Lactate Accumulation Rate Was Linked to Threshold Power in 182 Cyclists and Triathletes

A 15-second sprint told researchers something a ramp test did not. In 182 cyclists and triathletes, a sprint-derived measure of lactate accumulation explained roughly 5 percentage points more of the variation in threshold power than aerobic capacity and efficiency alone.

Lactate accumulation is usually treated as a by-product of hard riding rather than a predictor of anything. A study published in the European Journal of Applied Physiology on September 24, 2026 tested whether how fast an athlete produces lactate during an all-out sprint helps explain where that athlete crosses the two lactate turnpoints that coaches use to set training zones.

The answer was yes, and the direction may surprise anyone who reads high sprint output as a sign of a strong engine. Riders with a higher peak lactate accumulation rate tended to reach their turnpoints at lower power relative to body mass, not higher.

The sample was 182 cyclists and triathletes, 107 men and 75 women, recruited across a range of performance levels. Each completed a 15-second sprint test, an incremental lactate profile and a ramp test to exhaustion in a cycling laboratory.

The authors built hierarchical linear regression models that first entered relative maximal oxygen uptake and gross efficiency, then added one of two lactate accumulation markers: vLapeak, the peak rate, or vLamaxblood, the maximal blood lactate accumulation rate. The outcomes were body-mass-normalised power at the first and second lactate turnpoints, written as LT1rel and LT2rel.

What a Sprint Adds to a Lactate Profile

Threshold testing has long been dominated by two numbers: maximal oxygen uptake and efficiency. Together they describe how much oxygen an athlete can use and how much useful power comes out per unit of energy burned. In this dataset those two variables alone already accounted for most of the variation in turnpoint power.

The question the authors asked was whether a third dimension, the glycolytic side of the system, adds anything once the aerobic side is accounted for. That is what the lactate accumulation markers were there to capture, and both of them cleared the bar.

The reasoning is mechanical. Lactate turnpoints sit where production and clearance stop balancing. An athlete who floods the system quickly at a given intensity will hit that imbalance sooner, which shows up as lower relative power at the turnpoint even when aerobic capacity is respectable.

How the 182 Riders Were Tested

All three tests were cycling-based and done in a laboratory. The 15-second sprint produced the raw material for the lactate accumulation calculation. The incremental profile located LT1 and LT2. The ramp test to exhaustion supplied maximal oxygen uptake.

Both markers were derived from the same sprint effort but calculated differently. vLapeak uses the peak rate of rise. vLamaxblood is the maximal blood lactate accumulation rate, and its calculation involves an estimated alactic time interval that vLapeak does not require.

Running the two in parallel was the point. If the two calculation approaches disagreed, any conclusion about lactate accumulation would depend on a methodological choice rather than on physiology.

Why Higher Lactate Accumulation Tracked Lower Threshold Power

The coefficients were negative and reasonably tight. Higher vLapeak was associated with lower LT1rel, with a coefficient of -0.803 and a confidence interval running from -1.070 to -0.536. For LT2rel the coefficient was -0.900, with an interval of -1.165 to -0.635.

Relative maximal oxygen uptake and gross efficiency moved the other way, being positively associated with both outcomes. So the picture is of three separate levers: a bigger aerobic engine and better efficiency push turnpoint power up, while a faster lactate accumulation response pulls it down.

That is a useful corrective to a common assumption. A rider with a big sprint is not automatically a rider with a high threshold, and in this sample the sprint characteristic that produced impressive peak numbers was the one associated with an earlier turnpoint.

Two Calculations, One Conclusion

The parallel models mattered. The vLamaxblood models showed the same direction and significance with similar fit, which tells us the association did not hinge on whether the estimated alactic time interval was folded into the lactate accumulation calculation.

That is a quieter result than the headline number but arguably more useful. Labs and coaching platforms differ in how they derive these markers, and a finding that survives both approaches travels further than one tied to a single software default.

It also narrows the interpretation. Because the two calculations agree, the signal is more plausibly about the athlete than about the arithmetic.

What the Sex Comparison Did Not Show

With 107 men and 75 women in the sample, the authors were able to test whether sex changed the relationships. Sex and sex by predictor interactions were examined exploratorily, and they did not improve the models.

That is a null result, and it should be read as one. It means this dataset found no evidence that the lactate accumulation relationships differ by sex, not that such a difference has been ruled out. Exploratory interaction tests in a sample of this size are not well powered to detect modest effects.

Still, it is worth noting how often performance models are built on male-only samples. A mixed cohort of 182 riders in which the relationships held across both groups is a modest but real addition to the evidence base, echoing the broader measurement work behind efforts to standardize VO2 max across different exercise tests.

How Much a Cross-Sectional Study Can Settle

The authors are direct about the ceiling on these findings. The cross-sectional design precludes causal inference and cannot establish whether changes in vLapeak or vLamaxblood lead to changes in lactate turnpoint power. Nothing here says that lowering an athlete lactate accumulation rate would raise their threshold.

Both markers also come with an interpretive caveat. The authors describe them as indirect markers of the blood lactate accumulation response rather than direct measures of maximal glycolytic flux, which is a meaningful distinction for anyone tempted to treat the number as a readout of muscle biochemistry.

And the turnpoints themselves are not fixed objects. Lactate turnpoints are protocol- and model-dependent, so the same rider tested with a different step length or a different curve-fitting method can produce different numbers. Work on how briefly sprinting changes blood proteins is a reminder that short maximal efforts trigger a wide metabolic response, only part of which any single marker captures.

How to Read Lactate Accumulation Numbers in Training

For a rider who already has a lactate profile, this study offers a way to interpret the sprint number sitting next to it rather than a new session to add. A high lactate accumulation rate alongside a modest threshold is a coherent profile, not a contradiction.

What it does not license is a prescription. The study measured athletes once; it did not test whether any training approach shifts these markers or whether shifting them helps. Anyone drawing training conclusions is going beyond the data.

• Treat the sprint marker as descriptive context for a threshold test, not a target.
• Keep the testing protocol identical between retests, since turnpoints are protocol-dependent.
• Remember that aerobic capacity and efficiency were still the larger contributors in these models.
• Judge training by whether performance moves, not by whether a single marker moves.

Riders looking for evidence-backed ways to develop either side of that equation can start with the research on sprint interval training and power in high-level athletes and on live-high, train-low hypoxic training and VO2max. This article is general information and not individualized coaching or medical advice.