Check curve quality

How to interpret a lactate curve: outliers, quality and repeatable tests

Check the curve before adopting a threshold. Individual measurements, stage duration and test conditions determine how much confidence LT1 and LT2 deserve.

Recognize a plausible curve

As intensity rises, lactate often rises slowly at first and more sharply later. The aim is not a perfect line, but measurements, stages and context that fit together.

  • Intensity recorded clearly for every stage
  • Stages are regular and long enough
  • Read lactate values in the context of workload

Do not explain away outliers

A sharp rise or fall can result from sampling, strips, timing or a workload change. Mark it first and review the test process before assuming a physiological explanation.

  • Check sampling and strips
  • Compare measurement timing
  • Repeat under similar conditions when uncertain

Use the result responsibly

Use a clean curve for training ranges and compare later tests with the same method and a similar protocol. This does not replace medical diagnostics.

  • Do not derive LT1 or LT2 from one value
  • Read method spread as uncertainty
  • Keep conditions consistent for trends

Useful next steps for your test

Analyze your own lactate values

Enter pace or power and your measured lactate values. Get your curve, LT1, LT2, VLamax and training zones immediately; save and compare two of your own tests for free.

Why you can trust the analysis

LactateThreshold does not turn measurements into false precision. The app shows the curve, method comparison, plausible thresholds and the limits of your test protocol transparently.

Method comparison instead of a single black-box value
Clear separation of LT1, LT2, VLamax and training zones
Limits of self-testing are stated openly
Training guidance, not a medical diagnosis

Frequently asked questions

Must a lactate curve always rise?

Not every individual measurement rises. Check whether an unusual point fits the protocol or needs to be treated as a possible measurement issue.

When should I repeat the test?

Repeat when stages are missing, workload was not stable, or several values differ strongly without a plausible explanation.

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