Calculator

Poker variance calculator

Updated August 2026 · by Tom Howcroft

US edition. Simulate 20 or 100 poker result paths with 50, 80 and 95% bands, probability of loss, downswing depth, recovery estimate and downloadable assumptions.

What does this result mean?

A poker variance simulator shows how many different result paths can come from the same assumed win rate and standard deviation. This version draws 20 or 100 reproducible paths, overlays 50, 80 and 95 percent bands, estimates the probability of finishing below break-even, and translates the model into a downswing depth and recovery estimate. The lines are not predictions. They are examples under a fixed-edge normal model, designed to show why a good player can run badly and a short-term winner can still be unproven. Save or share the assumptions beside the result, then compare the output with your real session history and hand review before changing stakes.

Assumptions

Build the model

Win rate (BB/100)Your assumed long-run edge.Standard deviation (BB/100)How widely results swing per 100 hands.Hands in sampleThe sample length to simulate.

Simulated result paths 20 paths 100 paths

+2,500 BBExpected final result

10.7%Probability of finishing behind

+810 BBExpected downswing depth

16200Estimated hands to recover

−1,444 BB95% final low

+6,444 BB95% final high

Result paths and confidence bands

How the same edge can look completely different

PathsExpected50 / 80 / 95%

Final-result distribution

Where the model finishes

Accessible data table

Confidence bands through the sample

The table is the same model as the chart. It remains readable without colour, animation or a mouse.

Hands	Expected	50% range	80% range	95% range

Methodology

What the simulator is doing

Each path divides the selected sample into 50 equal blocks. For every block it adds the assumed win-rate expectation plus a seeded normal random draw scaled from the standard deviation. The seed comes from the visible inputs, so the same shared URL reproduces the same paths.

The expected result is win rate × hands / 100. Spread at each point is standard deviation × √(hands / 100). The 50, 80 and 95 percent bands use standard-normal critical values 0.674, 1.282 and 1.960.

The normal density and standardisation follow the NIST normal-distribution reference and its standard normal CDF table.

Limits

Model output, not poker advice

The model assumes a fixed edge, independent blocks and a stable standard deviation. Real games change. Table quality, tilt, fatigue, stake mix and non-normal tails all move the result. A confidence band describes outcomes under the assumptions. It does not prove the assumptions are true.

The downswing figure uses the long-run approximation standard deviation² / (2 × positive win rate). The recovery estimate divides that depth by the assumed edge. At a zero or negative win rate there is no positive-edge recovery estimate.

Version 2.0.0. Model and copy by Tom Howcroft, reviewed 5 August 2026. Use it for study and planning, never as a profit promise.

How to use the answer responsibly

Treat the calculator as a planning tool, not a verdict on one session. A live poker input is usually an estimate: your win rate is noisy, your standard deviation changes by game type, and your future volume rarely matches the clean number you type into a form. The useful habit is to save the assumptions beside the result so you know what would need to change before the decision changes.

If the result pushes against what you wanted to do, do not smooth the inputs until the answer feels nicer. Make the conservative version first, using a lower win rate, a higher swing rate or fewer weekly hours. Then run the optimistic version. The space between those answers is the real decision area: where a shot needs a stop rule, where a move up needs more buy-ins, or where a good-looking hourly still needs a bigger sample.

Overshove calculators become more useful when the inputs come from your own logged sessions. Rake, tips, travel, hours, stake mix and session length all change the number. A generic benchmark can teach the shape of the problem, but a clean personal log gives the number you should actually act on.

Questions

Why is my result range so wide?

Because variance is large relative to most win rates. Even a clear winner sees a wide 95 percent band over a finite sample, which is why short-term results mislead.

Does a bigger sample narrow the range?

Yes, but slowly. Spread grows with the square root of the sample while expected profit grows linearly, so the edge becomes clearer over long samples rather than overnight.

What standard deviation should I use?

Use your own tracked figure when possible. As rough starting points, online NLH is often lower than live NLH, while PLO is usually higher. The presets are examples, not claims about your game.

Are the 20 and 100 paths predictions?

No. They are seeded examples drawn from the visible assumptions. They show how different plausible paths can emerge from the same edge and volatility.

Can this simulator tell me whether I played well?

No. It models result variance only. Review hands, table selection, fatigue and decision quality separately before changing stakes or rewriting your view of your edge.

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