Tennis Analyzer is a micro-level tennis performance analysis mobile app. Use this app to track point-by-point match data and generate detailed statistical analysis, including serve percentages, high pressure points win percentage, serve direction patterns, and more. Coaches and players can use this app to conduct real-time, micro-level performance analysis, compare players, discover patterns, and identify areas for improvement.
This app may be used simply as a score tracker. However, to generate detailed statistical analysis, the user must enter information such as serve direction, shot count, last shot type, and shot result on a point by point basis. Therefore, this app requires a high level of concentration during the match.
The frontend is built using Google AppSheet, and the backend is built using Google Sheets and Google Apps Script.
backend/: Server-side logic.- Core File:
src/MicroStats.js - Handles data processing and statistical calculations.
- Core File:
frontend/: Frontend design.- Since AppSheet is a web-based, low code platform, there is no source code in this folder.
- Screenshots of AppSheet design.
🌐 Project Website: www.tennisanalyzer.app
- Google Play Store: Download for Android
- iOS: Install via AppSheet
- FAQ Document - Frequently Asked Questions
- Demo Videos - Tutorial playlist on YouTube
- Carlos Alcaraz vs Jannik Sinner (2022 US Open QF) - Video
- Stefanos Tsitsipas vs Novak Djokovic (2023 Australian Open Final) - Video
- Rafael Nadal vs Roger Federer (2017 Australian Open Final) - Video
- Iga Swiatek vs Elena Rybakina (2023 Australian Open 4R) - Video
- Ash Barty vs Danielle Collins (2022 Australian Open Final) - Video
- Ash Barty vs Elena Rybakina (2022 WTA Adelaide Final) - Video
- Brandon Holt vs Mikael Torpegaard (2018 NCAA, USC vs Ohio State) - Video
- Mackenzie McDonald vs Yannick Hanfmann (2015 NCAA, UCLA vs USC) - Video
- Published on Google Play since August 2023
- Small but growing international user base
- 50% monthly retention rate (~20 monthly active users (MAU) / ~40 installed audience)