Tasks completed: 2/2
- Create MLS sport module with 30 hardcoded stadiums
- Integrate MLS module with scrape_schedules.py
SUMMARY: .planning/phases/2.1-add-stadium-data-mls-wnba-nwsl-cbb/02.1-01-SUMMARY.md
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add 02-02-SUMMARY.md documenting pipeline regeneration
- Update STATE.md: Phase 2 complete, next is Phase 2.1
- Update ROADMAP.md: Mark Phase 2 as complete (2/2 plans)
- Performance: 5 plans, 37 min total, 7.4 min average
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Added year_opened field to stadium data across all 4 sport modules:
- MLB: 30 ballparks (1912-2023)
- NBA: 30 arenas (1968-2024)
- NHL: 32 arenas (1968-2021)
- NFL: 30 stadiums (1924-2020)
Updated Stadium object creation in all modules to pass year_opened.
Stadium dataclass already supported the field.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Phase 2: Stadium Foundation
- 2 plans created
- 5 total tasks defined
- Ready for execution
Plan 02-01: Audit & complete hardcoded stadium data
Plan 02-02: Regenerate canonical data and verify pipeline
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Create 01-03-SUMMARY.md documenting NFL module and orchestrator refactor
- Update STATE.md: Phase 1 complete, ready for Phase 2
- Update ROADMAP.md: Mark Phase 1 as complete (3/3 plans)
- Phase 1 total duration: 23 min across 3 plans
Phase 1: Script Architecture complete. All 4 core sports (MLB, NBA, NHL, NFL)
now have dedicated modules with consistent patterns.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Fix data quality issues across MLB, NBA, NHL, NFL with correct game→team→stadium canonical linking.
Creates PROJECT.md with requirements and constraints.
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>