Generate canonical games with team/stadium links for 5760 games across
NBA, MLB, NHL, NFL, and MLS.
Added missing team aliases:
- NFL WSH -> team_nfl_was (Washington Commanders)
- MLS NY -> team_mls_nyrb (NY Red Bulls)
- MLS ATX -> team_mls_aus (Austin FC)
Remaining 8 warnings are expected NFL playoff placeholders (TBD/AFC/NFC).
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Import WNBA_TEAMS from wnba module
- Add WNBA_DIVISIONS dict (single league structure, no divisions)
- Add WNBA to sport_mappings for team canonicalization
- Update arena_key to use 'arena' for WNBA (like NBA/NHL)
- Add WNBA team abbreviation aliases (LV, LAS, NYL, PHX, etc.)
- Add WNBA stadium aliases (Michelob Ultra Arena, Gateway Center, etc.)
Total teams: 167 (13 WNBA teams added)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add NFL entries to HISTORICAL_STADIUM_ALIASES dict:
- Caesars Superdome (Mercedes-Benz, Louisiana Superdome)
- Paycor Stadium (Paul Brown Stadium)
- Empower Field at Mile High (Broncos Stadium, Sports Authority, Invesco, Mile High)
- Acrisure Stadium (Heinz Field)
- EverBank Stadium (TIAA Bank, Alltel, Jacksonville Municipal)
- Northwest Stadium (FedExField, Jack Kent Cooke)
- Hard Rock Stadium (Sun Life, Land Shark, Dolphin, Pro Player, Joe Robbie)
- Highmark Stadium (Bills Stadium, New Era, Ralph Wilson, Rich Stadium)
- GEHA Field at Arrowhead Stadium (Arrowhead Stadium)
- AT&T Stadium (Cowboys Stadium)
- Lumen Field (CenturyLink, Qwest, Seahawks Stadium)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add NFL entries to TEAM_ABBREV_ALIASES dict:
- Historical relocations: OAK→LV, SD→LAC, STL→LAR
- Common 3-letter variations: JAC, GNB, KAN, NWE, NOR, TAM, SFO
- Direct match for WAS included for completeness
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Add NFL support to canonicalize_teams.py:
- Import NFL_TEAMS from scrape_schedules
- Add NFL_DIVISIONS dict with all 32 teams mapped to conference/division
- Include NFL in sport_mappings for canonicalization
- Add NFL_DIVISIONS to division_map lookup
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Current focus: Phase 3 - Alias Systems
- Phase planned, ready for execution
- Next action: Execute 03-01-PLAN.md
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Phase 03: Alias Systems
- 2 plans created
- 6 total tasks defined
- Ready for execution
Plan 1: Add NFL to canonicalization pipeline with aliases
Plan 2: Add MLS, WNBA, NWSL to canonicalization pipeline
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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>
Create nwsl.py following the established sport module pattern:
- 13 NWSL teams matching current 2025 season roster
- All 13 stadiums with complete data (capacity, year_opened, coordinates)
- Cross-referenced MLS coordinates for shared stadiums (10 shared with MLS)
- 3 NWSL-specific stadiums: SeatGeek Stadium, CPKC Stadium, WakeMed Soccer Park
Module exports:
- NWSL_TEAMS dict
- get_nwsl_team_abbrev() function
- scrape_nwsl_stadiums_hardcoded() function
- scrape_nwsl_stadiums() function with fallback system
- NWSL_STADIUM_SOURCES configuration
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
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 complete MLS stadium data following established sport module pattern:
- 30 MLS stadiums with capacity (soccer configuration) and year_opened
- MLS_TEAMS dict with all 30 teams
- get_mls_team_abbrev() function for team abbreviation lookup
- scrape_mls_stadiums_hardcoded() as primary source
- scrape_mls_stadiums_gavinr() as fallback source
- MLS_STADIUM_SOURCES configuration for fallback system
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>
- Filter bundled JSON to core 4 sports only (152 → 122 stadiums)
- Exclude MLS stadiums (incomplete data, deferred to Phase 2.1)
- Filter aliases to match (200 → 165 aliases)
- All fields populated: no empty state, zero capacity, or null year
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Ran scrape_schedules.py --stadiums-update
- Ran canonicalize_stadiums.py for canonical IDs
- Core sports: MLB:30, NBA:30, NHL:32, NFL:30 (122 total)
- MLS stadiums also included from comprehensive scrape (30)
- Stadium aliases generated for historical name mappings
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>
Extract NFL scrapers from monolithic scrape_schedules.py into dedicated
sport module following established pattern from nba.py/nhl.py:
- NFL_TEAMS: 32 teams with stadiums
- Game scrapers: ESPN API, Pro-Football-Reference, CBS Sports
- Stadium scrapers: ScoreBot, GeoJSON gist, hardcoded fallback
- NFL_GAME_SOURCES and NFL_STADIUM_SOURCES configurations
- get_nfl_season_string() for cross-calendar-year format (2025-26)
- scrape_nfl_games() convenience function with fallback
