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I was at a conference on fatigue a few months ago where one of the speakers was Mike Lambert, a well-known sports science researcher from Tim Noakes’s group at the University of Cape Town. One of the questions at the end of his talk was about the use of lactate monitoring; his answer was something along the lines of “We refuse to measure lactate, because we don’t believe it offers any useful predictive information.” As a result, the UCT sports science unit doesn’t do much work with certain teams like the South African swim team, because the swim coaches are convinced that lactate testing offers important feedback.
A new paper just published online in the European Journal of Applied Physiology reminded me of that discussion. Researchers in Austria performed a whole series of difference incremental and maximal tests on 62 volunteers to look for patterns. The basic finding was that the amount of lactate in the blood at “maximal lactate steady state” (MLSS: the point where you’re producing and clearing lactate at the same rate) isn’t correlated with how fast or fit you are.
This isn’t the first study to make this observation. But previous studies have used relatively homogeneous groups, which makes it hard to determine whether lactate levels really have an effect. With VO2max, for example, you can safely bet the someone with a VO2max of 75 will perform better on any endurance task than someone with a VO2max of 35. But if you take a group of people who all have VO2max clustered between 60 and 70, then VO2max becomes a very poor predictor of performance.
In this case, the study subjects ranged from sedentary (with 0 hours per week of sports or exercise) to very fit athletes training up to 24.5 hours per week. Their power output on the bike at MLSS ranged from 100 to 302 watts. But despite this wide range, it was still impossible to predict anyone’s power levels by looking at their lactate levels at MLSS.
So does this mean Lambert is right and lactate is useless? Not necessarily. It just means that a single lactate measurement in isolation is meaningless: you have to make repeated measurements and track your progress relative to your personal baseline, in order to eliminate the effects of individual variation.