Sportstime/.planning/phases/02-stadium-foundation/02-01-PLAN.md

phase, plan, type

phase	plan	type
02-stadium-foundation	01	execute

Audit and complete hardcoded stadium data across all 4 sport modules.

Purpose: Ensure all sport modules have complete, accurate stadium data that will flow through the canonicalization pipeline. Output: All 4 sport modules with complete stadium data (city, state, lat/lng, capacity, year_opened, teams).

<execution_context> ~/.claude/get-shit-done/workflows/execute-phase.md ~/.claude/get-shit-done/templates/summary.md </execution_context>

@.planning/PROJECT.md @.planning/ROADMAP.md @.planning/STATE.md @.planning/phases/01-script-architecture/01-03-SUMMARY.md

Key files: @Scripts/mlb.py @Scripts/nba.py @Scripts/nhl.py @Scripts/nfl.py

Current state:

• MLB, NBA, NHL, NFL modules have hardcoded stadium data with city, state, lat/lng, capacity, teams
• Missing field: year_opened (null in all canonical data)
• NFL module created in Phase 1 Plan 03 with 30 hardcoded stadiums
• Bundled stadiums_canonical.json has incomplete data (state="", capacity=0, missing NFL)

Expected stadium counts:

• MLB: 30 stadiums (30 teams)
• NBA: 30 stadiums (30 teams)
• NHL: 32 stadiums (32 teams)
• NFL: 30 stadiums (32 teams, 2 shared: SoFi Stadium, MetLife Stadium)

Stadium data structure: Each module has scrape_{sport}_stadiums_hardcoded() returning Stadium objects with:

• name, city, state, lat/lng, capacity, teams
• Missing: year_opened for filtering historical/renamed venues

Task 1: Audit stadium data completeness across all 4 sport modules Scripts/mlb.py, Scripts/nba.py, Scripts/nhl.py, Scripts/nfl.py 1. Read each sport module's hardcoded stadium function 2. Create audit report listing for each sport: - Stadium count (should match expected) - Fields present/missing - Any stadiums with missing lat/lng (should be 0) - Any stadiums with missing capacity (should be 0) 3. Identify gaps: stadiums missing from lists, incorrect coordinates, missing teams

Do NOT modify any files in this task - audit only. The goal is to understand current state before making changes. Print audit summary showing stadium counts per sport and any data quality issues found Audit report shows MLB:30, NBA:30, NHL:32, NFL:30 stadiums with all required fields documented

Task 2: Add year_opened to all hardcoded stadiums Scripts/mlb.py, Scripts/nba.py, Scripts/nhl.py, Scripts/nfl.py Add year_opened to each stadium's hardcoded data. Use the actual opening year for each venue:

MLB stadiums (sample):

• Fenway Park: 1912
• Wrigley Field: 1914
• Dodger Stadium: 1962
• Globe Life Field: 2020

NBA arenas (sample):

• TD Garden: 1995
• Madison Square Garden: 1968
• Chase Center: 2019
• Intuit Dome: 2024

NHL arenas: Many share with NBA - verify and match

NFL stadiums (sample):

• Lambeau Field: 1957
• SoFi Stadium: 2020
• Allegiant Stadium: 2020

For each module:

1. Update the hardcoded dict to include 'year_opened' key
2. Update Stadium object creation to include year_opened parameter
3. Ensure Stadium dataclass in core.py has year_opened field (verify first)

Research actual opening years from Wikipedia if unsure. Use the original opening year, not renovation years. Run python -c "from mlb import scrape_mlb_stadiums; s=scrape_mlb_stadiums(); print(f'MLB: {len(s)} stadiums, year_opened example: {s[0].year_opened if hasattr(s[0], \"year_opened\") else \"MISSING\"}')" for each sport All 4 sport modules have year_opened in hardcoded data, Stadium objects include year_opened field

Before declaring plan complete: - [ ] Audit confirms expected stadium counts: MLB:30, NBA:30, NHL:32, NFL:30 - [ ] All 4 modules have year_opened in hardcoded stadium data - [ ] No Python syntax errors in any module - [ ] Stadium dataclass supports year_opened field

<success_criteria>

• Task 1: Audit complete with documented counts and any gaps identified
• Task 2: year_opened added to all hardcoded stadiums in all 4 modules
• No import errors when loading modules
• Ready for Plan 02 (pipeline regeneration) </success_criteria>

After completion, create `.planning/phases/02-stadium-foundation/02-01-SUMMARY.md`:

Phase 2 Plan 01: Stadium Data Audit & Completion Summary

[Substantive one-liner]

Accomplishments

• [Stadium counts verified]
• [year_opened added to all modules]

Files Created/Modified

• Scripts/mlb.py - Added year_opened
• Scripts/nba.py - Added year_opened
• Scripts/nhl.py - Added year_opened
• Scripts/nfl.py - Added year_opened

Decisions Made

[Any gaps found and how resolved]

Issues Encountered

[Any data issues discovered]

Next Step

Ready for 02-02-PLAN.md (pipeline regeneration)