Devlog 10 - Latency Calibration
Rhythm Quest (Demo) » Devlog

Devlog 10 is up, where I write about my new latency calibration screen design.
Read it here: https://ddrkirby.com/rhythm-quest/devlog/10.html
Get Rhythm Quest (Demo)
Rhythm Quest (Demo)
Upcoming 2-button chiptune rhythm runner
Status | In development |
Author | DDRKirby(ISQ) |
Genre | Rhythm, Platformer |
Tags | 2D, chiptune, Music, Pixel Art, Runner, Singleplayer, Unity |
More posts
- Devlog 77 - More and More Bonus Levels61 days ago
- Demo v0.36.4 Released64 days ago
- Demo v0.36.0 Released69 days ago
- Devlog 76 - Tutorial Revamp99 days ago
- Devlog 75 - Game Scene RefactorsFeb 28, 2025
- Devlog 74 - Bottled Up, More Level Browser WorkJan 30, 2025
- Demo v0.35.0 ReleasedDec 22, 2024
- Devlog 73 - Multiple Difficulties, Song Select MenuDec 01, 2024
- Devlog 72 - General Improvements and OptimizationsNov 01, 2024
- Demo v0.34.0 ReleasedOct 31, 2024
Comments
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Thank you so much for writing this! I'm currently trying to implement a latency calibration screen in my own rhythm game, and your articles are one of the rare sources that explain the subject very well. They helped me tremendously.
I have one question though: on the first step, is it better to take the player's taps average delay, or median? From what I've read, I understand that the extremes should be ignored, but then I'm not sure what should be the best method to find the optimal value (especially if there are high discrepancies between each taps).
By the way, I should also mention that I loved the Rhythm Quest demo, and I'm eager to play the full game. :)
Thanks, I'm glad it was helpful!
The version of the calibration screen shown in Devlog #10 is an old one, for what it's worth (see https://rhythmquestgame.com/devlog/41.html)
For your question about measuring a player's taps, there is unfortunately no best answer :o) There are arguments for both; I think my current approach does a sort of hybrid where it attempts to use each of the players taps as a "base" and then see which one of their taps results in the lowest average discrepancy.
You should definitely experiment to see what works best! You can also do things like take the average, but filter out any values that don't lie within a certain expected range of inputs. You can visually show those inputs as being discarded, as well.