CourtMetrics: Unlocking Tennis Insights with Machine Learning

CourtMetrics is an advanced tennis analytics platform designed to enhance player performance and game analysis. It leverages cutting-edge machine learning models and Azure OpenAI services to deliver detailed player insights, match statistics, and video analytics. The platform enables users to upload or analyze match videos, compare player statistics, and visualize game trends through an intuitive dashboard. From coaches to analysts, CourtMetrics aims to revolutionize how tennis performance is evaluated by combining AI, data visualization, and user-friendly features. Product Functionalities Below is a walkthrough of the product’s core functionalities with accompanying screenshots: 1. Home Page ● Form for Analysis: Users can input player names, upload videos, or provide YouTube links for analysis. ● Output Section: Displays real-time video analysis results, including metrics and visualizations. 2. Video Download/Upload ● YouTube Video Download: Paste a YouTube link to download match videos for analysis. ● Local Video Upload: Upload match videos directly from your device. 3. Player Comparison ● Head-to-Head Analysis: Compare players based on metrics such as win percentages, rankings, and historical trends. ● Visualized Insights: Graphs and charts summarize comparative performance. 4. Video Metrics and Court Tracking ● Key Features: Track player movements, ball trajectory, and action detection using ML models. ● Mini-Court Visualization: Overlay of key points for enhanced clarity. 5. Ranking System ● Displays ATP player rankings with details such as points, nationalities, and match stats.

Publication Details

Journal
VTechWorks (Virginia Tech)
Published
2024-12-01
Primary Topic
Sports Analytics and Performance
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

CourtMetrics: Unlocking Tennis Insights with Machine Learning

VTechWorks (Virginia Tech)
Sports Analytics and Performance
article

CourtMetrics: Unlocking Tennis Insights with Machine Learning

article en

Abstract

CourtMetrics is an advanced tennis analytics platform designed to enhance player performance and game analysis. It leverages cutting-edge machine learning models and Azure OpenAI services to deliver detailed player insights, match statistics, and video analytics. The platform enables users to upload or analyze match videos, compare player statistics, and visualize game trends through an intuitive dashboard. From coaches to analysts, CourtMetrics aims to revolutionize how tennis performance is evaluated by combining AI, data visualization, and user-friendly features. Product Functionalities Below is a walkthrough of the product’s core functionalities with accompanying screenshots: 1. Home Page ● Form for Analysis: Users can input player names, upload videos, or provide YouTube links for analysis. ● Output Section: Displays real-time video analysis results, including metrics and visualizations. 2. Video Download/Upload ● YouTube Video Download: Paste a YouTube link to download match videos for analysis. ● Local Video Upload: Upload match videos directly from your device. 3. Player Comparison ● Head-to-Head Analysis: Compare players based on metrics such as win percentages, rankings, and historical trends. ● Visualized Insights: Graphs and charts summarize comparative performance. 4. Video Metrics and Court Tracking ● Key Features: Track player movements, ball trajectory, and action detection using ML models. ● Mini-Court Visualization: Overlay of key points for enhanced clarity. 5. Ranking System ● Displays ATP player rankings with details such as points, nationalities, and match stats.

VTechWorks (Virginia Tech)
Openalex Percentile: Top 26%
Sports Analytics and Performance
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

CourtMetrics: Unlocking Tennis Insights with Machine Learning · VTechWorks (Virginia Tech) (2024) | TGRS Research Map | TGRS