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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.
Lotto Max · 7/50 + 1/50 era · May 2019 – Apr 2026 · main · 722 Draws · Canonical archive; verification varies
2019-05-14 — 2022-10-25 · 361 Draws
252 training draws · 109 later validation draws
2022-10-28 — 2026-04-10 · 361 Draws
252 training draws · 109 later validation draws
2019-05-14 — 2026-04-10 · 359 Draws
251 training draws · 108 later validation draws
2019-05-28 — 2026-04-07 · 363 Draws
254 training draws · 109 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: 34,000,000
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.