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Reading the draws and working out what chance predicts.
LotteryOracle · F-45
Compare the modeled preference for 1–31 in the earlier and later halves of the latest complete records, and below versus at or above their median jackpot.
Popularity changes how much a win is shared, never whether it happens. These are estimates from prize tables, not records of individual choices.
Mega Millions · 5/70 + 1/25 era · Oct 2017 – Apr 2025 · main · 776 Draws · Canonical archive; verification varies
2017-10-31 — 2021-07-16 · 388 Draws
271 training draws · 117 later validation draws
2021-07-20 — 2025-04-04 · 388 Draws
271 training draws · 117 later validation draws
2017-10-31 — 2025-04-04 · 386 Draws
270 training draws · 116 later validation draws
2017-12-05 — 2025-03-25 · 389 Draws
272 training draws · 117 later validation draws
Four fixed comparisons; intervals are approximate and widened for multiplicity. They omit model error and serial dependence. Jackpot associations are not causal effects.
Median advertised jackpot, in the game’s currency: 152,000,000
crowd-timeline-birthday-v1
The latest eligible records are split into two chronological halves and two groups separated by the median advertised jackpot. Every group needs at least 200 complete draws. A single 1–31 coefficient is fitted with the existing crowd model, using 70% for fitting and later draws for validation. The displayed intervals reuse quasi-Poisson errors on the log multiplier and widen them for four estimates. They remain approximate: model error, dependence and changing player composition are not captured. A bounded, unidentified or unvalidated estimate is withheld.
interval = exp(log(multiplier) ± Φ⁻¹(1 − 0.05/8) × SE/multiplier)
Compare the modeled preference for 1–31 in the earlier and later halves of the latest complete records, and below versus at or above their median jackpot.
Popularity changes how much a win is shared, never whether it happens. These are estimates from prize tables, not records of individual choices.