New Hampshire Mega Millions Results
On Friday night, May 15, 2026, for New Hampshire's New Hampshire Mega Millions draw, 17 23 25 52 61 reappeared after a -day drought in the New Hampshire draw record. By the expected cadence of 1 in 12,103,014 draws, the interval is a long-gap event.
Winning numbers for 1 draw on May 15, 2026 in New Hampshire.
Draw times: Evening.
Our take on the New Hampshire Mega Millions results
May 15, 2026New Hampshire Mega Millions report — Friday night, May 15, 2026: 17 23 25 52 61 shows a notable pattern
On Friday night, May 15, 2026, for New Hampshire's New Hampshire Mega Millions draw, 17 23 25 52 61 reappeared after a -day drought in the New Hampshire draw record. By the expected cadence of 1 in 12,103,014 draws, the interval is a long-gap event.
Overview
On Friday night, May 15, 2026, for New Hampshire's New Hampshire Mega Millions draw, 17 23 25 52 61 reappeared after a -day drought in the New Hampshire draw record. By the expected cadence of 1 in 12,103,014 draws, the interval is a long-gap event.
Combo Profile
As a number pattern, 17 23 25 52 61 uses 5 distinct numbers and a wide spread from 17 to 61.
Why Droughts Matter
Droughts do not indicate what will happen next - they simply document what has already occurred. Their value lies in measuring distribution over long horizons and identifying when a combination performs far above or below its expected appearance rate.
Data Notes
This analysis uses the draw results recorded for Friday night, May 15, 2026 and compares them against the observed historical cadence for the game. This is descriptive, based on frequency tracking - not predictive modeling.
From Stepzero
Simply put: these reports are built to keep the long-horizon record steady as a reference point for continuity. The focus is long-horizon context.
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 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
The return of 17 23 25 52 61 expands the archive by one more data point. It is the accumulation of these entries, not a single draw, that defines the reliability of long-horizon analysis.