Singapore's HDB resale market generates tens of thousands of transactions every year. Each one is recorded, reported and publicly available. And yet, most buyers and sellers enter the market with a surprisingly incomplete picture of what their flat is actually worth — or what comparable flats have actually sold for.
The headline numbers are easy to find. Town-level medians, quarterly price indices, record-setting million-dollar transactions. These figures make for good news stories. But they're not particularly useful when you're trying to answer the question that actually matters: what should a flat like mine, in my block, on my floor, with my remaining lease, realistically transact for in today's market?
That's the question hdb insights is designed to answer. It's an independent data platform that analyses Singapore's HDB resale market using real transaction records — not broad averages, not agent estimates, not listing prices — to help buyers and sellers understand how resale prices actually behave across different towns, flat types and flat profiles. The approach is rigorous, transparent and built on a principle that sounds obvious but is rarely applied in practice: compare like with like.
Why Town-Level Medians Can Be Misleading
When most people look up HDB resale prices, they start with the town median — the midpoint price for all transactions of a particular flat type in a particular town over a given period. It's a useful starting point. It's also potentially misleading if treated as a reliable guide to what any specific flat is worth.
The problem is that town medians mix together flats with very different characteristics. A 4-room flat in Sengkang with 90 years of remaining lease on a high floor is a fundamentally different proposition from a 4-room flat in Sengkang with 60 years of remaining lease on a low floor — and yet both transactions feed into the same town median. When the mix of flats transacting in a given month skews towards newer or larger units, the median rises. When it skews towards older or smaller units, the median falls. The headline number moves, but the underlying market may not have changed at all.
This is why HDB Insights groups flats into comparable profiles before calculating any medians or trends. By controlling for remaining lease, floor level and floor area, the analysis strips out the compositional noise that makes raw town medians unreliable — and produces figures that more accurately reflect what genuinely similar flats are transacting for.
The difference can be significant. As the platform's own analysis shows, two Sengkang 4-room flats transacting in the same month can differ by S$370,000. That's not a rounding error — it's the distance between a flat profile that commands premium pricing and one that doesn't. Understanding which profile your flat belongs to is the difference between negotiating from a position of knowledge and negotiating from a position of assumption.
The Three Dimensions That Actually Drive HDB Resale Prices
hdb resale transaction data tells a clear story when you know how to read it. The platform's methodology identifies three dimensions that materially affect resale prices, and groups flats along these dimensions before any analysis is performed.
Remaining lease is the single most influential factor. But it doesn't affect prices in a smooth, linear way. Buyer behaviour shifts at certain lease thresholds — driven by CPF usage limits, bank financing rules and expectations about long-term value. Prices tend to adjust in steps rather than declining evenly as flats age. Concepts like Bala's Curve and age-adjusted pricing explain why flats with seemingly small differences in remaining lease can transact at noticeably different prices. HDB Insights groups flats into practical behavioural lease bands that reflect how the market actually values remaining lease — not how a straight-line depreciation model suggests it should.
Floor level is the second dimension, and it's more nuanced than most people realise. A flat on the 10th floor of a 12-storey block is a very different proposition from a flat on the 10th floor of a 25-storey block. Buyers compare flats based on their relative position within the block, not the absolute storey number. The methodology classifies floor levels by relative vertical position, which allows flats in blocks of different heights to be compared fairly and prevents analysis from being distorted by differences in block design.
Floor area is the third dimension, and it clusters around common HDB design layouts from different building periods rather than being evenly distributed across a range. A small difference in floor area can represent a meaningful layout change, while a larger difference may have little impact if both flats fall within the same design cluster. The platform groups flats into stable size clusters based on observed transaction patterns, creating a more accurate basis for comparison than arbitrary square-metre ranges.
Together, these three dimensions create flat profiles that are genuinely comparable — and the price analysis within each profile is correspondingly more reliable than any town-level figure can be.
HDB Resale Price Trends — Reading the Real Signals
Headline HDB resale price trends are reported monthly by property portals and news outlets. Prices went up. Prices went down. A new record was set. These reports are accurate as far as they go, but they rarely distinguish between genuine market shifts and compositional changes in the mix of flats transacting.
