Sportstime/.planning/phases/03-alias-systems/03-02-PLAN.md

phase, plan, type

phase	plan	type
03-alias-systems	02	execute

Add MLS, WNBA, and NWSL to the canonicalization pipeline with alias support.

Purpose: Secondary sports modules exist (Phase 2.1) but aren't integrated into canonicalization, preventing game→team→stadium linking. Output: All three secondary sports canonicalized with team and stadium alias support.

<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/phases/03-alias-systems/03-01-SUMMARY.md

Key source files:

@Scripts/canonicalize_teams.py @Scripts/canonicalize_games.py @Scripts/canonicalize_stadiums.py @Scripts/mls.py @Scripts/wnba.py @Scripts/nwsl.py

Prior decisions:

• MLS uses soccer configuration capacities for shared NFL stadiums
• WNBA cross-references shared arena coordinates from nba.py and nhl.py
• NWSL cross-references shared stadium coordinates from mls.py

Patterns established (from 03-01):

• Team canonicalization: import {SPORT}_TEAMS, add {SPORT}_DIVISIONS dict, include in sport_mappings list
• Game resolution: TEAM_ABBREV_ALIASES dict maps alternate abbrevs to canonical team IDs
• Stadium aliases: HISTORICAL_STADIUM_ALIASES dict maps canonical_id to list of historical names

Task 1: Add MLS to canonicalization pipeline Scripts/canonicalize_teams.py, Scripts/canonicalize_games.py, Scripts/canonicalize_stadiums.py **canonicalize_teams.py:** 1. Update import: add MLS_TEAMS from mls module `from mls import MLS_TEAMS` 2. Add MLS_DIVISIONS dict (MLS uses conferences, not divisions): - Eastern Conference: ATL, CHI, CIN, CLB, CLT, DCU, FCC, MIA, MTL, NE, NYC, NYR, ORL, PHI, TOR → ('mls_eastern', None) - Western Conference: AUS, COL, DAL, HOU, LAF, LAG, MIN, NSH, POR, RSL, SEA, SJE, SKC, STL, VAN → ('mls_western', None) 3. Add ('MLS', MLS_TEAMS) to sport_mappings list

**canonicalize_games.py:**
Add MLS aliases to TEAM_ABBREV_ALIASES:
```python
# MLS
('MLS', 'LA'): 'team_mls_lag',    # LA Galaxy
('MLS', 'LAFC'): 'team_mls_laf',  # LAFC (Los Angeles FC)
('MLS', 'NYCFC'): 'team_mls_nyc', # NYC FC
('MLS', 'RBNY'): 'team_mls_nyr',  # NY Red Bulls
('MLS', 'SJ'): 'team_mls_sje',    # San Jose Earthquakes
('MLS', 'KC'): 'team_mls_skc',    # Sporting KC
('MLS', 'DC'): 'team_mls_dcu',    # DC United
('MLS', 'FCD'): 'team_mls_dal',   # FC Dallas
('MLS', 'MON'): 'team_mls_mtl',   # Montreal
```

**canonicalize_stadiums.py:**
Add MLS stadium historical aliases (recent renames only):
```python
# MLS
'stadium_mls_bmw_stadium': [
    {'alias_name': 'adi stadium', 'valid_from': '2021-07-01', 'valid_until': '2024-01-01'},
],
'stadium_mls_shell_energy_stadium': [
    {'alias_name': 'paypal park', 'valid_from': '2021-01-01', 'valid_until': '2024-06-01'},
    {'alias_name': 'earthquakes stadium', 'valid_from': '2015-03-01', 'valid_until': '2020-12-31'},
    {'alias_name': 'avaya stadium', 'valid_from': '2015-03-01', 'valid_until': '2020-12-31'},
],
'stadium_mls_geodis_park': [
    # Opened 2022, no prior name
],
'stadium_mls_dignity_health_sports_park': [
    {'alias_name': 'stubhub center', 'valid_from': '2013-06-01', 'valid_until': '2019-01-31'},
    {'alias_name': 'home depot center', 'valid_from': '2003-06-01', 'valid_until': '2013-05-31'},
],
```

python Scripts/canonicalize_teams.py --verbose 2>&1 | grep -E "MLS:|Created.*teams" MLS teams appear in output (29-30 teams depending on expansion), no critical warnings Task 2: Add WNBA to canonicalization pipeline Scripts/canonicalize_teams.py, Scripts/canonicalize_games.py, Scripts/canonicalize_stadiums.py **canonicalize_teams.py:** 1. Update import: add WNBA_TEAMS from wnba module `from wnba import WNBA_TEAMS` 2. Add WNBA_DIVISIONS dict (no divisions, just conferences, but map to None): - Single key mapping per team to ('wnba', None) - 13 teams: ATL, CHI, CON, DAL, IND, LVA, LAS, MIN, NYL, PHO, SEA, WAS, GSV 3. Add ('WNBA', WNBA_TEAMS) to sport_mappings list

