Dataset: Issues & Pull Requests
Entity: Issues
Field ID: past_sprint_names
Type: Datetime
Description: The names of the closed sprints the issue participated to (before the currently attached sprint). The sprints are ordered by closure date (completion date). The currently attached sprint is excluded from this list, even if it is closed.
Source: App
Transformation logic:
Jira: the list of former sprint names attached to the issue
Other apps: N/A
From: |
|
Github (PRs, Issues) | N/A GitHub Projects does not expose the former sprints, only the current one |
Gitlab (PRs, Issues) | N/A |
Bitbucket (PRs) | N/A |
Azure DevOps (PRs, Issues) | N/A |
JIRA (Issues) | Calculated |
ClickUp (Issues) | N/A |
Trello (Issues) | N/A |
Reporting Use Cases
The Past Sprints field is a powerful tool for agile teams, providing a historical log of every closed sprint an issue was part of before its current one. Its primary use is to analyze and measure "sprint spillover" or "carryover," helping you improve the accuracy of your sprint planning and team velocity.
Filtering for Sprint Retrospectives: You can create reports to audit the outcomes of specific past sprints.
To find all issues that were once planned for "Q2 Sprint A" but were not completed and subsequently moved, you can use a filter like
Past Sprints contains "Q2 Sprint A". This is invaluable for sprint retrospectives to understand what work was carried over.
Measuring Sprint Spillover: The most critical use case is to quantify how much work is being pushed from one sprint to the next.
Spillover Rate: You can calculate the percentage of issues in your current workload that were carried over from previous sprints. A custom formula like
ROUND(COUNT_IF(LENGTH(past_sprint_names) > 0) / COUNT() * 100, 2)provides a key performance indicator for your planning accuracy. A consistently high rate suggests overcommitment or inaccurate estimations.Number of Handoffs: You can analyze how many sprints an issue typically lives through before completion with the metric
AVG(LENGTH(past_sprint_names)). A high number indicates chronic reprioritization or issues that are consistently underestimated.
Analyzing Spillover Sources: By using the
FLATTENfunction, you can identify which sprints are the biggest sources of unfinished work.A bar chart with the dimension
FLATTEN(past_sprint_names)and the metricCOUNT()will show which past sprints contributed the most carryover work, helping you pinpoint a particularly disruptive or poorly planned sprint.