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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 · 7/49 + 1/49 era · Sep 2009 – May 2019 · main · 503 Draws · Canonical archive; verification varies
2009-09-25 — 2014-07-11 · 251 Draws
175 training draws · 76 later validation draws
2014-07-18 — 2019-05-10 · 252 Draws
176 training draws · 76 later validation draws
2009-09-25 — 2019-05-10 · 251 Draws
175 training draws · 76 later validation draws
2009-10-30 — 2019-05-03 · 252 Draws
176 training draws · 76 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: 30,350,653
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.