[ANALYTICS]
What affects your merge time?
Real data from 300k+ pull requests across 8k+ contributors. See how PR size, team size, and using Greptile affects your merge velocity.
[PR SIZE ANALYSIS]
Size Matters
How PR size, lines changed, and team size affect merge times
PR Size vs Merge Time
Lines Changed vs Merge TimeCalculation: Median merge time by lines changed bucket.
What it shows: PRs over 500 lines have high risk of getting stuck. Files changed is often the strongest predictor of review time, not just lines of code.
What it shows: PRs over 500 lines have high risk of getting stuck. Files changed is often the strongest predictor of review time, not just lines of code.
Commits per PR vs Merge TimeCalculation: Median hours to merge vs number of commits per PR, with PR count distribution.
What it shows: Granularity directly impacts speed. Single-commit PRs average 17.7 hours, while 25+ commit PRs take 155 hours. Aim for 1-5 commits per PR.
What it shows: Granularity directly impacts speed. Single-commit PRs average 17.7 hours, while 25+ commit PRs take 155 hours. Aim for 1-5 commits per PR.
Files Changed vs Merge TimeCalculation: Median hours to merge vs number of files changed, with median lines changed per file. Dual-axis chart shows both time and complexity metrics.
What it shows: Files changed is often the strongest predictor of review time, more so than total lines. Each additional file adds coordination overhead and review complexity.
What it shows: Files changed is often the strongest predictor of review time, more so than total lines. Each additional file adds coordination overhead and review complexity.
Addition vs Deletion Impact on Merge TimeCalculation: Median merge time by addition/deletion ratio. Includes pure additions, pure deletions, and all ratios in between.
What it shows: Addition-heavy PRs take longer to review than deletion-heavy PRs. Pure additions are the slowest, while deletion-focused refactoring tends to merge faster.
What it shows: Addition-heavy PRs take longer to review than deletion-heavy PRs. Pure additions are the slowest, while deletion-focused refactoring tends to merge faster.
Break Up Large PRs
Keep PRs under 500 lines to avoid the exponential time penalty
Optimize Commit Granularity
Aim for 1-5 commits per PR for faster reviews
Limit Files Changed
Files changed is the strongest predictor of review time
How Greptile Helps
AI reviews large PRs 5x faster, reducing size penalties
[TEAM COMPLEXITY ANALYSIS]
Team Size Impact on Merge Time
How team size and coordination overhead affect merge velocity
Team Size vs Merge Time
Coordination Overhead AnalysisCalculation: Overhead % = ((Team time - Baseline time) / Baseline time) × 100. Baseline is single-author PRs.
What it shows: How much additional time is added due to coordination complexity. Greptile scales teams without proportional slowdown, making large team collaboration more efficient.
What it shows: How much additional time is added due to coordination complexity. Greptile scales teams without proportional slowdown, making large team collaboration more efficient.
Limit Team Size
Keep PR authors under 10 to minimize coordination overhead
Streamline Reviews
Use clear review guidelines to reduce back-and-forth
Set Time Limits
Establish review time expectations for faster feedback
How Greptile Helps
Reduces coordination overhead from 98% to 55% for large teams
[CONTRIBUTOR ANALYSIS]
Where Do You Stand?
See how your contribution patterns compare to the community
PR Distribution by ComplexityCalculation: PRs categorized by complexity (lines + files + commits), showing percentage distribution and average metrics per complexity level.
What it shows: Most PRs are simple (≤100 lines, ≤5 files). Complex PRs are rare but take exponentially longer. Benchmark your team against these industry patterns.
What it shows: Most PRs are simple (≤100 lines, ≤5 files). Complex PRs are rare but take exponentially longer. Benchmark your team against these industry patterns.
What makes you a heavy contributor?Calculation: Based on PR count percentiles from 8756+ contributors. Shows where you stand in the distribution of code contributions.
What it shows: Your contribution tier based on PR frequency. Higher tiers indicate more significant code impact and influence on the codebase.
What it shows: Your contribution tier based on PR frequency. Higher tiers indicate more significant code impact and influence on the codebase.