Powerball
patterns
Patterns controls
Patterns use longer windows and chunk the history into segments. Use a larger window for better context, and a smaller segment size if you want to see shorter-term swings.
Hot & Cold Persistence (last 1000 draws)
This chart breaks your selected history into segments and tracks the top recurring numbers across
those
segments. Each line is a number; each point is how many times that number appeared in that
segment.
What to look for:
(1) Long stretches where a line stays elevated (a “hot” run),
(2) extended flats near zero (a “cold” run), and
(3) how quickly numbers tend to revert back toward average.
Gap & Absence Patterns (last 1000 draws)
A gap is the number of draws between consecutive appearances of the same number.
This distribution shows what gap lengths are normal and what counts as a true outlier.
Key metrics:
P50 (the median gap) tells you the “typical” wait,
P90 marks a long-but-still-common wait,
and Max is the largest absence observed in the selected window.
Sum Band Stability (last 1000 draws)
Every draw has a sum (the total of the main numbers). Here we bucket sums into bands and show how
often
each band occurs. Over long histories, sums tend to cluster around a middle range.
Key metrics:
Mean and Median summarize the center; Std Dev (standard
deviation) shows spread.
Tighter spread means draws are more concentrated around the center band.
Odd/Even & High/Low Bias (last 1000 draws)
Instead of counting total odds vs evens, this shows the per-draw mix.
The x-axis is “how many” (e.g., 0–5 odds in a draw), and the bars show how often that mix occurs.
Odd mix shows balance behavior, while High mix uses a midpoint split to show
whether draws tend to
skew high or low. Most games cluster around balanced outcomes, with extremes happening—but less often.
Pairing & Co-occurrence Tendencies (last 1000 draws)
This ranks number pairs by lift:
how much more often two numbers appear together than you’d expect if they were independent.
Lift = 1.0 means “about as expected.” Values above 1.0 are “more together than expected,” and
values below
1.0 are “less together than expected.” Lift is shown alongside the raw co-occurrence count so you
can spot
pairs that look “strong” but are based on tiny samples.
Pattern Stability Over Time (last 1000 draws)
This is the “is anything drifting?” view. We compute a few segment-level metrics and plot them across time.
To keep them comparable, each line is shown as a z-score (how far above/below its own long-run
average).
Lines included:
(1) Mean Sum — do sums drift higher/lower over time?
(2) Odd Ratio — do odds dominate in certain eras?
(3) Top Share — does any single number dominate a segment more than usual?
Pattern Myths (Reality Checks)
Patterns are useful for understanding behavior—not for guaranteeing outcomes. Here are the most common traps, and the safer way to interpret what you’re seeing above.