We scraped every Airbnb listing in Washington, DC overnight. 12.3% of 1,030 listings pass 75/55 — and the ones that do are nearly identical to each other.
The verdict, up top
Moderate. Of 1,030 listings scraped on April 23, only 127 pass 75/55 — that's 22+ booked nights in the next 30 days and 16+ booked in the 30–60 day window. The median DC listing has 13 of the next 30 days booked. 12.3% of the market is performing; 87.7% isn't.
But this is a Moderate market with an unusually narrow winning path. The listings that pass aren't scattered randomly. They cluster in two corridors, they're run by owner-operators living on-site, and they share an amenity profile that high-rise condos and corporate-managed units can't replicate. If you're going to operate in DC, the data tells you exactly what you need.
Where every DC listing sits on the 75/55 grid
Each dot is one of 1,030 listings. Only the 12.3% in the top-right quadrant pass both thresholds — that's 127 listings.
Why DC isn't a normal STR market
Every other STR market we've measured is shaped primarily by demand. DC is shaped primarily by regulation, and you can't read the data without reading the law first.
DC issues two STR license types. A Short-Term Rental license requires the host to be physically present during every stay — effectively, you're renting a room in your own home. A Vacation Rental license allows whole-home rental but caps the property at 90 nights of unhosted use per year. Both require the property to be the host's primary residence, tied to the Homestead Tax Deduction. LLCs and corporate entities cannot hold the license. Condo HOAs must affirmatively permit STRs — and most don't.
That architecture explains the entire dataset. The 90-night cap means a Vacation Rental can produce at most ~25% calendar occupancy if the operator runs every legal night. The primary-residence requirement kills the "buy a condo, hire a manager, run it as Airbnb" investor playbook. The LLC prohibition disqualifies portfolio operators from running listings under their own name. What's left to compete at the top is one narrow archetype: the owner-occupied rowhouse.
DC's own estimate of the licensed STR universe is ~5,100 properties. AirDNA tracks 9,624. We scraped 1,030 with active calendars. The gap between those numbers is itself a finding — we'll come back to it.
What the calendars actually show
127 of 1,030 listings pass 75/55. The other 903 don't. Median next-30-day booked nights: 13. Median 30–60 day window: 9. Median 60–90 day window: 4. The median DC listing's calendar is roughly a third full and getting emptier the further you look.
The tier distribution makes the shape clearer:
| Tier | Listings | % of market |
|---|---|---|
| EXCEPTIONAL | 9 | 0.9% |
| PERFORMER | 13 | 1.3% |
| POTENTIAL | 92 | 8.9% |
| WATCH | 85 | 8.3% |
| AVOID | 801 | 77.8% |
| UNRELIABLE | 30 | 2.9% |
22 listings in the top tier, out of 1,030. That's a market where 98% of operators aren't building a viable business at the unit level. The path is rare and the formula is specific.
The AirDNA gap (and why their own data agrees with us)
AirDNA puts DC's market-wide occupancy at 58% with a Market Score of 58 ("Okay") — a moderately healthy market with room to enter. Pull on the thread and that picture comes apart from inside their own data.
Their listing count is 9,624. But by AirDNA's own breakdown, 55.9% of those listings require minimum stays of 30 nights or more. Stays of 30+ nights aren't short-term rentals — under DC's regulatory definition they're long-term residential leases, exempt from the STR licensing regime entirely. They're operators using Airbnb as a leasing channel, not competing for short-term-rental demand. Strip them out and the actual STR market shrinks to ~4,200 listings — about 44% of AirDNA's headline number. The "9,624 listings" framing overstates the competitive set by more than 2x.
The occupancy gap stacks on top. Our scrape shows median next-30-day calendar occupancy of 43% — 15 percentage points below AirDNA's 58% market average. Their estimate isn't wrong because their methodology is bad; it's wrong because their methodology is modeled. Our number comes from reading actual Airbnb calendars overnight. If you're underwriting a DC investment to a 58% occupancy assumption, you're underwriting to a number the listings themselves don't support.
Two peaks: cherry-blossom spring and federal-fiscal-year-end October
Monthly revenue index, normalized to January = 1.00. May peaks at 2.76× the winter low; October revives to 2.43× — a second peak unusual for non-coastal markets, driven by federal-fiscal-year-end activity.
