Two loads are enough for a force-velocity profile, if they are far apart
In short
Comparing a multiple-point method using eleven loads from 100% to 300% of bodyweight in 20% increments on a horizontal leg press against ten two-point methods pairing the 100% load with one other, the four widest-spread pairings (100% with 240%, 260%, 280% and 300%) correlated almost perfectly with the multiple-point method (r=0.906 to 0.993). Validity fell as the two loads moved closer together, as with 100% and 120%. A two-point method is a practical alternative to full multi-load testing provided the loads are sufficiently distinct.
A force-velocity profile is used to decide what kind of stimulus someone needs, but its outputs depend strongly on the testing method. The textbook approach loads a wide range and measures all of it, which takes as long as it sounds. This study asked whether two loads will do, and if so, which two.
How was the comparison made?
Sixteen men (20.0±1.4 years, 172.4±6.3cm, 69.2±7.6kg) performed maximal-effort horizontal leg press actions on a device driven by pneumatic artificial muscles. Loads ran from 100% to 300% of bodyweight in 20% increments — eleven in total.
Two kinds of profile were extracted and compared: a multiple-point method using all eleven loads, and ten two-point methods, each pairing the 100% bodyweight load with one of the remaining loads from 120% to 300%.
Which pairings worked?
The four pairings with the widest load differences — 100% with 240%, 260%, 280% and 300% — correlated almost perfectly with the multiple-point method, with correlation coefficients from r=0.906 to 0.993.
The opposite trend was equally clear. The closer the two loads, the worse the agreement. Pairings such as 100% and 120% produced lower concurrent validity for the profile parameters than well-separated pairings like 100% and 240%.
Why does the spread matter?
The force-velocity relationship is estimated as a straight line through two points. When those points sit close together, measurement error at either one is amplified directly into the slope. Push them apart and the same error moves the slope far less. This study shows that geometry holding up in actual measurement.
These results come from a horizontal leg press on a specific pneumatic artificial muscle device, with sixteen male participants. Transferring them directly to barbell squats or other equipment is not established. The underlying principle — wider-spread points give a more stable estimate — does not depend on the apparatus.
How this connects to your Muscle Index
The Muscle Index is computed from Big 3 one-rep maxes, and estimating a 1RM is also a matter of fitting a line through two points of weight and repetitions. The same trap applies — estimating from two sets as close together as five and six reps loads the result with error. A light high-rep set paired with a heavy low-rep set is far more stable.
If you are entering an estimate rather than a tested max, check which sets produced it before it goes into the Muscle Index calculator. Working with records without maximal attempts is covered in reps instead of maxes and high-rep ladders and maximal strength.
Frequently asked questions
Can a force-velocity profile be measured with only two loads?
Yes, provided the load difference is large enough. Pairings of 100% of bodyweight with 240% to 300% correlated almost perfectly with the multiple-point method using all eleven loads (r=0.906 to 0.993).
Which two loads should be chosen?
The two furthest apart that you can test. In this study, 100% of bodyweight paired with 240%, 260%, 280% or 300% gave the closest agreement, while closer pairings such as 100% and 120% showed lower validity.
Why do close-together loads produce a worse estimate?
Because the force-velocity relationship is fitted as a straight line through two points. When the points are close, measurement error at either one is amplified into the slope; as they move apart, the same error shifts the slope far less.
Under what conditions was this tested?
Sixteen men (20.0±1.4 years, 172.4±6.3cm, 69.2±7.6kg) performed maximal-effort actions on a horizontal leg press driven by pneumatic artificial muscles, against eleven loads from 100% to 300% of bodyweight in 20% increments.
Does the same principle apply to 1RM estimation?
Structurally, yes. Estimating a 1RM also fits a line through two points of weight and repetitions, so estimating from two sets as close together as five and six reps carries large error. A light high-rep set paired with a heavy low-rep set gives a more stable estimate.
Source: PLOS ONE