---
phase: 03-alias-systems
plan: 02
type: execute
---

<objective>
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.
</objective>

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

<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
</context>

<tasks>

<task type="auto">
  <name>Task 1: Add MLS to canonicalization pipeline</name>
  <files>Scripts/canonicalize_teams.py, Scripts/canonicalize_games.py, Scripts/canonicalize_stadiums.py</files>
  <action>
    **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'},
    ],
    ```
  </action>
  <verify>python Scripts/canonicalize_teams.py --verbose 2>&1 | grep -E "MLS:|Created.*teams"</verify>
  <done>MLS teams appear in output (29-30 teams depending on expansion), no critical warnings</done>
</task>

<task type="auto">
  <name>Task 2: Add WNBA to canonicalization pipeline</name>
  <files>Scripts/canonicalize_teams.py, Scripts/canonicalize_games.py, Scripts/canonicalize_stadiums.py</files>
  <action>
    **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
    ],
    ```
  </action>
  <verify>python Scripts/canonicalize_teams.py --verbose 2>&1 | grep -E "WNBA:|Created.*teams"</verify>
  <done>WNBA teams appear in output (13 teams), no critical warnings</done>
</task>

<task type="auto">
  <name>Task 3: Add NWSL to canonicalization pipeline</name>
  <files>Scripts/canonicalize_teams.py, Scripts/canonicalize_games.py, Scripts/canonicalize_stadiums.py</files>
  <action>
    **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)
    ],
    ```
  </action>
  <verify>python Scripts/canonicalize_teams.py --verbose 2>&1 | grep -E "NWSL:|Created.*teams"</verify>
  <done>NWSL teams appear in output (13-14 teams), no critical warnings</done>
</task>

</tasks>

<verification>
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)
</verification>

<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>

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