Planned Release Date: Oct 1, 2026

About This Software

AimFit evaluates your aim setup using gameplay you record yourself. Press F1 to record a session. The app analyzes the video and audio to detect shots, hits, and critical hits, while showing the current measurement step and what to test next.

Run several mouse sensitivity trials to build a curve showing the relationship between sensitivity and performance. AimFit marks the range where results are similarly strong and recommends a sensitivity based on what it measured.

For DPI, follow the guided ladder and test each step in sequence. The completed trials are compared to produce a recommended DPI.

Desk-height testing uses runs recorded at different heights. The results show how desk height and arm position affect aim performance, followed by a recommended height.

Recommendations are based only on measurements you have completed. If there is not enough data, or if the results are unstable, AimFit reports the issue and provides the reason.

AimFit is available for Windows only. Gameplay video analysis runs entirely offline on your PC. The app does not access game memory, inject code, alter game files, or automate aiming.

AimFit runs with administrator privileges. When an anti-cheat game runs as administrator, Windows does not pass the F1 hotkey and mouse input to an app running with standard privileges.

Anonymous usage-data collection is enabled by default. It can be disabled through the anonymous research-data sharing option in Settings.

Overwatch and Marvel Rivals are trademarks of their respective owners. AimFit is not affiliated with or endorsed by Blizzard Entertainment, NetEase Games, Marvel, or the respective rights holders.

AI Generated Content Disclosure

The developers describe how their game uses AI Generated Content like this:

AI tools were used to help draft some text, such as this store page description and the in-app guide (all reviewed by the developer). The application itself does not ship AI-generated content: every measurement, analysis, and recommendation is computed locally with deterministic algorithms.