The recorded restaurant no-show rate in the 2026 Resos No-Show Index is 2.33%. The benchmark covers 3,768,761 reservations at 2,417 restaurants between August 2025 and July 2026. It is based on recorded reservation outcomes, not a survey of what diners say they have done. You can read the full source data and method in the Resos No-Show Index 2026.
That number is useful because it has a defined denominator. It is not useful as a promise that every restaurant should sit at 2.33%. Your own rate depends on your restaurant mix, booking sources, service pattern, and how consistently staff record no-shows.
Key takeaways
- Recorded benchmark: 2.33% across 3.77 million eligible reservations and 2,417 restaurants.
- The riskiest patterns: 1 to 2 guests, bookings made 2 to 6 days ahead, dinner, Mondays, and January.
- Large parties are an inversion: 10+ parties recorded a 1.15% rate, compared with 2.63% for 1 to 2 guests, but more covers are exposed when a large party misses.
- Late cancellations matter: 56% of cancellations arrived within 24 hours of service or after it had started.
- Reminders show an association: Delivered SMS reminders were associated with a 16% lower recorded rate in a within-restaurant comparison.
Why restaurant no-show statistics disagree
Before choosing a benchmark, check three things: what is being measured, what the denominator is, and whether the result is recorded behavior or survey recall.
Recorded platform data
The 2.33% index rate counts a reservation when it has a final recorded outcome. The denominator contains recorded no-shows plus eligible reservations marked attended. Test and duplicate reservations, cancellations, unresolved bookings, and walk-ins are excluded. A no-show is a recorded no_show outcome, not an automatic timeout.
That produces a narrower and more reproducible measure than a broad industry estimate. It also has a limitation: a restaurant must record the outcome. Only 72.9% of eligible venues recorded at least one no-show, so the true rate may be higher than the recorded rate. Locations that do not consistently record no-shows can make a recorded rate look lower than the underlying behavior.
Platform figures and operator reports
Other published platform figures often land around 5% to 8%. OpenTable has published examples using a 5% no-show figure, while ResDiary’s UK and Ireland hospitality report reported 8% of bookings as no-shows in 2023, up from 5% in 2022. These figures are useful context, but they are not directly comparable with the index without knowing whether late cancellations, marketplace bookings, or different outcome rules are included.
Consumer surveys
Survey figures can exceed 20% because they usually ask diners whether they have ever missed a reservation, as in OpenTable’s consumer survey. That is a person-level memory measure. The index is a reservation-level recorded outcome. A diner who missed one booking five years ago is counted very differently in a survey than a restaurant recording one missed booking among hundreds of current reservations.
The practical conclusion is simple: use published figures to understand the range of measurement, then use your own reservation data to manage your operation.
Restaurant no-show rate by country
The country cut below includes the twelve countries that met the publication threshold of at least 30 restaurants and 1,000 reservations. Together, they represent 86% of the index dataset.
| Country | Recorded no-show rate | Reservations | Restaurants |
|---|---|---|---|
| Switzerland | 0.49% | 71,230 | 64 |
| Germany | 1.30% | 58,523 | 51 |
| Denmark | 1.31% | 28,606 | 30 |
| Australia | 1.41% | 251,804 | 213 |
| United Kingdom | 1.48% | 2,033,392 | 1,089 |
| Sweden | 1.75% | 26,984 | 35 |
| Spain | 2.18% | 104,047 | 65 |
| Georgia | 2.95% | 54,131 | 46 |
| Canada | 2.98% | 78,759 | 60 |
| United States | 3.17% | 309,604 | 316 |
| Italy | 4.71% | 118,488 | 45 |
| France | 5.88% | 101,795 | 60 |
Country differences are descriptive, not a ranking of guest reliability. They can reflect restaurant mix, booking sources, local booking habits, and how consistently staff record outcomes. The United Kingdom contributes 54% of all reservations in the index, so the overall result leans toward UK behavior.
No-show rate by party size
The smallest parties recorded the highest no-show rate. That is the opposite of the common assumption that the largest booking is always the most likely to disappear.
| Party size | Recorded no-show rate | Reservations | Restaurants |
|---|---|---|---|
| 1 to 2 guests | 2.63% | 1,860,642 | 2,399 |
| 3 to 4 guests | 2.13% | 1,150,708 | 2,379 |
| 5 to 6 guests | 2.28% | 414,338 | 2,331 |
| 7 to 9 guests | 1.73% | 187,425 | 2,231 |
| 10+ guests | 1.15% | 155,583 | 2,122 |
The rate is only one part of the decision. A party of ten has a lower probability of no-showing than a table for two, but ten covers are exposed when it happens. In expected lost covers per booking, a 10+ party carries roughly three times the risk of a two-top. Protecting large bookings with a clear policy, confirmation workflow, or waitlist plan can still make sense without treating every large party as a problem.
