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Aim Trainer

Hit 30 targets as fast and as accurately as you can, and see how your aim follows Fitts's law. Free, no sign-up. We save scores, with your IP address and country, to build comparisons.

By the Helibrain teamReviewed by Robert, biophysics PhD candidatePublished Last reviewed

Hit the targets

30 targets appear one at a time, in different places and sizes. Hit each one as fast as you can.

Click or tap the target. Clicks that miss lower your accuracy. Mouse and touch results are kept separate.

How to read your score

  • Average time per target: the whole run divided by the number of targets, in milliseconds (ms). Lower is better. Missed clicks cost time, so they show up here too.
  • Accuracy: hits divided by all your clicks in the play area.
  • Fastest hit: your quickest single target.
  • Throughput: speed and difficulty in one number, in bits per second (see below). Higher is better.
  • The chart: each dot is one target, its time against how hard it was. The dashed line is your own Fitts's-law line.

What is Fitts's law?

Fitts's law says that the farther away and the smaller a target is, the longer it takes to hit. Paul Fitts showed in 1954 that the time grows in a straight line with a target's "index of difficulty", measured in bits [1]. Today it is usually written as log2(distance / width + 1) [2]. Designers use it to make buttons easy to hit.

Quick facts

  • What it measures: how fast and accurately you point at targets: seeing where a target is, moving there and stopping on it.
  • Throughput with a mouse: lab studies using the standard method find about 3.7 to 4.9 bits per second [3].
  • Throughput with a finger: in one phone study, 16 people tapping targets reached about 7 bits per second [4]. Our numbers use a simpler method (below), so they are not directly comparable.
  • Small targets on touch screens: a finger's touch lands about 1 to 1.5 mm off on its own; targets smaller than about 7 mm get many misses [5].
  • Mouse and touch apart: results are kept separate per input.

How the aim trainer works

  1. Press Start in the middle of the play area. The clock starts.
  2. Hit the targets. 30 round targets appear one at a time, in three sizes, each well away from the last one. A click that misses counts against your accuracy; the target stays until you hit it.
  3. See your result, with your Fitts's-law line.

The targets come from our server, made from a random number (a seed). If you share your score, your friend gets the same seed and so exactly the same targets. Your clicks are scored on our server, which replays them against the targets.

We compute throughput from each target's distance and size as shown, without the corrections the lab standard adds for where clicks land [3]. That is why we say to compare with your own runs.

What affects your aim?

  • Distance and size. Far, small targets take longest: that is Fitts's law [1, 2].
  • The device. A mouse, a touchpad and a finger give different results. In lab studies the touchpad was much slower than the mouse [3].
  • Speed or care. Rushing raises misses, and every miss costs time. The best scores come from a steady pace.
  • Age. In one study, adults made fewer errors than children aged 12 to 14 and were faster than people aged 61 to 69 [6].
  • Practice. Times drop over the first few runs as you get used to the game.

What this test can and can't tell you

The aim trainer measures pointing speed and accuracy on this device today. It isn't a test of intelligence or of your brain's health, and a short score doesn't predict how good you would be at games.

Compare with your own earlier runs on the same device; a new mouse or a different screen size changes the numbers.

Frequently asked questions

What is a good aim trainer score?

Compare with your own runs on the same device: for a game like this, a good score is one that beats your last one. Once enough people have played, the result also shows how your first run compares with other players' first runs using the same input.

What is throughput in bits per second?

Throughput combines how hard the targets were and how fast you hit them. Difficulty is counted in bits: log2(distance / width + 1) [2]. Divide by the time each hit took and average, and you get bits per second. Lab studies with a mouse find about 4 to 5 bits per second with a stricter method [3].

Is it fair to compare mouse and touch?

No, and we don't. A finger and a mouse move differently, so the result only compares you with others who used the same input.

Why are my friend's targets the same as mine?

A shared score link carries the run's seed, so the targets come out the same. That makes a challenge fair.

Is the Helibrain aim trainer free?

Yes. The game and your full result are free: no sign-up, no email, no payment. We save results to build fair comparisons, as our privacy policy explains.

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Sources

  1. Fitts PM (1954). The information capacity of the human motor system in controlling the amplitude of movement. Journal of Experimental Psychology 47(6):381–391. doi.org/10.1037/h0055392
  2. MacKenzie IS (1992). Fitts' law as a research and design tool in human-computer interaction. Human–Computer Interaction 7(1):91–139. doi.org/10.1207/s15327051hci0701_3
  3. Soukoreff RW, MacKenzie IS (2004). Towards a standard for pointing device evaluation, perspectives on 27 years of Fitts' law research in HCI. International Journal of Human-Computer Studies 61(6):751–789. doi.org/10.1016/j.ijhcs.2004.09.001
  4. MacKenzie IS (2015). Fitts' throughput and the remarkable case of touch-based target selection. Human-Computer Interaction: Interaction Technologies (HCII 2015), LNCS 9170, 238–249. doi.org/10.1007/978-3-319-20916-6_23
  5. Bi X, Li Y, Zhai S (2013). FFitts law: modeling finger touch with Fitts' law. Proceedings of CHI 2013, 1363–1372. doi.org/10.1145/2470654.2466180
  6. Hertzum M, Hornbæk K (2010). How age affects pointing with mouse and touchpad: a comparison of young, adult, and elderly users. International Journal of Human-Computer Interaction 26(7):703–734. doi.org/10.1080/10447318.2010.487198

How we made this page: written by the Helibrain team from the studies listed above, and reviewed by Robert (biophysics PhD candidate) on 4 November 2026. We update it when the sources change.