Forecast actual attendance by ticket type, event type and day of week.
Type + ticket mode + day-of-week is the bulk of the prediction.
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Paid-ticket events no-show at 2–8%. Free RSVPs no-show at 30–50%. Comp tickets and guest lists no-show at 25–40%. Monday events no-show 15% more than their baseline; Saturday events 15% less. For free-RSVP events, you can safely over-book by 60–90% of capacity depending on baseline; Ticket Fairy\'s waitlist feature handles paid-event conversion of no-shows automatically.
Conference, meetup and RSVP organizers planning around confirmed count routinely end up operating at 50–70% of expected attendance. The failure mode is always the same: they confirmed 400, budgeted for 400, ordered catering for 400, and 240 showed up. The venue looks empty, the speakers play to a half-room, the vendor booths under-convert, and it reads as a failed event even when attendee satisfaction was high.
No-show is predictable. Once you know the ticket type and event type, you can forecast attendance within ±5% of actual. Then you plan around the forecast, not the confirmed count.
The tool uses these benchmarks, derived from industry operator surveys and ticketing-platform aggregated data. Each cell shows the typical low / middle / high estimate:
| Event type | Paid ticket | Free RSVP | Comp / guest list |
|---|---|---|---|
| Club / EDM | 3–8% | 35–55% | 20–40% |
| Concert / tour | 2–5% | 30–50% | 20–40% |
| Festival | 5–10% | 30–50% | 25–45% |
| Conference | 10–25% | 30–50% | 25–45% |
| Theatre / performing arts | 3–6% | 25–45% | 20–40% |
| Comedy | 3–7% | 30–50% | 20–40% |
| Networking / meetup | 10–28% | 40–60% | 25–50% |
Paid-ticket no-show is driven primarily by scheduling conflicts and illness — a 3% baseline is really "random life events." Free-RSVP no-show is driven by commitment softness (no wallet opens, no reminder, nothing lost if you don\'t show). Conference no-show is disproportionately high because many registrants are sent by employers, and several-day multi-session formats make partial attendance look like no-show in the data.
Events on days that compete with other commitments no-show more:
Walk-up is disproportionately under-planned. For event types where walk-up is significant, it\'s often 10–25% of total attendance:
Walk-up has a pricing implication. If you\'re genuinely a sell-out-prone event, pricing walk-up at a premium (10–20% above advance) generates meaningful incremental revenue and discourages the behaviour in a controlled way. If you\'re not sell-out-prone, walk-up pricing should match advance to not discourage an easy revenue tail.
Free networking event, 300-cap venue, Tuesday. Networking baseline free-RSVP no-show: 50%. Tuesday multiplier: +10% → 55%.
Action: open RSVP for 600, close once that\'s filled. Running a waitlist above 600 gets you an additional 50–80 attendees at the door, because some confirmations drop out on the day and the waitlist converts walk-in.
For free events, the "safe over-book" calculation (using a normal approximation to the binomial distribution, with a 1.65 σ margin for 95% confidence) is the standard mathematical approach. For paid events, the standard move is a waitlist-plus-refund model: you over-sell by the expected no-show percentage, waitlist anyone who wants in, and refund no-shows automatically so the P&L balances.
Conference organizers typically run tighter: they plan catering and space against a 15% no-show forecast (well below free-RSVP baselines) because registration has already filtered for commitment. They then run an aggressive reminder cadence (T-7, T-3, T-1, T-0) to tighten the no-show number further.
For free-RSVP events the safe over-book number solves:
n × (1 - p) + 1.65 × √(n × p × (1-p)) ≤ capacity
where n is confirmed count and p is the no-show rate. The 1.65 σ corresponds to a one-sided 95% confidence interval — i.e., a 5% risk that actual attendance exceeds capacity. For events where over-capacity is a hard fail (fire-marshal enforced), use 2.33 σ (99% CI) instead. The tool uses 1.65 σ as default.
For paid tickets, no-show runs 2-8% and you've been paid, so the sunk cost is lower. For free RSVPs (30-50% no-show), conferences (10-25%), and comp tickets (25-40%), it's the single biggest driver of half-empty rooms.
For free-RSVP events specifically, you can confirm more attendees than capacity and trust the no-show rate to bring the room size back to capacity. The tool suggests the over-book count that keeps the risk of actually exceeding capacity below 5%.
Genre-dependent. Club and comedy events have high walk-up volume (10-25% of final attendance). Conferences and ticketed festivals have almost none. The tool estimates volume by event type and day-of-week.
Yes for any event that might sell out. A waitlist turns no-shows into revenue and signals scarcity to late buyers. Ticket Fairy supports waitlists natively; this tool tells you roughly how deep your waitlist needs to be.
Reviewed and updated April 2026 by the Ticket Fairy events data team. Benchmarks in this tool are directional — for real-time analytics against your own event history, use Ticket Fairy Intelligence.
Ticket Fairy powers ticketing, marketing and analytics for thousands of events worldwide. The tool above is a taste — the real advantage kicks in when benchmarks run against your own live event.
