Do All Runners Benefit From Increasing Mileage?
I hear these two arguments often – increasing weekly mileage improves performance and high weekly mileage is necessary for optimal performance. As evidence supporting these beliefs proponents most often point to the training programs of elite long distance runners, who, as a group, all train with high weekly mileage. The logic is that since these are the fastest runners on earth and they all run high mileage it proves that high mileage is optimal. In effect the argument is that the high mileage is the reason these runners are elite. Additionally, many runners report that when they have increased weekly mileage their performance has improved, providing additional support for these two beliefs.
However, there are several challenges to these arguments, chief amongst them being that people are individuals with individual genetic talents. What works best for those with elite level genetic talents may not be best for those with average genetic talent. Additionally, when scientists have researched the effect of weekly mileage on performance the results have not shown that weekly mileage exerts a strong influence on performance.
These contradictory beliefs about the importance of increasing weekly mileage and the necessity of running high weekly mileage raise several questions. Is weekly mileage as important as is promoted by many runners? If so, can we determine if increasing mileage is equally beneficial for all runners? It is possible that some runners benefit from increasing mileage while others do not. It is also possible that different amounts of weekly mileage are optimal for different people, depending on things such as genetic talent or muscle fiber composition. The purpose of this paper is to examine some of the research on weekly mileage to see if we can determine if weekly mileage is as important as conventional training wisdom suggests and if increasing weekly mileage is equally beneficial to all runners.
A group of researchers in Switzerland wanted to determine if there was a relationship between training, life-style and running performance. To investigate this question the researchers decided to collect training and life-style data from all the runners in a popular 10 mile race held in Berne, Switzerland (1). They collected data on average weekly mileage for the previous year, average weekly mileage in the 3 months prior to the race, bodyweight, alcohol consumption, tobacco use, etc. The study sample consisted of 4358 male runners over age 16, which was 66% of the total number of runners. 42% of these male runners had been running 6 years or longer and an additional 31% had been running for 3 – 5 years, so nearly ¾ of the competitors were not beginner runners. As would be expected with any group this size there was a large range of average weekly mileage amongst all the runners, ranging from 0 – 100 km/week.
Performance in the race was electronically collected on all competitors by the race organizers and provided to the researchers. The performance range for the 5703 male competitors over age 16 was 49:19 min:sec to 1:57:18 hr:min:sec, with an average of 1:13:20 hr:min:sec. Based on delays due to the mass start and congestion at the finishing line the researchers estimated that the accuracy of the running times for the faster runners was below an error of 1% but may have risen to 2-4% for the slower runners (or about 2-4 minutes for the slower runners).
The researchers then used the survey data and correlated it with finishing time in the 10 mile race. Combined, the six variables of weekly training distance (-0.46), age (0.37), body mass index (0.23), years of regular running (-0.19), weekly training frequency (-0.11), and cigarette smoking (0.10) predicted 47% of run performance. Note that the correlation between weekly mileage and race performance was -0.46, which is not a strong predictor of performance – weekly training mileage predicted just 21% of race performance. The correlation between weekly mileage and performance (age adjusted), is shown in figure 1.
Figure 1: 10 mile running time and weekly mileage (km/wk)
The researchers didn’t stop with just this analysis though. They continued their investigation by dividing the runners into 3 groups based on finishing time, divided as follows:
|runners with a finishing time of 55 min. – 1:06 hr:min|
|runners with a finishing time of 1:06 – 1:14|
|runners with a finishing time of 1:14 – 1:25|
They then correlated finishing time with average weekly run mileage for each individual group. Finally they compared differences in performance between these runners and the runners who ran just 0.5 – 10 km week and graphed the results. The results are shown in figure 2.
Figure 2: Relationship between weekly run mileage and changes in 10 mile race performance separately plotted for 3 groups of runners. Percent running time reduction is in comparison to the running performance of those running just 0.5 – 10km per week.
The researchers noted some very interesting things about the relationship between weekly run mileage and race performance amongst the entire study population.
“First, the wide scattering of the 4000 observations makes it clear that weekly mileage is an insufficient predictor of individual race times. Second, the regression line reflecting the mean relation between habitual mileage and running times is not linear but levels off in the range of 80 to 100 km/week. Because of the narrow confidence limits of the regression curve (which are in turn due to the large sample size), this departure from linearity is highly significant.”
What they are saying in the first sentence is that weekly mileage alone is not a good predictor of performance. As noted above, it predicted just 21% of race performance. An examination of the provided data shows that lower mileage runners often outperformed higher mileage runners. The data also shows that although multiple runners ran the same weekly mileage performance in the 10 mile race was not equal, with a wide variation in finishing time amongst those with the same weekly training mileage. As an example the second fastest subject ran abut 23 km per week and finished in about 50 minutes while another runner also ran 23 km per week and finished at the back of the pack in about 1 hr and 30 minutes.
