Data-backed market note · August 2026
Updated: September 30, 2026. Published: September 29, 2026.
Counts and shares of pending sales that fell out of contract in Richmond city, Henrico and Chesterfield.
Broad Richmond-area headlines can hide important differences among Richmond city, Henrico County and Chesterfield County. This article keeps those jurisdictions separate and answers one narrow question with one defined public dataset.
The reader question
How often did pending home purchases cancel across the three jurisdictions in August 2026?
The short answer
Chesterfield had the highest cancellation count and share in August 2026, while Henrico had the lowest share. The county pattern does not identify the cause of a failed contract, so inspection, financing, appraisal, title and mutual-release scenarios remain separate questions.
| Measure | Richmond city | Henrico County | Chesterfield County |
|---|---|---|---|
| Purchase cancellations | 23 | 28 | 74 |
| Share of pending sales canceled | 10.3% | 8.0% | 15.6% |
| YoY change in cancellation share | -2.7 percentage points | -2.4 percentage points | 5.4 percentage points |
Why the distinction matters
A market statistic describes a defined group of listings or homes over a defined period. It does not describe every neighborhood, price band or property type. The useful move is to carry the county signal into a smaller comparison set rather than treating it as a verdict.
Decision context
Chesterfield had the highest cancellation count and share in August 2026, while Henrico had the lowest share. The county pattern does not identify the cause of a failed contract, so inspection, financing, appraisal, title and mutual-release scenarios remain separate questions. This is a dated county-level signal, not a property-level recommendation or forecast. Before acting, compare the home with same-type current competition and recent closed sales, then account for location, condition, concessions, association terms, financing and timing. The source period, geography and property-type definition should stay attached to the conclusion so a broad market statistic is not mistaken for proof about one home. It does not replace appraisal, inspection, lending, tax, legal, association, insurance or title advice, and it does not establish why a listing changed, whether a contract will close, or how any individual buyer or seller should proceed.
For buyers
A disciplined offer should preserve a clear financing file, realistic cash-to-close plan and property-specific diligence. Competitive pressure is not a reason to ignore risks that can prevent closing.
Build a property file before changing price or terms: recent same-type sales, current substitutes, listing and price-change history, condition, disclosures, association records when relevant, financing constraints and the cost of the protections you are considering.
For sellers
Backup-offer strategy, complete disclosures, pre-listing maintenance decisions and careful review of financing strength can reduce uncertainty, but no county statistic guarantees a contract will close.
Refresh the evidence immediately before launch and again if the response is weaker than expected. The best adjustment is tied to the competitive set and buyer feedback, not to a metro headline or a round-number target.
What this analysis does not prove
The public dataset counts cancellations and their share of pending sales; it does not provide reason codes or determine fault.
It also does not predict the outcome of a particular listing, establish causation, include unreported concessions, or replace legal, tax, lending, inspection or appraisal advice.
See the full report
August 2026 Home-Purchase Contract Cancellations includes the source table, geography, period and methodology note.
Source: Redfin Data Center. Data period: August 2026. Prepared September 29, 2026 from public data.
Frequently asked questions
How often did pending home purchases cancel across the three jurisdictions in August 2026?
Chesterfield had the highest cancellation count and share in August 2026, while Henrico had the lowest share. The county pattern does not identify the cause of a failed contract, so inspection, financing, appraisal, title and mutual-release scenarios remain separate questions.
Can this county-level result predict the outcome for one property?
No. The public dataset counts cancellations and their share of pending sales; it does not provide reason codes or determine fault. A property-specific decision still requires current same-type comparisons, condition, terms and location.
Michela Worthington