We aggregate publicly available listing signals and track availability calendars to infer bookings, rates, and performance trends. We also incorporate user inputs (e.g., expenses) for property-level models and enrich with structured market data where available.

We monitor calendar changes over time. A date that flips from "available" to "unavailable" is treated as a likely booking. Because last-minute bookings can be missed between data collection cycles, we apply a documented adjustment factor to occupancy. Revenue is modeled primarily as ADR × booked nights, with quality controls to flag outliers.

Market metrics are updated regularly (typically monthly), with many calendars checked weekly. Regulation pages are reviewed and refreshed on a recurring cadence and when laws change.

Different platforms use different inputs (data collection frequency, filters for blocked vs. booked, outlier rules, supply definitions). Chalet emphasizes transparent, investor-practical metrics and publishes methodology notes so you can understand how figures are derived.

Yes. We provide MTR context and data points within relevant market dashboards where available, since many investors blend STR and MTR strategies.

Hundreds of STR markets across the U.S., with coverage expanding. Start at Airbnb Market Analytics and drill into individual cities.