What Happens When You Compare Buyers vs. Sellers in London, Ontario’s Housing Market?
I fell down a housing-data rabbit hole recently after reading a fascinating U.S. housing analysis published by Redfin comparing the number of buyers and sellers currently active in the market.
Naturally, I asked myself:
“Could I recreate something similar for London, Ontario, using whatever public data I could access?”
So… I tried.
Before the economists publicly tackle me, let’s establish a few important facts:
This was:
- 94% curiosity
- 4% spreadsheets
- 3% hope
- and at least one questionable Excel decision
This is not an academic paper, economic forecast, or peer-reviewed market model. It is simply an exploratory exercise using publicly available data to estimate buyer and seller balance in the London, Ontario housing market during April 2026.
Still, the results were surprisingly interesting.
The Core Question: How Many Buyers Are Actually Active Right Now?
We can easily measure:
- Active listings
- New listings
- Completed transactions
- Months of inventory
But measuring the number of active buyers is much harder.
Unlike Redfin, I do not have access to mysterious proprietary behavioural datasets, so I needed to improvise.
My solution?
I used Realtor.ca traffic activity as a rough proxy for buyer participation.
Using Insights data, my selected London-area market generated approximately:
📊 45,389 monthly visitors during the first quarter of 2026.
Now obviously, not every person browsing REALTOR.ca is actively trying to buy a home.
Some people are:
- casually browsing
- checking prices
- comparing neighbourhoods
- stalking their ex’s house
- or simply enjoying the emotional chaos of real estate listings
So, I applied a heavy adjustment.
Adjusting for “Tire Kickers”
To account for casual browsing and inactive users, I reduced the estimated traffic pool by 50%.
That left an adjusted pool of approximately:
👥 22,695 potentially engaged users
From there, I applied another adjustment based on average market absorption / months of inventory trends over the first four months of 2026.
The reasoning was simple:
If inventory absorption is slowing, not every engaged platform user is likely to participate at the transactional level.
Using an average market absorption adjustment of approximately 5.45%, the model ultimately estimated:
🏠 Approximately 1,236 active buyers
Again:
This is not a precise buyer count.
It is simply a rough estimate built from publicly available behavioural and market activity data.
But for an exploratory exercise, it gives us something useful to compare against the listing inventory.
So… How Many Sellers Were Active?
At the end of April 2026, the London market showed:
🏠 1,985 active listings
At the same time, the model estimated:
👥 1,236 active buyers
That creates a market balance of approximately:
📊 1.6 listings per buyer
Or put another way:
London may currently have roughly 62 buyers for every 100 active listings.
Using a Redfin-style framework, the model suggests London had approximately:
60.6% more sellers than buyers during April 2026
But Homes Are Still Selling
This does not mean the market is frozen.
Far from it.
During April 2026:
- 🤝 432 transactions were completed
- 📈 Seller match rate: ~21.76%
- 🛒 Estimated buyer match rate: ~35%
What does that mean in plain English?
Buyers still appear capable of finding homes and completing transactions.
However, sellers are competing against significantly higher inventory levels than we experienced during the ultra-tight pandemic market years.
In simple terms:
Homes are still selling, but buyers currently have more choice and leverage than they did a few years ago.
Inventory Is Still Building
One of the more interesting findings came from looking at inventory absorption.
April’s:
- 📉 Sales-to-New-Listings Ratio (SNLR) was approximately 51%
- 📦 Months of Inventory (MOI) sat around 4.59 months
That means inventory is still being absorbed by the market — just not fast enough to fully offset incoming supply.
Broadly speaking:
The market appears to be transitioning from scarcity-driven conditions to a more balanced, inventory-heavy environment.
Final Thoughts
This was a fun attempt to adapt an interesting Redfin framework using local public data, REALTOR.ca insights, and some matching-model logic.
Was it perfect?
Absolutely not.
The exercise reinforced something important:
Housing markets are incredibly difficult to model accurately because buyer behaviour, sentiment, financing, timing, and local conditions all interact simultaneously.
Still, even imperfect exploratory models can help spark useful conversations about:
- supply
- demand
- inventory growth
- market psychology
- and transaction dynamics
And honestly?
Sometimes falling down a housing-data rabbit hole is kind of fun.
The Elevate Real Estate Group
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