Autocorrelation of Рапидо Про: a statistical link between draws was detected. The lag-1 ACF of sums = 0.010; some lags step outside the 95% confidence band ±0.438 (lags checked: 6, significant: 1).Data includes draw #365008 of 13.07.2026.
The strongest link is at lag 5 (ACF=-0.514), stepping outside the confidence band ±0.438. A lone significant lag on a long series is often a false positive — worth re-checking with other randomness tests.
Autocorrelation (ACF) measures the linear dependence between draws separated by k steps (lags), on a scale from −1 to +1. A value beyond ±1.96/√n is statistically significant. Click a number in the table below to build its own correlogram.
Where to next
Runs Test
Streaks and droughts of identical outcomes plus a Z-test of randomness for Рапидо Про draws.
OpenMarkov Chains
A transition-probability matrix: which number most often follows which in Рапидо Про.
OpenShannon Entropy
How evenly Рапидо Про number frequencies are spread — a measure of disorder.
OpenCombination Generator
Random and statistics-based combinations for Рапидо Про in a couple of seconds.
OpenFrequently Asked Questions
Does the Рапидо Про lottery have “memory” — do draws depend on one another?
Across 6 lags checked, 1 came out significant. This may be a quirk of the sample or a false positive — lone significant lags on long series are not rare. Worth re-checking with other randomness tests.
Can a Рапидо Про draw be predicted from past results?
Autocorrelation tests exactly that possibility: if the ACF is close to zero, past draws do not help to linearly predict the next one. Non-linear links are searched for with transition probabilities and by analysing what follows a given number.
Markov chains What follows a number
What are a significant lag and a confidence interval?
Lag k is a shift of k draws back; the ACF shows the link between a draw and the one k steps earlier. The significance threshold is ±1.96/√n, where n is the number of draws: an ACF beyond that band means the link is unlikely to be chance (at 95% confidence).
Does autocorrelation confirm that Рапидо Про is random?
The absence of autocorrelation is a strong but not the only sign of randomness. The full picture comes from a runs test, frequency entropy and Benford’s law: if none of them find deviations, the draw is statistically indistinguishable from random.
How do I use autocorrelation to pick numbers?
You don’t, directly: it is a randomness diagnostic, not a number picker. If Рапидо Про draws are random (the usual case), every combination is equally likely, and it is easier to reach for the generator to get ready-made numbers.