Tri-State Gimme 5 Results
On Monday night, March 9, 2026, the Tri-State Gimme 5 draw in Vermont marked a notable return: 10 13 24 31 33 reappeared in the draw after a -day drought. In a system where combinations should surface roughly once every 1 in 575,757 draws, an absence of this length stands out for anyone tracking long-horizon frequency trends.
Winning numbers for 1 draw on March 9, 2026 in Vermont.
Draw times: Evening.
Our take on the Tri-State Gimme 5 results
March 9, 2026Tri-State Gimme 5 report — Monday night, March 9, 2026: 10 13 24 31 33 shows a notable pattern
On Monday night, March 9, 2026, the Tri-State Gimme 5 draw in Vermont marked a notable return: 10 13 24 31 33 reappeared in the draw after a -day drought. In a system where combinations should surface roughly once every 1 in 575,757 draws, an absence of this length stands out for anyone tracking long-horizon frequency trends.
Overview
On Monday night, March 9, 2026, the Tri-State Gimme 5 draw in Vermont marked a notable return: 10 13 24 31 33 reappeared in the draw after a -day drought. In a system where combinations should surface roughly once every 1 in 575,757 draws, an absence of this length stands out for anyone tracking long-horizon frequency trends.
Combo Profile
As a number pattern, 10 13 24 31 33 uses 5 distinct numbers and a wide spread from 10 to 33.
Why Droughts Matter
Long gaps remain descriptive, not forward-looking - they highlight the tail behavior of the system. They make variance visible across extended windows.
Data Notes
This analysis uses the draw results recorded for Monday night, March 9, 2026 and compares them against the observed historical cadence for the game. This is descriptive, based on frequency tracking - not predictive modeling.
From Stepzero
To be clear: this reporting is built to document distribution behavior over time as a reference point for continuity. The priority is accuracy and continuity.
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.
Adding to the Long-Term Record
With its return, 10 13 24 31 33 contributes another meaningful data point to the historical dataset. Each draw - whether routine or statistically unusual - refines the long-term view of how large random systems behave over time.