NBA Basketball Video Labeling Contributor

About OpenTrain

OpenTrain AI is the hiring and contracting organization for this remote AI training role. OpenTrain helps people start and build careers in the fast-growing field of AI training and data labeling, where human contributors prepare the examples AI systems learn from.

• Create an OpenTrain account for free.
• Apply through OpenTrain for remote AI training opportunities.

About AI Training Work

AI training, also called data labeling or data annotation, is the human work behind modern artificial intelligence. Contributors label video, images, audio, text, and other information so AI systems can learn to recognize patterns and understand real-world activity.

• Remote work completed with an internet-connected computer or device.
• Flexible projects can fit around studies, another job, or family responsibilities.
• Attention to detail helps produce reliable training data.

The Role

As an NBA basketball video labeling contributor, you will watch full NBA games either live or within a couple of hours after they air. You will record specific in-game events and the exact quarter and game-clock information for each event in a provided template.

Examples of events include free throws, three-pointers, rebounds, and turnovers. Each entry should identify the player involved, the event type, the quarter, and the time remaining on the game clock.

• Entry-level contractor and part-time opportunity.
• Less than 20 hours per week.
• Worldwide remote participation.
• English-language work.
• Video action-recognition labeling using internal tooling.

What You'll Do

You will review NBA game footage and enter structured event data as the action occurs. The work requires careful attention to player identity, basketball action, quarter, and clock time so each label accurately reflects what happened in the game.

• Watch required NBA games live or shortly after they air.
• Identify the player involved in each relevant event.
• Classify the event, such as a free throw, three-pointer, rebound, or turnover.
• Record the quarter and game-clock time.
• Enter information using the provided template and instructions.

Requirements

This role is designed for someone familiar with basketball and its rules who can follow a consistent labeling process while watching complete games. No prior professional data-labeling experience is listed as required.

• Familiarity with the rules of basketball.
• Ability to watch full NBA games live or within a couple of hours after broadcast.
• Ability to accurately record events and timing information.
• Availability for less than 20 hours per week.

Compensation And Viewing Access

The listing advertises a $50 payment plus a paid streaming subscription, such as League Pass or YouTube TV, so you can watch the required NBA games. Compensation is also specified at $0.20 per label.

• Per-label compensation: $0.20 USD.
• Listed payment: $50.
• Paid streaming subscription provided for required NBA viewing.
• Contractor, part-time engagement.

Why This Work Matters

By labeling basketball actions and their precise timing, you help create structured examples that can support AI systems working with sports video. This is an accessible way to participate in the cutting edge of AI development while building experience in video annotation.

• Contribute to AI training through real-world sports footage.
• Use basketball knowledge in a focused data-labeling project.
• Work remotely with a flexible part-time schedule.

How To Apply

Review the opportunity through OpenTrain and submit your application through the platform. If selected, you will receive the project instructions, examples, template, and access details needed to begin labeling.

• Apply through OpenTrain.
• Review the labeling instructions and examples.
• Confirm that you can watch full required NBA games.
• Complete accurate event labels using the provided workflow.