Outcome calculator / hypothetical model
Explore the inputs.
Understand the arithmetic.
A win rate describes frequency. It does not describe the size of the wins, losses or costs. Change these example inputs to see the arithmetic.
Use one consistent unit and weighting throughout. These are invented examples; do not enter account identifiers or private records. Include costs here only if they are not already reflected in the average outcomes.
Break-even win frequency: 40.00% under these assumptions.
0.50 × 3 − 0.50 × 2 − 0 = 0.50
What this does—and does not—tell you
The model average is p × W − (1 − p) × L − C, where p is win frequency, W is average win, L is average loss magnitude and C is average cost. With W + L greater than zero, the break-even frequency is (L + C) / (W + L). This is arithmetic, not a prediction of future results.
Real records also need dates, the full inclusion policy, position sizing, costs, missing outcomes and a consistent unit. Variable exposure, dependence between outcomes and uncertain estimates matter. A bot-reported signal win rate is not automatically an account return.
How the opening example is calculated
With an illustrative 50% win frequency, average winning outcome of 3 units, average losing outcome of 2 units and zero additional costs, the model average is 0.5 units per outcome. These invented inputs are not realtrademaster results or a forecast.
What to ask when reviewing a result
What dates are covered? Are losses, breakevens and cancellations accounted for? Are values gross or net? Are instruments/units comparable? Is this a signal outcome log or an actual account record? Is the evidence complete and independently checked?