By George Kindler · Published October 6, 2026
You found the school district you want.
Now comes the harder question:
Can you actually get the house you want there?
A $350,000 budget can give you plenty of choices in one St. Louis County school district and leave you waiting for the right house in another.
And sometimes spending more isn’t even the problem.
The house you want may simply not come up very often.
I analyzed 2,868 qualifying single-family home sales across 22 St. Louis County-area school districts from January 1 through October 5, 2026 to answer a different kind of school-district question:
What did your budget actually buy—and what might you have to give up to stay in the district you want?
Historical closed-sale data—not today’s active inventory.
I’m not going to tell you which school district your household should choose.
School programs, services, attendance boundaries and individual student needs deserve their own research.
This page answers the housing side of the decision:
What did homes cost? How much of the market was within a certain budget? How often did a particular kind of house sell? And what changed when buyers crossed a school-district line?
School assignments can vary by exact address. Always verify the assigned schools directly with the district before making a school-driven purchase decision.
A district median tells you where the middle sale landed.
It does not tell you whether your budget would have reached 5% of the market, 30% of it, or most of it.
Enter your maximum purchase price and I’ll show you how much of each district’s 2026 closed-sale market actually fell within reach.
Source: MARIS district-specific closed-sale exports supplied by George Kindler. Analysis covers 2,868 QA-clean single-family sales from January 1 through October 5, 2026. Historical sales are not current inventory. School assignment must be verified by exact property address.
Price is only one way a home search gets difficult.
You can have enough money and still struggle because the house itself doesn’t come up very often.
Tell me what you’re looking for. The tool will compare actual closed sales across the districts in the dataset.
Source: MARIS district-specific closed-sale exports supplied by George Kindler. Analysis covers 2,868 QA-clean single-family sales from January 1 through October 5, 2026. Historical sales are not current inventory. School assignment must be verified by exact property address.
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.
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.
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.
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.
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.
| District | Matching Sales | Median Sold Price | Median CDOM | Sold Above Original List |
|---|---|---|---|---|
| Ferguson-Florissant | 4 | $120,000 | 28 | 0% |
| Hazelwood | 15 | $220,000 | 18 | 20.0% |
| Bayless | 3 | $255,000 | 2 | 66.7% |
| Mehlville R-IX | 18 | $277,000 | 8 | 61.1% |
| Webster Groves | 3 | $285,000 | 10 | 33.3% |
| Rockwood R-VI | 3 | $339,500 | 31 | 33.3% |
| Parkway | 6 | $345,500 | 4 | 66.7% |
| Lindbergh | 5 | $350,000 | 9 | 80.0% |
Swipe the table sideways to see every column.
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:
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.
Sometimes another $50,000 barely changes the search.
Sometimes it changes everything.
A few examples from the 2026 closed-sale data:
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:
| District | QA-Clean Sales | Median Sold Price |
|---|---|---|
| Normandy | 69 | $80,000 |
| Jennings | 37 | $88,000 |
| Riverview Gardens | 115 | $92,000 |
| Ferguson-Florissant | 232 | $141,000 |
| Ritenour | 124 | $156,103 |
| Hancock Place | 27 | $156,500 |
| Hazelwood | 296 | $200,750 |
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.
| District | Sales | Median | ≤$200K | ≤$250K | ≤$300K | ≤$350K | ≤$400K | ≤$500K |
|---|---|---|---|---|---|---|---|---|
| Affton 101 | 67 | $270,000 | 6.0% | 34.3% | 74.6% | 80.6% | 88.1% | 95.5% |
| Bayless | 31 | $254,799 | 22.6% | 48.4% | 87.1% | 93.5% | 96.8% | 100% |
| Brentwood | 28 | $401,000 | 0% | 7.1% | 17.9% | 35.7% | 50.0% | 75.0% |
| Clayton | 29 | $1,250,000 | 0% | 0% | 0% | 0% | 0% | 0% |
| Ferguson-Florissant | 232 | $141,000 | 75.9% | 90.9% | 97.8% | 99.6% | 100% | 100% |
| Hancock Place | 27 | $156,500 | 77.8% | 92.6% | 100% | 100% | 100% | 100% |
| Hazelwood | 296 | $200,750 | 49.7% | 75.3% | 90.5% | 94.9% | 97.3% | 100% |
| Jennings | 37 | $88,000 | 94.6% | 100% | 100% | 100% | 100% | 100% |
| Kirkwood R-VII | 133 | $575,000 | 0.8% | 1.5% | 9.0% | 15.0% | 21.1% | 40.6% |
| Ladue | 82 | $1,028,500 | 0% | 0% | 1.2% | 4.9% | 6.1% | 12.2% |
