Reading a ticket pacing curve
Total tickets sold tells you almost nothing. The shape of the curve between on-sale and doors tells you whether a show is fine, needs help, or needs help right now.
Danny Angove
Co-founder, Backline · 7 August 2026 · 4 min read
In short
- A pacing curve is cumulative tickets sold by date. Almost every useful judgement about a show comes from its shape rather than its current total.
- Three phases: the on-sale spike from people already waiting, a long flat middle, and a late run in the final fortnight. Each phase means something different.
- The flat middle is normal and misleads everyone. Panic in week four is usually panic about the shape of live ticket buying.
- The signal that matters is a stall: several consecutive days with no movement at a point where the curve should still be rising.
- Sell-through against capacity is the only comparable figure across rooms. Raw tickets sold cannot be compared between a 400 and a 2,000 capacity venue.
Most teams look at one number for a show: how many tickets have gone. It is the least informative number available, because it cannot tell you whether 340 sold is good news or a problem without knowing the capacity, the on-sale date and the shape of what happened in between.
The curve tells you all three.
The three phases
The three phases of a pacing curve
IllustrativePhase one, the on-sale spike. The first 48 to 72 hours, driven by people who already knew and were waiting: mailing list, followers, fans of the support act, the local promoter's list. This is the clearest read available on your committed audience in that market, because nobody in this phase needed persuading.
A weak on-sale means one of two things, and it matters which. Either the audience there is smaller than you thought, or they did not know. Check whether the announcement actually reached them: email sent, socials posted, local press placed, link working.
Phase two, the flat middle. Weeks of near-nothing. This is normal, it is what live ticket buying looks like, and it causes more unnecessary panic than anything else in the business. People do not decide about a Tuesday in November while it is still September.
Phase three, the late run. The final two weeks, often the final five days, and frequently a third or more of total sales. A show sitting at 55 percent with ten days to go is usually going to be fine.
Where the useful signal is
Since the middle is flat by nature, "sales are slow" is not information. Two things are.
A stall. No movement at all for several consecutive days at a point in the curve where there should still be a trickle. That is different from slow: slow is a shallow slope, a stall is a flat line. A stall four or more weeks out is the moment to act, because there is still time for local press, a support announcement, a targeted push or a radio drop to work.
A shape that does not match the market. If you are playing three cities and two have the same profile while the third is flat from the start, that third city is telling you something specific about your reach there rather than about ticket buying in general.
Slow, stalled, or fine
Illustrative| What you see | What it means | Do this | |
|---|---|---|---|
| Flat middle, shallow slope | Normal ticket buying | Nothing. Check again next week | |
| No movement for 7 days, 4+ weeks out | A genuine stall | Local press, support announcement, targeted push | |
| No movement for 7 days, under 2 weeks out | Late, options are narrow | Social push and list email. Discount last | |
| Weak on-sale, then normal shape | The announcement did not reach people | Check email, socials, link, local press placement | |
| One city flat while others pace | A market problem, not a ticketing problem | Look at whether you have evidence of an audience there at all | |
| 55 percent at 10 days out | Usually fine | Hold. The late run is a third of sales |
Sell-through is the comparable unit
Tickets sold is not comparable across shows. Sell-through, tickets divided by capacity, is.
- 340 in a 400 capacity room is 85 percent, an excellent story, and a candidate for a bigger room next time.
- 340 in a 2,000 capacity room is 17 percent, and needs a decision about production, papering or scaling the room.
This is why capacity has to be recorded per show even when nobody thinks it matters. Without it, none of the pacing analysis works and every comparison across a run is guesswork.
Pollstar's 2025 year-end analysis put the top 100 tours at 8.9 billion dollars from 67 million tickets, with a per-show average of about 2.5 million dollars and 19,000 tickets. Those are stadium economics rather than yours, and the useful part for a smaller run is the same discipline: measure against capacity, not against last time.
Getting the data
Three routes, in descending order of convenience.
An automatic ticketing feed. Where your ticketing partner offers one, daily totals arrive without anyone doing anything, and capacity and venue detail come with them. This is the version that actually gets used, because it does not depend on somebody remembering.
A box-office export. A weekly or daily CSV of cumulative totals per date. Works fine, needs a person.
Manual entry. A number typed in once a week. Better than nothing, and enough for stall detection, which is most of the value.
Whichever route, keep the figures aggregate. A pacing curve needs a date, a running total and optionally gross revenue. It never needs a buyer's name, email address or postcode, and an analytics tool that asks for those is creating a data protection liability in exchange for nothing. Ours rejects an upload whose columns look like buyer details, and names the offending column rather than silently importing it.
Asking about a run in one question
IllustrativeWhich Vela Court shows are behind, and how far out are they?
Data readget_live_showsget_ticket_sales
Four of the six upcoming shows have ticket data. Two need attention.
Glasgow, 6 weeks out, 34 percent sell-through, no movement for 9 days. This is the one I would act on first: it is a genuine stall with time to respond.
Leeds, 3 weeks out, 47 percent, still adding a few tickets most days. Slow rather than stalled.
Bristol at 78 percent and Manchester at 71 percent are both pacing normally for their stage in the curve.
Two shows have no ticket data connected, so I cannot say anything about them.
Illustrative example using a fictional project. The last line matters: the assistant reports which shows it has no data for rather than quietly leaving them out of the answer.
A weekly routine
Per show, once a week, four questions:
- Has it moved in the last seven days? If not, and the show is more than two weeks out, that is this week's job.
- What is the sell-through, and how does it compare to the same point in the curve for a comparable show?
- Is the pattern consistent with the other dates on the run, or is this one different?
- If it needs help, is there time for the thing you are proposing to work? Local press needs a fortnight. A social push works in days. Discounting is the last option and it teaches your audience to wait.
That takes about five minutes across a run, and it is the difference between finding a problem while it is solvable and finding it in the final week.
Common questions
- What is a ticket pacing curve?
- A chart of cumulative tickets sold by date between on-sale and the show. It has three phases: an on-sale spike from people already waiting, a long flat middle, and a late run in the final fortnight that frequently accounts for a third or more of sales.
- When should I worry about slow ticket sales?
- When the curve stalls rather than when it is slow. A shallow slope through the middle weeks is normal. Several consecutive days of no movement at all, four or more weeks out, is the point to act, because there is still time for press, a support announcement or a targeted push to work.
- Why is sell-through better than tickets sold?
- Because it is comparable across rooms. Three hundred and forty tickets is 85 percent of a 400 capacity venue and 17 percent of a 2,000 capacity one, and those are completely different situations. Sell-through requires capacity to be recorded per show, which is the field teams most often skip.
- Should ticket data include buyer details?
- No. Pacing analysis needs a date, a cumulative total and optionally gross revenue. Names, email addresses and postcodes add nothing to the analysis and make you responsible for other people's personal data.
Sources
- 1Pollstar, December 2025. 2025 Year End Business Analysis
- 2Spotify, 2026. Loud and Clear: takeaways
Danny Angove
Co-founder, Backline
Danny Angove is a co-founder of Backline. He works on the music business side of the platform: what managers, labels and independent artists actually need to see, and which numbers are worth arguing about.
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