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- MLB_TEAMS dictionary with all 30 teams
- Game scrapers: Baseball-Reference, MLB Stats API, ESPN
- Stadium scrapers: MLBScoreBot, GeoJSON, hardcoded fallback
- MLB_GAME_SOURCES and MLB_STADIUM_SOURCES configurations
- scrape_mlb_games() convenience function
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>
- Add RegionMapSelector UI for geographic trip filtering (East/Central/West)
- Add RouteFilters module for allowRepeatCities preference
- Improve GameDAGRouter to preserve route length diversity
- Routes now grouped by city count before scoring
- Ensures 2-city trips appear alongside longer trips
- Increased beam width and max options for better coverage
- Add TripOptionsView filters (max cities slider, pace filter)
- Remove TravelStyle section from trip creation (replaced by region selector)
- Clean up debug logging from DataProvider and ScenarioAPlanner
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Fix same-day different-city validation in C2C routes (no more impossible
games like Detroit 7:30pm AND Milwaukee 8pm on the same day)
- Cap C2C trips at 14 days max with 3 middle stops, prefer shortest routes
- Add sport icon and name to game rows in trip itinerary
- Add horizontal scroll to route dots in suggested trip cards
- Allow swipe-to-dismiss on home sheet (trip planner still blocks)
- Generate travel segments for suggested trips
- Increase DAG route lookahead to 5 days for multi-day drives
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add local canonicalization pipeline (stadiums, teams, games) that generates
deterministic canonical IDs before CloudKit upload
- Fix CanonicalSyncService to use deterministic UUIDs from canonical IDs
instead of random UUIDs from CloudKit records
- Add SyncStadium/SyncTeam/SyncGame types to CloudKitService that preserve
canonical ID relationships during sync
- Add canonical ID field keys to CKModels for reading from CloudKit records
- Bundle canonical JSON files (stadiums_canonical, teams_canonical,
games_canonical, stadium_aliases) for consistent bootstrap data
- Update BootstrapService to prefer canonical format files over legacy format
This ensures all entities use consistent deterministic UUIDs derived from
their canonical IDs, preventing duplicate records when syncing CloudKit
data with bootstrapped local data.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add CKStadiumAlias model for CloudKit record mapping
- Add fetchStadiumAliases/fetchStadiumAliasChanges to CloudKitService
- Add syncStadiumAliases to CanonicalSyncService for delta sync
- Add subscribeToStadiumAliasUpdates for push notifications
- Update cloudkit_import.py with --stadium-aliases-only option
Data Architecture Updates:
- Remove obsolete provider files (CanonicalDataProvider, CloudKitDataProvider, StubDataProvider)
- AppDataProvider now reads exclusively from SwiftData
- Add background CloudKit sync on app startup (non-blocking)
- Document data architecture in CLAUDE.md
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Add autocomplete suggestions for Home/Away team fields filtered by selected sport
- Apply themed background to StadiumVisitSheet and StadiumPickerSheet
- Add listRowBackground for consistent card styling in Form sections
- Fix data observation with @ObservedObject for AppDataProvider
- Clear team names when sport selection changes
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Stadium Progress & Achievements:
- Add StadiumVisit and Achievement SwiftData models
- Create Progress tab with interactive map view
- Implement photo-based visit import with GPS/date matching
- Add achievement badges (count-based, regional, journey)
- Create shareable progress cards for social media
- Add canonical data infrastructure (stadium identities, team aliases)
- Implement score resolution from free APIs (MLB, NBA, NHL stats)
UI Improvements:
- Add ThemedSpinner and ThemedSpinnerCompact components
- Replace all ProgressView() with themed spinners throughout app
- Fix sport selection state not persisting when navigating away
Bug Fixes:
- Fix Coast to Coast trips showing only 1 city (validation issue)
- Fix stadium progress showing 0/0 (filtering issue)
- Remove "Stadium Quest" title from progress view
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
- Document Export layer (PDFGenerator, asset services)
- Add iOS 26 API notes (deprecated CLGeocoder, Swift 6 patterns)
- Add Documentation section pointing to docs/
- Expand Future Phases with market research findings (bucket list, group coordination, fan community)
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
Competitive analysis and feature recommendations for sports road trip planning,
including stadium bucket list tracking, AI planning, and group coordination.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
