Canadian Premier League Analytics Database

The most comprehensive open dataset for the Canadian Premier League (CPL).

Features

• 309+ historical matches (2019-2025)
• Official 2025 standings from CanPL API
• Historical closing odds from major bookmakers (Coming Soon)
• Team metadata with stadium coordinates
• RESTful JSON API
• Free, open data (CC-BY-4.0)

What Makes This Unique?

The most comprehensive open dataset for Canadian Premier League analysis. Perfect for building prediction models, tracking team performance, and research.

What's Included

• Complete match results (2019-2026)
• Team statistics (shots, possession, corners, etc.)
• Historical lineups
• Weather data for every match
• Travel distance calculations
• Historical closing odds (Preview - full data coming soon)

Data Coverage

• Matches: 500+ matches across 7 seasons
• Teams: All 9 CPL clubs (current and historical)
• Updates: Weekly during season
• Quality: Validated against official CPL records

Quick Start

import pandas as pd

# Load all CPL matches
matches = pd.read_csv('data/matches/cpl_2024.csv')

# Filter for Forge FC home matches
forge_home = matches[matches['home_team'] == 'Forge FC']

# Calculate home win percentage
win_pct = (forge_home['home_goals'] > forge_home['away_goals']).mean()
print(f"Forge FC home win rate: {win_pct:.1%}")

Using the Data Loader

from scripts.data_loader import CPLDataLoader

loader = CPLDataLoader()

# Load matches for specific seasons
matches = loader.load_matches(seasons=[2023, 2024])

# Get standings
standings = loader.get_standings(2024)

# Get team form
form = loader.get_recent_form('Forge FC', n_matches=5)

# Head-to-head record
h2h = loader.get_head_to_head('Forge FC', 'Cavalry FC')

API Endpoints

Base URL: https://canadasoccerapi.com

Endpoint	Description
/api/matches	Match results with filtering
/api/standings	League standings by season
/api/teams	Team metadata and coordinates
/api/odds	Historical closing odds (Preview - limited data)

Closing Odds API (Preview)

Note: Historical odds scraping is in development. Currently only 5 matches from the 2024 CPL playoffs are available. Full historical data will be added in a future update.

# Get available 2024 playoff odds (limited)
curl "https://canadasoccerapi.com/api/odds?season=2024"

Response includes:

• closing_home, closing_draw, closing_away - Match result odds
• bookmaker - Currently only betexplorer_avg
• scraped_at - When odds were captured

Project Structure

canpl-analytics/
├── README.md                    # This file
├── schema.sql                   # Database schema
├── data/
│   ├── matches/                 # Match results by season
│   │   ├── cpl_2019.csv
│   │   ├── cpl_2020.csv
│   │   └── ...
│   ├── closing_odds/            # Weekly closing odds
│   │   ├── cpl_2024_closing_odds.csv
│   │   ├── cpl_2025_closing_odds.csv
│   │   └── README.md
│   ├── team_stats/              # Team statistics
│   ├── historical_odds/         # Betting odds history (legacy)
│   └── README.md                # Data dictionary
├── scripts/
│   ├── data_loader.py           # Helper to load data
│   ├── data_validator.py        # Quality checks
│   ├── cpl_results_scraper.py   # Match scraper
│   └── weather_integration.py   # Weather data
├── examples/
│   ├── basic_analysis.ipynb     # Jupyter notebook tutorial
│   └── poisson_model.py         # Example betting model
├── docs/
│   ├── data_dictionary.md       # Field definitions
│   ├── methodology.md           # Data collection methods
│   └── contributing.md          # How to contribute
└── LICENSE

Example Use Cases

1. Betting Models - Build Poisson regression models for match predictions
2. Market Efficiency Analysis - Compare predictions to closing odds
3. Closing Line Value (CLV) - Measure edge by comparing bet prices to closing
4. Performance Analysis - Track team form and trends over time
5. Travel Impact Studies - Quantify away travel disadvantage
6. Weather Effects - Analyze how temperature/rain affects scoring
7. Playoff Predictions - ML models for championship odds

Example: Analyze Closing Odds (Preview)

Note: This example uses limited sample data from 2024 playoffs only.

import pandas as pd
import requests

# Fetch closing odds from API (limited to 2024 playoff data)
response = requests.get('https://canadasoccerapi.com/api/odds?season=2024')
odds = pd.DataFrame(response.json()['odds'])

# Only 5 matches currently available
print(f"Available matches: {len(odds)}")

# Calculate implied probabilities
odds['implied_home'] = 1 / odds['closing_home']
odds['implied_draw'] = 1 / odds['closing_draw']
odds['implied_away'] = 1 / odds['closing_away']

# Calculate bookmaker margin (overround)
odds['margin'] = odds['implied_home'] + odds['implied_draw'] + odds['implied_away'] - 1

print(f"Average margin: {odds['margin'].mean():.1%}")

Example: Simple Prediction Model

from examples.poisson_model import PoissonModel
from scripts.data_loader import load_cpl_matches

# Load and train
matches = load_cpl_matches()
model = PoissonModel()
model.fit(matches)

# Predict match
probs = model.predict_probabilities('Forge FC', 'Cavalry FC')
print(f"Home win: {probs['home_win']:.1%}")
print(f"Draw: {probs['draw']:.1%}")
print(f"Away win: {probs['away_win']:.1%}")

Installation

# Clone the repository
git clone https://github.com/yourusername/canpl-analytics.git
cd canpl-analytics

# Install dependencies
pip install pandas numpy scipy matplotlib seaborn requests beautifulsoup4

# Or use requirements.txt
pip install -r requirements.txt

Data Sources

• CanPL.ca - Official match results
• OneSoccer - Match statistics
• OpenWeatherMap - Weather data
• Public betting markets - Historical odds

Contributing

Found an error? Have additional data? Submit a pull request!

See docs/contributing.md for guidelines.

Ways to Contribute

• Add missing match data
• Improve data quality
• Add new statistics
• Create analysis examples
• Report bugs

License

CC-BY-4.0 - Free to use with attribution.

Acknowledgments

Data sourced from CanPL.ca, OneSoccer, and public betting markets.

Special thanks to the CPL community for supporting open data initiatives.

Contact

Questions? Open an issue or reach out on Twitter.

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