You Want the Schools. But Can You Get the House Too?

Yes—but the bigger question is how many chances you would have had.

From January 1 through October 5, 2026, 10 of 146 qualifying Lindbergh single-family home sales closed for $250,000 or less. That’s 6.8% of the market we analyzed.

So $250,000 did buy homes in Lindbergh.

But it put a buyer into a narrow part of the district’s market.

At $300,000, the number increased to 32 sales, or 21.9%.

At $400,000, it increased to 76 sales, or 52.1%.

That’s the difference between asking “Can I buy there?” and asking “How much of the market can I actually shop?”

A budget can technically work and still leave you waiting for a house you actually want.

Read the full Lindbergh Schools buyer guide

It bought a meaningful part of the market—but not most of it.

In the study period, 83 of 285 qualifying Mehlville single-family home sales closed for $300,000 or less. That’s 29.1%.

At $350,000, the picture changed: 143 sales, or 50.2% of the market, closed at or below that price.

That $50,000 difference didn’t simply buy a little more house.

Historically, it moved the buyer from shopping less than a third of the district’s closed sales to reaching about half of them.

Read the full Mehlville School District buyer guide

In this dataset, $300,000 reached 74.6% of Affton’s qualifying sales and 29.1% of Mehlville’s.

That doesn’t make one district better.

It means the same budget occupied a very different position in each housing market.

A $300,000 buyer in Affton was shopping across most of the 2026 closed-sale market we analyzed.

A $300,000 buyer in Mehlville was shopping below the middle of the market.

That’s the kind of difference a district median alone can hide.

Among homes that closed for $250,001 to $300,000 in 2026, Ferguson-Florissant gave the most house: a median of 2,051 square feet at $136 a square foot. The runner-up was Hazelwood, at 1,944 square feet and $143. Maplewood-Richmond Heights gave the least, 1,088 square feet at $241. The newest homes were in Valley Park, built 1993 on median.

Here, “what $300,000 buys” means the homes that closed between $250,001 and $300,000: the top of a $300,000 budget, where a buyer spending close to the full amount actually shops. 289 homes in the 22 districts closed in that range.

More square feet isn’t the only way to get more house. Look at the year-built column: a smaller, newer house can mean fewer near-term repairs, and the days-on-market column shows how fast that part of each district moved.

Among homes that closed for $200,001 to $250,000 in 2026, Ferguson-Florissant gave the most house: a median of 1,756 square feet at $127 a square foot. The runner-up was Hazelwood, at 1,648 square feet and $134. Webster Groves gave the least, 868 square feet at $254. The newest homes were in Hazelwood, built 1967 on median.

Among homes that closed for $300,001 to $350,000 in 2026, Hazelwood gave the most house: a median of 2,669 square feet at $126 a square foot. The runner-up was Mehlville R-IX, at 1,725 square feet and $191. Kirkwood R-VII gave the least, 1,292 square feet at $249. The newest homes were in Valley Park, built 1994 on median.

Among homes that closed for $350,001 to $400,000 in 2026, Hazelwood gave the most house: a median of 3,016 square feet at $118 a square foot. The runner-up was Affton 101, at 2,501 square feet and $144. Kirkwood R-VII gave the least, 1,476 square feet at $253.

Among homes that closed for $450,001 to $500,000 in 2026, Mehlville R-IX gave the most house: a median of 2,935 square feet at $161 a square foot. The runner-up was Parkway, at 2,787 square feet and $176. Webster Groves gave the least, 1,900 square feet at $262. The newest homes were in Rockwood R-VI, built 1988 on median.

The district that gives you the most house changes with the budget, so start from your own number. The house tool above runs the same comparison for a specific size and layout.

Let’s stop comparing a 1,000-square-foot bungalow in one district with a 3,000-square-foot two-story in another.

For this comparison, I narrowed the data to one specific kind of house:

3 bedrooms · 2 bathrooms · ranch · 1,300–1,500 square feet

That’s a practical way to approximate a buyer asking:

“What would a roughly 1,400-square-foot ranch cost in different school districts?”

The answer isn’t just a price.

It’s also how often that house showed up.

Lindbergh vs. Mehlville: What Did a Similar Ranch Cost?

In Lindbergh, 5 matching homes sold during the study period. The median sale price was $350,000.

In Mehlville, 18 matching homes sold. The median sale price was $277,000.

That’s a $73,000 difference in the median matching sale.

But price is only half the story.

The Mehlville dataset produced more than three times as many matching sales.

So a buyer choosing between these districts wasn’t only deciding whether Lindbergh was worth paying more for.

They were also deciding whether they were willing to shop from a smaller pool of houses that fit the same basic description.

