Alright, folks, I’ve been diving deep into some roulette systems again, and I wanted to share the latest results from my recent experiment in this thread since it ties into our ongoing discussions. I ran 1000 simulated spins to compare three popular strategies: Martingale, D’Alembert, and Fibonacci. My goal was to see how they stack up in terms of balance management, win/loss patterns, and overall sustainability.
For those unfamiliar, Martingale is all about doubling your bet after every loss, aiming to recover everything with one win. D’Alembert takes a calmer approach, increasing bets by one unit after a loss and decreasing after a win. Fibonacci, meanwhile, follows that famous number sequence, ramping up bets after losses but more gradually than Martingale.
I set up the simulation with a starting balance of $1000, betting on red/black for consistency, and used a standard European roulette table with a single zero. Here’s the breakdown: Martingale was a wild ride—big wins early on, but a nasty losing streak around spin 400 wiped out the balance fast. It’s high-risk, no question. D’Alembert held steadier, with smaller swings, but the profits were modest, peaking at $1250 before dipping back to $950 by the end. Fibonacci? It surprised me. It climbed slowly to $1300 by spin 700 but couldn’t sustain it, finishing at $1050 after some late losses.
What stood out was how table limits and bankroll size matter. Martingale crumbled under a 7-loss streak—real casinos would’ve capped me sooner. D’Alembert felt safer but didn’t deliver big returns. Fibonacci offered a middle ground but needed patience and a decent starting pot.
I’m planning to tweak the parameters next—maybe test with different bet sizes or a double-zero wheel. If anyone’s tried these systems in real play or has suggestions for the next sim, I’d love to hear about it. Data’s only as good as what we make of it, so let’s dig into this together.
For those unfamiliar, Martingale is all about doubling your bet after every loss, aiming to recover everything with one win. D’Alembert takes a calmer approach, increasing bets by one unit after a loss and decreasing after a win. Fibonacci, meanwhile, follows that famous number sequence, ramping up bets after losses but more gradually than Martingale.
I set up the simulation with a starting balance of $1000, betting on red/black for consistency, and used a standard European roulette table with a single zero. Here’s the breakdown: Martingale was a wild ride—big wins early on, but a nasty losing streak around spin 400 wiped out the balance fast. It’s high-risk, no question. D’Alembert held steadier, with smaller swings, but the profits were modest, peaking at $1250 before dipping back to $950 by the end. Fibonacci? It surprised me. It climbed slowly to $1300 by spin 700 but couldn’t sustain it, finishing at $1050 after some late losses.
What stood out was how table limits and bankroll size matter. Martingale crumbled under a 7-loss streak—real casinos would’ve capped me sooner. D’Alembert felt safer but didn’t deliver big returns. Fibonacci offered a middle ground but needed patience and a decent starting pot.
I’m planning to tweak the parameters next—maybe test with different bet sizes or a double-zero wheel. If anyone’s tried these systems in real play or has suggestions for the next sim, I’d love to hear about it. Data’s only as good as what we make of it, so let’s dig into this together.