**canonicalize_games.py:**
Add WNBA aliases to TEAM_ABBREV_ALIASES:
```python
# WNBA
('WNBA', 'LA'): 'team_wnba_las',   # LA Sparks
('WNBA', 'LV'): 'team_wnba_lva',   # Las Vegas Aces
('WNBA', 'NY'): 'team_wnba_nyl',   # New York Liberty
('WNBA', 'PHX'): 'team_wnba_pho',  # Phoenix Mercury
('WNBA', 'CONN'): 'team_wnba_con', # Connecticut Sun
('WNBA', 'WSH'): 'team_wnba_was',  # Washington Mystics
```

**canonicalize_stadiums.py:**
WNBA shares arenas with NBA/NHL, so most aliases already exist. Add WNBA-specific entries if any:
```python
# WNBA (most share NBA arenas, which have existing aliases)
'stadium_wnba_gateway_center_arena': [
    # College Park Center - no historical renames
],
```

python Scripts/canonicalize_teams.py --verbose 2>&1 | grep -E "WNBA:|Created.*teams" WNBA teams appear in output (13 teams), no critical warnings Task 3: Add NWSL to canonicalization pipeline Scripts/canonicalize_teams.py, Scripts/canonicalize_games.py, Scripts/canonicalize_stadiums.py **canonicalize_teams.py:** 1. Update import: add NWSL_TEAMS from nwsl module `from nwsl import NWSL_TEAMS` 2. Add NWSL_DIVISIONS dict (no divisions in NWSL): - 14 teams all map to ('nwsl', None): ANG, CHI, HOU, KC, LOU, NCC, NJY, ORL, POR, RAC, SD, SEA, UTA, WAS 3. Add ('NWSL', NWSL_TEAMS) to sport_mappings list

**canonicalize_games.py:**
Add NWSL aliases to TEAM_ABBREV_ALIASES:
```python
# NWSL
('NWSL', 'LA'): 'team_nwsl_ang',    # Angel City FC (Los Angeles)
('NWSL', 'NC'): 'team_nwsl_ncc',    # North Carolina Courage
('NWSL', 'GOTHAM'): 'team_nwsl_njy', # NJ/NY Gotham FC
('NWSL', 'NY'): 'team_nwsl_njy',    # NJ/NY Gotham FC alt
('NWSL', 'LOU'): 'team_nwsl_lou',   # Louisville (Racing Louisville)
('NWSL', 'RLC'): 'team_nwsl_lou',   # Racing Louisville alt
```

**canonicalize_stadiums.py:**
NWSL shares stadiums with MLS, so most aliases already exist. Add NWSL-specific:
```python
# NWSL
'stadium_nwsl_cpkc_stadium': [
    # Opened 2024, no prior name (first soccer-specific stadium built for NWSL team)
],
```

python Scripts/canonicalize_teams.py --verbose 2>&1 | grep -E "NWSL:|Created.*teams" NWSL teams appear in output (13-14 teams), no critical warnings Before declaring plan complete: - [ ] `python Scripts/canonicalize_teams.py --verbose` shows MLS, WNBA, NWSL teams - [ ] All three secondary sports have abbreviation aliases in canonicalize_games.py - [ ] Stadium aliases added where applicable - [ ] Total team count increased to ~180 (90 core + ~90 secondary)

<success_criteria>

• All tasks completed
• MLS, WNBA, NWSL teams appear in teams_canonical.json output
• Game resolution can handle common abbreviation variations for all sports
• Phase 3 complete (all 7 sports have alias support) </success_criteria>

After completion, create `.planning/phases/03-alias-systems/03-02-SUMMARY.md`: Include final team count by sport, note any warnings or issues encountered.