Multi-Table Tournament (MTT) Variance Calculator
This MTT Variance Calculator runs a Monte Carlo simulation of your tournament schedule to project expected profit, confidence intervals, downswing probabilities, and the minimum bankroll needed at a 5% risk of ruin.
Enter your field size, buy-in, rake, ROI, and payout structure to see where your results are likely to land over hundreds or thousands of events.
Tournament Parameters
Payout Distribution
Key Statistics
Results Distribution
Downswing Analysis
Understanding the Results
ROI (Return on Investment)
ROI is your average profit percentage per tournament over the long run. A 20% ROI means you profit 20 cents for every dollar invested.
Variance & Standard Deviation
Variance measures how much your results can deviate from expected value. Higher variance means wider swings in results.
Confidence Intervals
Confidence intervals show the range where your actual results will likely fall. 70% interval means 7 out of 10 times your results will be in this range.
Bankroll Management
Conservative bankroll management suggests 100+ buy-ins for MTT play. Our calculator shows required bankroll for 5% risk of ruin.
How to Use the MTT Variance Calculator
The calculator needs five core inputs plus optional advanced settings. Here is what each one controls and how to set it correctly.
Set your tournament parameters
Select the field size (or enter a custom number), your buy-in amount in dollars, and the rake percentage. These define the prize pool and your cost per event.
Enter your ROI
ROI is your average profit percentage per tournament over a large sample. A 20% ROI means you profit $0.20 for every $1.00 invested. If you are unsure, start with 10% to 15% for a realistic estimate at low and mid stakes.
Choose a payout structure
Standard (15% paid) is the most common. Flat (20% paid) reduces variance by paying more players. Steep (10% paid) increases variance with larger top prizes. Pick the one closest to the tournaments you play.
Read your results
The calculator shows expected profit, standard deviation, probability of loss, required bankroll at 5% risk of ruin, 70% and 95% confidence intervals, a distribution chart, and downswing probabilities at 50 and 100 buy-ins.
For more control, click Show Advanced Options inside the calculator to adjust the number of tournaments per simulation, Monte Carlo sample size (higher means more accurate but slower), and an optional starting bankroll for risk of ruin calculations.
Reading Your Poker Variance Calculator MTT Results
The calculator outputs six key metrics. Here is how to read each one and what it tells you about your tournament schedule.
Expected Profit + CI
Average outcome and the range where 70% and 95% of runs land
Downswing Analysis
Worst downswing in buy-ins and probability of 50 or 100 BI drops
Required Bankroll
Minimum bankroll to keep risk of ruin below 5% for your schedule
Expected profit and confidence intervals
Your expected profit is the average outcome across all Monte Carlo samples. The 70% confidence interval shows where 7 out of 10 simulation runs landed. The 95% interval shows the realistic extremes.
If your 95% lower bound is deeply negative, you either need more volume, a higher ROI, or a larger bankroll to survive the swings.
Downswing analysis
The calculator tracks the worst downswing in each simulation run and reports the maximum in buy-ins. It also shows the probability of hitting a 50 or 100 buy-in downswing across your sample.
Even a player with 20% ROI in 1,000-player fields has a real chance of a 100+ buy-in stretch below expectation. For a deeper look at how standard deviation drives these swings, see our variance in poker guide.
Required bankroll (5% RoR)
This figure tells you the minimum bankroll needed to keep your risk of ruin below 5% over the simulated schedule.
Compare it with the output from our bankroll calculator for a cross-check. If the two numbers differ significantly, the gap is usually caused by the ROI estimate: a small drop in true ROI can double your required bankroll.
The Maths Behind This MTT Variance Calculator
A min-cash is far more likely than a win. In a 1,000 runner field with 150 places paid, a cashing player takes first place roughly 0.67% of the time. Any model that makes deep finishes more likely than min-cashes will overstate both expected profit and variance.
Why MTT Variance Is Higher Than Cash Games
Only 10% to 20% of the field gets paid in a typical MTT, and prizes are heavily concentrated at the top.
Standard deviation per tournament runs roughly 3 to 5 times a cash game session of similar duration, which means longer and deeper downswings even for winning players. Published field data puts a 1,215 runner MTT at about 9 buy-ins of standard deviation per event.
To model cash game variance separately, use our poker variance simulator.
Your edge at the table only matters if you are playing where the fields are soft enough to sustain it. Check out the best poker sites with exclusive rakeback deals to make sure you are not leaving money on the table.
MTT Variance and Bankroll Questions
How accurate is a Monte Carlo MTT variance simulation?
Accuracy depends on sample size and how realistic your inputs are. At 10,000 Monte Carlo samples (the default), the confidence intervals stabilise well. Confidence bands are empirical percentiles across all runs rather than a normal approximation, because tournament results are strongly right skewed and a normal curve misstates both tails. Increasing to 50,000 or 100,000 samples in the advanced options tightens the estimates further but takes longer to compute. The biggest source of error is not sample size but your ROI estimate: if your true ROI is 10% but you entered 20%, every output will be overly optimistic.
How many tournaments do I need before trusting my ROI?
At minimum 1,000 tournaments for a rough estimate and 3,000 to 5,000 for a number you can plan around. MTT ROI converges much slower than cash game win rates because of the top-heavy payouts. A player who ran hot in a few final tables early can show 40% ROI over 500 events and still be a 10% ROI player long term. Use conservative ROI estimates in the calculator until you have 3,000+ results tracked.
Which payout structure should I use in the calculator?
Standard (15% paid) fits most online MTTs on major sites. Use Flat (20% paid) for tournaments with flatter structures like bounty events or lower-guarantee dailies where more players cash. Use Steep (10% paid) for high-roller events, Sunday majors, or any tournament where the winner takes 25%+ of the prize pool. If you mix formats, run the simulation once for each structure and compare the downswing probabilities.
How does ICM affect MTT variance?
ICM (Independent Chip Model) changes the real-dollar value of chips at different stages of a tournament, especially near the bubble and at final tables. The variance calculator models overall tournament outcomes but does not account for individual ICM decisions within a single event. If you want to see how chip stacks translate to dollar equity at a final table, use our ICM guide alongside this tool.
How big a bankroll do I need for MTTs?
The calculator returns the minimum bankroll that keeps your risk of ruin below 5% over the schedule you entered, read as the 95th percentile of maximum drawdown across every simulation run. As a rough guide, MTT players need roughly 3 to 5 times the bankroll a cash game player needs for equivalent stakes, because standard deviation per tournament runs 3 to 5 times higher. Larger fields need more: a 5,000 runner schedule swings far harder than a 200 runner one at the same buy-in.
What is a normal MTT downswing for a winning player?
Far deeper than most players expect. Because only 10% to 20% of the field cashes and prizes are concentrated at the top, a genuinely winning tournament player will hit stretches of 100 buy-ins or more below expectation. Run the simulation at your own ROI and field size and read the downswing probabilities rather than relying on a rule of thumb, because the answer changes sharply with field size and payout shape.