Phuket residential market — supply, pricing, yields

Independent multi-source scrape: 2,369 sale records (Properstar + FazWaz) across 24 submarkets · 853 rental records (760 with nightly USD ADR) from Booking shoulder-season scrape (22-25 Sep 2026).

Sale records

2,369

across 24 submarkets

Median $/m²

$5,239

Choeng Thale (top)

Top STR net yield

9.3%

Mai Khao · Apartment STR

Top LTR net yield

7.3%

Rawai · Villa LTR

Overview Sale Pivots Rentals + Yields

Sale-side pivots →

Submarket × Type × Beds crosstabs. Median + mean $/m² (flag rows = >30% gap). Submarket ranking by $/m². Click any n to drill into underlying listings.

5 pivots · 2,369 records · 24 submarkets

Rentals + Yields →

Separate STR (Booking nightly) and LTR (12-mo lease) yields, plus side-by-side head-to-head comparison showing which strategy wins per submarket × type × beds.

STR + LTR + sensitivity + verdicts

Read order. Start with sale-side pivots to anchor on $/m² by submarket. Then open rentals + yields to see which submarkets convert that supply into cash flow. The honest verdict block on the second page maps "sweet spot · best cell · yield crusher · marketing-claim audit".

Floating nav (right edge) jumps between sections within each report and switches between pages. Drilldown buttons (every n) open the underlying listings.

Methodology. Sale-side: Properstar live listings + FazWaz project-directory entries (entry + top units, sized by type heuristic). Rental: Booking dated (3-night mid-Sep window) + no-date scrapes, parsed and deduped. Yield: ADR median × 365 × occupancy ÷ price median for sale, with operator split / opex / tax for net. Year-2 stabilised; Year-1 realised typically 50–70% of paper.

Premium > $500/night villas (branded Marriott / Banyan / Twinpalms) are systematically under-sampled on Booking — yield sensitivity panel models +30–80% ADR uplift for that segment.

Methodology + caveats inline on each report. Code: pivot_phuket.py, build_html.py, parse_and_unify_rentals.py.