b2KIT

Story Point Estimator

Estimate story points using planning poker, T-shirt sizing, or Fibonacci sequences with team velocity calibration and confidence levels.

Tested tool guide Tested browser tools Checked August 16, 2026

What Story Point Estimator does, with a checked example

Story points measure relative size, not clock time, and this tool keeps that distinction explicit. It runs planning poker rounds - each estimator privately picks a Fibonacci card, all votes are revealed together, and wide spreads mark stories for discussion - and it supports T-shirt sizing when a rough bucket is enough. Confidence levels attach to each vote so low-confidence items stand out. Feed in the team's calibrated velocity and the tool converts the backlog total into sprints and calendar weeks. The trap: the forecast is only as good as the velocity you enter, and points are not hours.

Worked example

A concrete input and expected output from the current implementation.

Input

Backlog sizes: 3, 5, 8, 13, 5, 3, 8 points. Velocity: 15 points per sprint. Sprint length: 2 weeks.

Expected output

Total: 45 points. At 15 points per sprint, that is 3 sprints, or about 6 weeks of calendar time.

The tool sums the sized stories to 45 points and divides by the entered velocity of 15 points per sprint, giving 3 sprints, then multiplies by the 2-week sprint length for the 6-week forecast.

How the result is produced

1

Estimation methods

Planning poker runs as a round: every estimator privately picks a card from the Fibonacci sequence (1, 2, 3, 5, 8, 13, 21), all cards are revealed at once, and the spread is shown. Votes that cluster converge on a median size; a wide gap, such as a 5 and a 13, signals a story the team does not understand yet, so it goes back for discussion before a re-vote.

2

Velocity calibration

You enter the points the team actually completed over recent sprints, and the tool totals the sized backlog and divides by that velocity to forecast the number of sprints required, then multiplies by sprint length to state calendar time. Confidence levels attach to individual estimates, so low-confidence items stand out for decomposition before they are committed.

Good uses

  • Run planning poker rounds for a handful of stories in a backlog refinement session and settle on the median when votes cluster.
  • Size a large release backlog with T-shirt buckets in one pass, then enter the team's calibrated velocity to forecast how many sprints the release needs.
  • Surface why estimates disagree: reveal the votes on a story that split between 5 and 13, discuss what each side assumed, and re-vote.

Limits and checks

  • Story points are relative effort, not time. Until the team has a velocity derived from completed work, the sprint count is an assumption, not a schedule.
  • Fibonacci gaps are unequal: the jump from 8 to 13 is larger than from 3 to 5. Averaging votes across a wide spread hides the real disagreement, so the discussion matters more than the number.
  • Velocity is team-specific and drifts as membership or backlog scale changes. Entering another team's velocity, or a stale one, produces confident-looking dates that will not hold.

Common questions

Can I convert story points straight to hours or days?

No, and converting defeats the method. Points compare items to each other and to a reference story, which keeps estimates stable and avoids the anchoring that hour-based guessing produces. Use the velocity calibration instead: backlog points divided by points per sprint gives sprints, then multiply by sprint length for calendar time.

When should I use T-shirt sizing instead of planning poker?

Use shirts for a fast first pass over a large backlog where rough buckets are enough to sequence the work. Switch to Fibonacci planning poker for stories the team will actually commit to in the next sprint or two, where the finer scale and the voting discussion surface hidden complexity. The tool supports both, so teams often run shirts for triage and poker for commitment.

References and verification

The example and behavioral notes were checked against the browser implementation. Standards and primary references below define the relevant format, formula, or platform behavior.

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