Variance Calculator

Load a tournament schedule and get the profit distribution over N samples: downswings, risk of ruin and the bankroll it takes to survive them.

v0.7.4

1. Schedule

Fill in your schedule — for every tournament you play set a name, type, buy-in, AFS, your ROI and your ITM rate. New rows are added with «+ Add». A real MTT session almost never consists of identical tournaments, so list them all for an accurate estimate. You can also import a ready schedule.

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Example schedules

2. Simulation launch

Set the key inputs before the run — rakeback %, bankroll and how many tournaments go into one sample. The longer the distance, the deeper the estimate.

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200 tournaments/sample
Payout ladder
750 of 5,000 places paid (15.0%). Min cash ≈ 1.75× buy-in.
1st
14.3%
2nd
10.2%
3rd
7.3%
4th
5.2%
5th
3.7%
6th
2.7%
7th
1.9%
8th
1.4%
9th
0.97%
10–750
paid tail
0.03%–0.95%
751–5000
no cash
85.0% of field

Volume needed to verify a chosen ROI

Not «is the player profitable at all», but a specific claim: suppose the long-run ROI after fees really is +X%. How many tournaments before that +X% is hard to mistake for ordinary variance?

Field size
Fee %
Confidence %
Tested ROI %

Current answer: if the player's long-term ROI is +10 %, you need about 29 k – 37 k tournaments to be 95% likely to see it separate from zero. That is roughly 166 full fields of 200 players.

If long-term ROI isPlay this manyFull fields
+30 %3.3 k – 4.1 k18.4
+20 %7.3 k – 9.3 k41.4
+15 %13 k – 17 k73.7
▸+10 %29 k – 37 k166
+5.0 %117 k – 149 k663
+2.5 %469 k – 596 k2.7k
+1.0 %2.9 M – 3.7 M16.6k
+0.50 %12 M – 15 M66.3k
+0.10 %293 M – 372 M1657.5k

Ranges include the model's residual noise buffer. Near 0% ROI the required volume explodes, because a tiny positive result is almost indistinguishable from normal tournament variance.

Volumes assume a symmetric normal shape. Real MTT results lean right, so for tight targets the true range is a little lopsided — treat this as a ballpark.

Other calculators

The simulator answers the question about the long run. The maths of a single hand is what the other tools are for.