No-show rate by booking lead time
The index does not support the usual assumption that the earliest bookings are always the flakiest. The highest rate appeared in the 2 to 6 day window.
| Booked ahead | Recorded no-show rate | Reservations | Restaurants |
|---|---|---|---|
| Same day | 2.09% | 1,458,490 | 2,353 |
| 1 day | 2.40% | 602,325 | 2,364 |
| 2 to 6 days | 2.67% | 907,550 | 2,370 |
| 7 to 13 days | 2.57% | 343,507 | 2,306 |
| 14 to 29 days | 2.34% | 270,985 | 2,243 |
| 30+ days | 1.96% | 183,329 | 2,021 |
Lead time here means the number of restaurant-local calendar days between booking creation and the service date. For operators, the useful action is to test reminders and confirmation timing around the 2 to 6 day danger window rather than assuming a 30-day booking needs the most intervention.
The worst days, services, and months
The index points to a concentration of risk in particular service patterns:
- Monday is the worst day: 2.69%. Wednesday is the best at 2.09%.
- Dinner is riskier than lunch: 2.63% versus 1.84%, a 43% difference.
- January is the worst month: 2.62%. August is the best at 2.14%.
These are aggregate patterns, not rules for every venue. Use them as prompts for your own cut of the data. A Monday lunch at your restaurant may behave differently from the index average, especially if your booking mix is concentrated in one service.
Late cancellations are the hidden no-show problem
No-show reporting can understate the number of tables that become difficult to resell. The index contains 566,049 cancellations. Of those, 317,541, or 56%, happened within 24 hours of the booking or after it had started. A further 40,360 cancellations, or 7.1% of all cancellations, arrived after the start time.
| Cancellation timing | Share of cancellations |
|---|---|
| After the booking started | 7.1% |
| 0 to 2 hours before | 17.4% |
| 2 to 6 hours before | 15.0% |
| 6 to 24 hours before | 16.6% |
| 24 to 48 hours before | 11.6% |
| 2 to 6 days before | 17.4% |
| 7+ days before | 14.6% |
This distinction matters operationally. A no-show gives you no warning. A late cancellation gives you some warning, but often not enough to fill the table. Track both measures, and track how often released tables are backfilled from your waitlist.
What the data says about reminders
Reservations with a delivered SMS reminder recorded a 16% lower no-show rate than reservations at the same restaurants without a delivered reminder. The comparison covered 46,884 exposed reservations at 257 restaurants that had bookings in both groups.
That is an association, not a causal estimate. Restaurants that use reminders may also have better booking workflows, more engaged staff, or different guests. The result supports testing delivered reminders in your own operation. It does not support promising that SMS will reduce your rate by a fixed percentage.
The same caution applies to deposits and other no-show protection. Descriptive rates for protected and unprotected reservations are not enough to prove that the payment requirement caused the difference. Restaurant type, service, guest mix, and booking conditions can all create selection bias.
How to use these statistics in your restaurant
Start with a clean baseline:
- Define no-show consistently. Count only reservations with a final attended or no-show outcome.
- Exclude cancellations, unresolved reservations, duplicates, tests, and walk-ins from the denominator.
- Calculate the rate as no-shows divided by eligible reservations.
- Break it down by party size, local lead time, weekday, service period, and month.
- Track late cancellations separately, including whether they happen within 24 hours or after service starts.
- Test one operational change at a time, such as delivered reminders or a clearer cancellation path.
Do not set your target by copying a global benchmark. Set it by comparing your own rate across comparable periods and checking whether you are recovering released tables. A lower rate is useful, but a higher cancellation rate with successful waitlist backfill can be a healthier operational outcome than silent no-shows.
Frequently Asked Questions
What is the average no-show rate for restaurants?
Why are some published restaurant no-show rates much higher?
Which restaurant reservations are most likely to no-show?
How common are late restaurant cancellations?
Do SMS reminders reduce restaurant no-shows?
The bottom line
The best current recorded benchmark is 2.33%, but the more useful finding is that no-shows are unevenly distributed. Small parties, the 2 to 6 day booking window, dinner, Mondays, and January all sit above the overall rate in the index. Late cancellations add another layer of pressure, with 56% arriving within 24 hours or after service begins.
Use the benchmark to ask better questions of your own data. Define the denominator, separate no-shows from late cancellations, and test changes against a stable baseline. That produces a number your team can actually operate against.
Related guides: How to calculate and reduce your no-show rate | How to reduce no-shows at your restaurant | Do SMS reminders reduce no-shows? | Do large parties no-show more? | Waitlist management | No-show cost calculator