Expected Value Calculator
Add each possible outcome, its probability, and its payoff. You can enter probability as a decimal (0.25) or percent (25).
What Is Expected Value?
Expected value (EV) is the average result you would expect if the same decision were repeated many times. It is one of the most practical tools in probability, finance, risk analysis, game theory, and everyday decision-making.
Instead of asking, “What outcome is most likely?” expected value asks, “What is the long-run average value of this choice?” That difference is powerful.
EV = Σ (probability × outcome value)Where each probability is between 0 and 1, and all outcomes represent the value (gain or loss) of each scenario.
How to Use This Calculate Expected Value Calculator
Step-by-step
- Enter an Outcome name so your scenarios are easy to read.
- Enter a Probability for each outcome (for example: 0.2 or 20).
- Enter the Payoff Value for each outcome (positive for gains, negative for losses).
- Click Calculate Expected Value.
The calculator shows your raw expected value, normalized expected value, total probability, and estimated standard deviation. If probabilities do not sum to 100%, you will get a warning so you can review your assumptions.
Why Expected Value Matters in Real Life
1) Personal finance and investing
Expected value helps compare choices like investments, side-business projects, and insurance decisions. A choice with a higher EV is generally better in the long run, even if short-term outcomes vary.
2) Career decisions
When evaluating job offers, relocation, or further education, EV can help quantify uncertain outcomes. You can assign estimates to salary upside, job stability, and costs, then compare alternatives more objectively.
3) Everyday choices under uncertainty
Should you buy an extended warranty? Take a guaranteed discount now or gamble on a bigger reward later? Expected value gives structure to decisions that often feel emotional.
Worked Examples
Example A: Raffle ticket
You pay $10 for a ticket. There is a 2% chance to win $400, and a 98% chance to win nothing.
- Win scenario payoff: +$390 net (400 - 10), probability 0.02
- Lose scenario payoff: -$10 net, probability 0.98
EV = (0.02 × 390) + (0.98 × -10) = -2.00
So the average long-run result is a loss of $2 per ticket.
Example B: Freelance project decision
You can spend 20 hours bidding a project. There is a 40% chance of earning $2,000 profit, and 60% chance of earning $0. Assume your opportunity cost is $500.
EV = (0.40 × 2000) + (0.60 × 0) - 500 = +300
In expectation, this effort is worth +$300, which may justify doing it depending on your risk tolerance and current priorities.
Common Mistakes to Avoid
- Probabilities not adding up: If your model is complete, probabilities should total 1 (or 100%).
- Forgetting net payoff: Include costs, fees, taxes, and time value where relevant.
- Using EV alone for high-risk choices: Two options can have the same EV but very different volatility.
- Overconfidence in assumptions: EV is only as good as the probability estimates you enter.
Expected Value vs. Most Likely Outcome
The most likely outcome is the single scenario with the highest probability. Expected value is the weighted average across all outcomes. These can point to different choices. A rare but large payoff can raise EV even if it is not the most likely event.
Quick FAQ
Can expected value be negative?
Yes. A negative EV means the decision loses value on average over repeated trials.
Should I always pick the option with the highest EV?
Not always. Consider risk tolerance, cash flow constraints, uncertainty in your estimates, and downside protection.
What if probabilities do not sum to 100%?
This calculator still provides a normalized EV so you can inspect results, but you should usually refine your assumptions until probabilities represent a complete set of outcomes.
Final Thoughts
If you want better decisions under uncertainty, expected value is one of the most useful concepts to master. Use it for money choices, time allocation, business ideas, and strategic planning. The goal is not perfect prediction—it is consistently better thinking.