The second thing the researchers are saying is that while race performance generally improved with increases in weekly mileage across the entire group (those who ran higher weekly mileage generally performed better than those who ran lower weekly mileage) that the race performance leveled off somewhere between 50 and 62 miles/week. This means that further increases in weekly mileage beyond 50-62 miles/week were not associated with better race performance. Those who ran 62 miles/wk performed the same as those who ran 50 miles/wk. Contrast this finding with the oft stated belief that the high mileage run by elites is necessary for optimal performance. The data presented in fig 1 suggests that, on average, mileages beyond about 50 mpw did not result in faster race times.
Based on the data found in figure 1, we reach the conclusion that weekly mileage does have an influence on performance in that increases in weekly mileage can result in improved performance. However, the influence of weekly mileage is not strong, predicting just 21% of finishing time. We can also conclude, based on the leveling of the relationship curve, that continually increasing weekly mileage does not cause continual improvements in race finishing time. There appears to be an upper limit to improvements due to increases in weekly mileage. Finally, this data shows that, on average, the relationship between increasing weekly mileage and race performance levels off at about 50 mpw. This leveling occurs at a significantly lower weekly mileage than that recommended by those who use the training mileage of elite athletes as their guide.
The data in figure 2 provides a very different perspective on the relationship between weekly mileage and race performance. By segregating runners based on finishing time it provides a more detailed picture of the relationship between weekly mileage and performance for different groups of runners. Recall that the % change in 16 km run time (the “y” axis in fig. 2) is derived by comparing performance to those runners who ran just 6.2 miles or less per week.
Fastest 1/3: The data shows that increases in weekly mileage were linearly associated with better performance for only the fastest 1/3 of runners. In this group those who ran higher weekly mileages outperformed those who ran lower weekly mileages (just as conventional training wisdom suggests). On this topic the researchers noted, “The runners from the fastest third of the sample showed significantly greater differences in 16km times with higher levels of weekly mileage than runners from the medium and slowest third…”
Middle 1/3: For the middle 1/3 of runners, race performance was better for those who ran higher weekly mileage up to a peak of about 40 km/wk. Performance for those runners in this group who ran more than about 25 miles/wk was not better than those who ran 25 miles/wk. Those who ran a weekly mileage more than 25 miles/wk did not run faster race times but they didn’t run slower race times than those who ran 25 miles/wk either.
Slowest 1/3: For the slowest 1/3 of runners, race performance was also better for those who ran higher weekly performance up to a peak of about 25 miles/wk. However, race performance for those in this group who ran more than 25 miles/wk was worse than those who ran 25 miles/wk. The relationship between weekly mileage and performance of those in this group stands in stark contrast to the relationship for those runners in the fasted 1/3 group.
There are several important conclusions we can draw from the data in fig. 2. First, we can conclude that faster runners benefit from increasing weekly mileage, as the graph clearly shows a linear increase in performance with higher weekly mileages of the competitors. Those who ran higher weekly mileage performed better than those who ran lower weekly mileage. The implication of this linear relationship between weekly mileage and race performance is that increasing weekly run mileage results in improved performance for those in this group. Many runners, as noted in the introduction, believe that increasing weekly mileage produces better performance. This finding supports that belief. Many runners also point to the high weekly mileage of elite runners as evidence of the effectiveness and necessity of running high weekly mileage. Again, the graph of the relationship between weekly mileage and race performance for the fastest 1/3 of runners supports this belief.
Compare the graph of faster runner performance in fig. 2 to the mileage/performance graph in fig. 1. No leveling in race performance was seen with increasing weekly mileage for the faster runners as shown in fig. 2. A clear leveling of performance occurred at around 50 mpw for the entire subject population as seen in fig. 1. This indicates that the leveling of race performance at 50mpw seen is fig. 1 is not accurate for the group of faster runners.
The second observation we make is that the graph of the relationship between weekly mileage and race performance for the middle 1/3 of runners is very different than that for the fastest 1/3 of runners. The graph for the middle 1/3 of runners shows a clear leveling of performance at about 25 mpw. Those runners in this group who ran more than about 25 mpw did not perform better than those who ran only 25 mpw. The higher mileage runners didn’t run any faster but they didn’t run any slower either. Performance for those running 25 – 62 miles/wk was equal. Recall that in the fastest 1/3 of runners, those who ran 62 miles/wk outperformed those who ran 25 miles/wk. The conclusion we can draw from this is that middle of the pack runners also benefit from increasing mileage. However, the leveling of race performance of the middle third of runners indicates that beyond a certain weekly mileage these runners can expect race performance to level off and that additional increases in mileage will not result in faster race performance. Note also that the leveling of race performance occurs at around 25 mpw, a significantly lower weekly mileage than is recommended by many training programs.
