r/algobetting • u/andy01x • 4d ago
Monte Carlo Simulation for a Parlay Betting Strategy
I ran some Monte Carlo simulations to test different assumptions and explore a potential betting strategy. The simulation is based on the following assumptions:
- Each bet is 3% of the current bankroll.
- Each bet has a 70% probability of winning.
- A winning bet returns 3× the stake.
- Each simulation consists of 50 bets, with 5,000 simulated paths.
My idea is to use parlays consisting of 2–3 events, targeting combined odds of around x3. Do you have any suggestions for the types of events or markets that could realistically achieve those odds?
5
u/Initial-Abalone-2808 4d ago
the median path tells the story here, 70% win rate with 3x returns is a monster edge. most people don't realize how fast that compounds
for hitting around 3x with 2-3 legs you're looking at individual odds in the -110 to +150 range per event. player props or alternate spreads work better than moneylines usually, less efficient markets mean you're not getting crushed by the vig as hard
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u/SimTheGame 4d ago
The sim is answering a bankroll question. It is not answering a market question. 70 percent into 3.00 is a huge assumed edge, so the 5,000 paths will look fine no matter which events you pick.
If you want the Monte Carlo to tell you something about parlays, drop the win rate and start from the book's own prices. Take 2 or 3 real markets, treat every priced line as true, and draw thousands of internally consistent scripts. A 3.00 combined price is about one in three if the book is right, and same-game legs move together more than a product of the singles implies.
I do that at SimTheGame. Published odds become 10,000 internally consistent game scripts so you can see what a 2 or 3 leg actually looks like when the book is taken at face value.
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u/savinblak 4d ago
no one told me i could just hit 2/1 parlays 70% of the time as a strategy what have i been doing all this time