HDB Insights approaches trend analysis differently. By tracking prices within comparable flat profiles over time, the platform identifies trends that reflect real market behaviour rather than statistical noise. When the median for a specific flat profile in a specific town rises over several quarters, that's a genuine signal. When the town-level median rises because more high-floor, high-lease flats happened to transact that month, that's compositional drift — useful to note, but not a meaningful guide to what your flat is doing.
This approach produces analysis that's directly applicable to decision-making. The question of whether to sell a Sengkang HDB flat immediately after MOP or hold becomes answerable with data rather than guesswork when you can track how flats in your specific profile have performed post-MOP over multiple years. The question of whether a high-floor premium still holds in Sengkang 4-room flats becomes concrete when you can compare high-floor and mid-floor medians within the same lease band and size cluster.
The million-dollar HDB analysis and the most expensive HDB flats ever sold lists provide broader market context — but even these are most useful when understood through the lens of what specific flat attributes (lease, floor, area, location) consistently command the highest prices.
The Personalised Flat Median — Your Flat, Not the Town Average
Perhaps the most practically useful feature on HDB Insights is the personalised flat median tool. Instead of relying on a town-level median that mixes hundreds of different flat profiles together, you can get a median calculated specifically for flats comparable to yours — same lease band, same relative floor position, same size cluster.
The difference between a town median and a personalised median can exceed S$100,000. For a seller, that gap represents the difference between pricing your flat realistically and either leaving money on the table or overpricing and watching your listing stagnate. For a buyer, it represents the difference between making an offer grounded in what comparable flats have actually transacted for and negotiating blind against a number pulled from a property portal headline.
The tool doesn't tell you what your flat is "worth" — no tool can, because every transaction depends on buyer motivation, market timing and negotiation dynamics. What it does is give you the most reliable benchmark available: what genuinely comparable flats have sold for, based on HDB resale transaction data analysed with a methodology designed to strip out the noise.
Town Insights — Deep Analysis by Location
The Town Insights section provides location-specific analysis for Singapore's HDB towns. Sengkang is currently the most developed section, with dedicated analysis covering resale price records, MOP timing decisions, floor-level premiums, below-median transactions and price gap breakdowns — all built on the same comparable-profile methodology.
The depth of Sengkang coverage illustrates what's possible when transaction data is analysed properly. Rather than a single median figure and a line chart, you get a layered understanding of how different flat profiles within the same town behave differently in the market — and why. The Sengkang resale record analysis identifies exactly which flat attributes drove the highest recorded price. The below-median pricing analysis examines why some sellers accept significantly less than the prevailing median — and what structural factors (not just negotiation skill) explain the discount.
As the platform expands to cover additional towns, the same analytical framework will apply — providing buyers and sellers across Singapore with comparable-profile insights specific to their location.
Built on Transparency
The methodology page explains exactly how flats are grouped, how medians are calculated, and why the approach differs from most property portals. The glossary defines the key concepts — Bala's Curve, age-adjusted pricing, rolling medians, flat profiles — in plain language. The about page is transparent about the platform's independence and purpose.
This transparency matters because data analysis is only as useful as the methodology behind it. Two platforms can report different medians for the same town and flat type simply because they group flats differently. When the methodology is visible, you can assess whether the analysis reflects how the market actually works — or whether it's just another way of averaging numbers that shouldn't be averaged.
Using HDB Insights in Your Decision-Making
Whether you're a seller deciding when to list, a buyer assessing whether an asking price is reasonable, or simply someone trying to understand what's happening in the HDB resale market, the value of HDB Insights is the same: it replaces assumption with evidence.
The hdb resale price trend data, analysed at the flat-profile level rather than the town level, gives you a more accurate picture of market direction. The personalised median gives you a benchmark calibrated to your specific flat. The town-level deep dives give you context for the structural factors — remaining lease decay, floor-level premium compression, layout-driven price gaps — that affect your flat's position within the broader market.
Start with the personalised flat median to see where your flat sits relative to genuinely comparable transactions. Explore the analysis articles for data-driven insights into specific market dynamics. And use the methodology and glossary to understand the framework behind the numbers — because in a market where S$370,000 can separate two flats of the same type in the same town in the same month, understanding the data properly isn't optional. It's essential.