Cash5 Results
On Sunday night, May 3, 2026, the Cash5 draw in Connecticut brought 01 04 10 13 27 back after days away. Given an expected cadence of 1 in 324,632 draws, this interval places the result well beyond typical spacing and makes it a meaningful entry for long-term distribution tracking.
Winning numbers for 1 draw on May 3, 2026 in Connecticut.
Draw times: Evening.
Our take on the Cash5 results
May 3, 2026Cash5 report — Sunday night, May 3, 2026: 01 04 10 13 27 shows a notable pattern
On Sunday night, May 3, 2026, the Cash5 draw in Connecticut brought 01 04 10 13 27 back after days away. Given an expected cadence of 1 in 324,632 draws, this interval places the result well beyond typical spacing and makes it a meaningful entry for long-term distribution tracking.
Overview
On Sunday night, May 3, 2026, the Cash5 draw in Connecticut brought 01 04 10 13 27 back after days away. Given an expected cadence of 1 in 324,632 draws, this interval places the result well beyond typical spacing and makes it a meaningful entry for long-term distribution tracking.
Combo Profile
As a number pattern, 01 04 10 13 27 uses 5 distinct numbers and a wide spread from 1 to 27.
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 Sunday night, May 3, 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 focuses on documenting distribution behavior over large samples. Each report is a snapshot of observed outcomes, designed to support disciplined, long-term analysis.
Additional Context
Context improves with scale. As more draws accumulate, isolated anomalies either normalize into baseline rates or reveal persistent deviations that warrant closer monitoring. 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.
Adding to the Long-Term Record
The return of 01 04 10 13 27 expands the archive by one more data point. It is the accumulation of these entries, not a single draw, that defines the reliability of long-horizon analysis.