Appzotic
Portfolio PickleBall Pro
Sports · AIWeb applicationProduct

PickleBall Pro

AI pickleball analysis

AI pickleball analysis for rallies, shot patterns, and player form — plus tournament setup for clubs.

See every view Build something like this
This product holds
  • AI rally and shot analysis
  • Player form and match insight
  • Tournament types and hosts
  • Categories with experience levels
PickleBall Pro · PickleBall Pro
Product
PickleBall Pro
Industry
Sports · AI
Platform
Web application
Status
Product
Year
2026
What’s inside

The product, module by module.

Everything a client would actually use — not a feature dump, the operating pieces of the system.

01

AI match analysis

Turn recorded rallies into shot patterns and player form coaches can act on.

Practice follows evidence, not memory of the last game.
02

Tournament types

Individual, pair, or event in one control.

The form matches how the sport is actually played.
AI engineeringProduct designWeb engineering
How it looks

Every view we shipped.

Click any screen to open it full size. These are the live product surfaces — dashboards, flows, and themes.

The brief

Why it exists, and what it changed.

The problem

Matches were recorded, but shot patterns and form never became comparable insight — and events still lived in chat.

What we built

An AI analysis product with a professional landing and a create-event flow for individual, pair, and event formats.

What changed

Coaches can read the match; organisers can name an event, add a host, and define categories in one form.

01

Rally-level signal

Pickleball is not tennis-with-a-wiffle. Shot patterns and kitchen play need their own model of the game.

Impact · Analysis has to name the rally, not a generic highlight reel.
02

Format variety

Individual, pair, and event tournaments cannot share a naive form.

Impact · The type has to change what categories mean.
How it’s built

Delivery path, stack, and system shape.

Phase 01

Analysis

Match insight from rallies — shot patterns, player form, and comparable sessions.

Phase 02

Create flow

Name, type, host, and categories with experience levels when the club still needs an event.

React
TypeScript
Tailwind
Experience
Public site
Player and organiser console
Edge & trust
Auth
Application
Match analysis
Tournaments
Players
Categories
Data
Rallies
Events
Hosts
Operations
Analyse
Create
Publish
Encrypted in transit and at rest End-to-end observability Independently scalable services
Impact

What a buyer should feel after launch.

AI

rally-level insight

3

event types

Insight per rally

Coaches can compare sessions instead of relying on memory.

“Finally a pickleball product that analyses the match — and still lets us stand up an event without a spreadsheet.”
Tournament director
PickleBall Pro
More work

Other products in the studio.

Project FAQ

The details behind the delivery.

How long did the project take?

The core engagement ran for a focused sports product cycle. Discovery and architecture came first, followed by incremental releases and a structured transition into continuous improvement.

Why was this technology stack selected?

React, TypeScript and Tailwind provided the best balance of team fit, ecosystem maturity, security, delivery speed and long-term operating cost. Every major choice was documented through architecture decisions.

How were security and scalability handled?

Threat modeling, least-privilege access, automated security checks and observability were built into delivery. Load and failure testing validated the critical paths before launch.

What support followed launch?

Appzotic provided launch command, operational monitoring, knowledge transfer and a prioritized evolution roadmap. The client could choose continued product support or full internal ownership.

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