The table below asks a simpler question than “what did a house cost?” It holds the style and size steady—ranch homes in two size ranges—and compares what buyers paid per square foot in each school district.

The same small ranch sold for a median of $298 a square foot in the Kirkwood School District and $231 in Mehlville R-IX. On a 1,200-square-foot house, that’s about $80,000 for the same basic house in a different district.

That gap is demand, and it shows up twice: in the price per square foot and in how quickly the house sold.

Ranch style and size are held steady; condition is not, because MLS data doesn’t record it. Some groups are small (Kirkwood has 6 sales in each range), so read those medians as directional.

Districts with at least 5 matching ranch sales are shown. Price per square foot uses each listing’s reported living area.

The count matters as much as the median.

Three matching sales and 18 matching sales are not the same buying experience.

A low count does not mean a buyer cannot purchase that kind of house in the district. It means that very few homes matching those exact criteria closed during the period we studied.

And a small sample also means the median price should be treated as directional rather than as a precise prediction of the next sale.

Competition metrics are historical signals, not promises about the next listing.

Sometimes buyers keep raising their budget because they assume price is why they can’t find the right house.

But what if the house itself is scarce?

If only three homes matching your criteria sold in a district during more than nine months of 2026, you could have enough money to buy one and still spend a long time waiting for the right opportunity.

That is a different problem than being priced out.

A price problem can sometimes be solved by changing the budget.

A scarcity problem usually forces a different decision:

change the district, change the house, or accept that the search may take longer.

Scarcity and competition are related, but they are not the same thing.

A house type can be rare without every sale becoming a bidding war.

That’s why the tool also looks at days on market and sale price compared with original asking price.

For the roughly 1,400-square-foot 3-bed / 2-bath ranch cohort:

• Lindbergh had 5 matching sales, a 9-day median CDOM, and 80% sold above original list price.
• Mehlville had 18 matching sales, an 8-day median CDOM, and 61.1% sold above original list price.
• Parkway had 6 matching sales, a 4-day median CDOM, and 66.7% sold above original list price.

Those are small, highly specific cohorts, so don’t turn them into a prediction about the next house.

Use them for what they are:

evidence that price, availability and competition are three separate parts of the buying decision.

Parkway School District buyer guide

Buyer activity changes throughout the year. Spring often brings stronger demand, while late summer and fall can bring fewer showings. The pattern isn’t identical in every district.

A home that sold in April reflects the buyers who were competing when that contract was negotiated. Those same conditions may not exist when another homeowner lists in August.

Read the chart as a pattern, not a forecast. Showings count tours, not unique buyers—one buyer can tour several homes. Each district follows its own curve, and fewer showings in a month doesn’t by itself mean lower sale prices.

Yes—a couple of months later. In this year’s St. Louis County-area sales, the median sale price climbed through spring, peaked in June at $379,500 and was $302,750 by September. Part of that drop is smaller homes selling later in the year: per square foot, prices went from $189 in June to $174 in July, August and September.

No. Every year since 2016, St. Louis County’s median sale price has climbed from a winter low to a summer high, then eased back. In a typical year the swing is about 30%, and it has ranged from 22% to 52%, in the low-rate years before COVID and in the higher-rate years since.

Sometimes another $50,000 barely changes the search.

Sometimes it changes everything.

A few examples from the 2026 closed-sale data:

• Affton: At $250,000, 23 of 67 sales (34.3%) were within budget. At $300,000, 50 sales (74.6%) were within budget.
• Pattonville: $250,000 reached 31 of 108 sales (28.7%). $300,000 reached 63 sales (58.3%).
• Mehlville: $300,000 reached 83 of 285 sales (29.1%). $350,000 reached 143 sales (50.2%).
• Lindbergh: $300,000 reached 32 of 146 sales (21.9%). $350,000 reached 52 sales (35.6%).
• Parkway: $300,000 reached 24 of 399 sales (6.0%). $350,000 reached 74 sales (18.5%).

The point isn’t that you should automatically spend another $50,000.

It’s to understand what the extra money actually buys you.

If another $50,000 barely changes your options, stretching may not solve the problem you think it will.

If it opens a much larger part of the market, at least you can see the tradeoff before deciding whether the higher payment is worth it.

If “cheapest” means the lowest median closed single-family home price in this specific 2026 dataset, the lowest-price districts were:

That is a housing-price comparison.

It is not a ranking of school quality, desirability, safety, or where anyone should live.

It also doesn’t mean every house in a lower-median district is comparable with every house in a higher-median district. Condition, size, age, location and housing stock can be very different.

That’s why the interactive lets you move beyond the district median and compare the kind of house you actually want.

Percentages mean:

Share of QA-clean 2026 closed single-family sales in that district that sold at or below the stated price.

