1RM estimates

[Guest guest]

Always wanted to ask the group about this, but never got around to it.

In McArdle, Katch and Katch there are 2 equations for estimating 1RM

in trained and untrained subjects:

Untrained: 7 – 10 reps = 68% of 1RM

1RM, Kg = 1.554 (7-10RM weight, kg) – 5.181

Trained: 7 – 10 reps = 79% of 1 RM

1RM, Kg = 1.172(7-10RM weight, kg) + 7.704

Groups thoughts on there validity?? Practical Application??

Ta

Simon O'Connor

Perth Western Australia

[Guest guest]

Simon O'Connor wrote:

<Always wanted to ask the group about this, but never got around to it.

In McArdle, Katch and Katch there are 2 equations for estimating 1RM in

trained and untrained subjects:

Untrained: 7 - 10 reps = 68% of 1RM 1RM, Kg = 1.554 (7-10RM weight, kg)

- 5.181

Trained: 7 - 10 reps = 79% of 1 RM

1RM, Kg = 1.172(7-10RM weight, kg) + 7.704>

Iain Styles writes:

I'm not at all sure how they did their Mathematics. Their equations for

1RM appear to be based on some sort of linear regression (in other

words, they performed a 'best fit' of a linear equation to their data).

I also fail to see how their equations relate to the stated percentages

of 1RM - they don't match mathematically. If the percentages were

correct then the equations should be:

1RM = 1.47 (7-10RM weight) for untrained subjects, 1RM = 1.27 (7-10RM

weight) for trained subjects.

There is no mention of what the errors in a statistical analysis of the

data might be, so I would say that it was of extremely limited value as

the variation between individuals is likely to be very high, due to

factors such as muscle fibre composition and natural lactic tolerance

levels.

An interesting sub-question arising from this is what training did their

subjects undertake. It would appear to be strength-endurance based, as

this is the quality that appears to have improved.

In short, there is too much variation between individuals for such

prescriptive formulae to be of any practical use.

Iain Styles

Birmingham, UK

[Guest guest]

Simon O'Connor wrote:

<Always wanted to ask the group about this, but never got around to it.

In McArdle, Katch and Katch there are 2 equations for estimating 1RM in

trained and untrained subjects:

Untrained: 7 - 10 reps = 68% of 1RM 1RM, Kg = 1.554 (7-10RM weight, kg)

- 5.181

Trained: 7 - 10 reps = 79% of 1 RM

1RM, Kg = 1.172(7-10RM weight, kg) + 7.704>

Iain Styles writes:

I'm not at all sure how they did their Mathematics. Their equations for

1RM appear to be based on some sort of linear regression (in other

words, they performed a 'best fit' of a linear equation to their data).

I also fail to see how their equations relate to the stated percentages

of 1RM - they don't match mathematically. If the percentages were

correct then the equations should be:

1RM = 1.47 (7-10RM weight) for untrained subjects, 1RM = 1.27 (7-10RM

weight) for trained subjects.

There is no mention of what the errors in a statistical analysis of the

data might be, so I would say that it was of extremely limited value as

the variation between individuals is likely to be very high, due to

factors such as muscle fibre composition and natural lactic tolerance

levels.

An interesting sub-question arising from this is what training did their

subjects undertake. It would appear to be strength-endurance based, as

this is the quality that appears to have improved.

In short, there is too much variation between individuals for such

prescriptive formulae to be of any practical use.

Iain Styles

Birmingham, UK

[Guest guest]

Simon O'Connor wrote:

<Always wanted to ask the group about this, but never got around to it.

In McArdle, Katch and Katch there are 2 equations for estimating 1RM in

trained and untrained subjects:

Untrained: 7 - 10 reps = 68% of 1RM 1RM, Kg = 1.554 (7-10RM weight, kg)

- 5.181

Trained: 7 - 10 reps = 79% of 1 RM

1RM, Kg = 1.172(7-10RM weight, kg) + 7.704>

Iain Styles writes:

I'm not at all sure how they did their Mathematics. Their equations for

1RM appear to be based on some sort of linear regression (in other

words, they performed a 'best fit' of a linear equation to their data).

I also fail to see how their equations relate to the stated percentages

of 1RM - they don't match mathematically. If the percentages were

correct then the equations should be:

1RM = 1.47 (7-10RM weight) for untrained subjects, 1RM = 1.27 (7-10RM

weight) for trained subjects.

There is no mention of what the errors in a statistical analysis of the

data might be, so I would say that it was of extremely limited value as

the variation between individuals is likely to be very high, due to

factors such as muscle fibre composition and natural lactic tolerance

levels.

An interesting sub-question arising from this is what training did their

subjects undertake. It would appear to be strength-endurance based, as

this is the quality that appears to have improved.

In short, there is too much variation between individuals for such

prescriptive formulae to be of any practical use.

Iain Styles

Birmingham, UK

[Guest guest]

" curtin2001s " <callsime@h...> wrote:

> In McArdle, Katch and Katch there are 2 equations for estimating

1RM in trained and untrained subjects:

Untrained: 7 – 10 reps = 68% of 1RM

1RM, Kg = 1.554 (7-10RM weight, kg) – 5.181

Trained: 7 – 10 reps = 79% of 1 RM

1RM, Kg = 1.172(7-10RM weight, kg) + 7.704

Groups thoughts on there validity?? Practical Application??>

Validity? Practical application? I think " valid " can have quite a

broad spectrum here. There are many 1 rep maximum equations and many

come close to approximating the " area under the curve " or

the " general population. " I think practical application is there -

when I'm designing a new program, for example, I'll use a

known " safe " rep range and then extrapolate based on the equations.

How accurate are they? Well, let's just say I find them to be a good

ball park but then I need to hone in.

The issue is that you have so many different types of bodies out

there. Poliquin has a few tests he performs and when I'm

evaluating clients, I use a similar one - I basically try to find a

weight that the client can max out at " around " 10 reps. Then I have

them do 7 sets to failure. Why 7? That is a number I picked simply

because I did not want this to turn into a German volume training

session but on the other hand I wanted sufficient sets to understand

what was happening.

You'll see some clients do 12, 10, 9, 9, 8, 10, 12, 10 etc ... while

others might do 10, 8, 4, 2, 1, 1, 1 ...

[Note that this sort of 10 rep test is not really suitable for the Olympic

and related lifts because of the increased risk of injury associated with high

rep

OL lifting. Mel Siff]

In fact, they'll vary widely from muscle group to muscle group.

Obviously the test is prone to error as well - for example, I set a

rest period for 1 minute but how will the results vary if it were a

30 second versus a 5 minute rest? Should I simply use heart rate as

the determining factor to begin the next set?

What the test tells me is simply if I get the 10, 5, 1, 1, 1 then

I'm going to train either lower reps or lower sets while the 12, 10,

9, etc will probably get a tad higher volume - in these cases that 1

rep maximum equation can be thrown out the door because someone with

a lot of muscular endurance may hit 30 reps at 70% while someone

else can only hit 5.

I guess to summarize my long-winded ramblings, I think 1RM equations

are great to get a ballpark estimate of where to start - instead of

randomly throwing plates on and floundering for a few workouts, you

can get closer than guessing. I also think that every individual is

very different and therefore it's important to cue into their

reaction to various rep ranges, volume, intensities, etc and learn

to adapt based on that feedback and not rely too heavily on the

equation.

Likness

Atlanta, GA

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