Tri-State Pick 3 Results
On Wednesday night, May 13, 2026, the Tri-State Pick 3 draw in Vermont produced a notable return: 350 after 1709 days of absence. Against an expected cadence of 1 in 1,000 draws (~500 days), the gap registers as a clear deviation in timing that merits documentation in the historical record.
Winning numbers for 2 draws on May 13, 2026 in Vermont.
Draw times: Evening, Midday.
Our take on the Tri-State Pick 3 results
May 13, 2026Tri-State Pick 3 report — Wednesday night, May 13, 2026: 350 returns after 1,709 days
On Wednesday night, May 13, 2026, the Tri-State Pick 3 draw in Vermont produced a notable return: 350 after 1709 days of absence. Against an expected cadence of 1 in 1,000 draws (~500 days), the gap registers as a clear deviation in timing that merits documentation in the historical record.
Overview
On Wednesday night, May 13, 2026, the Tri-State Pick 3 draw in Vermont produced a notable return: 350 after 1709 days of absence. Against an expected cadence of 1 in 1,000 draws (~500 days), the gap registers as a clear deviation in timing that merits documentation in the historical record.
A Long-Awaited Return
The present log shows 350 showing up again after 1709 days with no exact prior date available here. The duration alone signals an extended absence.
Combo Profile
As a digit shape, 350 contains 3 distinct digits while showing no repeats. Its range is 0 to 5 with a moderate spread.
Why Droughts Matter
Extended gaps are context markers, not a cue - they show where spacing departs from typical cadence. They provide a clean read on long-run variance.
Data Notes
In detail: this report documents results recorded for Wednesday night, May 13, 2026 and benchmarks them against historical frequency baselines. It is context-focused, not predictive.
From Stepzero
Simply put: this reporting is shaped to keep the record consistent over time for analysts and long-run tracking. The focus is long-horizon context.
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. 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
Across the long-horizon record, this result adds a fresh entry to the record to the archive. The long-run picture sharpens as entries accrue.