First month for $1.Use codeGet started

Appreciation lean

Austin-Round Rock-San Marcos, TX

A repricing market where underwriting discipline matters more than growth narratives.

Last updated 2026-07-31

F32/100
High-caution marketF grade · 32/100 market scoreOnly worth deeper work when the specific deal is clearly better than the market average.

Austin still carries long-term demand credibility, but the public-market snapshot shows values and rents both under pressure. That makes it a better market for basis-sensitive buyers than for investors relying on heroic rent growth.

Analyze a property in this marketBack to marketsAverage deal analysis in Austin

Average deal benchmark

Average deal in this market

This is the quick market-level baseline for what a typical deal looks like before you underwrite a real address.

Typical priceVerified
$424,339Typical market home value
Typical rentVerified
$1,647Average monthly rent
Rent-to-valueEstimated
4.66%Gross annual rent divided by home value
1-year rent trendVerified
-0.9%Recent rent direction

Verified metrics come from sourced market files. Estimated metrics are derived from those inputs.

Strategy fit

What's working in this market

Austin-Round Rock-San Marcos, TX is classified as an appreciation market, but the current numbers point to a reset phase rather than easy momentum. The overall market score is 32/100, flagged as Higher caution, with typical home value at $424,339 and 1-year home value change at -5.2%. That price decline may create opportunity, but it also means investors need to be careful about entry price and assumptions.

Cash-flow support looks limited on the surface. Average rent is $1,647, rent-to-value strength is 4.66%, and the 1-year rent trend is -0.9%. Price-vs-rent pressure is -4.3%, which reinforces the idea that this is a basis-sensitive market: the deal may work when bought well, but the broad market numbers do not suggest generous rent coverage at typical pricing.

Which strategy this favors

This market currently favors basis-sensitive buy-and-hold investors more than pure cash-flow buyers, BRRRR operators, or flippers. The appreciation classification and price reset tag may appeal to investors willing to hold through volatility, but the 32/100 score, -5.2% home value change, -0.9% rent trend, and 4.66% rent-to-value strength all argue for cautious acquisition pricing rather than aggressive short-term resale or refinance assumptions.

Generated from this market's real Zillow-backed metrics only — not a recommendation, and not informed by facts about the city beyond the numbers shown above.

County snapshot

Local context inside the market

These counties add local context after the market screen. Use them to see where conditions look stronger or weaker before you underwrite a specific address.

County overlays are loading for this market.

Caldwell County · 62/100

Home value: $284,198Average rent: $1,585Rent-to-value: 6.69%

Bastrop County · 52/100

Home value: $359,509Average rent: $1,811Rent-to-value: 6.05%

Williamson County · 38/100

Home value: $403,016Average rent: $1,673Rent-to-value: 4.98%

Hays County · 28/100

Home value: $372,221Average rent: $1,554Rent-to-value: 5.01%

Sourced metrics

What the sourced market data says

Rating breakdown

How the screening score is built

Rent-to-value strength50% weight
4.66%Higher rent-to-value ratios improve the first-pass screen.
1-year rent trend25% weight
-0.9%Positive rent growth improves the score.
Price-vs-rent pressure25% weight
-4.3%When home values run ahead of rents, the score gets penalized.

Underwriting

What this means for deal analysis

  • Treat metro-level rent softness as a warning against aggressive pro forma rent growth.
  • Use longer hold and slower exit scenarios because supply-heavy counties can create more negotiation room.
  • Look for counties or submarkets where price resets outpaced rent declines rather than assuming Austin works everywhere.
Verify before you buy

Market averages are a screen, not a verdict

  • Verify whether the listing county is outperforming or lagging the broader Austin snapshot.
  • Run a downside case with flat rent for 12 months before trusting the deal.
  • Check insurance and tax assumptions separately because the metro average does not capture parcel-level drag.
Methodology

How this page is built

  • Numeric market metrics are pulled from Zillow Research metro files at build time, not copied by hand.
  • County context uses Zillow Research county files plus Census TIGERweb county polygons so the local snapshot maps to real boundaries.
  • The overall market score is a transparent screening heuristic built from rent-to-value, 1-year rent trend, and price-vs-rent pressure.
  • Unsupported metrics such as days-to-pending are intentionally removed instead of scraped or inferred.

Zillow Research ZHVI metro file

Metro home values as of 2026-07-31.

Open sourceAccessed 2026-09-15

Zillow Research ZORI metro file

Metro rents as of 2026-07-31.

Open sourceAccessed 2026-09-15

Zillow Research ZHVI county file

County home values used for the supporting county snapshot.

Open sourceAccessed 2026-09-15

Zillow Research ZORI county file

County rents used for the supporting county snapshot.

Open sourceAccessed 2026-09-15

Census TIGERweb county polygons

Official county boundaries used to render the city-level map footprint.

Open sourceAccessed 2026-09-15

Zillow research definitions

Reference definitions for Zillow housing and rent market metrics.

Open sourceAccessed 2026-09-15
FAQ

Common questions

Why does this page show a score at all?

The market score is a transparent screening heuristic built from Zillow Research home-value, rent-trend, and rent-to-value inputs. It is not a buy recommendation or a substitute for address-level underwriting.

What do the county snapshots represent?

The page shows county-level snapshots inside the market footprint so you can see where conditions look stronger or weaker. Treat them as supporting context, not automatic buy boxes.

What should I do after reading this page?

Use the page to decide whether the market deserves deeper attention, then run a real property-level analysis inside InstantlyAnalyze before making an offer.