If you only skim one headline number, you can misread the Livermore market. You want a clear picture so you can time your move, price with confidence, or write a winning offer. In this guide, you’ll learn the key stats, how to read them in Livermore’s micro-markets, and practical steps to put the numbers to work. Let’s dive in.
The median sale price is the middle value of recent sales. It helps you see the market’s center and is less affected by ultra‑high or low sales. The average sale price is the mean and can swing when a few luxury homes close. In Livermore, look at both side by side, and compare the same property type and size so a change in mix does not fool you.
Price per square foot helps compare similar homes and track neighborhood changes. It varies with condition, lot size, and how square footage is measured. Exclude unique properties and adjust for condition when you use this stat in Livermore’s older central areas versus newer subdivisions.
Inventory is the count of active listings at period end, a snapshot of supply. Months of Supply (MOS) estimates how long it would take to sell current inventory at the recent sales pace. About 6 months is often considered balanced, while lower often favors sellers. Use rolling 3 to 12 month views to smooth short-term swings, and compare by price band.
DOM tracks days from listing to contract. CDOM counts total days across relists, which is more robust if a home is withdrawn and reintroduced. In Livermore, shorter DOM usually signals strong demand, but watch for pre‑marketing and listing tactics that can distort DOM.
The sale‑to‑list price ratio shows negotiating pressure by comparing the sale price to the last list price. Over 100 percent means buyers are bidding above list. Always confirm whether a ratio references the original list price or the last list price after reductions.
Comparing pending sales to active listings gives a fast read on demand versus supply. A higher pending/active ratio suggests a tighter market. Pair it with new listing counts and closed sales to see momentum.
Rising price reductions across similar listings can signal cooling or initial overpricing. Look for a pattern with longer DOM and higher MOS before calling a trend. Isolated cuts often reflect strategy rather than a broader shift.
A higher share of cash or investor purchases can speed up closings and reduce negotiation windows. Distressed sales, when present, can pull down averages. These details are often best seen in MLS and county recorder data.
Livermore’s 94550 and 94551 zip codes include distinct neighborhoods with different price behavior. Single‑family homes dominate, but townhomes and condos form their own lanes. Older central homes and newer planned communities often move on different timelines and at different price per square foot levels.
The Livermore Valley Joint Unified School District serves most of the city. School boundaries can influence buyer demand and price resilience. Keep your analysis neutral and compare neighborhoods by consistent property type and size to stay apples‑to‑apples.
Major employers, including Lawrence Livermore National Laboratory, support stable demand in the area. Livermore also serves commuters along the I‑580 corridor to Silicon Valley and the East Bay. Transportation updates and commute changes can shift buyer interest across neighborhoods.
In‑fill projects and new subdivisions can change inventory and temporarily lift averages due to new‑build premiums. When pricing or valuing a resale, do not mix it with new construction comps. Check city planning and building permit activity to understand near‑term supply.
California’s Prop 13 affects turnover, and rules like Proposition 19 can influence downsizing or move decisions. In some newer communities, special assessments can affect monthly costs. Factor these into your pricing and offer strategies.
Like much of the Bay Area, Livermore is seasonal: spring typically brings more listings and sales. Winter can be slower, but lower competition sometimes creates opportunities. Use year‑over‑year or rolling averages to see past the calendar noise.
Filter by property type, bed/bath count, size range, and lot size. Separate resales from new construction. Granularity by zip code, neighborhood, and price band matters in Livermore.
Use 3 and 12 month rolling stats to offset monthly volatility. Combine MOS, DOM, and sale‑to‑list ratio to form a clear narrative instead of relying on a single stat.
Small counts in a price band can mislead. If a segment has under 10 sales in a month, zoom out to a longer period or a larger area.
Active listings are stock. New listings, pendings, and closings are flows. Compare them together to read momentum and turn‑of‑the‑market signals.
Be explicit about whether your stat is monthly, 3 month, or 12 month trailing. Clarify if sale‑to‑list uses original or last list price.
Pending counts often lead closed sales by 30 to 60 days. Confirm unusual spikes or dips against county records to rule out reporting artifacts.
When you pair the right stats with Livermore’s local context, you can see momentum early and act with confidence. Whether you need pricing precision for a listing or a bidding strategy for a purchase, a disciplined read on MOS, DOM, and sale‑to‑list ratio will anchor your decisions. If you want a custom, micro‑market report and a clear action plan for your goals, the Jenn Collins Group is ready to help.