Cash5 Results
On Monday night, April 6, 2026, during the Cash5 draw in Connecticut, 06 15 18 19 35 landed again after a -day wait in Connecticut results. Given an expected cadence of 1 in 324,632 draws, the interval lands deep in the long-gap tail.
Winning numbers for 1 draw on April 6, 2026 in Connecticut.
Draw times: Evening.
Our take on the Cash5 results
April 6, 2026Cash5 report — Monday night, April 6, 2026: 06 15 18 19 35 shows a notable pattern
On Monday night, April 6, 2026, during the Cash5 draw in Connecticut, 06 15 18 19 35 landed again after a -day wait in Connecticut results. Given an expected cadence of 1 in 324,632 draws, the interval lands deep in the long-gap tail.
Overview
On Monday night, April 6, 2026, during the Cash5 draw in Connecticut, 06 15 18 19 35 landed again after a -day wait in Connecticut results. Given an expected cadence of 1 in 324,632 draws, the interval lands deep in the long-gap tail.
Combo Profile
As a number pattern, 06 15 18 19 35 uses 5 distinct numbers and a wide spread from 6 to 35.
Why Droughts Matter
Droughts do not indicate what will happen next - they simply document what has already occurred. Their value lies in measuring distribution over long horizons and identifying when a combination performs far above or below its expected appearance rate.
Data Notes
This analysis uses the draw results recorded for Monday night, April 6, 2026 and compares them against the observed historical cadence for the game. This is descriptive, based on frequency tracking - not predictive modeling.
From Stepzero
Stepzero produces these reports to provide a calm, evidence-first record of how draw patterns unfold over time. The aim is clarity and continuity - a reference point for long-horizon tracking rather than a call to action.
Additional Context
Stability comes from the accumulation of entries. One draw alone does not define the pattern, but the record grows more reliable with each addition to the dataset. Distribution analysis depends on consistent documentation. Each draw updates the record, allowing analysts to test whether deviations persist, reverse, or revert to expected ranges.
Adding to the Long-Term Record
Over the long run, this appearance extends the historical ledger to the long-run dataset. Stability comes from the growing record, not any one draw.