# MAPE Calculator

> Measure forecast accuracy as a percentage: MAPE, symmetric MAPE and weighted WAPE from actual and forecast values, with zero actuals handled explicitly.

Category: Statistics & probability · Applies to: Worldwide · Last updated: 2026-10-29
Interactive calculator: https://calculators.geekmidst.com/calculators/mean-absolute-percentage-error-calculator

MAPE averages each error as a percentage of the actual value, so forecasts of different-sized items can be compared. WAPE and sMAPE are shown because MAPE misbehaves near zero.

Also called: Forecast accuracy calculator, Mean absolute percent error calculator.

## Inputs
- Actual values (default 100, 200, 250, 50)
- Forecast values, same order (default 110, 180, 250, 60)

## Results
- MAPE
- sMAPE (symmetric, 0–200%)
- WAPE (Σ|error| ÷ Σ|actual|)
- Forecast accuracy (100% − MAPE, floored at 0)
- Pairs used for MAPE
- Pairs excluded (actual = 0)

## Formula

```
MAPE = 100% ÷ n × Σ|Aᵢ − Fᵢ| ÷ |Aᵢ| (Aᵢ ≠ 0);  sMAPE = 100% ÷ n × Σ 2|Aᵢ − Fᵢ| ÷ (|Aᵢ| + |Fᵢ|);  WAPE = 100% × Σ|Aᵢ − Fᵢ| ÷ Σ|Aᵢ|
```

Where:
- Aᵢ: actual value
- Fᵢ: forecast value
- n: pairs included in each measure

## Worked example
1. Percentage errors: 10/100 = 10%, 20/200 = 10%, 0%, 10/50 = 20%.
2. MAPE = (10 + 10 + 0 + 20) ÷ 4 = 10%.
3. WAPE = (10 + 20 + 0 + 10) ÷ 600 = 6.67%, lower because the large-volume items were forecast well.

**Result:** The forecasts have a MAPE of 10% and a volume-weighted error (WAPE) of 6.7%.

## What the result means

MAPE treats a 10-unit miss on a small item as worse than the same miss on a big one. That suits comparing items, but small actual values can blow it up, and it punishes over-forecasts more than under-forecasts. WAPE weights by volume and is usually the better single number for totals such as inventory.

## Assumptions and limits
- Errors are measured on actual values: MAPE skips pairs where the actual is 0 and reports how many were skipped.
- sMAPE uses the 0–200% definition with (|A| + |F|) ÷ 2 in the denominator, skipping pairs where both are 0.
- MAPE is unstable when actual values are close to zero, and meaningless for data that can be negative or have an arbitrary zero (such as temperatures).
- “Accuracy = 100% − MAPE” is a reporting convention, not a statistical measure.

## Questions

### What is a good MAPE?

It depends on how predictable the series is. Compare against a simple benchmark, such as last period’s value, rather than a fixed threshold.

### Why do MAPE and WAPE differ?

MAPE averages percentages, so every item counts equally. WAPE divides total error by total volume, so big items count more.

## Related calculators
- [Mean Absolute Error Calculator](https://calculators.geekmidst.com/calculators/mean-absolute-error-calculator)
- [RMSE Calculator](https://calculators.geekmidst.com/calculators/root-mean-square-error-calculator)
- [Percent Error Calculator](https://calculators.geekmidst.com/calculators/percent-error-calculator)

Source: GM¹X CalcVerse — https://calculators.geekmidst.com/calculators/mean-absolute-percentage-error-calculator