Seasonal Patterns in Sprint Velocity
Analyze how holidays, summer vacations, Q4 freezes, and annual events create predictable velocity dips. Learn to plan around seasonal patterns.
Detailed Explanation
Seasonal Velocity Patterns
Sprint velocity is not constant throughout the year. Predictable events create recurring dips that teams can plan around.
Common Seasonal Dips
January: -10% (new year ramp-up, annual planning)
March-April: -5% (spring break, some holidays)
June-August: -15% (summer vacations, staggered PTO)
November-Dec: -20% (holidays, code freezes, year-end)
Holiday Impact Calculation
A 2-week sprint with 2 public holidays and 1 person on PTO:
Normal capacity: 5 people x 10 days = 50 person-days
Holiday sprint: 5 x 8 days (holidays) - 3 days (PTO) = 37 person-days
Capacity loss: 26%
If normal velocity is 30, expect: 30 x 0.74 = ~22 points
Q4 Code Freeze
Many organizations freeze deployments in November-December:
Pre-freeze sprint: Velocity drops as team rushes to finish
Freeze sprints: Velocity may increase (tech debt, tooling work)
Post-freeze: Velocity dips as team re-engages with feature work
Year-Over-Year Analysis
Track velocity by quarter over multiple years to identify recurring patterns:
Q1 Q2 Q3 Q4
2024: 28 32 27 24
2025: 30 33 28 25
Pattern: Q2 is strongest, Q4 is weakest
Planning Around Seasons
- Reduce sprint commitments proactively during known low-capacity periods
- Front-load Q1 and Q2 with high-priority features
- Use Q4 freezes for tech debt, documentation, and tooling improvements
- Communicate seasonal forecasts to stakeholders in advance
Key Takeaway
Seasonal dips are normal and predictable. Planning for them (rather than being surprised) builds trust with stakeholders and prevents team burnout during holidays.
Use Case
Use this analysis when creating annual roadmaps, setting quarterly OKRs, or explaining velocity dips during holiday seasons to management.