Cash 25 Results
On Tuesday night, February 3, 2026, during the Cash 25 draw in West Virginia, 06 07 09 12 15 18 returned following a -day absence in West Virginia. With an expected cadence of 1 in 177,100 draws, the gap sits well beyond typical spacing.
Winning numbers for 1 draw on February 3, 2026 in West Virginia.
Draw times: Evening.
Our take on the Cash 25 results
February 3, 2026Cash 25 report — Tuesday night, February 3, 2026: 06 07 09 12 15 18 shows a notable pattern
On Tuesday night, February 3, 2026, during the Cash 25 draw in West Virginia, 06 07 09 12 15 18 returned following a -day absence in West Virginia. With an expected cadence of 1 in 177,100 draws, the gap sits well beyond typical spacing.
Overview
On Tuesday night, February 3, 2026, during the Cash 25 draw in West Virginia, 06 07 09 12 15 18 returned following a -day absence in West Virginia. With an expected cadence of 1 in 177,100 draws, the gap sits well beyond typical spacing.
Combo Profile
As a number pattern, 06 07 09 12 15 18 uses 6 distinct numbers and a wide spread from 6 to 18.
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
As documented: this analysis summarizes the recorded draws for Tuesday night, February 3, 2026 with benchmarking against long-run cadence. The focus is documentation over prediction.
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
Record-keeping at scale becomes the foundation for analysis. Each outcome, whether typical or unusual, contributes to the stability and clarity of the long-run picture. 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
This result adds a measurable entry to the long-term record. Over time, those entries are what sharpen distribution analysis and reveal whether the system is tracking its expected cadence.