Turn an abstract quantity into a physical distance and draw it to scale, and a number nobody can feel becomes one anybody can see.
At the 2026 Hungarian Grand Prix, Lewis Hamilton qualified second, 0.012 seconds behind pole. On the broadcast, that flashes up as “+0.012s,” and then it’s gone. Do you feel anything? I don’t. I can’t picture 12 thousandths of a second, and neither can you, because nobody has a sense for it.
So let me tell you the same fact a different way. Hamilton was 1.1 metres behind. About a car’s nose. Now it’s real. You can see the two cars almost level, one just edging the other over the line.
Nothing about the fact changed. Only the unit did. That distance between a number and a feeling is one of the most common problems I encounter in data visualisation, and it has a pleasingly simple fix. When a quantity won’t land, stop trying to make it more precise and start translating it into something the reader’s body already understands. Usually, that something is distance.
Why a number doesn’t land
You’re bad at abstract quantities and good at physical ones. Ask someone whether 0.238 seconds is a lot more than 0.012, and they’ll do arithmetic. Ask them whether 20 metres is a lot more than one metre, and they’ll just know, instantly, in their body. Distance, size, and “how long would it take to walk there” are units you’ve been calibrating since before you could talk.
This is why “an area the size of Wales” beats a figure in square kilometres, and why a transit map’s walking times land harder than a count of stops. You’re not giving the reader new information. You’re handing them a grip they already know how to hold.
The method in one line
Here’s the whole trick:
distance = your quantity × a meaningful rate
The rate is whatever turns your unit into space. For a time gap between two moving cars, the rate is speed. A Formula 1 car crosses the finish line at around 300 kilometres per hour, which is about 83 metres every second. So a tenth of a second is roughly eight metres of track, and Hamilton’s 0.012-second gap works out to a little over a metre.
That’s the arithmetic. The interesting part is what you do with it.
The ordinary way first
The obvious move is to put the numbers in a bar chart.
There’s nothing wrong with this. It’s honest, it ranks the drivers correctly, and it shows that the gap back to sixth is far larger than the gap to second. If your question is “how much slower was each driver?” this answers it.
But look at it and notice what you don’t feel. Hamilton’s sliver and Verstappen’s longer bar are just two lengths on a page. You know sixth was further back. You don’t sense how far. The bar chart answers “how much.” It has no idea about “how far,” because a bar isn’t a place.
Now draw it on the track
Here are the same six numbers again, except this time each car sits on a straight, to scale, set back from the reference by its gap turned into metres. The straight is just a ruler: a finish line and a cross-line every five metres behind it. (This is from the Gap Visualizer Tool, which draws qualifying gaps to scale.)
Now you feel it. Hamilton is right on Norris’s gearbox, close enough to touch. Leclerc, only a quarter of a second further back, is more than 20 metres away. And the top six, covered by barely half a second on the timing screen, are strung out across nearly 50 metres of tarmac. That last fact was true in the bar chart too. It just didn’t mean anything until it had a length you could pace out.
Laid out to scale like this, the drawing lets the emptiness do the work. The reader already knows a racing car is small and 50 metres is a long way, so the space between first and last carries a weight no bar can.
How the drawing is made
The maths is almost embarrassingly simple, and I think that’s a feature. You take each gap in seconds and multiply it by a single speed:
distance in metres = gap in seconds × (speed in km/h ÷ 3.6)
That speed is one number for the whole grid: the reference car’s measured speed through the trap near the start-finish line, on its fastest lap, taken straight from the timing data. It isn’t a top speed or an average lap speed, just how fast the pole car was going as it crossed the line. The round rule of thumb is about eight metres per tenth at 300 kilometres per hour; this session was a touch quicker over the line, which is why Hamilton’s 0.012 seconds comes out at 1.1 metres and the top six spread to 47.
Then you place the cars. The reference car’s nose sits on the line, and every other car goes straight back by its own distance, sorted by gap. That’s the whole layout, in one dimension.
There’s one honest wrinkle worth stating, because it’s exactly what a careful reader will poke at. The cars are also nudged slightly sideways, so none hides directly behind the one ahead. That sideways position carries no data whatsoever. It exists purely so you can see every car. Only the distance along the straight means anything.
Being honest about the model
I should be upfront about what this drawing is and isn’t, because a good visualisation tells you its own limits.
It’s a freeze-frame. What it says is: If both cars were travelling at the reference car’s line speed, this is how far back the second car would be at the instant the leader crosses the line. The gap itself was actually built up all over the lap, in the corners as much as on the straights, but the drawing expresses all of it at that one speed. That’s exactly why I draw it on a straight and rule the straight in metres. Near the line, flat out, a single speed is about as honest as a single number gets. Wrap the same gap around the slow corners, and it would lie, because the car isn’t doing that speed there.
A couple of smaller honesties. The whole grid is measured with the reference car’s speed, so a trailing car’s own line speed doesn’t change where it’s plotted. And the trap that reads that speed sits near the line, not exactly on it, so “at the line” is really “about at the line.”
None of this is hidden in the tool, and naming it here doesn’t weaken the picture. The version I’d stand behind in one line: The gaps are real, the proportions are real, and the track is illustrative. That’s what keeps it from being fake-precise, and a reader trusts a chart that tells them what it can’t do.
When to reach for space
None of this makes the bar chart wrong. It makes it right for a different question. The rule of thumb I use: When your point is about magnitude or ranking, use length or position, and a bar chart is hard to beat. When your point is spatial—when the whole idea is how far or how big—borrow the reader’s sense of real space and put the data into it at scale. The gap between two cars is a spatial idea wearing a temporal disguise. Remove the disguise, and it lands.
This isn’t really about racing
Time-to-distance is just one instance of a broader move, and once you see it, you’ll use it everywhere. Almost any invisible unit can be mapped onto a physical one you can picture:
- a data-transfer figure becomes enough to stream a whole film twice
- a budget becomes a stack of banknotes as tall as a building, or the nurses it would pay for a year
- a carbon figure becomes trees, or flights, or a distance driven
The pattern never changes. Find the rate that turns your unit into something the body knows, then, wherever you can, draw it to scale so the reader doesn’t have to imagine it for themselves. You supply the picture. Their intuition supplies the meaning.
The takeaway
When a number isn’t landing, the instinct is to add decimal places, or a bigger font, or a percentage. Try the opposite. Ask what physical thing your quantity is equivalent to, and hand the reader that instead. A hundredth of a second is nothing. A car’s nose is something. The data didn’t change. You just gave it a body.
So next time a number won’t land, give it a distance.
Bhavin Lathia
Bhavin Lathia buildsFormula Dream, a set of free tools and a companion app for following Formula 1. He's interested in making dense sports data feel intuitive to people who aren't data experts.
