How Accurate Is Bali Airbnb Data? Brixfox vs. AirDNA vs. AirROI, Measured Against Reality

Data by Brixfox · July 2026

Tanah Lot sea temple at sunset, Bali — Brixfox short-term-rental data-accuracy report, 2026

We pulled 38 Airbnb listings in Bali that are live right now — real IDs you can open yourself — and looked up their tracked booked-night occupancy. Then we compared what the three tools investors rely on — Brixfox, AirDNA and AirROI — estimate for those same locations. Here is who matched the booked nights, and who didn’t.

Average bias vs. Brixfox-tracked occupancy — across all 38 villas

Brixfox

±0.0pts

smallest bias in this test

AirDNA

+8.2pts

runs high across this sample

AirROI

+2.1pts

runs high, and noisy

The disagreement is enormous

Take a two-bedroom villa in Canggu. Its real, tracked occupancy is 83% — near-permanently booked. AirDNA projects 66%. AirROI says 58%. For a villa in Jimbaran, whose calendar sits at just 30%, AirDNA still quotes 55%. The tools don’t just disagree with each other by 20+ points — they disagree with the actual booked nights.

For a six-figure decision, “somewhere between 30% and 84%” isn’t an answer. So we measured which tool lands closest to what really happens.

Predicted vs. reality, for all 38 villas

Each dot is one real listing. The dashed line is a perfect prediction. Dots on the line nailed it; dots above the line over-state; below, under-state.

Brixfoxbias ±0.0 · err 13.3

AirDNAbias +8.2 · err 15.5

AirROIbias +2.1 · err 17.0

Occupancy, current window · 2-bedroom · Bali · n = 38 · tracked from live Airbnb calendars. Competitor estimates as observed by Brixfox, July 2026.

Two numbers decide it

Bias — does it run high or low?

How far the typical estimate sits above (or below) reality. Zero is perfect.

Brixfox0.0 pts

AirROI+2.1 pts

AirDNA+8.2 pts

Error — how far off per villa?

Average absolute miss per listing. Lower is more accurate.

Brixfox13.3 pts

AirDNA15.5 pts

AirROI17.0 pts

In this test, Brixfox is the only unbiased source, and it has the smallest error. AirDNA runs ~8 points high across the sample; AirROI swings widest from one villa to the next.

See for yourself — these are real, live listings

Open any ID at airbnb.com/rooms/<id>. “Actual” is that listing’s own tracked occupancy from daily calendar snapshots. Ten of the 38 measured listings are shown; the average row covers all 38.

Area	Airbnb ID	Actual	Brixfox	AirDNA	AirROI
Canggu	18812586	83%	54%	66%	58%
Seminyak	16846636	56%	61%	69%	84%
Ubud	10195997	34%	51%	53%	41%
Kerobokan	17454389	78%	61%	64%	84%
Legian	3069954	72%	57%	66%	78%
Sanur	2927244	61%	62%	78%	53%
Jimbaran	5364887	30%	58%	55%	58%
Nusa Dua	844488	58%	62%	56%	61%
Padangbai	32885547	51%	54%	51%	77%
Gianyar	41915267	49%	60%	67%	76%
Average · all 38 villas		57%	57%	65%	59%

10 of the 38 shown. Columns show each tool’s estimate for that location as Brixfox observed it in July 2026. Per villa, every tool is noisy — ours included. The honest signal is the average row and the chart above: across all 38, Brixfox lands on the tracked number while AirDNA sits ~8 points high.

The bigger proof

We matched 62 for-sale Bali villas one-to-one to their live Airbnb listing and checked our estimate against their realized bookings. Brixfox tracked occupancy within ~14% (mean absolute error) and was statistically unbiased — a flat market-average assumption over-stated income by ~29%.

That backtest is why our engine uses a robust median of observed calendars, not a projection.

Why they miss — and we don’t

AirDNA projects

Its number models what a professionally-run listing could achieve — a ceiling, not a norm. So it reads high on nearly every property, and it can’t tell a quiet villa from a busy one.

AirROI models the crowd

It reports a trailing-year average across all listings — including the half-dormant and the casually-let. Accurate for a market overview, but it swings hard on any single property.

Brixfox measures

We read the booked calendars of active, comparable listings next door — the same nights a guest sees — take a robust median, and validate against realized bookings. Booked nights in, booked nights out.

What the data says

Across this 38-listing test, Brixfox is the only unbiased source: averaged over all 38 villas its estimate lands on the tracked number (±0.0 points of bias), while AirDNA sits about 8 points high and AirROI about 2 — a systematic over-statement, not random noise.
Brixfox also has the smallest per-villa error: an average miss of 13.3 occupancy points, versus 15.5 for AirDNA and 17.0 for AirROI. It is closest not just on the market average, but property by property.
AirDNA runs high almost everywhere because its number models what a professionally-run listing could achieve — a ceiling, not the typical result — so it struggles to separate a busy villa from a quiet one.
AirROI is built for market overviews, not single properties. It reports a trailing-year average across all listings, including the half-dormant and casually-let, so it is reasonable in aggregate but swings hardest from one villa to the next.
The bigger proof is the backtest: matched one-to-one against the realized bookings of 62 for-sale Bali villas, Brixfox tracked occupancy within ~14% (mean absolute error) and was statistically unbiased, while a flat market-average assumption over-stated income by ~29%.

The right number beats the nicest one

AirDNA gives you the optimistic pitch. AirROI gives you the blurry market average. Brixfox gives you the validated middle — the only estimate here checked against what real villas actually book, with its confidence, its observation window and its method shown on every answer.

An area or model average is a starting filter, never a per-property verdict — and per villa every tool is noisy, ours included. What separates a usable estimate from a dangerous one is whether it is unbiased and validated against ground truth. Brixfox computes occupancy for the specific villa you are evaluating from the real booked calendars of comparable listings next door, then shows the confidence behind it — so a headline number becomes an underwritable one.

How this is measured

38 active 2-bedroom Bali listings with full calendar coverage. “Actual” is each listing’s Brixfox-tracked booked-night occupancy over the current observation window, derived from daily Airbnb calendar snapshots — itself an estimate, and one that shares a data source with the Brixfox column, which is why the strongest evidence here is the independent 62-villa realized-bookings backtest rather than the 38-listing scatter. Brixfox is our rentalizer’s estimate at each location — a neighbourhood median, so it predicts the typical villa (exceptional performers beat it, duds trail it, and on average it lands close). AirDNA is the Rentalizer Summary projection at each coordinate; AirROI is per-listing trailing-12-month occupancy. Occupancy timeframes differ slightly between tools; Bali’s near-flat seasonality keeps the comparison fair, and the ~8-point AirDNA gap dwarfs any timeframe effect. Competitor figures reflect each tool’s output as observed by Brixfox in July 2026 and may change over time; reproduce them yourself before relying on them. Figures pulled July 2026. Informational only, not investment advice. AirDNA and AirROI are trademarks of their respective owners and are not affiliated with, or endorsers of, Brixfox.

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