Tournament Swiss round estimate calculator

Calculate idealized halving rounds needed and idealized undefeated players after those rounds with your own figures.

Your numbers

Use the units shown. Results update as you change valid inputs.

Use idealized halving rounds needed and idealized undefeated players after those rounds to compare changes to your inputs. The method and limits below explain the scope.

Examples

Examples

Try the starting example

Players in idealized field
16
Desired maximum idealized undefeated count
1
Idealized halving rounds needed
4
Idealized undefeated players after those rounds
1
Idealized record-count distribution by wins
0: 1; 1: 4; 2: 6; 3: 4; 4: 1

Try another scenario

Players in idealized field
16
Desired maximum idealized undefeated count
2
Idealized halving rounds needed
3
Idealized undefeated players after those rounds
2
Idealized record-count distribution by wins
0: 2; 1: 6; 2: 6; 3: 2
Calculation method

Calculation method

Idealized halving rounds needed

Smallest r with players/2^r≤supplied undefeated target, using exact integer comparisons.

Idealized undefeated players after those rounds

Players/2^r under perfect same-record halving without draws or byes.

Idealized record-count distribution by wins

Players×choose(r,wins)/2^r; fractions are expected/idealized field counts, not an actual pairing schedule.

Symbols and units
a
Players in idealized field
b
Desired maximum idealized undefeated count

Use the units shown. A list keeps the order in which you enter its values. The symbol ^ means “raised to the power of”.

Assumptions & limits

Assumptions & limits

  • A no-draw/no-bye idealized halving worksheet, not an actual Swiss-system pairing, tiebreak, elimination or tournament-regulation engine. Real fields and same-record pairings may not realize these fractional counts.
Are these inputs private?

These calculations run in your browser. A shared link contains the values you choose to share. Only questions submitted to the separate AI finder are sent to OpenAI.

Further reading

OpenStax: finite probability and sampling without replacement; rules are explicit in each worksheet ↗

Background reading; this does not imply endorsement or independent review of SumFizz.

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