Which US city has the highest Airbnb estimated occupancy? Seattle, WA at 40.3%, against 29.3% in the median of 34 US markets

What does the figure count?

Estimated occupancy is Inside Airbnb's own review-based model, run by UpRev with each region's average stay. It is an estimate built from reviews, not a count of bookings, and it reads low because a review follows check-out.

Estimated occupancy: Inside Airbnb's own review-based model with its own constants. Each review in the window stands for two stays (a 50% review rate); each stay lasts the average stay Inside Airbnb sets for the region, or the listing's minimum stay if longer; the nights are divided by the nights in the window and capped at 70%. The window runs from 1 July to the day before the snapshot; reviews follow check-out, so the last weeks undercount and the estimate reads low. UpRev checks each region's average stay against Inside Airbnb's own per-listing estimate, which rounds the nights and caps them at 255 a year; a region's stay must match at least 99% of listings, and the table below gives the measured match.

How should the ranking be read?

Read the ranking as a comparison of review activity per bookable home, not of revenue. A market where guests review more often, or stay longer than its average stay assumes, rises in this table without a single extra booked night, and a market of long minimum stays reads differently from one of weekend stays.

What does the ranking not say?

It does not say what a home earned, what a night was paid, or which nights were booked: the model sees reviews, and every estimate in it is capped by the model itself.

Which markets are left out of a cell?

Floors: every figure of a cell over fewer than 10 homes is left blank, its counts included. A price percentile needs at least 30 homes with a near-term quote; a smaller class shows "too few".

Why do the collection days matter?

Inside Airbnb collects each region on its own days, so the regions' calendars were read at different distances from each month ahead, and a gap in open nights between two regions partly reflects the days each was collected. Every row carries its own snapshot date, and the method page sets out the rest.

What can this data not show?

• Prices by month ahead: the calendar files carry no prices, only one quote per listing.
• Year-on-year change: the earliest snapshot Inside Airbnb offers free for any of the regions is from December 2025.
• Booked against blocked nights: the calendar does not separate them.
• Paid rates or revenue: the prices are quoted rates, and this benchmark makes no revenue estimate.
• Earlier quarters: each region is compared with its June 2026 snapshot only.
• Causes: the figures describe listings, not the rules, events or seasons behind them.

More rankings and comparisons

• Airbnb Nightly Price by City
• Airbnb Open Nights by City
• Airbnb Market Comparison: every market side by side
• Airbnb Market Data: every market's own page