Jersey Cash 5 Results
On Wednesday night, May 13, 2026, the Jersey Cash 5 draw in New Jersey produced a notable return: 01 03 14 21 28 after days of absence. Against an expected cadence of 1 in 1,221,759 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Winning numbers for 1 draw on May 13, 2026 in New Jersey.
Draw times: Evening.
Our take on the Jersey Cash 5 results
May 13, 2026Jersey Cash 5 report — Wednesday night, May 13, 2026: 01 03 14 21 28 shows a notable pattern
On Wednesday night, May 13, 2026, the Jersey Cash 5 draw in New Jersey produced a notable return: 01 03 14 21 28 after days of absence. Against an expected cadence of 1 in 1,221,759 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Overview
On Wednesday night, May 13, 2026, the Jersey Cash 5 draw in New Jersey produced a notable return: 01 03 14 21 28 after days of absence. Against an expected cadence of 1 in 1,221,759 draws, the gap registers as a clear deviation in timing that merits documentation in the historical record.
Combo Profile
Beyond the drought, the numbers show a clean structure: 5 distinct numbers with no repeats, spanning 1 to 28 (wide spread).
Why Droughts Matter
Large gaps are best treated as context, not directional - they show how distribution tails behave. They help analysts track drift against expected cadence.
Data Notes
The method: this report summarizes outcomes logged on Wednesday night, May 13, 2026 and evaluates them against long-run frequency baselines. This is descriptive, not predictive.
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
Long-horizon measurement matters most when viewed across extended windows. As samples expand, the distribution becomes clearer and anomalies settle into their expected ranges.
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
Over the long run, this appearance adds one more entry to the historical dataset. The accumulation, not any single draw, builds reliability.