Swiss Tournament Round Count log₂(n)
Compute ceil(log2 N) undefeated-halving planning heuristic; Swiss draws, pairing constraints and standings tie-breaks can prevent a unique winner, so not guaranteed required rounds.
Description
A doubling-capacity estimate provides a simple Swiss-round planning heuristic.
A doubling-capacity estimate provides a simple Swiss-round planning heuristic. Actual pairing and tie resolution depend on tournament rules.1
Enter integer participants 2–1000000. Return recommended heuristic rounds and corresponding power-of-two capacity.
When to use Swiss Tournament Round Count log₂(n)
Use Swiss Tournament Round Count log₂(n) when you need to evaluate the supplied records under the calculation and evidence rules below. This does not guarantee a unique winner or implement Swiss pairings.
Prepare the supplied game state, observations and explicit variant settings. Follow the card, board, coordinate and state conventions in the calculation rules.
How to use Swiss Tournament Round Count log₂(n) and understand its results
- Prepare the supplied game state, observations and explicit variant settings. Follow the card, board, coordinate and state conventions in the calculation rules.
- Enter participantCount using the field table and calculation rules, then run the tool.
- Read halvingModelMinimumRounds, unbeatenSlotCapacityAfterModelRounds. The explanation below defines the units, signs, ordering and any flags or placeholder values.
- If the tool reports an input issue, correct the values and run it again. Apply the stated assumptions when interpreting a successfully returned result.
| Input field | Meaning | Value type; see rules below | Requirement |
|---|---|---|---|
| participantCount | Participant count | number | Required |
Enter integer participants 2–1000000. Return recommended heuristic rounds and corresponding power-of-two capacity.
rounds=ceil(log2(participants)); capacity=2^rounds Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.
| Output field | Meaning | Value type |
|---|---|---|
| halvingModelMinimumRounds | Halving model minimum rounds | number |
| unbeatenSlotCapacityAfterModelRounds | Unbeaten slot capacity after model rounds | number |
{
"input": {
"participantCount": 17
},
"output": {
"halvingModelMinimumRounds": 5,
"unbeatenSlotCapacityAfterModelRounds": 32
}
}Limitations and assumptions
This does not guarantee a unique winner or implement Swiss pairings.
Numeric inputs, where present, must be finite. Follow the calculation-specific rules for overflow, underflow and exceptional cases. Missing required fields, extra fields, wrong value types and violations of the calculation rules are input errors.
Alternative or Complementary methods
Use Single-Elim Byes Next Power of Two: A single-elimination bracket can be padded to the next power of two. Byes reduce contested first-round matches, while every elimination requires a loss. For a complementary task, use Elo Win Probability Expectancy: Elo expected scores are complementary logistic fractions. Expected score includes draws rather than describing win probability alone.
References
-
Swiss Tournament Round Count log₂(n) — tool.io
Similar or alternative tools
- Single-Elim Byes Next Power of Two
A single-elimination bracket can be padded to the next power of two. Byes reduce contested first-round matches, while every elimination requires a loss.
- Elo Win Probability Expectancy
Elo expected scores are complementary logistic fractions. Expected score includes draws rather than describing win probability alone.