Training Monotony

Monotonous training produces increased fatigue and is a risk factor for Overtraining and Overtraining Syndrome.

Training Monotony is not about boredom, but is a way of measuring the similarity of daily training. By calculating a simple number, it's easy to evaluate a training program, and understand its effectiveness. Training Monotony can be calculated using a spreadsheet or using Runalyze.com or TrainAsOne.com. The calculation is based on each day's training stress, dividing the average by the standard deviation for each rolling seven day period.

Contents

1 Training Monotony and Overtraining

It is long been recognized the athletes cannot train hard every day. Modern training plans recommend a few hard days per week, with the other days as easier or rest days. A lack of variety in training stress, known as Training Monotony, is considered a key factor in causing Overtraining Syndrome. There is also evidence that increased training frequency results in reduced performance benefits from identical training sessions as well as increased fatigue.

2 Training Monotony and Supercompensation

Training Monotony is related to Supercompensation and the need for adequate rest to recover from training.

Exercise produces a temporary decrease in fitness, followed by a recovery and Supercompensation.

With sufficient rest between workouts, fitness improves.

Without sufficient recovery time, the fatigue builds up until injury or Overtraining Syndrome occurs.

3 Quantifying monotony

One approach to measuring monotony is statistically analyze the variation in workouts. The first stage is to work out a measure of the daily TRIMP (TRaining IMPulse). From this daily TRIMP it's possible to calculate the standard deviation for each 7 day period. The relationship between the daily average TRIMP value and the standard deviation can provide a metric for monotony. The monotony value combined with the overall training level can be used to evaluate the likelihood of Overtraining Syndrome.

4 Monotony Calculations

The original work on training monotony used TRIMP^cr10 and TRIMP^zone, but I substitute TRIMP^exp for TRIMP^zone because of the advantages noted in TRIMP. (Simply using daily mileage or duration could be used to get an estimate of Training Monotony.) From the daily TRIMP values for a given 7 day period the standard deviation can be calculated. (If there is more than one workout in a day, the TRIMP values for each are simply added together.) The monotony can be calculated using

Monotony = average(TRIMP)/stddev(TRIMP)

This gives a value of monotony that tends towards infinity as stddev(TRIMP) tends towards zero, so I cap Monotony to a maximum value of 10. Without this cap, the value tends to be unreasonably sensitive to high levels of monotony. Values of Monotony over 2.0 are generally considered too high, and values below 1.5 are preferable. A high value for Monotony indicates that the training program is ineffective. This could be because the athlete is doing a low level of training; an extreme example would be a well-trained runner doing a single easy mile every day. This would allow for complete recovery, but would not provide the stimulus for improvement and would likely lead to rapid detraining. At the other extreme, doing a hard work out every day would be monotonous and not allow sufficient time to recover. The Training Strain below can help determine the difference between monotonous training that is inadequate and monotonous training that is excessive.

4.1 Updated Monotony Formula

The formula above Is useful, but Its sensitivity to higher levels of monotony can overwhelm Your training data. This is particularly obvious when using the training strain calculations below. A small modification results in Training monotony values between 0.29 and 1.0. Here is the updated formula:

Monotony = average(TRIMP)/( stddev(TRIMP) + average(TRIMP) )

When the standard deviation tends toward zero, the monotony value now tends towards 1.0 rather than Infinity. The highest standard deviation in a seven day period is from a single training day, combined with six days of rest. This results in a monotony of about 0.2899. (Note that you can still get a divide by zero error if there is no training load for the entire week, as both average and standard deviation are both zero. Treating this as a special case and assuming a training monotony of either 0 or 0.2899 is probably reasonable depending on usage.)

5 Training Strain Calculations

A similar calculation can be used to calculate a value for Training Strain.

Training Strain = sum(TRIMP) * Monotony

The value of Training Strain that leads to actual Overtraining Syndrome would be specific to each athlete. An elite level athlete will be able to train up much higher levels than a beginner. However this Training Strain provides a better metric of the overall stress that an athlete is undergoing than simply looking at training volume.

6 A simple TRIMP^cr10 based calculator

This calculator will show the TRIMP^cr10 values for each day, the Monotony, the total TRIMP^cr10 for the week and the Training Strain.

Day	Duration (min)	CR10 Rating	TRIMP(CR10)
1
2
3
4
5
6
7

Monotony:
Total TRIMP:
Training Stress:

7 TRIMP^exp Examples

For these examples we will use just a few simple workouts. Let's assume a male athlete with a Maximum Heart Rate of 180 and a Resting Heart Rate of 40, giving a Heart Rate Reserve of 140. Let's assume our hypothetical athlete does his easy runs at a 9 min/mile pace and heart rate of 130. We'll use only one of the type of workout, a tempo run his easy runs at a 7 min/mile pace and heart rate of 160. This gives us some TRIMP^exp values for some workouts.

	Miles	Duration	TRIMPexp
Easy	4	36	51
Easy	6	54	76
Easy	10	90	127
Easy	20	180	254
Tempo	4	28	80
Tempo	8	56	159

Here is a sample week's workout with three harder workouts, a 4 mile tempo, a 10 mile mid-long run and a 20 mile long run with four mile easy runs on the other days, a total of 50 miles.

Monday	Tempo 4	80
Tuesday	Easy 4	51
Wednesday	Easy 10	127
Thursday	Easy 4	51
Friday	Easy 4	51
Saturday	Easy 20	254
Sunday	Easy 4	51
Stdev		70
Avg		95
Total		665
Monotony		1.36
Training Strain		903

If we give our athlete a single day's rest on Sunday, we reduce the mileage by 4 miles to 46 miles, total TRIMP^exp goes down by 51, but the Monotony of drops more significantly to 1.15 and the Training Strain drops by 199. So the mileage has dropped about 9%, but the Training Strain has dropped by 22%.

Monday	Tempo 4	80
Tuesday	Easy 4	51
Wednesday	Easy 10	127
Thursday	Easy 4	51
Friday	Easy 4	51
Saturday	Easy 20	254
Sunday	Rest	0
Stdev		77
Avg		88
Total		614
Monotony		1.15
Training Strain		704

A further rest day on Tuesday drops the Training Strain by a further 21%.

Monday	Tempo 4	80
Tuesday	Rest	0
Wednesday	Easy 10	127
Thursday	Easy 4	51
Friday	Easy 4	51
Saturday	Easy 20	254
Sunday	Rest	0
Stdev		82
Avg		80
Total		563
Monotony		0.98
Training Strain		553

If we compare this with an extreme example of a monotonous training plan, we have a slightly lower mileage (46 v 50), and a 57% lower total TRIMP^exp (414 v 927), but the monotony is remarkably high at 4.7 and the training strain is 2.2x higher. In practice, there would be greater day to day variations, even within the same 6 mile easy run, so the results would not be quite so dramatic.

Monday	Easy 6	54
Tuesday	Easy 6	54
Wednesday	Easy 10	90
Thursday	Easy 6	54
Friday	Easy 6	54
Saturday	Easy 6	54
Sunday	Easy 6	54
Stdev		13
Avg		59
Total		414
Monotony		4.69
Training Strain		1,944