iRefFoos

Auto-Timer Analytics

⏱️ Auto-Timer Analytics

Auto-Timer Sessions

-
practice + broadcast starts

Device Models Seen

-
unique hardware types

Practice Challenges

-
real challenges started (excl. demos)

Broadcast Games

-
new games started in player mode
Detection Success — by Device Model

Success Funnel by Device

Sessions started → Practice challenges triggered → Broadcast games started. A device model where challenges and games are low relative to sessions suggests ball detection is not working reliably on that hardware.
Loading...
Engagement Depth — How Many Sessions Per Device

Session Depth Distribution

For each device model, how many individual devices (installs) fall into each usage tier. Devices stuck at "tried once" on a model that otherwise has heavy users points to environment/setup, not hardware.
Tried once
2–5 sessions
6–20 sessions
20+ sessions
Loading...
Mode Preference — Practice vs Broadcast

Mode Split by Device

How sessions are split between practice and broadcast modes per device model.

Device Summary Table

All-time totals by device model.
Loading...
Role Selection & Trail Style

Role Usage

How often each role is chosen — from the role picker. All-time, any time a user selects or switches role.

Ball Trail Style Usage

Which trail style is active when any auto-timer session begins — across all roles.