The Gap Illusion: Why "Due" Numbers Aren't
Track how long it has been since each number appeared and a tempting story emerges: surely the long-absent ones are due. The data — and probability — say otherwise.
Gap analysis measures the draws since each number last appeared. It is one of the most-requested views we have — and the easiest to misread. The chart below shows the current gap for each number against its long-run average gap.
Current gap vs the long-run mean gap. A number above its mean is not 'due' — draws are independent.
The fallacy, named
When a number sits well above its average gap, instinct says it is "due." That instinct is the gambler's fallacy: the belief that independent events self-correct. They do not. The draw has no memory of how long a ball has waited; its chance of appearing is identical whether it last showed up yesterday or two years ago.
What gaps are actually good for
Gap data is still worth charting. It describes a game's texture, it surfaces data problems, and it is a clean way to teach why "due" reasoning fails — you can watch long-absent numbers stay absent and short-gap numbers reappear, exactly as independence predicts. PatternSight presents the gap alongside that caveat so the chart educates instead of misleads.