Radar charts explained: spider charts, radial graphs and when to use them
By the Lightchart team · Updated
The short answer
A radar chart (also called a spider chart, web chart or radial graph) plots several measures for one item on axes that radiate from a central point. Joining the values makes a polygon, so you can see an item’s overall profile, and compare a few items by their shapes, at a glance.
Radar charts are popular in product comparisons, skills assessments and sports analytics, anywhere one thing is scored on several dimensions. They’re also easy to misuse. Here’s how to read a radar diagram, when its shape tells the story, and when a plain bar chart does the job better.
How to read a radar chart
- Find the axes. Each spoke is one measure, such as Speed, Price, Support, Features or Design.
- Check the scale. The rings mark equal steps, usually from 0 at the center to the maximum at the edge. Every axis must use the same scale, or the shape means nothing.
- Read the polygon. Points far from the center are strengths, points near it are weaknesses. A lopsided shape shows a specialist; a round one shows an all-rounder.
- Compare shapes, not areas. When two polygons overlap, look at where each one sticks out rather than which looks bigger.
Radar, spider, web or radial: what’s the difference?
Mostly nothing. Radar chart, spider chart (because it looks like a web), web chart and star plot all mean the same chart. Excel and Google Sheets call it a radar chart.
Radial graph is looser. Plenty of people use it to mean a radar chart, but it also describes radial bar charts, where ordinary bars are bent around a circle. A radar chart has spokes and a polygon. A radial bar chart has curved bars. If someone asks for a radial graph, a quick sketch saves a redraw.
Radar chart vs grouped bar chart
The honest competitor to a radar chart is a grouped bar chart showing the same scores. Each has a job.
| Radar chart | Grouped bar chart | |
|---|---|---|
| Best at | Overall profile and shape | Exact comparisons per measure |
| Number of items | One to three | Two to five |
| Number of measures | Five to eight | Any, within reason |
| Reading precision | Low; values float on spokes | High; every bar shares a baseline |
| Sensitive to axis order | Yes; reordering changes the shape | No |
A worked example
Say your team is choosing between two project management tools and has scored each from 0 to 10 on speed, price, support, features and design. Tool A scores 8.5, 5.5, 9, 6 and 7.5; Tool B scores 6, 8.5, 5, 8 and 5.5.
On a radar chart, Tool A’s polygon bulges towards Speed and Support, and Tool B’s towards Price and Features. In two seconds the room sees two different personalities: a fast, well-supported tool and a cheaper, feature-rich one. That’s the radar chart’s real strength: it turns a table of scores into a recognizable shape.
Now ask “how much better is B on price?” The radar chart can’t say. The grouped bars in the figure above show it immediately: 8.5 against 5.5. Use the radar chart to frame the trade-off, and the bars, or a simple table, to settle it.
When a radar chart works
- You're showing one item's profile, like a candidate's skills or a product's review scores, and the shape is the point.
- Every measure uses the same scale, ideally 0–10 or 0–100%.
- You're comparing two or three items at most, with clearly different colors or line styles.
- Higher is better on every axis. Mixing in measures where low is good, like price, makes the shape misleading unless you invert them.
When to choose bars instead
- When exact values matter. Spokes make values hard to compare precisely. Bars on a shared baseline don’t.
- When you have more than three items. Overlapping polygons turn into a tangle, the kind of web nobody wants to untangle in a meeting.
- When measures use different units. Revenue in dollars and satisfaction out of 10 can’t share rings without normalizing them first.
- When the area could mislead. A polygon’s area grows faster than its values, so a product that scores twice as high looks far more than twice as big.
How to make a radar chart that reads well
- Keep to five to eight axes, labeled in plain words.
- Start every axis at zero and use the same maximum.
- Order the axes meaningfully, grouping related measures, because order changes the shape.
- Show at most three series: one filled and accented, the others as outlines.
- Use a filled, semi-transparent shape for the main item and plain outlines for the rest, so overlaps stay readable.
- Label the key values directly, and give the chart a title that says what the shape means.
Whichever you choose, the rule is the same as for any chart: decide the one thing the reader should notice, then pick the form that makes it obvious. For a profile, that’s often a radar chart. For a precise comparison, it’s usually bars. Our guide to grouped and stacked bars covers the next decision.
Frequently asked questions
What is a radar chart used for?
Comparing an item's profile across several measures on the same scale: a product's scores on price, speed and support, a candidate's skills assessment, or a player's season stats.
Is a spider chart the same as a radar chart?
Yes. Radar chart, spider chart, web chart and star plot all describe the same thing: values on axes that radiate from a center, joined into a polygon.
Is a radial graph the same as a radar chart?
Often, but not always. People search for radial graph when they mean a radar chart, but the term is also used for radial bar charts, where bars are drawn around a circle. Check which one you need before you build it.
How many variables should a radar chart have?
Five to eight axes is the sweet spot. With fewer than five the shape says little; with more than ten the labels crowd and the polygon becomes hard to read.
Can I make a radar chart in Lightchart?
Not yet. Radar charts are coming to Lightchart. In the meantime, a grouped bar chart shows the same comparison precisely, and Excel and Google Sheets both include a basic radar chart.
Why does the order of the axes matter on a radar chart?
Because the polygon's shape depends on which measures sit next to each other. Reordering the axes can make the same scores look balanced or lopsided, so group related measures and keep the order fixed across charts.
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