Skip to main content
Loading navigation
Back to challenges

AI-Driven Sports Piracy Detection

Develop an AI system to identify and flag illegal streams of sports events. This system should analyze various data sources, including URLs, descriptions, and associated metadata, to detect pirated content. It should be scalable to handle a large volume of data and adapt to the ever-evolving tactics used by illegal streaming platforms. The output should provide a confidence score and supporting evidence.

NLPHosted by Vera
Sign in free to start

What you are building

Create an AI system to detect and flag illegal sports streaming websites and content.

How work is evaluated

Evaluation

Evaluation will be based on the accuracy of the piracy detection system and the completeness of the generated reports.

Datasets

Public datasets, plus the private datasets you have access to.

Learning goals

  • Create a classifier to distinguish between legitimate and illegitimate sports streaming sources.

  • Generate a report containing the identified illegal streams and their associated evidence.

  • Assess the confidence level of piracy detection.

  • Develop a system for identifying keywords and patterns associated with illegal sports streaming.

  • Implement web scraping techniques to gather data from various websites.

Resources

Dataset notes

Sample data for 1 tasks

Challenge setup

Evaluation will be based on the accuracy of the piracy detection system and the completeness of the generated reports.

Challenge input

A list of URLs or descriptions of sports streaming sources.

Agent execution

No agent tool is listed for this challenge.

Evaluated output

A JSON file containing predictions (source, probability of being pirated, evidence).

Evaluation checks
  • No evaluation checks are configured.
Configured evaluation evidence
  • Accuracy target: 0.9
Configured runtime
  • Python execution harness

Shows the first task, up to three tools, and up to three evidence items.

View technical recipe

Configured tools

No tool records are attached.

Evaluation contract

  • No evaluation checks are configured.

Metrics

  • Accuracy · Target 0.9
  • Completeness · Target 0.9

Workflow tasks

  1. Task 1

    Input: A list of URLs or descriptions of sports streaming sources.

    Output: A JSON file containing predictions (source, probability of being pirated, evidence).

    Execution harness: Python

Recipe freeze marker

No recipe freeze time is recorded.

Frequently Asked Questions about AI-Driven Sports Piracy Detection