Experimental cells
164 games × 4 strategiesSeparate sub-experiment · Protocol v1.0.0
Can R1,000 a month produce one R100,000 payout?
Sixteen controlled cells measure the first target hit before R12,000 and R36,000 spending limits. Exact probabilities are published beside 1.6 million seeded entrant paths.
TargetOne gross payout ≥ R100,000
Monthly capR1,000 in every strategy
Horizons12 and 36 months
GamesFour transparent Class C models
Completed reference study
The endpoint is rare.
The denominator stays visible.
Every percentage uses 100 000 independent synthetic entrants per game–strategy cell. A hit ends that entrant's path; otherwise the path reaches its spending cap.
Entrant paths
1 600 000100 000 per cellGross target
R 100 000Not the same as net wealthLargest MC deviation
0.255 ppVersus exact probabilityPrimary result
More attempts do not have one universal effect.
The fixed monthly budget is identical. What changes is the stake, attempt count, and payout multiple required to cross R100,000.
Moving from 20 × R50 to 200 × R5 reduces three-year incidence because the smaller stake needs a much rarer multiplier.
The same move increases incidence because every ticket shares one sufficiently large tail outcome and the smaller stake creates more attempts.
The crash-target model makes probability approximately proportional to stake, so fixed spend nearly equalises the four strategies.
Exact estimands and seeded checks
All 16 cells
Exact first-passage probability is the primary estimate. Monte Carlo is an independent reproducibility check, not a substitute for the known probability law.
| Game | Strategy | RTP | 12 mo exact | 36 mo exact | 36 mo simulated | Winners / 1,000 | Spend / observed winner |
|---|---|---|---|---|---|---|---|
| Controlled jackpot slot | 20 bets × R50720 maximum bets · 2 000× required | 96% | 6,39% | 17,97% | 17,98% | 179.8 | R 181 699 |
| Controlled jackpot slot | 50 bets × R201 800 maximum bets · 5 000× required | 96% | 4,40% | 12,63% | 12,53% | 125.3 | R 269 022 |
| Controlled jackpot slot | 100 bets × R103 600 maximum bets · 10 000× required | 96% | 2,96% | 8,61% | 8,65% | 86.5 | R 398 369 |
| Controlled jackpot slot | 200 bets × R57 200 maximum bets · 20 000× required | 96% | 1,19% | 3,54% | 3,52% | 35.2 | R 1 005 309 |
| Controlled crash target | 20 bets × R50720 maximum bets · 2 000× required | 97% | 10,99% | 29,48% | 29,50% | 295.0 | R 102 976 |
| Controlled crash target | 50 bets × R201 800 maximum bets · 5 000× required | 97% | 10,99% | 29,48% | 29,49% | 294.9 | R 103 023 |
| Controlled crash target | 100 bets × R103 600 maximum bets · 10 000× required | 97% | 10,99% | 29,48% | 29,25% | 292.5 | R 103 939 |
| Controlled crash target | 200 bets × R57 200 maximum bets · 20 000× required | 97% | 10,99% | 29,48% | 29,28% | 292.8 | R 103 952 |
| Controlled lottery tail | 20 bets × R50720 maximum bets · 2 000× required | 80% | 0,19% | 0,57% | 0,54% | 5.4 | R 6 624 418 |
| Controlled lottery tail | 50 bets × R201 800 maximum bets · 5 000× required | 80% | 0,48% | 1,43% | 1,41% | 14.1 | R 2 538 564 |
| Controlled lottery tail | 100 bets × R103 600 maximum bets · 10 000× required | 80% | 0,96% | 2,84% | 2,85% | 28.5 | R 1 244 041 |
| Controlled lottery tail | 200 bets × R57 200 maximum bets · 20 000× required | 80% | 1,90% | 5,60% | 5,64% | 56.4 | R 619 792 |
| Controlled virtual accumulator | 20 bets × R50720 maximum bets · 2 000× required | 90% | 10,24% | 27,68% | 27,51% | 275.1 | R 111 804 |
| Controlled virtual accumulator | 50 bets × R201 800 maximum bets · 5 000× required | 90% | 10,24% | 27,68% | 27,93% | 279.3 | R 110 017 |
| Controlled virtual accumulator | 100 bets × R103 600 maximum bets · 10 000× required | 90% | 10,24% | 27,68% | 27,61% | 276.1 | R 111 293 |
| Controlled virtual accumulator | 200 bets × R57 200 maximum bets · 20 000× required | 90% | 10,24% | 27,68% | 27,64% | 276.4 | R 111 268 |
Cumulative incidence
Same budget, four paths.
20 bets × R5050 bets × R20100 bets × R10200 bets × R5
How to read this
A payout threshold changes the comparison.
At R50, a 2,000× payout reaches the target. At R5, the same outcome pays only R10,000, so the entrant needs 20,000×. More wagers cannot compensate automatically for a thinner eligible tail.
- 20 × R50
- 17,97%
- 200 × R5
- 3,54%
Ruleset registry
Nothing is hidden behind a brand name.
These are synthetic experimental distributions. They isolate tail mechanics and are not advertised as replicas of commercial products.
Controlled jackpot slot
96% RTPclass-c-jackpot-slot-1.0- Replication class
- C — synthetic experimental game
- Maximum multiple
- 20 000×
- Model
- GreyScienx controlled tail-shape model
Independent spins; gross multiplier table does not change with stake.
Controlled crash target
97% RTPclass-c-crash-target-1.0- Replication class
- C — synthetic experimental game
- Maximum multiple
- 20 000×
- Model
- GreyScienx constant-edge first-passage model
The target multiplier is declared before the draw; P(reach target) = 0.97 / target multiplier.
Controlled lottery tail
80% RTPclass-c-lottery-tail-1.0- Replication class
- C — synthetic experimental game
- Maximum multiple
- 100 000×
- Model
- GreyScienx controlled attempt-count model
Each wager is one independent ticket; the sole prize is 100,000× gross at probability 8 per million.
Controlled virtual accumulator
90% RTPclass-c-accumulator-target-1.0- Replication class
- C — synthetic experimental game
- Maximum multiple
- 20 000×
- Model
- GreyScienx constant-margin first-passage model
Independent synthetic events; the offered target has P(success) = 0.90 / target multiplier. No real matches are used.
Reproducibility bundle
Inspect every input and result.
The seed, source hash, exact formulas, aggregate outputs, audit sample, and checksums are public.
Interpretation boundary
A large gross payout is not a recommendation.
This study uses fictional money, synthetic entrants, and controlled probability laws. It does not identify a game to play, estimate an undisclosed commercial product, or imply that a target hit is likely, repeatable, or profitable after spending.