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Event No-Show Rate: Formula, Benchmarks, and Forecast

How to calculate an event no-show rate from your door list, cited free vs paid benchmarks, a registration-weighted attendance forecast, and a free CSV log.

An event's no-show rate is the share of registered seats that never checked in: (registered − checked in) ÷ registered. Measure it from your own door list after every event, split by paid and unpaid seats, and within a season you'll have a show rate to multiply against next month's registrations. That number sets the catering order, the door staffing, and how far, if at all, you can sell past the room.

The formula, and what counts as a no-show

No-show rate
(registered seats − checked-in seats) ÷ registered seats

Count seats, not registrations: a family of five on one registration is five seats. A cancellation before the door opens comes out of registered, and a refund is a cancellation. A walk-up who never registered isn't in the formula; count walk-ups separately.

The complement is the show rate, checked in ÷ registered, and that's the number you'll carry forward. A 12% no-show rate is an 88% show rate. On one event it's a fact about that night. Across a season, split by ticket type, it's a forecast.

Measure it from your own door list

Start with the last event that already happened. You need seats registered when the door opened and seats checked in when it closed, per event and per ticket type. Paid and unpaid is enough to start.

Labor Day Cruise, last week's sailing
Seats registered
150 (the sample season's sold count; use yours)
Checked in at the dock
131 (yours comes off the door list)
No-shows
150 − 131 = 19 seats
No-show rate
19 ÷ 150 = 12.7%
Show rate
131 ÷ 150 = 87.3%

One sailing is a data point, not a rate. Log it; the rate is what the log says after eight or ten of them.

Splitting by segment is where the number earns its keep. The registration list in the free app carries a quantity, a paid flag, and a check-in flag on every entry, so a list filtered to one event is the whole input. Here's the sample list for the Friday Sunset Cruise, read as if the boat had sailed.

Friday Sunset Cruise, the sample registration list
Registrations
5, covering 14 seats
Paid seats
Kelly Hammel 2, Marcus Bell 4, Priya Raman 2, Dana Whitfield 1 = 9
Unpaid seats
The Okonkwo family, 5
Checked in
Kelly Hammel and Marcus Bell, 6 seats, all paid
Paid no-show rate
(9 − 6) ÷ 9 = 33%
Unpaid no-show rate
(5 − 0) ÷ 5 = 100%
Overall no-show rate
(14 − 6) ÷ 14 = 57%

Fourteen seats is far too few to trust: one family of five moved the overall rate by 36 points. Keep the split on every event, then pool each segment across events until it holds a few hundred seats.

Benchmarks: free events vs paid events

Published figures are a sanity check for your first season, not a substitute for your log. Two things hold across every source below: free events lose far more registrants than paid ones, and the gap between a good night and a bad one is wide enough that an average alone will mislead you.

SourceWhat was measuredFigure
Pheedloop, Event Data Lab Report #05 (April 2026)Median no-show, 1,070+ in-person events with check-in dataAbout 20% overall; about 28% for free events (389 events), about 17% for paid (683 events)
Same report, the bad nights25th percentile, and events losing over half their expected attendance47% no-show for free events vs 32% for paid; 22% of free events lose over half, vs 14% of paid
Same report, by sizeMedian no-show by attendee countAbout 32% at 10 to 49 attendees, 23% at 50 to 149, 19% at 150 to 499, 18 to 19% above 500
Eventbrite UK organizer roundup (April 2021)Organizers' own dropout figures for free eventsQuoted rates run 30% to 50%; one plans for 50% dropout on every free event. One over-allocated 50 to 60 tickets on a 400-person target and landed near 85% attendance
Livestorm, 2026 Webinar Benchmark ReportShow-up across 33,786 webinar sessions and 7.06 million registrations in 202551.3% average show-up, a 48.7% no-show rate for mostly free online sessions

What isn't in that table is a paid no-show rate by ticket price. None of these sources splits paid events by price band, so the gap between a $35 class and a $175 tournament is something only your own log can show. The free-versus-paid gap is about commitment, so treat a registered-but-unpaid seat as its own segment even at the same price; it behaves like a free seat until the money clears. If you run free events and the no-shows hurt, the lever is a small commitment at registration, a refundable deposit or a nominal ticket, with the show rate logged before and after.

Forecasting attendance from registrations

Once the log has a show rate per segment, the forecast is a weighted sum: split current registrations into the segments you measured, multiply each by its historical show rate, and add them up.

Expected attendance
sum across segments of (seats registered in the segment × that segment's historical show rate)

Use your own pooled show rate as soon as you have one. Until then, borrow the benchmark medians above and label the forecast as borrowed.