Pattern #1 — Two corridors, and the metro tells you which streets
DC's winning listings concentrate in two geographic clusters. The first is dominant. The second is real.
Capitol Hill produces 32.4% pass rates. Of the 102 listings nearest Capitol Hill, 33 pass 75/55 — nearly 3x the citywide rate. Among the 22 top-tier listings in the entire dataset, 9 are anchored to Capitol Hill — 41% of the top tier from a neighborhood that holds about 10% of the market. The strongest individual metro stations by pass rate are all Capitol Hill stations: Eastern Market at 31.4%, Potomac Ave at 22.0%, Capitol South at 20.0%.
The 14th Street corridor — Logan Circle through U Street — is the secondary cluster. Listings within 0.5 miles of Logan Circle pass at 21.7%. Within 0.5 miles of 14th & U, 19.4%. U Street as a neighborhood passes at 15.8%. These rates aren't Capitol Hill, but they're materially above the 12.3% citywide baseline. The corridor draws a different operator profile — younger demographics, walk-to-restaurants positioning, smaller average unit — but it produces winners at roughly half the Capitol Hill rate.
A note on Dupont, which gets recommended often and shouldn't be: Dupont passes 75/55 at 4.0% — a third of the citywide rate. Dupont listings do generate bookings (review velocity is 1.94/month, above DC median), but the bookings don't fill calendars densely enough to clear 75/55. If you're underwriting Dupont, model it as a moderate-occupancy / higher-rate product, not a high-occupancy product.
Metro proximity is its own independent signal stacked on the corridor effect:
Pass rate roughly doubles for listings within walking distance of a metro station
Listings within a quarter-mile of a station pass at 18.1%. Beyond two miles, pass rate craters to 2.1%. Top-tier listings sit at a median 0.39 miles from a station; bottom-tier at 0.56 miles.
Pass rate roughly doubles between same-block and one-mile-plus, then collapses past two miles. Top-tier listings sit at a median of 0.39 miles from a station; bottom-tier listings sit at 0.56 miles. The rule of thumb: if the unit isn't a 5–10 minute walk to a station, the data says don't bother.
Pattern #2 — DC's top tier is independent operators, and the regulation is why
In most STR markets we measure, professional portfolio operators dominate the top tier. They have process, dynamic pricing tools, ops scale, photography, and the time to optimize. In DC, that group is stuck in the middle.
Half of DC's top tier is single-listing owner-operators. Portfolio operators are stuck in the middle.
The regulation prohibits LLC-held licenses and requires the property to be the host's primary residence. Portfolio operators (5+ listings) by definition cannot run a license under their own name — and the data shows what that produces. Top-tier Superhost rate is 95.5%.
Half of DC's top tier comes from hosts who operate exactly one listing. Across the 22 top-tier listings, there are 21 unique host names — David has two, every other operator has one. The mid tier, by contrast, is dominated by portfolio operators: Sojourn, Blueground, Home Sweet City, Luxury Bookings, the same names AirDNA lists as DC's largest. They're all there. They're just not at the top.
The reason is structural. The regulation prohibits LLC-held licenses and requires the property to be the host's primary residence. Portfolio operators running 50+ units in DC are by definition doing something the licensing regime doesn't accommodate. The operators who don't have to fight that friction — actual rowhouse owners with one license, one address, one Homestead Tax Deduction — get to run their listings without the operational and legal overhead. They build review velocity. They earn Superhost. They win.
This is the rare case where regulation is a feature, not a bug, for the small operator. The barriers that make DC unattractive to portfolio buyers are the same barriers that protect the unit-economics of the owner-occupier.
Pattern #3 — Review velocity tells you who's booking
Review frequency is the most reliable proxy for booking velocity we have, because reviews land on Airbnb's public record after every completed stay. The DC pattern matches the universal pattern — a clean 2.5x gap between top and bottom.
Top-tier DC listings earn 2.5× the monthly reviews of bottom-tier listings
Median total reviews tell the same story — top tier 143 reviews, bottom tier 39. DC's top tier is dominated by operators who have run the same unit for years and built a reputational moat.
