SportsTime

An iOS app for planning multi-stop sports road trips across North America. Plan your ultimate stadium-hopping adventure with intelligent route optimization, real-time game schedules, and detailed trip itineraries.

Features

• Multi-Sport Trip Planning - Plan trips across 7 professional leagues
• Three Planning Modes
  • By Date Range - Find the best games within your travel window
  • By Must-See Games - Build a trip around specific matchups you want to attend
  • By Cities - Select departure/arrival cities and discover games along the route
• Intelligent Route Optimization - TSP solver optimizes multi-stop routes for minimum travel time
• Driving Constraints - Respects max daily driving hours and number of drivers
• Offline-First - Works without internet using locally cached schedule data
• PDF Export - Generate detailed trip itineraries with maps, stadium info, and nearby attractions
• Stadium Tracking - Track which stadiums you've visited across all leagues

Supported Leagues

League	Sport	Season
MLB	Baseball	March - October
NBA	Basketball	October - June
NHL	Hockey	October - June
NFL	Football	September - February
MLS	Soccer	February - December
WNBA	Basketball	May - October
NWSL	Soccer	March - November

Requirements

• iOS 26.0+
• Xcode 26.0+
• Swift 6.0+

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/SportsTime.git
   cd SportsTime
   

2. Open the project in Xcode:

   open SportsTime.xcodeproj
   

3. Build and run on simulator or device.

Project Structure

SportsTime/
├── SportsTime/                 # Main app target
│   ├── Core/                   # Data layer
│   │   ├── Models/
│   │   │   ├── Domain/         # Pure Swift structs (Trip, Game, Stadium, Team)
│   │   │   ├── CloudKit/       # CKRecord wrappers
│   │   │   └── Local/          # SwiftData models
│   │   └── Services/           # CloudKit, Location services
│   ├── Planning/               # Domain layer - trip planning logic
│   │   └── Engine/             # TripPlanningEngine, RouteOptimizer, etc.
│   ├── Features/               # Presentation layer - SwiftUI views
│   │   ├── Home/
│   │   ├── Trip/
│   │   ├── Schedule/
│   │   ├── Progress/
│   │   └── Settings/
│   ├── Export/                 # PDF generation
│   └── Resources/              # Bundled JSON data
├── SportsTimeTests/            # Unit tests
├── Scripts/                    # Python data pipeline
│   └── sportstime_parser/      # Schedule scraping & CloudKit upload
├── data/                       # Local data files
└── docs/                       # Documentation

Architecture

Clean MVVM with feature-based modules and offline-first data architecture.

Three-Layer Architecture

1. Presentation Layer (Features/) - SwiftUI Views + @Observable ViewModels
2. Domain Layer (Planning/) - Trip planning algorithms
3. Data Layer (Core/) - Models and services

Data Flow

AppDataProvider.shared (Single Source of Truth)
         │
         ├── Bundled JSON (bootstrap on first launch)
         ├── SwiftData (local persistence)
         └── CloudKit (background sync)

All schedule data flows through AppDataProvider.shared - never access CloudKit or SwiftData directly for canonical data.

Development

Build

xcodebuild -project SportsTime.xcodeproj \
  -scheme SportsTime \
  -destination 'platform=iOS Simulator,name=iPhone 17,OS=26.2' \
  build

Run Tests

# All tests
xcodebuild -project SportsTime.xcodeproj \
  -scheme SportsTime \
  -destination 'platform=iOS Simulator,name=iPhone 17,OS=26.2' \
  test

# Specific test suite
xcodebuild -project SportsTime.xcodeproj \
  -scheme SportsTime \
  -destination 'platform=iOS Simulator,name=iPhone 17,OS=26.2' \
  -only-testing:SportsTimeTests/EdgeCaseTests \
  test

Data Pipeline

The Python pipeline scrapes schedules from multiple sources and uploads to CloudKit:

cd Scripts
pip install -r requirements.txt
python -m sportstime_parser scrape --sport all --season 2026
python -m sportstime_parser upload --sport all

Test Suite

124 tests across 11 phases covering:

• Trip planning engine (all 3 scenarios)
• Route optimization (TSP solver)
• Travel estimation
• Game filtering and matching
• Edge cases and boundary conditions
• Concurrency behavior

Documentation

• CLAUDE.md - Development guidelines and architecture details
• ARCHITECTURE.md - Detailed system architecture
• docs/TEST_PLAN.md - Test suite documentation
• docs/MARKET_RESEARCH.md - Competitive analysis

License

MIT License - see LICENSE file for details.