#096 · Bet Tracking & Performance Tool

Betting Variance Calculator

Quantify the spread around an expected betting result when each wager has the same stake, odds and win probability. This is a model of independent binary bets, not a promise that returns will be normally distributed.

Calculator

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How to use this betting tool

  1. Enter equal stake and decimal odds.
  2. Enter the assumed win probability.
  3. Choose the number of independent bets.
  4. Compare expected profit with standard deviation and the approximate range.

What this tool calculates

Each bet has two net outcomes: stake × (odds−1) on a win and −stake on a loss. Variance measures squared dispersion around the expected profit.

Per-bet variance = p(win−μ)² + (1−p)(loss−μ)². Total variance = n × per-bet variance; SD = √variance.

The 95% range uses expected profit ±1.96 standard deviations and a normal approximation. It is not a confidence guarantee.

Worked example

For 100 independent $100 bets at odds 2.00 with a 52% win chance, expected profit is $400 while standard deviation is close to $999.

Win outcome+$100
Loss outcome−$100
Expected wins52 of 100
Expected profit$400

Tips and limitations

  • Correlation can make real variance higher than this independent-bet model.
  • Changing stakes or odds require bet-level data rather than one common input.
  • Variance is expressed in squared currency; standard deviation is easier to interpret.

FAQ

What is betting variance?

It is the probability-weighted squared spread of possible profit outcomes around their expected value.

Why is variance shown in squared dollars?

Squaring deviations prevents positive and negative differences from cancelling; standard deviation converts the result back to dollars.

Does a larger sample remove betting risk?

No. Relative fluctuations often shrink, but the absolute standard deviation generally grows with the square root of the number of bets.

What assumptions does this calculator make?

Bets are independent and share the same stake, decimal odds and win probability.

Is the 95% range exact?

No. It is a normal approximation and can be poor for small samples or extreme probabilities.

Dispersion measures

Expected profitProbability-weighted average
VarianceAverage squared deviation
Standard deviationSquare root of variance

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