this study answers that question. It took on average less than 1 day to recover when training was conducted 3 times per week, but recovery time increased to 3.6 days when training was conducted 5 days per week. Something is amiss with this finding. Consider that if takes less than a day to recover, it seems logical that you could train every day with no problem. However, despite the fact that our subjects “recovered” in less than 1 day during the 3 training days per week, recovery time increased to 3.6 days when they increased training to 5 days per week. Why would recovery time increase if the subjects were fully recovered from the previous training session? Recall that the researchers defined recovery as a return to the most recent level of performance. It would seem that even though the subjects were recovered enough to repeat a previous performance, they were not completely recovered. They were recovered enough to duplicate a previous effort, but recovery to a previous level of performance is not the same as fully recovered. As they continued to workout prior to full recovery, their level of fatigue increased. With the increasing level of fatigue also came a much slower rate of recovery. The more fatigued they became, the longer and longer it took to recover. Not surprising, the rate of improvement also slowed during the 5 days of training per week period. Increasing levels of fatigue would certainly account for this also. This is our second significant finding from this study. The lesson here is that even though you may have recovered enough to duplicate a previous performance it does not mean that you are fully recovered. And if you choose to workout prior to full recovery, it will take you even longer to recover. If you persist in training prior to recovery, your level of fatigue will grow and along with the increasing level of fatigue will come a slower rate of recovery and a decrease in your rate of improvement (and I would add an increase in the risk of injury). The next item of note is that rate of recovery did not improve with training. Despite a significant improvement in both performance and fitness, the subjects did not recover faster as they became fitter. Their adaptation to training during the 3 days per week training period did not allow them to increase training frequency to 5 days per week and still recover fully. During the 5 days per week of training, there was a progressive increased in the magnitude and duration of fatigue from each training session – not only did the subjects not recover faster, they went in the opposite direction and took increasingly longer periods of time to recover. The last item to be addressed is the invariant training intensity. The training intensity for these subjects was not highly intense, but even so, it was not changed during the course of the study. Would the subjects have recovered faster if they had varied the training load? Would they have recovered faster if easy or recovery training sessions had been included in this training program? It’s an interesting question, but unfortunately I don’t know of any research that directly addresses this particular topic. It is possible that varying the training load via the addition of easy days may have allowed faster recovery. However, based on research examining rates of injury my personal belief is that easy or recovery sessions do not speed recovery. For a more detailed discussion of injury rates, see the series “How much should you run” in the training section of this web site. Summary We started this article with a discussion of the high mileage training habits of elite runners. Is high mileage the best training method for everyone? Clearly the answer is no, if for no other reason than many simply can not recover fast enough to handle the high training frequency required to run high weekly mileage. This study shows that training volume should be governed by recovery rate and like all physical characteristics, recovery rate varies by the individual. Some people recover quickly enough that they can train daily and recover. On average though, most runners will not recover in 1 day and should not train daily. As compelling as it may be to emulate the training of elites, unless you also posses an elite recovery rate you are unlikely to benefit from the training volume of an elite athlete. Reference: 1. Busso T., Benoit H., Bonnefoy R., Feasson L., Lacour, J., Effects of training frequency on the dynamics of performance response to a single training bout. J. Appl. Physiol. 2002, 92, 572-580.
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