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Training Monotony

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[[File:Tired athlete.jpg|right|thumb|350px|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 ~~via my [[SportTracks Dailymile Plugin]]~~using Runalyze.com or TrainAsOne.com. The calculation is based on [[TRIMP| each day's training stress]], dividing the average by the standard deviation for each rolling seven day period.

=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]]<ref name="Meeusen-2013"/><ref name="Armstrong-2002"/>. There is also evidence<ref name="Busso-2003"/> that increased training frequency results in reduced performance benefits from identical training sessions as well as increased fatigue.

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.

==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.)

=Training Strain Calculations=

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

=TRIMPexp 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 TRIMPexp values for some workouts.

{| class="wikitable" style="margin-left: auto; margin-right: auto; border: none;"!

! Miles

! Duration

|}

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.

{| class="wikitable" style="margin-left: auto; margin-right: auto; border: none;"

! Monday

! Tempo 4

|-

| 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 TRIMPexp 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%.

{| class="wikitable" style="margin-left: auto; margin-right: auto; border: none;"

! Monday

! Tempo 4

|-

| 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%.

{| class="wikitable" style="margin-left: auto; margin-right: auto; border: none;"

! Monday

! Tempo 4

|-

| 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 TRIMPexp (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.

{| class="wikitable" style="margin-left: auto; margin-right: auto; border: none;"

! Monday

! Easy 6

|-

| Stdev

|

| 13

|-

| Avg

|

| 59

|-

| Total

|

| 414

|-

| Monotony

|

| 4.69

|-

| Training Strain

|

| 1,944

|}

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