| Lindbergh | 146 | $400,000 | 3.4% | 6.8% | 21.9% | 35.6% | 52.1% | 69.9% |
| Maplewood-Richmond Heights | 35 | $325,000 | 5.7% | 17.1% | 37.1% | 60.0% | 77.1% | 82.9% |
| Mehlville R-IX | 285 | $350,000 | 2.8% | 13.3% | 29.1% | 50.2% | 67.0% | 84.2% |
| Normandy | 69 | $80,000 | 94.2% | 94.2% | 95.7% | 97.1% | 98.6% | 100% |
| Parkway | 399 | $490,000 | 0.5% | 2.0% | 6.0% | 18.5% | 32.3% | 53.1% |
| Pattonville | 108 | $285,000 | 12.0% | 28.7% | 58.3% | 79.6% | 91.7% | 97.2% |
| Ritenour | 124 | $156,103 | 79.8% | 97.6% | 100% | 100% | 100% | 100% |
| Riverview Gardens | 115 | $92,000 | 99.1% | 99.1% | 100% | 100% | 100% | 100% |
| Rockwood R-VI | 388 | $529,000 | 1.5% | 3.6% | 8.0% | 16.5% | 24.2% | 43.6% |
| University City | 89 | $443,400 | 25.8% | 31.5% | 34.8% | 43.8% | 46.1% | 55.1% |
| Valley Park | 27 | $313,000 | 11.1% | 29.6% | 48.1% | 70.4% | 85.2% | 96.3% |
| Webster Groves | 121 | $425,000 | 2.5% | 7.4% | 24.8% | 35.5% | 47.1% | 65.3% |
Swipe the table sideways to see every price level.
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.
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.
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.
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.
Source: MARIS district-specific closed-sale exports supplied by George Kindler. Analysis covers 2,868 QA-clean single-family sales from January 1 through October 5, 2026. Historical sales are not current inventory. School assignment must be verified by exact property address.
There isn’t one school district that is “best” for every buyer, and this page does not rank districts by school quality.
If schools matter to your decision, research the individual schools, programs and current official performance information that matter to you.
What I can show you here is the housing tradeoff: what homes cost, how much of a district fell within your budget, what kind of house your money bought, and how often that house actually sold.
By median closed single-family sale price in this dataset, the lowest-price districts were Normandy, Jennings, Riverview Gardens, Ferguson-Florissant, Ritenour, Hancock Place and Hazelwood.
That is a housing-price comparison, not a ranking of the schools or communities.
Yes, but it was historically uncommon in the period studied.
Ten of 146 qualifying Lindbergh sales closed for $250,000 or less—6.8% of the district’s sales in the dataset.
At $300,000, the share increased to 21.9%. At $400,000, it reached 52.1%.
For the default comparable-home cohort—3 bedrooms, 2 bathrooms, ranch style and 1,300–1,500 square feet—five Lindbergh homes matched.
Their median sale price was $350,000.
Because five sales is a small comparison group, use that price together with the count rather than treating $350,000 as a prediction of the next sale.
The same 3-bedroom, 2-bath, 1,300–1,500-square-foot ranch search produced 18 Mehlville sales with a $277,000 median.
The important difference was not only the lower median price.
There were also substantially more matching sales in the Mehlville data than in Lindbergh.
No.
Historical sale count is not a forecast of the next listing.
A low count tells you that relatively few homes matching those criteria closed during the study period. That is useful evidence of scarcity, but it cannot tell you when the next matching house will come to market.
No.
This page analyzes closed sales from January 1 through October 5, 2026.
Current inventory changes every day.
The historical data is meant to answer a different question: whether your budget and house preferences were common or unusual in the market buyers actually purchased.
No.
School-district boundaries can cross cities, neighborhoods and ZIP codes. Verify the assigned schools for any serious property directly with the school district before making a school-driven purchase decision.
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.
Maybe the district is non-negotiable.
Maybe the ranch is.
Maybe keeping the payment below a certain number matters more than either one.
There isn’t a universal right answer.
But there is a difference between making a compromise because you understand the market and making one because you’ve spent three months refreshing listings and nothing seems to fit.
If you want to compare your actual budget, the kind of house you’re trying to buy and the districts you’re considering, ask me.
I’ll tell you what I see in the numbers—and where I’d widen the search first.
School district is one filter. Compare all 116 St. Louis neighborhoods →
Grew up in South St. Louis, lived in Dogtown for 6 years, now in South County. You'll find us at Wellspring on Lindbergh on Sundays. I'm not selling you a house — I'm showing you how to think about buying or selling a house.