Aim: Fitts's Law, Touch Targets and What a Good Score Is

Seeing something is one skill. Getting your hand onto it quickly and accurately is another. In Aim, targets pop up at random spots and you hit each one as fast as you can, so your score combines reaction time and movement time. Here's how it works, the 70-year-old law that predicts it, and what a good score looks like.

How the game works

After the countdown a round target appears somewhere in the play area. Tap or click it. The next one appears after a short random gap of 0.4 to 1.2 seconds, and taps during the gap are ignored. Your time for each target runs from the frame it appears to the moment you touch it.

Difficulty sets the target size: 96 px across on Easy, 72 on Medium and 52 on Hard. On a typical phone screen that's roughly 15, 11 and 8 mm. Tapping off the target is an error. On Easy you redo that target, and on Medium and Hard the set restarts.

Two parts to every hit

Each time breaks down into two parts:

• Reaction time:spotting the target and starting to move. Because you don't know where it will appear, this part is slower than a simple reaction like Lights Out, where you know exactly where to look.
• Movement time: getting your finger or cursor to the target and landing on it. This is the part a law of human movement describes.

Fitts's law

In 1954 the American psychologist Paul Fitts showed that the time to point at a target depends on two things: how far away it is and how big it is. Doubling the distance or halving the size adds roughly the same fixed amount of time. He combined the two into a single “index of difficulty”. Scott MacKenzie later refined the formula, in a form now standard in human–computer interaction research:

Movement time = a + b × log₂(distance ÷ width + 1)

Here a and bdepend on the person and the device. Fitts's law is used to design everything from cockpit controls to the size of buttons on your phone, and it is why our Hard targets are so much more demanding than Easy ones even though they are only half as wide.

What the touchscreen studies show

• Fingers are quick but imprecise.Bi, Li and Zhai (2013) found that a fingertip's landing point scatters by about 1.5 mm whatever the speed. With 7.2 mm targets about 7 % of taps missed. At 4.8 mm that rose to around a quarter. Simple taps over 2–3 cm took about 385–490 ms in their tests, with the target already visible.
• Speed costs accuracy.MacKenzie (2015) had people tap back and forth between targets on a phone. Each tap took about 341 ms, with no reaction to wait for. Errors were 2.7 % on 10 mm targets and 12.2 % on 6.2 mm targets.
• Touch is efficient. In that study finger tapping handled about 7 bits of difficulty per second. Typical figures for a mouse are around 4–5 bits per second. Touch wins because there is no cursor to steer.

What score to expect

We couldn't find a peer-reviewed study that measures exactly this task: a target appearing at a random spot on a phone and a single tap. Popular aim-trainer “averages” online have no published source, so we've left them out. Combining the evidence gives a reasonable estimate, though. A visual reaction of around 250 ms, a little extra for not knowing where to look, and 250–400 ms of finger movement puts a typical time per target at roughly 500–700 ms.

With a mouse your times will differ. You have to move the cursor rather than your finger, and Fitts's law fits the cursor journey just as well, so compare yourself with your own past results on the same device.

How to get better

• Return to the middle. Hovering your finger near the centre of the play area keeps every target within a short reach.
• Look with your whole field of view.Don't stare at where the last target was. A relaxed, wide gaze picks up the next one sooner.
• Aim for the centre. Your landing point scatters by a millimetre or two, so aiming dead centre leaves room for it, especially on Hard.
• Build accuracy first, then speed. One miss costs you a whole set on Medium and Hard. Get your errors near zero, then push the pace.

For general ways to sharpen up, see how to improve your reaction time.

Sources

1. Fitts, P. M. (1954). The information capacity of the human motor system in controlling the amplitude of movement. Journal of Experimental Psychology, 47(6), 381–391.
2. MacKenzie, I. S. (1992). Fitts' law as a research and design tool in human-computer interaction. Human–Computer Interaction, 7(1), 91–139.
3. Bi, X., Li, Y. & Zhai, S. (2013). FFitts law: modeling finger touch with Fitts' law. Proceedings of CHI 2013, 1363–1372.
4. MacKenzie, I. S. (2015). Fitts' throughput and the remarkable case of touch-based target selection. HCI International 2015, LNCS 9170, 238–249.
5. Soukoreff, R. W. & MacKenzie, I. S. (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.