Pick 6 Results
On Thursday, February 2, 2023, the Pick 6 draw in New Jersey brought 05 16 20 31 36 41 back after days away. Given an expected cadence of 1 in 9,366,819 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 February 2, 2023 in New Jersey.
Draw times: Evening.
Our take on the Pick 6 results
February 2, 2023Pick 6 report — Thursday, February 2, 2023: 05 16 20 31 36 41 shows a notable pattern
On Thursday, February 2, 2023, the Pick 6 draw in New Jersey brought 05 16 20 31 36 41 back after days away. Given an expected cadence of 1 in 9,366,819 draws, this interval places the result well beyond typical spacing and makes it a meaningful entry for long-term distribution tracking.
Overview
On Thursday, February 2, 2023, the Pick 6 draw in New Jersey brought 05 16 20 31 36 41 back after days away. Given an expected cadence of 1 in 9,366,819 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, 05 16 20 31 36 41 uses 6 distinct numbers and a wide spread from 5 to 41.
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
This analysis uses the draw results recorded for Thursday, February 2, 2023 and compares them against the observed historical cadence for the game. This is descriptive, based on frequency tracking - not predictive modeling.
From Stepzero
Importantly: these reports are intended to sustain continuity in the archive for analysts and long-run tracking. The focus is long-horizon context.
Additional Context
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. 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
Over the broader record, 05 16 20 31 36 41 adds one more entry to the historical dataset. It is the cumulative record that makes analysis stable.