A percentage is more useful than a simple yes or no.

If 6% of a district’s sales were within your budget, homes at that price existed—but you were shopping a very different market than someone whose budget reached 75% of the district’s sales.

And none of these percentages tell you what’s listed today.

They tell you where your budget sat inside the market buyers actually closed on during the study period.

See what a sub-$1M search actually looked like in Clayton vs. Ladue.

Across the 22 St. Louis County-area school districts, the median annual property tax on homes sold in 2026 was $3,624, according to MLS sales records. District medians ranged from $1,446 to $11,638, across 2,856 sales from January 1 to October 5, 2026.

The bill follows the county’s assessed value and the local tax rates, not the price the house sold for. That is why the table below lists each district’s typical bill rather than a tax rate.

For homes that sold for $250,000 to $349,999 in 2026, the median annual property tax was $3,261, and the middle half of bills ran from $2,869 to $3,700, according to MLS sales records across 22 St. Louis County-area school districts.

For homes of 1,500–1,999 square feet, the median annual property tax ranged from $1,850 in Jennings to $5,860 in Ladue, among the 20 districts with at least five such sales in 2026, according to MLS sales records.

Comparing the same size house matters because a district with bigger or newer homes will show a higher median bill even if similar houses are taxed about the same.

University City is a good example.

Its median sale price in this dataset was $443,400.

But 31.5% of its qualifying sales still closed for $250,000 or less.

That doesn’t mean a $250,000 buyer had access to the same houses as a $443,000 buyer.

It means a single median number can hide a wide distribution of housing condition, size, location and price.

That’s why this page shows both:

where the middle of the district landed and how much of the market actually fell below your budget.

When the house you want doesn’t fit the district you want, there are only a few levers to pull.

You can spend more.

You can accept a different kind of house.

You can broaden the district.

Or you can wait.

The hard part is knowing which compromise actually changes your options.

The interactive should help answer that.

If changing the budget from $300,000 to $350,000 adds dozens of historical matches, that’s useful.

If adding $50,000 barely changes the search but broadening the square-footage range or crossing a district line changes it dramatically, that’s useful too.

The goal isn’t to push you toward the most expensive option.

It’s to show you what each decision buys you before you make it.

School-district boundaries in St. Louis County do not follow city names, ZIP codes or neighborhood labels cleanly.

A listing can say “Crestwood,” “Florissant,” “Ballwin” or “St. Louis” without that city name settling the school-district question.

And MLS school fields can be wrong.

During QA for this project, obvious district-assignment errors had to be corrected before the housing metrics were regenerated.

So use this page to compare housing markets.

When a specific school assignment matters to your purchase, verify the exact address directly with the school district before you write an offer.

I started with district-specific MARIS searches for closed single-family homes from January 1 through October 5, 2026.

The source searches were limited to properties identified as vacant or owner occupied.

Then I ran a separate QA pass before using the data for this page.

Five records were removed because the public remarks explicitly showed a current tenant or current lease.

Three obvious school-district misassignments were corrected after geography review.

The final dataset contains 2,868 qualifying closed sales across 22 St. Louis County-area school districts.

For property taxes, I pulled a second set of district-specific MARIS exports that include each listing’s annual tax amount and matched them to this dataset by address, close date and price. 2,856 of the 2,868 sales matched with a tax amount. The tax is the seller’s most recent annual bill as listed in MLS, not a projection of the next owner’s bill.

How the numbers work

Median sold price is the middle Close Price in the district.

25th percentile is used as a more stable lower-market reference than the single cheapest sale.

Budget share is the percentage of qualifying district sales that closed at or below the selected budget.

Comparable-house analysis uses the actual house characteristics in the dataset rather than estimating a price by multiplying a district-wide price per square foot.

The default “roughly 1,400-square-foot ranch” comparison means:

exactly 3 bedrooms · exactly 2 bathrooms · Ranch architectural style · 1,300–1,500 square feet

Days on market uses CDOM from the source data.

Sold above original asking compares Close Price with Original List Price.

Percentiles in the interactive (25th, 75th and the middle 50%) use linear interpolation between ranked sale prices, the same method as Excel’s PERCENTILE.INC.

What this data cannot tell you

This is historical closed-sale data.

It does not show today’s active inventory.

It does not guarantee that a similar house will become available.

It does not predict how long you personally will wait.

It does not determine whether a school district or individual school is right for you.

And it does not replace address-level school-boundary verification.

The tool above answers the housing question.

The individual district guides go deeper into boundaries, communities, school structure, official research sources and the things buyers should verify before making an offer.

The 2026 housing dataset on this page covers 22 St. Louis County-area districts. Additional St. Louis-area district guides remain available below even when they are not part of this specific housing dataset.