Original episode & show notes | Raw transcript
The podcast’s primary argument is that for over a century, exercise science has used lactate as an indirect proxy to determine a fundamental performance metric: the maximum sustainable work rate. Early physiologists wanted to find an objective marker for what they described as “the maximum rate [an athlete] can keep up for a long time without fatigue.” They landed on blood lactate because its concentration rises sharply when an athlete surpasses this sustainable intensity.
However, with the advent of the power meter, cyclists can now directly measure this work rate. The goal of lactate testing was always to estimate this sustainable power output. Now, we can measure the power output itself. In essence, using a power meter to try and validate a lactate test is working backward. The power data is the gold standard for performance measurement that lactate testing has always tried to approximate.
To understand the present, we must look at the past.
The Age of VO2 Max: In the early 20th century, the cutting-edge metric was VO2 max—the maximum volume of oxygen an individual can consume. It established a clear correlation: more oxygen equals more speed. However, VO2 max testing had its problems. It required a maximal, exhaustive effort, which could be risky for some individuals and difficult for unmotivated or untrained subjects whose muscular systems would fail before their aerobic systems reached their peak.
The Need for Sub-Maximal Testing: Researchers needed a reliable, sub-maximal way to gauge aerobic fitness and performance capacity. This led them to investigate physiological markers that changed at different exercise intensities.
The Rise of Lactate: As early as the 1930s, scientists like Owles noted that blood lactate levels remained stable during low-intensity exercise but began to rise above a certain “critical rate of work.” This observation was the birth of the “lactate threshold” concept. Over the decades, various protocols were developed, leading to the common definitions we hear today:
LT1 (First Lactate Threshold): Often called the “aerobic threshold,” this is the point where lactate begins to rise above baseline resting levels. It’s sometimes defined as a concentration of 2 millimoles per liter (mmol/L).
LT2 (Second Lactate Threshold): Often called the “anaerobic threshold,” “Maximal Lactate Steady State (MLSS),” or “Onset of Blood Lactate Accumulation (OBLA),” this is the intensity above which lactate production outpaces clearance, causing it to accumulate rapidly. This is the threshold most closely associated with FTP and is famously, though often inaccurately, pinned at a concentration of 4 mmol/L.
A crucial misunderstanding that the podcast dismantles is the idea of lactate as a metabolic waste product.
Lactate is a Fuel, Not Waste: Lactate is a valuable intermediate product of glycolysis (the breakdown of glucose). When you exercise, your muscle cells break down glucose into pyruvate. If energy is needed quickly, or if the mitochondria can’t process pyruvate fast enough, pyruvate is converted to lactate. This lactate is not a dead end.
It can be shuttled to nearby mitochondria within the same muscle cell and used for aerobic energy production.
It can exit the muscle cell, travel through the bloodstream, and be taken up and used as fuel by other muscles, the heart, and the liver (where it can be converted back to glucose).
The Problem with Blood Lactate Measurement: A lactate meter reading from a finger prick is a single snapshot of the concentration of lactate in your peripheral blood. It tells you nothing about the rate of appearance (how much is being produced and entering the blood) versus the rate of disappearance (how much is being cleared from the blood).
An elite athlete like Tadej Pogačar might have very low blood lactate levels at high power outputs. This doesn’t necessarily mean he isn’t producing lactate; it means his highly developed aerobic system (with immense mitochondrial density) is incredibly efficient at clearing and using that lactate as fuel, so very little of it accumulates in the blood. Conversely, a very powerful but less aerobically trained athlete might show high lactate levels because their production rate temporarily overwhelms their clearance capacity.
The podcast presents a key paper, “Justification of the 4 mmol/l lactate threshold” by Mader and Heck, to illustrate a critical point: the fallacy of division. This fallacy occurs when you assume that what is true for a group average is true for every individual in that group.
The study found that while the average blood lactate concentration at Maximal Lactate Steady State (MLSS) across their 16 subjects was almost exactly 4.0 mmol/L, the individual values ranged from 3.0 to 5.5 mmol/L. There was no correlation between an individual’s actual performance capacity (their MLSS running speed) and their blood lactate concentration at that speed.
The podcast provides a compelling case study of a world-class cyclist whose FTP was around 370 watts. A standard 3-minute ramp test suggested his LT2 was around 300 watts (at 4 mmol/L). However, his actual sustainable threshold was a full 70 watts higher, with a corresponding lactate value over 12 mmol/L. This discrepancy arises because short-stage ramp tests don’t allow the aerobic system enough time to fully activate and stabilize, especially in athletes with high anaerobic capacity. The initial stages are fueled more by glycolysis, leading to an early, sharp rise in lactate that doesn’t reflect the true steady-state capability.
This brings us back to the central argument. All lactate testing protocols—ramp tests, MLSS tests, etc.—are laboratory methods designed to estimate the highest power output you can sustain. They are trying to find your Functional Threshold Power (FTP).
Your power meter, combined with your power-duration curve from training and maximal efforts, shows you this directly. The “functional” in FTP is key. It’s the actual, real-world power you can produce. The podcast host defines threshold elegantly and simply:
The point at which someone fatigues faster above it and slower below it.
This is a performance-based definition. By analyzing your power data (specifically, looking for the inflection point on a logarithmic power-duration curve), you can identify this threshold without a single pinprick. You have the answer that scientists with Douglas bags and chemical assays have been chasing for a century. You are, as the podcast puts it, “home the whole time.”