Skip to main content

The csa_prediction_engine library provides a suite of tools and functions for performing relevance-based predictions using the Cambridge Sports Analytics Prediction Engine API. The package is designed to facilitate single and multi-task predictions, allowing for flexible model evaluation and experimentation.

Project description

Cambridge Sports Analytics Prediction Engine

The CSA Prediction Engine is the official Python client for interacting with the Cambridge Sports Analytics (CSA) API. It enables relevance-based predictions using flexible configurations, including support for batch jobs, grid evaluations, and multi-task prediction workflows.

📦 Source code: github.com/CambridgeSportsAnalytics/csa_prediction_engine

🔍 Key Features

  • Single Task Predictions: Support for predictions with one dependent variable and one set of circumstances.
  • Multi-y Predictions: Perform predictions with multiple dependent variables and a single set of circumstances.
  • Multi-theta Predictions: Perform predictions with one dependent variable and multiple sets of circumstances.
  • Relevance-Based Grid Predictions: Generate optimal predictions by evaluating all thresholds and variable combinations.
  • Grid Singularity Predictions: Analyze grid predictions to find the singular optimal solution.
  • MaxFit Predictions: Find the best-fit model based on adjusted relevance.

🚀 Installation

Install via PyPI:

pip install csa-prediction-engine

Requires Python 3.11

📘 Documentation & Examples

For example scripts, OpenAPI specs, and quickstart usage, visit the companion repo: 👉 CSA Prediction Engine Quickstart

🤝 Contributing

We welcome feedback, feature suggestions, and bug reports. Reach out to our team 📧 support@csanalytics.io

⚖️ License

Copyright c) 2023 - 2025 Cambridge Prediction Analytics, LLC. All rights reserved.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

csa_prediction_engine-2.3.0.tar.gz (23.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

csa_prediction_engine-2.3.0-py3-none-any.whl (61.6 kB view details)

Uploaded Python 3

File details

Details for the file csa_prediction_engine-2.3.0.tar.gz.

File metadata

  • Download URL: csa_prediction_engine-2.3.0.tar.gz
  • Upload date:
  • Size: 23.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.6

File hashes

Hashes for csa_prediction_engine-2.3.0.tar.gz
Algorithm Hash digest
SHA256 19bdb8a1e3a94bbba8bcd699c55948542aa3e58a0fcf4d8e454dfdc97d307fcc
MD5 d2d4c972313663e46e2fd4d4783ef635
BLAKE2b-256 45b3055813d8ac1b58b2b32e0b79f397d6eda77780fb8099f5d973742ef81199

See more details on using hashes here.

File details

Details for the file csa_prediction_engine-2.3.0-py3-none-any.whl.

File metadata

File hashes

Hashes for csa_prediction_engine-2.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 4f6342a17e0f5bbb88fe2fdbb954abd6ffdb1057b3fbed83aaa91f03db7bd65c
MD5 b7cbfa98aba37ec2b278a930076454e0
BLAKE2b-256 c48d90d70d2238e51fb90ca6adee55c732574e9feab1990fbaf45dac56b76376

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page