Development of AI-Powered Football Analytics System

# AI-Based Football Pitch Video Analytics System – Freelancer Project Brief

## Project Overview

We are looking for a freelancer or team to develop an AI-powered computer vision and player performance analysis system for indoor football / mini football pitches.

The system will be used in multiple football pitch locations across Türkiye.

The software must:

* Track every player during the match
* Analyze player and team performance
* Automatically generate statistics and ratings
* Upload the match analysis to a website shortly after the match ends

A complete hardware setup is already available for the first pitch:

* 6 cameras installed
* 1 high-performance PC
* NVIDIA RTX 5080 GPU
* Remote access via Tailscale is already configured

The first implementation will be done on this pitch, but the system must later support easy deployment to many different football pitches.

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# Most Important Requirement: Player ID Tracking

The most critical and difficult part of the project is making sure that players never get mixed up.

On these pitches:

* Players do not wear fixed uniforms
* Players may wear similar clothes
* There is no jersey color requirement
* Players frequently overlap, block each other, and move between cameras
* Up to 14 players are on the field at the same time

Because of this, the system must have a very strong player tracking and re-identification system.

Expected behavior:

* Each player receives one unique ID at the beginning of the match
* That player must keep the same ID during the entire match
* If the player disappears for a few seconds, moves behind another player, or leaves the camera view, the same ID must be restored
* If the player moves from one camera to another, the ID must remain the same
* During collisions, crowded situations, or when players look similar, IDs must still not switch

Expected accuracy:

* Player ID stability / no ID switching: 99%+
* Goal count and total match score: 99%+
* Distance and speed calculations: 95%+

This requirement is the highest priority when selecting the freelancer.

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# Match Flow

Normally, there are 14 players on the pitch.
The match starts when the players are split into two teams of 7 vs 7.

The system must be able to:

* Detect the start of a match automatically
* Or allow an admin to manually start the match

Important:

* A match can last up to 60 minutes
* Immediately after one match ends, another match may start on the same field
* The software must support back-to-back matches without restarting the system

Expected workflow:

1. Capture video from all cameras
2. Detect all players
3. Assign a unique ID to each player
4. Track every player throughout the match
5. Detect and track the ball
6. Detect events such as goals, shots, assists, passes, runs, etc.
7. Calculate all statistics automatically after the match ends
8. Upload the results to the website within a maximum of 15 minutes after the match

The system should work in real time or near real time.

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# Required Player Statistics

The system must generate at least the following statistics for each player:

* Goals scored
* Total shots
* Shots on target
* Assists
* Pass count
* Pass accuracy
* Ball touches
* Ball losses
* Tackles / interceptions
* Total distance covered (meters / kilometers)
* Average speed
* Maximum speed reached during the match
* Heatmap
* Most active areas on the pitch
* Defensive / offensive activity
* Overall activity level
* Ranking inside the team

The system should also be expandable in the future for additional features such as:

* Sprint count
* Sprint duration
* Dribbling success
* Pressing intensity
* Expected Goals (xG)
* Pass network visualization
* Team tactical analysis
* Automatic highlight generation
* AI-generated video summary

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# Player Rating System

At the end of the match, each player must receive an automatic performance rating.

The rating should be calculated using metrics such as:

* Goals
* Assists
* Shots
* Passing performance
* Distance covered
* Speed
* Defensive contribution
* Ball losses
* Positioning
* Overall activity

The rating may be:

* Out of 10
* Or out of 100

In addition, the system should generate a short AI-written comment for each player.

Example for a good performance:
“You played with a high tempo throughout the match and contributed 2 goals and 1 assist. You were one of the most effective players on the pitch.”

Example for a weaker performance:
“You had some defensive impact, but your offensive contribution remained limited. You can improve by taking more shots and connecting more passes.”

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# Website / User Experience

At the beginning, there will be no user registration or login system.

Players will visit the website and find their own match.

The website must allow filtering by:

* City
* District
* Football pitch name
* Date
* Time

After opening a match, the user should see:

* List of all detected players
* A frame / image of each player captured by the AI
* The player’s match ID shown next to the frame

Example:

* Player image
* ID #3443

The user will identify themselves by saying “This is me”, and then open their own statistics.

The player page should include:

* Statistics
* Rating
* Heatmap
* Maximum speed
* Distance covered
* Goals / assists
* AI-generated comment

Additional requested visual features:

* “Man of the Match” screen
* FIFA Ultimate Team style player cards
* Optional FIFA-style walkout animation for the best player
* Downloadable player card after the match

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# Admin Panel

An admin panel is required.

The admin panel must allow:

* Adding new football pitches
* Defining city, district, pitch name, camera configuration
* Connecting a local computer / server to a pitch
* Adding and configuring cameras
* Viewing all matches
* Manually starting and ending matches
* Correcting wrongly matched player IDs if necessary
* Monitoring the status of the system
* Testing camera connections
* Seeing which pitch each analysis belongs to

The software should be as plug-and-play as possible.

When a new football pitch is added:

1. Cameras are connected
2. The local computer is configured
3. The software is installed
4. Data automatically syncs to the main system

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# Technical Requirements

The freelancer should have proven experience with:

* Computer Vision
* Multi-object tracking
* Re-identification (ReID)
* DeepSORT, ByteTrack, BoTSORT or similar systems
* YOLO, Detectron or similar detection models
* Multi-camera synchronization
* Cross-camera player tracking
* Real-time video processing
* GPU optimization
* Web panel development
* Backend and database development
* API development

Preferred experience:

* Sports analytics
* Football / basketball tracking projects
* NVIDIA GPU optimization
* Multi-camera systems

Please share:

* Previous similar projects
* Screenshots
* Videos
* GitHub repositories
* Demos

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# Deliverables

The freelancer is expected to deliver:

* Fully working player and ball tracking system
* Match analysis system
* Website / web panel
* Database structure
* Installation documentation
* Documentation for adding new football pitches
* Recommended camera placement and camera angle guide
* Source code
* Training / usage video

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# Project Timeline and Long-Term Cooperation

This is not a small one-time project.

If the freelancer successfully completes the project, we expect long-term cooperation for:

* Additional modules
* More football pitches
* Mobile application
* More advanced statistics and analysis

All rights to the idea, software, and project belong to us.
The freelancer must agree to confidentiality and, if necessary, transfer of rights.

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# Additional Items We Would Like the Freelancer to Explain

When applying, please also explain:

* Which technologies and architecture you would use
* How you would solve the player ID switching problem
* Estimated FPS and processing delay
* How you would measure and guarantee accuracy
* Whether the system will work locally, in the cloud, or hybrid
* How the system behaves if internet access is lost
* How multi-camera synchronization will work
* How the system can be expanded in the future

We also prefer the project to be divided into milestones such as:

1. Player tracking and stable IDs
2. Ball, goal, and event detection
3. Statistics generation
4. Website and player interface
5. Multi-pitch support
6. Final deployment and optimization

We prefer to first build a working MVP for one football pitch, then expand to multiple locations.

The software must be well documented so that another developer can continue working on it in the future.

The project will operate in Türkiye and should comply with local data privacy requirements where necessary.


Note: Although the current setup includes 6 cameras, we are open to reducing the number of cameras in the first MVP if it improves player tracking stability, reduces ID switching, and provides a more reliable system. We prefer the minimum number of well-positioned cameras that gives the best balance between field coverage and player re-identification accuracy. Show More