Top-tier DC listings post nearly four reviews per month — roughly four completed stays — meaning a property booking out continuously and accumulating social proof on a steady cadence. Bottom-tier listings post 1.5 reviews per month: a stay every three weeks, give or take. That's a calendar that isn't filling.
Total reviews tells the same story. Top-tier listings have 143 reviews at the median; bottom-tier have 39. DC's top tier isn't dominated by new entrants — it's dominated by operators who have been running this exact unit for years and have built a reputational moat.
If you're evaluating a property, look at its review-per-month rate as a leading indicator. Below 2 per month and you're looking at a Watch or Avoid candidate. Above 3 per month and the listing is doing real volume.
Pattern #4 — What top-tier DC listings have that nobody else does: outdoor space and a front door
The amenity differential between top and bottom tells the cleanest single story in the dataset. Top-tier listings aren't stuffed with luxury features — they're stuffed with markers of a specific building typology. The rowhouse, not the high-rise condo, not the suburban detached home.
Five amenities clear the bar (≥10pp differential, present in at least 5% of either tier, monotonic across all three buckets):
| Amenity | Top % | Mid % | Bottom % | Gap |
|---|---|---|---|---|
| City skyline view | 31.8% | 8.7% | 6.8% | +25.0pp |
| Private patio or balcony | 45.5% | 35.9% | 26.7% | +18.7pp |
| Private entrance | 95.5% | 83.7% | 82.1% | +13.4pp |
| Free street parking | 72.7% | 62.0% | 60.4% | +12.3pp |
| Exterior security cameras on property | 77.3% | 87.0% | 87.9% | −10.7pp |
Top-tier DC is a private urban rowhouse — not a high-rise condo, not a suburban detached home
Five amenities clear the audit's ≥10pp / ≥5% / monotonic bar. Four point the same direction (top over-indexes on rowhouse markers); the fifth — exterior security cameras — under-indexes in top tier, the Ring-doorbell signature of detached single-family homes.
Read these together: top-tier DC is a private urban rowhouse with elevated outdoor space, its own front door from the street, dense-urban-street parking instead of a driveway, and no need for owner-installed exterior cameras because the unit itself is the building's facade.
The smoking gun for the typology theory is what's absent. Of the 22 top-tier listings in the dataset, zero have Elevator, Building staff, Gym, Pool, Doorman, or Concierge. Not "few." Zero. The entire high-rise condo product is structurally absent from DC's top tier — because condo HOAs refuse STR permission and the regulation enforces it. The legal short-term rental market in DC is a rowhouse market by exclusion.
DC also doesn't reward the suburban detached-house product. Free parking on premises — a marker of single-family homes with driveways — under-indexes outside the top tier. Outdoor security cameras, the Ring-doorbell signature of detached-house operators, over-index in bottom tier. DC's top tier isn't a McMansion in upper Northwest. It's a 3-bedroom rowhouse with a rooftop deck.
The data does not separate on bedroom count. Top, mid, and bottom all have a median of 3 bedrooms; pass rates are roughly flat across 1- through 5-bedroom listings. DC doesn't reward bigger or smaller. It rewards location. If you're picking a property here, the size of the unit is a second-order question. The street it sits on is the first-order question.
For agents and property managers: if your listing is a high-rise condo, you're probably not going to crack the top tier no matter what you do, because the regulation's downstream effects exclude the product class. If your listing is a Capitol Hill or Logan Circle rowhouse with a private balcony, the unit-level path to the top is unusually clear.
The operator paradox
The five largest property managers in DC's market (per AirDNA) are Sojourn (306 listings), Blueground (292), Timeshare-RoomPicks (264), Luxury Bookings FZE (133), and Home Sweet City (89). All five appear in our data. None concentrate in the top tier. Sojourn and Home Sweet City both show meaningful presence in mid and bottom buckets; their top-bucket presence is roughly zero.
The operators with the most resources are stuck below the operators with the least
DC's five largest property managers — Sojourn (306), Blueground (292), Timeshare-RoomPicks (264), Luxury Bookings FZE (133), Home Sweet City (89) — all appear in our data. None concentrate in the top tier. The regulation made size an operational cost rather than a competitive advantage.
