Agile Velocity Forecasting: How Many Sprints Are Left, With a Range
October 29, 2026
Velocity is the amount of work (usually story points) a team completes per sprint. Forecasting uses past velocities to estimate how many sprints the remaining backlog will take: sprints = backlog points ÷ velocity. Because velocity varies, a range is more honest than a single date.
Past six sprints: 21, 25, 24, 28, 22, 24 points. The mean is 144 ÷ 6 = 24. Deviations are −3, 1, 0, 4, −2, 0; squared they sum to 30; divided by 5 gives a variance of 6 and a standard deviation of 2.45.
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Open the Standard Deviation Calculator →Forecast With a Range
The remaining backlog is 168 points. At the average velocity of 24: 168 ÷ 24 = 7.0 sprints. At an optimistic velocity of 26.45 (mean plus one SD): 6.35, so 7 sprints rounded up. At a cautious velocity of 21.55 (mean minus one SD): 7.8, so 8 sprints. At the worst of the last six (21): 8 sprints. With two-week sprints, the forecast is 14 weeks at the average and 16 weeks in the cautious case. Present it as 'most likely 7 sprints, probably no more than 8'. Round up since a partial sprint still takes a whole one.
| Scenario | Velocity | Sprints for 168 points | Weeks (2-week sprints) |
|---|---|---|---|
| Optimistic (mean + 1 SD) | 26.5 | 6.35, i.e. 7 | 14 |
| Average | 24.0 | 7.0 | 14 |
| Cautious (mean − 1 SD) | 21.5 | 7.8, i.e. 8 | 16 |
| Worst recent sprint | 21 | 8.0 | 16 |
Scope Changes and Re-Forecasting
Backlogs change: if the team adds an average of 6 points per sprint of new work, the net burn-down is 18 points a sprint, and 168 points would take 9.3 sprints. Update the forecast after each sprint with the latest velocity (a rolling average of the last 3 to 6 sprints). Account for holidays and team changes: if a member is away for a sprint, scale the velocity by capacity. For a new team without history, start with a small number of sprints to establish a baseline.
Common Pitfalls
Comparing velocity across teams (point scales differ), using velocity as a performance target (which encourages inflating estimates), forecasting without considering the quality and the stability of the backlog, and ignoring dependencies. Use the range and communicate uncertainty. Monte Carlo simulation using the past sprint throughput can give probabilities of reaching a date.
Practical Tips
Keep stories small and consistently sized, count only fully completed stories, and track throughput (items per sprint) as an alternative that doesn't depend on estimation. Share the forecast regularly with stakeholders, and update it with real data.
Frequently Asked Questions
How do I forecast sprints remaining?
Divide the remaining backlog points by average velocity.
Why give a range?
Because velocity varies from sprint to sprint.
How do I account for new work being added?
Subtract the average added points from the velocity to get the net burn-down.
Should velocity be compared between teams?
No, point scales differ.
How many sprints should the average cover?
Typically the last 3 to 6.