We tested 10,000 sessions of 1,000 drops in our Plinko model, recording 10 million outcomes. Every session used the same settings: 9 rows, Medium risk, a starting balance of 1,000 virtual credits and a 1-credit bet. We then calculated the results at RTP settings from 98% to 110%, one percentage point at a time, and separately at 120%.
This is the model used in our free Plinko game and simulator. We wanted to see what would happen to the money if the balls landed in the same places but the payouts changed. Every comparison starts again with 1,000 credits. That covers all 1,000 bets, so no session ends early because it runs out of funds.
What happened to the balances?
At the 98% setting, 3,066 of the 10,000 sessions finished in profit. At 100%, that rose to 4,843. At 110%, it reached 9,788. The share of profitable sessions increased at every step from 98% to 110% in this sample, but not by the same amount each time.
At 100%, the average final balance was 999.80 credits. The median was 998.3 credits, the middle of the results when ranked from lowest to highest. Moving from 100% to 110% added an average of 100.46 credits to the final balance. That does not mean every session received exactly 100 extra credits.
The slider setting and the payout table's theoretical RTP are slightly different. At the 100% setting, for example, the table returns about 99.96% in theory. You can see the exact figure in the interactive's details. But that small difference does not explain away the variation between sessions: even an exact 100% theoretical RTP would not guarantee that every session returned its starting balance.
Why did eight profitable sessions turn into losses?
Moving from 99% to 100% increased the average final balance by 9.81 credits. Yet 252 sessions ended with less money, and eight went from a profit to a loss.
The reason is in those two payout tables. In our model, the outermost slots dropped from 17× to 15×, while the slots next to them increased from 5.2× to 5.7×. The other payouts stayed the same. Those neighboring slots are more likely to be hit than the edges, so the table's theoretical return increased overall. But a particular session with enough edge hits could receive less money.
Take session 11. At 99%, it finished with 1,001.4 credits, a small profit. At 100%, it finished with 998.9 credits, a small loss. Its seven edge hits paid 14 credits less, while its 23 hits in the neighboring slots added 11.5 credits. The same drops therefore returned 2.5 credits less in total.
This is one of the eight profit-to-loss examples, not a typical session.
This reversal comes from these particular payout tables. It is not a universal effect of raising RTP or a calculation error. We discussed uneven payout changes in our previous study. Here, you can see what that means for the money in one saved session.
Were there still losses above 100%?
At the experimental 105% setting, 1,473 sessions finished with a loss. At 110%, 210 still did. A higher expected return does not remove the possibility of an unfavorable set of landings over 1,000 drops.
At 120%, there were no losing sessions in this sample. All 10,000 finished in profit. That is not a guarantee of profit. The center slots still return less than the bet in this table, and a different set of landings can produce a loss.
All balances here are virtual. Settings above 100% are part of our model experiment, not casino offers. The results apply only to the configuration we tested: 9 rows, Medium risk and 1,000 drops.
Try your own session
You can use the same settings in our Plinko simulator and run your own 1,000 drops. It will generate new landings, so your result may differ. This article uses saved sessions so that changes in the payouts are not mixed up with changes in the random outcomes.
The results come from 10,000 saved sessions in our own Plinko model. The interactive compares the same outcomes under different RTP settings. These results describe this experiment, not a prediction of a future game or a casino implementation.
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