feat(02.1-03): integrate NWSL module with scrape_schedules.py

Update scrape_schedules.py to import NWSL stadium functionality from nwsl.py:
- Add import for NWSL_TEAMS, get_nwsl_team_abbrev, scrape_nwsl_stadiums
- Remove inline NWSL_TEAMS dict (now imported from nwsl.py)
- Remove stub scrape_nwsl_stadiums function (now using module implementation)
- Update docstrings and comments to reflect module structure

Stadium scraping now uses modules for all secondary sports:
- MLS: 30 stadiums from mls.py
- WNBA: 13 arenas from wnba.py
- NWSL: 13 stadiums from nwsl.py

Only CBB remains inline (350+ D1 teams requires separate scoped phase).

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

Scripts/scrape_schedules.py

@@ -8,8 +8,11 @@ This script coordinates scraping across sport-specific modules:
 - nba.py: NBA scrapers
 - nhl.py: NHL scrapers
 - nfl.py: NFL scrapers
+- mls.py: MLS stadiums
+- wnba.py: WNBA stadiums
+- nwsl.py: NWSL stadiums
 
-Non-core sports (WNBA, MLS, NWSL, CBB) remain inline pending extraction.
+CBB (College Basketball) remains inline pending extraction (350+ D1 teams).
 
 Usage:
     python scrape_schedules.py --sport nba --season 2026
@@ -79,35 +82,18 @@ from wnba import (
     scrape_wnba_stadiums,
     WNBA_STADIUM_SOURCES,
 )
-
-
-# =============================================================================
-# NON-CORE SPORT TEAM MAPPINGS
-# TODO: Extract to separate modules (nwsl.py, cbb.py)
-# NOTE: MLS_TEAMS is now imported from mls.py
-# NOTE: WNBA_TEAMS is now imported from wnba.py
-# =============================================================================
-
-NWSL_TEAMS = {
-    'LA': {'name': 'Angel City FC', 'city': 'Los Angeles', 'stadium': 'BMO Stadium'},
-    'SJ': {'name': 'Bay FC', 'city': 'San Jose', 'stadium': 'PayPal Park'},
-    'CHI': {'name': 'Chicago Red Stars', 'city': 'Bridgeview', 'stadium': 'SeatGeek Stadium'},
-    'HOU': {'name': 'Houston Dash', 'city': 'Houston', 'stadium': 'Shell Energy Stadium'},
-    'KC': {'name': 'Kansas City Current', 'city': 'Kansas City', 'stadium': 'CPKC Stadium'},
-    'NJ': {'name': 'NJ/NY Gotham FC', 'city': 'Harrison', 'stadium': 'Red Bull Arena'},
-    'NC': {'name': 'North Carolina Courage', 'city': 'Cary', 'stadium': 'WakeMed Soccer Park'},
-    'ORL': {'name': 'Orlando Pride', 'city': 'Orlando', 'stadium': 'Inter&Co Stadium'},
-    'POR': {'name': 'Portland Thorns FC', 'city': 'Portland', 'stadium': 'Providence Park'},
-    'SEA': {'name': 'Seattle Reign FC', 'city': 'Seattle', 'stadium': 'Lumen Field'},
-    'SD': {'name': 'San Diego Wave FC', 'city': 'San Diego', 'stadium': 'Snapdragon Stadium'},
-    'UTA': {'name': 'Utah Royals FC', 'city': 'Sandy', 'stadium': 'America First Field'},
-    'WAS': {'name': 'Washington Spirit', 'city': 'Washington', 'stadium': 'Audi Field'},
-}
+from nwsl import (
+    NWSL_TEAMS,
+    get_nwsl_team_abbrev,
+    scrape_nwsl_stadiums,
+    NWSL_STADIUM_SOURCES,
+)
 
 
 # =============================================================================
 # NON-CORE SPORT SCRAPERS
-# TODO: Extract to separate modules (wnba.py, mls.py, nwsl.py, cbb.py)
+# NOTE: MLS, WNBA, NWSL stadiums are now imported from their respective modules
+# TODO: Extract CBB to separate module (350+ D1 teams requires separate scoped phase)
 # =============================================================================
 
 def _scrape_espn_schedule(sport: str, league: str, season: int, date_range: tuple[str, str]) -> list[Game]:
@@ -373,21 +359,12 @@ def scrape_cbb_cbssports(season: int) -> list[Game]:
 
 # =============================================================================
 # NON-CORE STADIUM SCRAPERS
-# TODO: Extract to separate modules (nwsl.py, cbb.py)
 # NOTE: scrape_mls_stadiums() is now imported from mls.py
 # NOTE: scrape_wnba_stadiums() is now imported from wnba.py
+# NOTE: scrape_nwsl_stadiums() is now imported from nwsl.py
+# TODO: Extract CBB to separate module (350+ D1 teams requires separate scoped phase)
 # =============================================================================
 
-def scrape_nwsl_stadiums() -> list[Stadium]:
-    """Fetch NWSL stadium data (hardcoded)."""
-    print("\nNWSL STADIUMS")
-    print("-" * 40)
-    stadiums = []
-    # Would include NWSL stadium data here
-    print(f"  Found {len(stadiums)} NWSL stadiums")
-    return stadiums
-
-
 def scrape_cbb_stadiums() -> list[Stadium]:
     """Fetch College Basketball arena data."""
     print("\nCBB STADIUMS")