Our third observation is that the graph of the relationship between weekly mileage and race performance for the slowest 1/3 of runners is very different from both the fastest 1/3 of runners and the middle 1/3 of runners. In this graph we see that race performance was highest in those who ran about 25 mpw. Runners in this category who ran more or less than 25 mpw performed worse than those who ran about 25 mpw. The greater the difference between a runners weekly mileage and 25 mpw the worse the performance in comparison to those runners who ran 40 km/wk. The conclusion we can draw from this data is that slower runners, like middle of the pack runners, also improve race performance with increases in weekly mileage up to about 25 mpw. However, at this point their performance diverges significantly from the other two groups in our study. In the case of slower runners additional increases in weekly mileage beyond 25 mpw were correlated with a slower race performance. Those running 12 mpw performed very similarly to those running 40 mpw, with both groups running slower than those who averaged about 25 mpw. This indicates that, for this group of runners, increasing mileage beyond about 25 mpw not only didn’t produce improved race performance, but actually resulted in a slower race performance.
This data quite compellingly shows that increasing mileage does not benefit all runners equally. By correlating weekly mileage and race performance for 3 distinct groups of runners rather than simply taking the average of all 4000+ runners it becomes clear that the relationship between weekly mileage and performance is not the same for all runners. The correlations lead us to conclude that some runners benefit more from increasing weekly mileage than do others. We also see that the benefit of increasing mileage levels off much sooner for some runners than others and at a much lower weekly mileage than is suggested by many as the optimal weekly run mileage. For some runners increasing mileage beyond a certain point not only doesn’t produce additional improvements but actually causes a decline in performance.
This is not the only study showing that increases in weekly mileage do not equally benefit all athletes. A study of cross-country skiers found that 4 years of increasing mileage failed to cause performance improvements in half of the subjects (2). In this study subjects were divided into two groups based on changes in performance from a full year of training. One group, the higher performing group, responded to increases in training volume. The other group, which was the lower performing group, did not respond to increases in training volume. A review of the training data of both groups revealed that the lower performing group had not improved performance during the previous four years of training despite significant annual increases in training volume. Though this study divided subjects into two instead of three groups, the results are consistent in showing that some athletes respond well to increases in weekly mileage while others respond to a point and then stop improving despite additional increases in weekly mileage.
I speculate that those genetic factors that most influence race performance also play a strong role in ability to adapt and improve from increases in weekly mileage. The genetic factors that make faster runners faster runners also allow them to improve with increases in weekly mileage, at least to some amount of weekly mileage beyond that measured in this study. Those genetic traits of middle of the packers that result in this group not running particularly fast also prevent them from continually improving from increases in weekly mileage beyond a certain point. Their genetics do seem to allow them to run additional weekly mileages without a decline in performance, at least up to some weekly mileage greater than that measured in this study. And the genetic talents of the slowest runners unfortunately prevent them from either running fast or improving with increases in weekly mileage beyond very modest amounts.
I further suggest that this explains the contradiction between the observation that elite runners all run high weekly mileages and research studies, such as this one, that show a modest correlation between weekly mileage and race performance. The data from this study clearly supports the belief that elite runners do benefit from increasing weekly mileage to high levels, while others do not. I suggest then the same genetic factors that allow elites to run so very fast also allow them to adapt and improve from very high weekly mileages. Those with less than elite level speed are less likely to benefit from increasingly high weekly mileages. I believe the correlation between race performance and weekly mileage for the 3 groups of runners in this study supports this genetic explanation. There are surely exceptions, but I suggest this genetic explanation to generally be the case.
The argument is frequently advanced that increasing weekly mileage improves performance and that high weekly mileage is necessary for optimal performance. The speed and training habits of elite runners are frequently used as evidence supporting these beliefs. In contrast to these beliefs, research shows a modest correlation between weekly mileage and race performance. The research reviewed here leads us to the conclusion that different athletes respond differently to increases in weekly mileage. The data suggests that the performance of faster athletes improves with each increase in weekly mileage, up to some high level. Performance for runners with average genetic talents levels off at a much lower weekly mileage with no further improvements despite additional increases in weekly mileage. Finally, performance peaks at relatively low weekly mileages for those athletes with seemingly low genetic talents and then declines as weekly mileage continues to increase. I suggest that the genetic factors that greatly influence an athlete’s natural, inborn speed also determine that athlete’s response to increasing weekly mileages.
- Marti B, Abelin T, Minder C. Relationship of training and life-style to 16-km running time of 4000 joggers – The ’84 Berne Grand-Prix Study Int J Sports Med 1988, 9, 85-91
- Gaskill, S., Serfass, R., Bacharach, D., Kelly, J., Responses to training in cross-country skiers, Med Sci Sports Exerc, 1999, 31(8), 1211-1217