Property Scores

ShiokNest, walkability, and investment scores by location

How to Use the Score Map

Key Takeaways

  • Map data is refreshed from URA, HDB and OneMap APIs — hover any marker for live values.
  • Use the filter panel to narrow results by district, bedroom type, price range, or tenure.
  • Click any marker or polygon to drill down into the underlying property or area detail.

What It Does

This map colours each district by the average score of properties within it. Darker colours indicate higher scores. Zoom in to see individual property bubbles — the size represents score magnitude and the colour shows relative ranking.

Why It Matters

Score Types Explained

  • Investment Score: Combines rental yield, capital appreciation, liquidity, and location factors. OCR typically scores highest on yield; CCR on prestige.
  • Profitability Score: Based on historical transaction win rates and median returns. High-volume condos in established areas tend to lead.
  • En-Bloc Score: Evaluates redevelopment potential — older buildings with low plot ratio utilisation in freehold land score highest.
  • Walkability Score: Proximity to MRT, schools, hawker centres, malls, parks, and clinics. Mature estates like Toa Payoh and Bishan dominate.
  • ShiokNest Score: Composite of all four sub-scores — the overall quality metric.

How to Use

Look for districts with consistently high scores across multiple dimensions — these represent the most well-rounded property markets. Districts where investment scores are high but walkability is low may signal emerging areas with future upside. Click individual properties to see their detailed score breakdown.

How It Works

  • Pan and zoom to the area of Singapore you are interested in.
  • Use the filter panel to narrow results by district, bedroom type, or price range.
  • Hover any marker or polygon for a tooltip with exact values.
  • Click a marker to open the underlying property or area detail page.

Examples

Investment score map: finding high-opportunity OCR condos before the crowd

Inputs
Score type
Investment Potential
Segment
OCR filter
Threshold
Score ≥ 65 (top quartile)
Layer
District choropleth + individual property bubbles
Results
High-score OCR districts
D19, D27, D18
Top-scoring developments
Appear as large dark bubbles in northeast and north
Insight
D19 cluster outscoring CCR average by 8 points

How to read this: Zoom into D19 on the Investment score layer and individual condo bubbles emerge — larger bubbles indicate higher scores, with colour confirming rank. Developments scoring 65+ in D19 are flagging strong yield + price momentum + MRT proximity combinations. Clicking a bubble opens the property card showing the score breakdown: which of the 7 factors (yield, momentum, MRT, lease, liquidity, en-bloc, segment) are driving the score. This spatial view surfaces non-obvious opportunities that list-based searches miss.

En-bloc probability map: identifying aging CCR developments with redevelopment upside

Inputs
Score type
En-Bloc Probability
Segment
CCR (D9, D10, D11)
Filter
Developments built before 1995 (lease ≥ 30 years remaining)
Layer
Individual property bubbles
Results
High en-bloc score clusters
D10 Ardmore area, D11 Novena fringe
Score drivers
Low GPR utilisation + age + owner consent feasibility
Price premium indicator
High en-bloc score + below-median PSF = buy signal

How to read this: En-bloc potential generates real price premiums: developments that successfully complete collective sales typically transact at 20–40% above secondary market prices in the 12 months before the collective sale is announced. The map highlights which CCR developments have the structural conditions for en-bloc (old age, underutilised plot ratio, manageable unit count for 80% consent). A buyer who purchases at secondary market price before an en-bloc announcement benefits from the full premium. Switch to the PSF layer to confirm a high-en-bloc-score development is still priced below its district median — the ideal entry combination.

Tips & Pitfalls

Expert Tips

  • Zoom out first to spot macro patterns before diving into individual districts.
  • Compare this map against the rental yield map to find high-demand, low-price outliers.
  • Use the legend to understand colour encoding — the same colour can mean different things on different maps.

Common Pitfalls

  • Judging a district by headline colour alone — the underlying sample size varies wildly across Singapore.
  • Confusing median with mean when both are shown — means are skewed by luxury outliers.
  • Forgetting that new-launch prices are discounted — resale prices are a better benchmark for fair value.

Frequently Asked Questions

Where does the map data come from?
Data is sourced from URA (Urban Redevelopment Authority), HDB, OneMap, and official Singapore government APIs, refreshed monthly.
How often is the map updated?
Transaction-based maps refresh monthly as URA and HDB publish new data. Planning layers (Master Plan, GLS) update as gazetted.
Can I filter by district or bedroom type?
Yes — use the filter panel on the map. Filter state is preserved in the URL so you can share a deep link to a specific view.

Related Resources

Map Browse all maps Insight Rental Yield Insight Calculator District Comparison Calculator Guide Property Guides Insight Investment Score Insight Profitability Score Insight En-Bloc Score Insight Walkability Score