Value Betting Simulator With Graph
How to read and use the value betting simulator?
Here’s a quick glossary for each control/output in your value betting simulator:
Inputs (how the sim runs)
- Number of Bets: How many bets do you want to simulate in a row. More bets = a longer “season,” so you can see how your bankroll might grow or shrink over time.
- Mean Offered Odds (decimal): The average odds you’re getting from the bookmaker. In decimal odds, 2.50 means you get 2.5× your stake back if you win (so a $10 bet returns $25, profit $15). This is just the “typical” price; with dispersion turned on, it can wiggle around.
- Mean Edge / EV (%): Your average advantage per bet. If EV is +5%, it means that on average, every $100 you bet is expected to make $5 profit in the long run. It doesn’t mean you win every time—just that the math is in your favor over many bets.
- % Bankroll Stake: If you choose “Percent” staking, this is what slice of your current bankroll you bet each time. For example, 1% on a $1,000 bankroll is a $10 bet; if your bankroll grows to $1,200, 1% becomes $12. It scales up and down automatically.
- Kelly Scale (0–1): A smart sizing rule that tries to grow your bankroll fast while controlling risk. 1 is full Kelly (aggressive), 0.5 is half-Kelly (safer), 0 would mean no Kelly at all. Most people use less than 1 to avoid big swings.
- Monte Carlo Trials: How many alternate “parallel universes” the simulator runs. Each trial is a different random path. More trials give you a better picture of best case, typical, and worst case outcomes.
Realism knobs in betting simulation (make it closer to real life)
Odds Dispersion (lognormal σ, %)
How much the odds bounce around their average. 0% means the odds stay the same; higher % means sometimes you’ll get slightly better or worse prices, like in real betting, where odds change.
EV Std Dev per bet (%)
How much your edge (your advantage) changes from bet to bet. In real life, some picks are stronger and some are weaker. A higher number means more variety in how good your bets are.
Clamp EV to [%min, %max]
Sets hard limits so your edge doesn’t go crazy. For example, -20, 40 means the simulator won’t let your EV be worse than −20% or better than +40% on any single bet.
Autocorrelation ρ (0–0.95)
This controls streakiness. With 0, each bet’s quality is independent. With a higher number (like 0.6), if you’re on a “good run,” it tends to stay good for a while (and same for bad runs). It mimics hot/cold streaks.
Shock Std Dev (%)
How big each new “push” to your edge is from one bet to the next. Think of it like the daily ups and downs added on top of your average edge. Bigger shocks = choppier ride.
RNG Seed (optional)
Type any number to freeze the randomness. Using the same inputs and the same seed gives the exact same results again—handy for sharing and checking.
Risk limits
Stop-Loss (% of bankroll)
A safety brake. If your bankroll drops by this percent from the start (say 50%), the simulator stops that run. It models you saying, “I’ll quit if I’m down too much.”
Take-Profit (% of bankroll)
A target to lock in wins. If your bankroll grows by this percent (say +100%), the sim stops that run to show what happens if you take the money and walk away.
View toggles
Show Curves
Shows a handful of example bankroll paths over time. It’s like watching a few possible journeys your money could take.
Show Quantiles
Shows three lines: 5%, 50% (median), and 95%. Together, they form a “confidence envelope” that shows likely low, typical, and high bankroll levels at each step.
Show Histogram
Shows a bar chart of final ROI (your ending profit as a percent of your starting bankroll) across all the trials. It’s a snapshot of how often each ending result happens.
What are “Equity Quantiles (5% / 50% / 95%)”?
Imagine all your trials lined up at bet #50, or bet #200. The 5% line is where only 5 out of 100 runs did worse than that value (a bad-case line). The 50% line is the middle (half did better, half worse). The 95% line is where only 5 out of 100 runs did better (a great-case line).
Together, they show your likely range as you go along, not just the final result.
How to analyze the Final ROI distribution
Where is the center?
Look at the median or mean. If most outcomes are above 0%, you’re usually making money.
How wide is it?
A wide distribution means results jump around a lot (higher risk). A narrow one means more predictable endings.
How much is below 0%?
Those bars show how often you end up losing overall. Less area below 0 is better.
Is it skewed?
A long right tail (some big positive endings) means there’s a chance of very good outcomes, even if typical results are modest.
Cross-check with other stats:
If the distribution looks nice but Max Drawdown is huge, the journey might be too painful. A higher Sharpe-style value means better reward for the risk you’re taking.
The role of this value betting simulator is to help you understand the big fluctuations you can face while using this strategy.
A betting simulator is capable of visualizing the possible outcomes of a sports betting scenario or strategy.
The purpose of this value betting simulator is not to offer you a correct prediction of your future profits.
Nothing can simulate this. Using the above tool helps you imagine and rationalize the risks and possible outcomes of sports betting.
Sports betting simulators allow bettors to practice and refine their strategies without taking the risk of possible failures and losses.
What is a sports betting simulator?
A sports betting simulator is an algorithm that helps users familiarize themselves with the betting process and test new strategies.
A betting simulator also helps its users to develop a better understanding of how different odds can cause losing/winning streaks.
By replicating real-time betting dynamics such as variance, they provide a practical way to build experience before placing actual bets.
What are the functionalities of Sports Betting Simulators?
The main functionalities of sports betting simulators are designed to replicate multiple possible outcomes of a betting scenario/strategy.
Sports betting simulators allow users to review their betting history, track performance, and identify which strategies are working best.
Some simulators even offer tutorials and feedback to help users improve their betting techniques. Such a tool is the staking simulator developed by BetMetricsLab.
What is a value betting simulator?
Value betting simulators focus specifically on value betting—a strategy that involves identifying odds that are higher than they should be based on statistics.
A value betting simulator is designed to help bettors understand the phenomenon called variance. It also helps to visualize profit spikes, losing streaks, and the range of profits a bettor can achieve in the long term.
A value bet simulator will display higher maximum profits when users increase the positive expected value of each bet placed.
The main goal of such simulators is to help bettors understand that even the best strategies can end up in a loss for a short period.
Components of the value betting simulator
1. Number of bets
The simulation of a value betting activity offers a more accurate and better-visualized graph when the number of bets is high.
Variance in value betting can have a major influence even when the number of bets placed is significant, such as 500.
For this reason, I advise using at least 1000 bets in your simulation as a starting point.
2. Average odds and stakes
The stakes you use will not affect the trendline of your value betting simulation. However, changing the average odds will have a direct effect on how variance can influence your long-term returns.
Higher odds cause higher fluctuations and a higher possibility of not making profits even after a significant number of bets.
3. Expected Value
The Expected Value in betting, when it appears in percentage like in the simulator above, is a prediction of how much profit you can expect to win per bet placed.
This percentage value represents the average net return you can expect after a large number of bets placed on the same odds with the same expected value.
In the value betting simulator above, the expected value is input by yo,u and it represents the net return you expect to make on your bets.
This value is used to calculate the true possibility of the outcome, which is then used to simulate the betting balance.
Please note that while the expected value can provide an estimate of potential betting outcomes, it is based on averages and probabilities, so variance and fluctuations will modify the results.
4. More simulations
Because of the effect of variance in value betting, the simulator above performs 5 simulations for each set of input data.
This visualization helps you understand the overall trend of your strategy and the possible highs and lows when it comes to profit potential.
Please note that value betting simulations have the main role of predicting possible scenarios only.
Based on my experience, when it comes to actual value betting, many factors will change that can result in similar or different profits compared to what you have seen in the simulator.
