Contents（9）
Key points
- Streaks are normal in unmodified random. They are not evidence of a broken or biased generator.
- Human intuition expects alternation earlier than real random produces it; that gap is often the real complaint.
- A fewer-repeats policy weighs candidates against recent results. Repeats shrink but never reach zero.
- When the odds must not change per draw (prize draws and audits), keep the standard tools. Use the fewer-repeats pages where fair rotation matters.
Streaks are not a defect
When a die shows 4 three times in a row, many people suspect a loaded die. But a perfectly untouched random source produces streaks all the time: the same face three times in a row starts about once per 36 positions, which comes out to two or three streaks per 100 rolls.
Streaks stand out because of intuition. People expect alternation sooner than real random delivers it. Bar-Hillel and Wagenaar's review showed that sequences people write by hand contain fewer streaks than genuine random sequences do. Real randomness looks wilder than a "proper-looking" list.
The same shows up in gacha-style draws. A draw with fixed rates never looks at the previous result, so long dry spells and back-to-back rare pulls are both inside the odds. Treating only the lucky streak as surprising misses the point: in a truly random draw, streaks in either direction are the norm.
Why “the same person again?” stings
When a draw or shuffle keeps landing on the same person, users carry two feelings at once: doubt about the tool, and frustration from those who keep waiting for their turn.
The second feeling comes from reading a pool of candidates as a rotation. For rosters and weekly presentation orders — anything where history is part of the job — a policy that weighs recent results in the candidates' odds is simply more comfortable to use.
Music apps have run into the same complaint. Spotify adjusts its shuffle so the same track is less likely to play back-to-back; the Spotify Engineering write-up is listed in the sources.
How the fewer-repeats policy works
The dedicated pages on this site use the following approach.
- The entropy source is the same in-browser cryptographic random the standard tools use.
- Before each pick, recent results raise an “unlikelihood” score per candidate: a heavy penalty for the value just drawn, a light one for anything that came up repeatedly in a short window.
- The actual outcome is then drawn at random among the candidates, with the scores shaping the weights.
Because the penalties stay soft, repeats never reach zero, and no single outcome is permanently favored or banned. Long-run frequencies keep returning to an even spread instead of amplifying a bias, and the sequence never locks into a cycle such as 1→2→3…
How recent results change the chances of the next roll
1. The last four rolls (newest on the right)
2. Compare the chances on the next roll
Standard random gives every face a 1/6 chance (about 16.7%), regardless of recent results.
| Face | Standard random | Fewer repeats |
|---|---|---|
| 1 | 16.7% | 20% |
| 2 | 16.7% | 20% |
| 3 | 16.7% | 6% |
| 4 | 16.7% | 20% |
| 5 | 16.7% | 14% |
| 6 | 16.7% | 20% |
- 3 appeared twice in a row, so make 3 less likely.
- 5 appeared recently, so make 5 slightly less likely too.
3. Draw with these chances (this example rolled 2)
3 still has a 6% chance on the next roll. No face is ruled out.
Compare 100 and 1,000 rolls
The simulator below rolls a standard die and the fewer-repeats die for the same number of trials and lines the face counts and streaks up side by side. Each press draws a fresh pair of sequences (nothing is saved).
At 100 trials, both sides routinely show a face appearing 20 times while another shows up 8. At 1,000 trials, the fewer-repeats side's totals approach the theoretical 1/6 and the rolls-equal-to-previous count clearly drops, along with a shorter longest streak.
Both sides roll a six-sided die the same number of times; the face counts and streaks are shown side by side. Every press draws fresh results.
Note: the fewer-repeats side does not match the independent-roll theory. That deviation is the policy's history-awareness working. For calculations that need the exact theory, use the standard random tools.
Which policy to use
| Situation | Better fit | Why |
|---|---|---|
| Prizes, audited draws | Standard random | Odds must not change between draws when accountability matters. |
| Casual game luck | Either | Fewer repeats when streaks annoy you; standard when testing odds. |
| Daily duties, presentation order | Fewer-repeats policy | Recent winners and first positions repeat less. |
| Learning or testing probability | Standard random | Comparing with theory needs independent trials. |
Which one to use
Decide by purpose, not by which sounds better. Where the odds must not move between draws, standard random is the right answer. Where fair rotation is what users actually experience, the fewer-repeats pages are more comfortable.
Sources
- Bar-Hillel, Maya & Wagenaar, Willem A. (1991), “The perception of randomness”, Advances in Applied Mathematics, 12(4), 428–454. Streaks in real random sequences clash with what people expect.
- Falk, Ruma & Konold, Clifford E. (1997). “Making sense of randomness: Implicit encoding as a basis for judgment”. Psychological Review, 104(2), 301–318.
- Spotify Engineering (2025-11-13). “Shuffle: Making Random Feel More Human”.
Updated: 2026-10-10