The operators with the most resources, the most pricing sophistication, the most ops infrastructure — stuck below the operators with the least. A Capitol Hill homeowner running one listing as a Vacation Rental is, on average, outperforming a 300-unit corporate operator. That inversion doesn't happen in unregulated markets. It happens here because the regulation has made size an operational cost rather than a competitive advantage.
The takeaway for investors: don't pick DC because you can scale. Pick DC because you can't.
Who should still operate here
Three operator profiles, three different verdicts:
The Capitol Hill or Logan Circle rowhouse owner. You live in DC. You own (or are buying) a 2–4 bedroom rowhouse in one of the two corridors. You'll register it as your primary residence and run it as a Vacation Rental during travel windows or as a Short-Term Rental for hosted stays. Verdict: the path is clear. Build the listing for the rowhouse archetype — private patio or rooftop, private street entrance, full kitchen, walking distance to a metro station. Photograph the city view if you have one. Aim for 3+ reviews per month within the first 90 days.
The investor planning a corporate-owned condo. You're sourcing a DC condo for an LLC, planning to hire a property manager, expecting 58% occupancy on AirDNA's projection. Verdict: skip. The license you'd need can't be issued to your ownership structure. The condo HOA almost certainly prohibits the use anyway. Even where it's permitted, top-tier high-rise units are structurally absent from the data — you can't buy your way to the formula because the formula doesn't include your product.
The medium-term-rental operator. You're considering a 30+ night minimum-stay product, optimizing for traveling consultants, federal contractors, and graduate program rotations. Verdict: different game. This sits outside the STR regulatory regime and outside our 75/55 framework. AirDNA's data shows 55.9% of DC listings already running this play, so the segment is competitive — but it's also where the regulation creates the least friction. If your model works at 30-night minimums, DC is viable. Just don't underwrite it as STR.
- Register the property as your primary residence and pick the license that fits — Vacation Rental for unhosted travel windows, STR for hosted stays.
- Build the listing for the rowhouse archetype: private patio or rooftop, private street entrance, full kitchen, walking distance to a metro station.
- Photograph the city view if you have one. The +25pp skyline-view differential is the strongest single amenity signal in the dataset.
- Aim for 3+ reviews per month within the first 90 days. Below 2/month is a Watch or Avoid signal.
- The license you would need cannot be issued to your ownership structure — LLCs and corporate entities are barred.
- The condo HOA almost certainly prohibits the use anyway. Check bylaws before any deal math.
- Top-tier high-rise units are structurally absent from the data (zero of 22). You cannot buy your way to the formula because the formula does not include your product.
- Skip DC. Look at less-regulated markets where the corporate-condo playbook still works.
- This sits outside the STR regulatory regime — and outside our 75/55 framework.
- AirDNA shows 55.9% of DC listings already running this play. The segment is competitive but the regulation creates the least friction here.
- If your model works at 30-night minimums, DC is viable. Just do not underwrite it as STR — the calendars do not behave that way.
- Verify against your target neighborhood: corporate-housing demand concentrates near federal contractor corridors, not the rowhouse corridors.
What to do next
This is a Moderate market. The path through it is the rowhouse-on-a-corridor-with-a-Superhost-owner formula and only that formula. If your situation matches it, the data says build. If your situation doesn't match it, the data says move on — pretending you can be the exception is how the bottom tier gets built.
Verify the formula in your own market before you commit capital. Run STRecon on your target neighborhood and look at the top tier directly. If the top performers all share three traits, you're looking at a market with a real formula. If they don't, you're looking at a market that's just hard.
Methodology note: Analysis based on 1,030 active Airbnb listings in a Washington, DC market boundary, scraped April 23, 2026. Tier gradient analysis compared top-tier listings (n=22, Exceptional + Performer) against middle tier (n=92, Potential) and bottom tier (n=886, Watch + Avoid). Watch was folded into Bottom for DC per a market-specific decision; the Watch cohort represents underperforming-but-cleaner listings adjacent to Avoid, and merging maximized statistical power in the Bottom comparison group. Patterns reported meet a monotonic gradient requirement — they must show consistent direction across all three bands. Regulation context sourced from DC Department of Licensing and Consumer Protection (dlcp.dc.gov). AirDNA comparisons sourced from airdna.co/vacation-rental-data/app/us/district-of-columbia/washington/overview. Full DC market report: /market/washington-dc