Using AI to Automate Ball Possession Tracking

AI Football Analytics Video Analytics YOLO

Leveraging AI to compute ball possession and enhance football match analysis through automated video analytics.

Table of Contents

  1. Introduction
  2. The Importance of Ball Possession
  3. AI-Driven Solution
  4. Implementation Steps
  5. Conclusion

Introduction

Ai is revolutionizing the sports industry by providing advanced analytics and insights that were previously unattainable. In football, AI-driven solutions can enhance match analysis, player performance evaluation, and strategic decision-making. One key area where AI can make a significant impact is in automating the calculation of ball possession during matches.

The Importance of Ball Possession

Ball possession is a critical metric in football. A 2020 study over 625 UEFA matches revealed that teams with higher possession rates won 49.2% of the time. Accurately measuring ball possession can provide valuable insights into team performance and strategy.

AI-Driven Solution

To automate the calculation of ball possession, we aim to use computer vision techniques. Our approach focuses on detecting players and the ball, identifying teams, and determining possession, all in real-time.

Implementation Steps

Step 1: Player Detection

We utilized YOLOv5 for detecting players, ensuring accurate and efficient identification of players on the field.

Step 2: Team Identification

We implemented the following approach for classifying teams:

Figure: Team identification using an HSV filter (credit to tryolabs.com)

Step 3: Ball Detection (In progress)

We will use a fine-tuned YOLOv5 model, trained specifically on football footage, for detecting the ball.

Step 4: Ball Possession Calculation (In progress)

We plan to determine ball possession by calculating the distance between players and the ball, applying a threshold to ensure accurate possession metrics.

Conclusion

By planning to integrate AI with video analytics, our system aims to provide accurate and automated ball possession metrics, enhancing football analytics. This approach illustrates the potential of AI in sports, offering insights that will improve team performance and strategies.