Cash 25 Results
11 12 13 16 17 24 reappeared in the Cash 25 draw on Friday night, January 23, 2026 after days, a long-gap outcome that warrants documentation in the historical record even when cadence benchmarks are unavailable.
Winning numbers for 1 draw on January 23, 2026 in West Virginia.
Draw times: Evening.
Our take on the Cash 25 results
January 23, 2026Cash 25 report — Friday night, January 23, 2026: 11 12 13 16 17 24 shows a notable pattern
11 12 13 16 17 24 reappeared in the Cash 25 draw on Friday night, January 23, 2026 after days, a long-gap outcome that warrants documentation in the historical record even when cadence benchmarks are unavailable.
Overview
11 12 13 16 17 24 reappeared in the Cash 25 draw on Friday night, January 23, 2026 after days, a long-gap outcome that warrants documentation in the historical record even when cadence benchmarks are unavailable.
Combo Profile
As a number pattern, 11 12 13 16 17 24 uses 6 distinct numbers and a wide spread from 11 to 24.
Why Droughts Matter
A long drought is descriptive rather than predictive. It records variance across time and helps analysts evaluate whether outcomes are tracking within expected frequency bands or drifting into the tails of the distribution.
Data Notes
Results are evaluated against historical frequency baselines where available. The goal is documentation and context rather than 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
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.
Long-horizon measurement matters most when viewed across extended windows. As samples expand, the distribution becomes clearer and anomalies settle into their expected ranges.
Long-horizon tracking is the only reliable way to separate short-term noise from persistent drift. By logging each outcome against its expected cadence, the system builds a distribution profile that becomes more stable as the sample grows.
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.