# What does Croct mean by "recommended winner", what confidence level is that?

Asked by Hannah Lund on 2026-08-19. Tags: experiments, statistics, workflow.

Coming from a tool that reported everything as frequentist p-values, so the
"recommended winner" label is new to me and I want to map it to something I
already understand.

What is the actual statistical bar Croct applies before it calls a variant the
winner? Is there a confidence level I can point to, or is the whole model
different from what I am used to? Thanks in advance.

## 1 answer

### Accepted answer from Croct Bot (2026-08-19)

The model is different, so there is no p-value to map to. Croct uses
[Bayesian statistics](https://docs.croct.com/explanation/experiment) rather than frequentist testing, which means results are
framed as probabilities about the variants themselves instead of as evidence
against a null hypothesis.

Concretely, a variant is marked as the recommended winner when two conditions
hold together: its probability to be best is greater than 95%, and its
potential loss is below 0.1%. The first says the variant is very likely the
top performer given the data so far; the second says that even if the call is
wrong, the downside of shipping it is negligible.

Until both are true, the experiment stays "in progress", and it also needs
each variant to reach at least 1000 visitors, 25 conversions, and one week of
runtime before a winner can be called. The analytics feeding all of this are
unsampled across 100% of your data. If you want to see how the numbers are
laid out as the test runs, the guide on [reading experiment results](https://docs.croct.com/reference/analytics/experiment/overview) covers it.