PR Size (p75)
Last updated: February 5, 2026
Overview
PR Size (p75) measures the 75th percentile of pull request sizes across your team or organization. This metric helps you understand typical PR size patterns and optimize your code review process for better collaboration and quality.
What It Measures
PR Size (p75) shows the size threshold where 75% of pull requests are at or below that value, and 25% are larger. This metric provides a more reliable picture of your team's PR size patterns than averages, as it's less affected by occasional extremely large PRs.
Example: If your team's PR Size (p75) is 300 lines:
75% of your PRs are 300 lines or smaller
25% of your PRs exceed 300 lines
This represents your "typical large PR" rather than worst-case scenarios
Where to Find This Metric
Go to Productivity>Velocity>Delivery
Team Performance Reports: Compare teams and track trends over time
Individual Analytics: Personal PR size patterns and comparisons to team
Targets: Monitor and alert on PR size thresholds
Custom Dashboards: Include in tailored reports and visualizations
How It's Calculated
Size Definition
PR Size is measured as total lines of code changed, including:
PR Size = Lines Added + Lines Deleted + Lines Modified
Important: Only meaningful code changes are counted. Span automatically excludes:
Generated files (e.g., package locks, build outputs)
Dependencies and vendor code
Files matching your configured ignore patterns (using gitignore syntax)
Non-developer activity (bots, automated commits)
Percentile Calculation
Collect all merged PR sizes for the selected entity (person, team, org) and time period
Sort PRs from smallest to largest
Find the value at the 75th percentile position
Note: Only merged PRs from developer contributors are included. Draft, closed, or abandoned PRs don't affect this metric.
Interpreting the Results
What Different Values Mean
Impact on Workflow | ||
< 200 LOC | ✅ Small PRs - Very focused, incremental changes | Fast reviews, easy to understand, low cognitive load |
200-500 LOC | ✓ Moderate PRs - Manageable size for most changes | Reasonable review time, good balance |
500-1000 LOC | ⚠ Large PRs - Approaching upper limits of effective review | Longer review times, more back-and-forth |
> 1000 LOC | 🔴 Very Large PRs - Difficult to review effectively | High review burden, increased defect risk, delayed cycle time |
Interpreting Your Results
High P75 Values May Indicate
Process Patterns:
Feature-complete development style (entire features in one PR)
Infrequent commit and merge cadence
Batch-style development workflows
Long-running feature branches
Potential Challenges:
Increased review burden on teammates
Longer PR cycle times
Higher cognitive load for reviewers
Increased risk of defects slipping through
More difficult to provide quality feedback
Low P75 Values May Indicate
Process Patterns:
Incremental development approach
Frequent integration and merging
Well-scoped, focused changes
Strong trunk-based development practices
Benefits:
Faster, more effective code reviews
Lower cycle times
Easier to understand and test changes
Reduced review friction
Better collaboration
Recommended Thresholds
Default Working Norm
Span's recommended threshold for PR Size (p75) is 1,000 lines of code.
This default suggests that keeping your 75th percentile at or below 1,000 lines represents healthy engineering practices. However, optimal thresholds vary based on:
Programming language: Some languages are more verbose than others
Architecture style: Monorepos may have different patterns than microservices
Team maturity: Established teams may optimize for smaller PRs over time
Project type: Infrastructure vs. application code may differ
Related Metrics
Understanding PR Size (p75) alongside other metrics provides deeper insights:
Other Size Metrics
PR Size (p50/median): Shows the "typical" PR size (50th percentile)
PR Size (p90): Captures very large outlier PRs
PR Size (average): Mean value, more affected by outliers
PR Size (max): Largest PR in the period
Review & Quality Metrics
PR Cycle Time: Larger PRs typically take longer to merge
Time to Review: First review time correlates with PR size
PR Review Cycles: Larger PRs often need more iterations
PR Revert Rate: Larger PRs have higher defect risk
Delivery Metrics
Total Merged PRs: Volume of work alongside size patterns
Merge Frequency: How often changes are integrated
Common Use Cases
1. Process Optimization
Monitor P75 over time to validate process improvements:
After introducing PR size guidelines
Following developer education on incremental commits
When implementing trunk-based development
2. Team Comparisons
Compare P75 across teams to:
Identify teams with different development practices
Share best practices from teams with optimal sizes
Understand workflow variations across the organization
3. Individual Coaching
Use P75 at the individual level to:
Identify developers who might benefit from guidance on PR scoping
Recognize developers modeling best practices
Personalize onboarding and mentorship
4. Risk Assessment
Correlate PR Size with quality metrics:
Do larger PRs correlate with higher revert rates?
Is there a relationship between size and defects?
How does size impact cycle time and delivery velocity?
5. Workflow Health
Track P75 as a leading indicator:
Rising P75 may signal growing scope or time pressure
Sudden increases warrant investigation into root causes
Sustained high P75 suggests process intervention needed
Automated Insights
PR Size Outlier Detection
Span automatically identifies when an individual's PR Size (p75) is notably higher than their team's baseline using statistical outlier detection (Median Absolute Deviation).
Requirements:
Minimum 5 merged PRs per person
At least 4 teammates for meaningful comparison
When flagged, investigate:
Is the person working on legitimately larger features?
Do they need support breaking down work more granularly?
Are there patterns in which types of changes are large?
Configuration Options
Customizing What Counts
In your Span organization settings, you can configure:
Ignore Patterns: Define files to exclude using gitignore syntax
Lock files and dependencies
Generated code
Documentation (if desired)
Build artifacts
Test File Patterns: Track test code separately from production code
Repository Filters: Exclude certain repositories from calculations if needed
Best Practice: Ensure organization-wide consistency in ignore patterns for accurate team comparisons.
Important Considerations
Data Requirements
For reliable P75 calculations:
Minimum PRs: At least 5 merged PRs per person for individual metrics
Time Period: Longer periods (30-90 days) provide more stable results than weekly views
Team Size: Comparisons require at least 4 people for statistical validity
What's NOT Counted
Draft, closed, or abandoned PRs (only merged PRs)
Bot or automated commits
Files matching your ignore patterns
Non-developer contributor activity
Time Period Sensitivity
Different aggregation windows show different patterns:
7-day rolling: Sensitive to recent changes, good for immediate feedback
30-day rolling: Balanced view for monthly trends
90-day rolling: Smooth long-term patterns, best for strategic initiatives
Taking Action
If Your P75 Is Higher Than Desired
Educate on Incremental Development
Share benefits of smaller, focused PRs
Demonstrate techniques for breaking down work
Establish team guidelines for PR scoping
Review Workflow Bottlenecks
Are long-running branches causing large merges?
Is infrequent integration leading to batching?
Do developers have concerns about "too many PRs"?
Improve Work Decomposition
Better story splitting in planning
Feature flags for incremental feature delivery
Architectural patterns that support modularity
Set Team Norms
Define target PR size ranges
Use Span working norms to monitor adherence
Celebrate improvements and model best practices
Best Practices for Healthy PR Sizes
✅ Break down large features into independently mergeable chunks
✅ Use feature flags to ship incomplete features safely
✅ Separate refactoring from functional changes
✅ Extract infrastructure changes into separate PRs
✅ Keep formatting/style changes in dedicated PRs
✅ Leverage git commits to tell a story of incremental progress
Where to Find This Metric
PR Size (p75) is available throughout Span:
Metrics Dashboard: Delivery category alongside other code review metrics
Team Performance Reports: Compare teams and track trends over time
Individual Analytics: Personal PR size patterns and comparisons to team
Working Norms: Monitor and alert on PR size thresholds
Custom Dashboards: Include in tailored reports and visualizations