Fall Sporting Clays Classic, 26 days out
Seats sold so far
142 of 200 (sample season)
Paid seats
134 (your split; the sample list's teams pay when they register)
Registered, unpaid
8 (your split; J. Reinhart's 2 unpaid seats are among them)
Paid show rate from your log
94% (your number)
Unpaid show rate from your log
60% (your number)
Expected attendance
134 × 0.94 + 8 × 0.60 = 126 + 4.8, about 131 shooters

Hold it loosely this far out. Registrations arrive late: Livestorm's 2026 report found 49.6% of webinar registrations land in the final week and 15.3% on the day itself. It's webinar data, but the shape is the point: re-run the forecast weekly.

Using the forecast: catering, staffing, and the oversell decision

  • Catering: order to the forecast, then round toward the cheaper mistake. On a dinner cruise, running out costs more, so round up; where leftovers do, round down.
  • Door staffing: time one check-in at your own door, multiply by expected attendance, and divide by the minutes you'll let people queue. Staff to expected attendance, not registrations.
  • Waitlist releases on a sold-out event: release a seat when a cancellation comes in or a no-show is confirmed at the door, unless you're deliberately overselling.

Should you oversell to cover no-shows?

Sometimes, and the rule is short. Oversell only when the capacity is a preference rather than a legal or safety limit, when turning someone away costs less than an empty seat, and when your log is long enough to show your best-attended night. Size the oversell to the highest show rate you've recorded, so even a full night fits.

Maximum oversell
capacity ÷ highest show rate you've recorded − capacity

A vessel's certificate of inspection, a fire marshal's occupancy number, or a count of shooting stations is a hard ceiling. Don't oversell past it; run a same-day standby line and fill confirmed no-shows from it.

Saturday Skyline Dinner Cruise, sold out at 120
Capacity
120 seats, a vessel limit (sample season)
Paid show rate from your log
87.3% median, 96% on your best night (your numbers)
Expected empty seats at the median
120 × (1 − 0.873), about 15
Arithmetic oversell ceiling
120 ÷ 0.96 − 120 = 5 seats
What to actually do
Nothing past 120. The certificate is the cap, so those 15 likely-empty seats go to a standby line at the dock

A free event in a room with headroom runs the same arithmetic against a softer ceiling; the Eventbrite UK over-allocation in the table above is that case.

A reminder sequence that lowers the rate

Reminders don't change who committed; they change who forgot. Treat the sequence below as a schedule to test: run it for a season, compare each segment's show rate before and after, and keep the touches that moved it. Published effect sizes come mostly from medical scheduling, so measure your own.

TouchWhenChannelWhat it carries
ConfirmationOn registrationEmailDate, time, address, what to bring, an add-to-calendar link, and how to cancel. A cancellation is a seat you can resell; a no-show isn't.
One week out7 days beforeEmailDetails again plus anything new. Ask unpaid registrants to pay now or release the seat.
Day before24 hours beforeText with consent, otherwise emailShort: time, address, what to do if they can't make it.
Morning of2 to 4 hours beforeTextOne line: doors open at this time, reply if you're running late. Replies feed the standby line.

Track it every event

  1. Close the door list after each event and record seats registered, seats paid, seats checked in, and paid seats checked in. Seats, not registrations.
  2. Compute the no-show rate overall and per segment, and note free or paid, ticket price, and capacity so you can sort the log later.
  3. After eight to ten events, pool each segment and take its median show rate and its highest. The median feeds the forecast; the maximum sets the oversell ceiling.
  4. Before each upcoming event, split current registrations into the same segments, multiply by the segment show rates, and set catering, staffing, and standby counts from the result.
  5. Keep the log in the no-show log template below, or start in the registration list: enter each registration with its quantity and paid status, check people in at the door, and read registered and checked in off the event summary.

Questions people ask

What is a good no-show rate for an event?

Lower than your own last season. For a sanity check, Pheedloop's April 2026 analysis of 1,070+ in-person events put the median at about 20%, paid events near 17%, free events near 28%, and small events of 10 to 49 people around 32%. A free event near 50% is where several organizers in Eventbrite UK's 2021 roundup said they plan to be: a reason to add a commitment step, not to panic.

Should you oversell an event to cover no-shows?

Only when the capacity is a comfort limit rather than a legal or safety one, when a turned-away guest costs less than an empty seat, and when you've logged enough events to know your best-attended night. Size the oversell to that night's show rate, never the average. Where a certificate of inspection or an occupancy number sets the cap, don't oversell; run a standby line instead.

How do you count a no-show when one registration covers several seats?

Count seats. A registration for four that arrives as two people is two no-shows, not zero and not one. That's why the log tracks seats registered and seats checked in rather than names, and why the registration list carries a quantity on every entry.

Skip the spreadsheet

The free registration list does this math for every product you enter, in your browser, with no account. Who's coming, who's paid, who's checked in. The door list that updates as people arrive.

Open the registration list

Updated September 5, 2026 · Written by Upforge, Cincinnati

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