Use cases · Sports & field operations
Footage tagging and highlight search
Tag game, training or event footage with suggested moments and short descriptions, so coaches and editors search for the clip they need instead of scrubbing through hours of video.
Where it starts
The trigger.
New footage is uploaded after a game, training session or event.
How it runs today
- Finding a moment means scrubbing through hours of footage.
- Tags depend on whoever had time to log the session.
- Good clips are lost because nobody can find them again.
The workflow
Four bounded steps.
Each step has an owner and a stop rule.
- 01 / Ingest
Read new footage and its basic details, such as date, team and session, from approved storage.
- 02 / Suggest
Suggest moments and short descriptions using the tag list the team agreed.
- 03 / Review
A coach or editor accepts, corrects or removes suggested tags.
- 04 / Search
Staff search confirmed tags and jump straight to the moment in the footage.
Where people stay in control
Approval points.
- A coach or editor confirms tags before they are shared outside the team.
- Footage of minors or private sessions follows the organisation’s consent and access rules.
How we would measure it
Against a baseline.
Measured before and after, on the same work.
Time to find a requested clip.
Share of suggested tags accepted without correction.
Footage hours tagged per week.
Related
Go deeper.
Build the missing pieceCustom tools and applications for the gaps that matter.Image vs. video processingWhen a single frame is enough, and when you need motion, sequence and time.Make your footage searchableA four-step playbook to agree a short tag list, suggest tags on new footage, have a coach or editor confirm them and let staff jump straight to the moment they need.How to tag sports footage with AIHow can a team, club or league use computer vision to tag game and training footage so coaches and editors find the clip they need in seconds?
More use cases
Other places to start.
Sports & field operations
Movement and activity analysis from video
Count repetitions, score form or track activity from ordinary video, with results a coach or supervisor can check.
See the workflow Sports & field operationsField inspection photo reports
Turn the photos and notes field crews capture on site into an organized inspection report, with possible issues flagged for a qualified person to confirm.
See the workflow Sports & field operationsVenue occupancy and crowd flow
Count people entering, leaving and gathering in areas of a venue from existing cameras, without identifying anyone, so staff can open gates, move people and plan staffing.
See the workflowAn illustrative workflow pattern, not a result from a specific customer.
Bring the messy version
One workflow.
A better way to run it.
Show us the tools, the handoffs, and the part that keeps slowing your team down.
---
title: "Footage tagging and highlight search: AI Use Case"
description: "Tag game, training or event footage with suggested moments and short descriptions, so coaches and editors search for the clip they need instead of scrubbing through hours of video."
url: https://lidvizion.ai/use-cases/footage-tagging-and-highlight-search/
site: Lid Vizion
index: https://lidvizion.ai/llms.txt
---
[Use cases](https://lidvizion.ai/use-cases/) · Sports & field operations
# Footage tagging and highlight search
Tag game, training or event footage with suggested moments and short descriptions, so coaches and editors search for the clip they need instead of scrubbing through hours of video.
[Talk through this workflow](https://lidvizion.ai/contact/?need=milestone-delivery&from=%2Fuse-cases%2Ffootage-tagging-and-highlight-search%2F#write) · [Build the missing piece](https://lidvizion.ai/services/custom-software/)
Where it starts
## The trigger.
New footage is uploaded after a game, training session or event.
How it runs today
- Finding a moment means scrubbing through hours of footage.
- Tags depend on whoever had time to log the session.
- Good clips are lost because nobody can find them again.
The workflow
## Four bounded steps.
Each step has an owner and a stop rule.
1. 01 / Ingest
Read new footage and its basic details, such as date, team and session, from approved storage.
2. 02 / Suggest
Suggest moments and short descriptions using the tag list the team agreed.
3. 03 / Review
A coach or editor accepts, corrects or removes suggested tags.
4. 04 / Search
Staff search confirmed tags and jump straight to the moment in the footage.
Where people stay in control
## Approval points.
- A coach or editor confirms tags before they are shared outside the team.
- Footage of minors or private sessions follows the organisation’s consent and access rules.
How we would measure it
## Against a baseline.
Measured before and after, on the same work.
### Time to find a requested clip.
### Share of suggested tags accepted without correction.
### Footage hours tagged per week.
Related
## Go deeper.
- [Build the missing piece](https://lidvizion.ai/services/custom-software/): Custom tools and applications for the gaps that matter.
- [Image vs. video processing](https://lidvizion.ai/resources/basics/image-vs-video-processing/): When a single frame is enough, and when you need motion, sequence and time.
- [Make your footage searchable](https://lidvizion.ai/guides/make-your-footage-searchable/): A four-step playbook to agree a short tag list, suggest tags on new footage, have a coach or editor confirm them and let staff jump straight to the moment they need.
- [How to tag sports footage with AI](https://lidvizion.ai/answers/how-to-tag-sports-footage-with-ai/): How can a team, club or league use computer vision to tag game and training footage so coaches and editors find the clip they need in seconds?
More use cases
## Other places to start.
[All use cases](https://lidvizion.ai/use-cases/)
- [Movement and activity analysis from video](https://lidvizion.ai/use-cases/video-movement-analysis/): Sports & field operations Count repetitions, score form or track activity from ordinary video, with results a coach or supervisor can check.
- [Field inspection photo reports](https://lidvizion.ai/use-cases/field-inspection-photo-reports/): Sports & field operations Turn the photos and notes field crews capture on site into an organized inspection report, with possible issues flagged for a qualified person to confirm.
- [Venue occupancy and crowd flow](https://lidvizion.ai/use-cases/venue-occupancy-and-crowd-flow/): Sports & field operations Count people entering, leaving and gathering in areas of a venue from existing cameras, without identifying anyone, so staff can open gates, move people and plan staffing.
An illustrative workflow pattern, not a result from a specific customer.
Bring the messy version
## One workflow. A better way to run it.
Show us the tools, the handoffs, and the part that keeps slowing your team down.
[Let’s map your workflow](https://lidvizion.ai/contact/) · [Read our approach](https://lidvizion.ai/approach/)