Sports Annotation
Quick Annotate
At Quick Annotate, we deliver real-time insights through our Live Sports Analysis solutions. Designed for coaches, analysts, broadcasters, and sports-tech platforms, our services turn fast-paced game action into meaningful, actionable data—right as it happens.
What We Offer:
Real-Time Game Monitoring
Live Data Capture & Processing
Instant Player & Team Performance Metrics
Real-Time Video Tagging & Breakdown
Play-by-Play Event Annotation
Introduction
Live Sports Analysis
In today’s fast-paced sports environment, real-time data is a game-changer. At Quick Annotate, our Live Sports Analysis solutions empower teams, coaches, broadcasters, and sports-tech platforms with instant insights during live matches. By combining high-precision data capture with expert tagging and analysis, we help you make smarter, faster decisions — right as the action unfolds. Whether it’s tracking player movement, tagging key events, or analyzing team strategies in real time, we deliver the edge you need when every second counts.
Soccer Video Annotation
Our soccer annotation services focus on two core areas: Player Movement and Event Tagging.
- Player Movement Annotation captures every player’s speed, direction, and position using manual tracking, smart cameras, and sensors (GPS/IMUs). It analyzes trajectories, heatmaps, distances, and physical metrics to reveal insights into tactical shape, space usage, and performance.
- Event Annotation involves tagging key in-game actions like passes, shots, and tackles. These are recorded with details such as player, location, outcome, and type of event. This structured data supports match analysis and predictive modeling.
Introduction
At QuickAnnotate, we bring intelligence to the field by delivering in-depth video annotation solutions for soccer. Our services focus on capturing both player movements and key in-game events with high accuracy, leveraging a combination of manual expertise, automated systems, and wearable technologies. By analyzing every run, pass, and tactical action, we transform raw footage into rich, structured data that fuels performance analysis, strategy development, and AI model training. Whether you’re optimizing team tactics or building predictive analytics, our soccer annotation unlocks the insights hidden in every match.nts.
Basketball Video Annotation
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Basketball video annotation plays a vital role in performance analysis and AI model development by offering detailed insights into key in-game actions.
Shot Detection focuses on identifying and analyzing shot attempts. This involves detecting the ball and hoop, tracking the ball’s motion, and classifying whether the shot is a make or miss. Annotations include precise labeling of the ball, hoop, and shot outcome, which are essential for model training and performance evaluation.
Pass Tracking involves recognizing and analyzing passes between players. This is achieved by tracking both players and the ball, and identifying changes in possession. Annotators label the passer, receiver, and ball trajectory to provide accurate datasets for training sports analytics systems.
Introduction
Basketball annotation focuses on capturing key in-game actions like shot detection and pass tracking.
- Shot Detection involves identifying shot attempts by detecting the ball and hoop, tracking the ball’s motion, and classifying outcomes (make or miss).
- Pass Tracking analyzes player passes by tracking ball movement and changes in possession, labeling passers, receivers, and ball trajectory.
American Football
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- Goal:
To label and categorize different types of plays during a football game for analytical and training purposes. - Process:
Human analysts manually review and tag each play by watching game footage. - Categories:
- Offensive Plays: Run, pass, punt, field goal, kickoff
- Defensive Plays: Coverage types, blitzes
- Special Teams: All plays involving kicking or return units
- Details Annotated:
- Team formations and player personnel on the field
- Direction of play (e.g., left/right, upfield/downfield)
- Outcomes of the play such as yards gained or lost, completions, and penalties
Introduction
American football is a highly strategic and data-rich sport where every play offers valuable insights. Accurate annotation of gameplay footage plays a crucial role in performance analysis, strategy development, and training machine learning models. The focus lies in labeling and categorizing various types of plays, helping teams and analysts to make data-driven decisions.
Volleyball
· Goal:
To identify and categorize all serve-related actions in a volleyball match.
· Annotation Includes:
o Server Identification: Labeling the player performing the serve.
o Serve Type: Tagging the type of serve (e.g., float serve, jump serve).
o Serve Outcome: Noting the result of the serve (e.g., ace, in-play, out).
o Ball Trajectory (Optional): Annotating the path or arc of the served ball.
Introduction
Volleyball is a dynamic sport where high-speed actions like serves and spikes can significantly impact the game’s outcome. Annotating these key events enables teams, analysts, and AI systems to break down performance, evaluate strategies, and enhance training effectiveness. By categorizing serves and spike actions, valuable insights into player behavior, technique, and match flow can be uncovered.
Ice Hockey
Puck Tracking
The primary aim of puck tracking in ice hockey is to automatically detect and follow the puck throughout a game. This is achieved using advanced techniques like object detection and motion analysis, which may also involve specialized cameras and sensors. For training and model evaluation, annotators label the puck’s exact position frame by frame to ensure accurate tracking data.
Player Roles Identification
Understanding player roles is essential for analyzing game strategies. This involves identifying and classifying each player’s position and function on the ice.
Key methods include:
- Position on Ice: Assessing typical zones occupied, such as defense players staying near their net.
- Movement Patterns: Monitoring common skating paths and behavioral trends.
- Event Involvement: Recognizing participation in key events like faceoffs (centers) or defensive plays like shots from the point.
Introduction
In the fast-paced sport of ice hockey, detailed video analysis and data annotation play a vital role in enhancing performance evaluation, strategic planning, and AI-based sports analytics. Two of the most critical aspects in this domain are puck tracking and player role identification. Puck tracking focuses on accurately locating and following the puck throughout the game using object detection, motion analysis, and often specialized cameras or sensors. Simultaneously, identifying player roles involves analyzing their positions on the ice, movement patterns, and involvement in game events to categorize their functions accurately.
Handball Annotation
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Handball annotation focuses on identifying critical gameplay actions such as goalkeeper and throw detection to support video analysis and AI model training.
- Goalkeeper Detection aims to locate and track the goalie using jersey color, goal position, and movement patterns. Annotations label the goalie’s location and actions for accurate analysis and system training.
- Throw Detection involves identifying throw attempts by analyzing player pose, arm motion, and ball trajectory. Key frames are annotated to mark the start, end, and flight of the throw.
These annotations are essential for developing intelligent systems that can evaluate player performance and automate event recognition in handball matches.
Introduction
Handball annotation focuses on key game actions like goalkeeper and throw detection. Goalkeeper detection tracks the goalie using jersey color, position, and movements. Throw detection identifies throw attempts by analyzing ball tracking, arm motion, and player pose. These annotations support training and evaluation for AI and performance analysis.
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