House prices in LD2 (Builth Wells)

This article shows price per square metre data and various charts to help you understand the housing market in LD2 - stats were last calculated on 01 November 2024.

Defining 'LD2'

This analysis is limited to properties whose postcode starts with "LD2", this is also called the postcode district. There are no official postcode district names so I've just labelled it LD2, Builth Wells. It is shown in red on the map below.

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Price per square metre

Knowing the average house price in LD2 is not much use. However, knowing average price per square metre can be quite useful. Price per sqm allows some comparison between properties of different size. We define price per square metre as the sold price divided by the internal area of a property:

£ per sqm = price ÷ internal area

For example in September 2024, Cwmgwrgi, , Builth Wells, LD2 3HT sold for £580,000. Given the internal area of 251 square metres recorded on the EPC, the price per sqm is £580,000 ÷ 251 sqm = £2,310.

England & Wales have been officially metric since 1965. However house price per square foot is prefered by some estate agents and those of sufficiently advanced age ;-). It is a huge pain to code the automatic conversion for square meters to square feet for all the graphs and charts on LD2 and elsewhere. All the conditionals turn my tidy code for into spaghetti. I will get around to it at some point, but for now you can just divide everything by 10 in your head, move a decimal place and you'll be close enough. If you want to be more precise 1 sqm = 10.76391 sqft.

Distribution of £ per sqm for houses vs flats in LD2

The chart above is called a histogram, it helps you see the distribution of house price per sqm in LD2 To make this chart we put all the sales data into a series of £ per sqm 'buckets' (e.g. £2,350 to £2,500, £2,500 to £2,650, £2,650 to £2,800 etc...) we then count the number of sales with within in each bucket and plot the results. The histogram is based on 117 sales that took place in LD2, in the last 24 months.

Generate a custom histogram like the one above but based on your own criteria.

You can see the spread of prices above. This is because although internal area is a key factor in determining valuation, it is not the only factor. Many factors other than size affect desirability; these factors could be condition, aspect, garden size, negotiating power of the vendor etc.

The spread of prices will give you a feel of the typical range to expect in LD2, Builth Wells. Notably, only 25% of properties that sold recently were valued at more than £3,060 sqm. For anything to be valued more than this means it has to be more desireable than the clear majority of LD2 homes.

Box plot of £ per sqm for LD2

Tip: click on the chart to see the values.

The chart above is called a boxplot (or a box-and-whisker plot). Box plots, like histograms, are used to graphically represent the distribution of data, showing the central tendency, spread of the distribution. In the context of £ per square metre property price distributions, box plots represent the variation in property prices within a geographic area e.g. Builth Wells. The chart above shows a boxplot for 'LD2' as well as the 'LD' postcode area.

  • Median: The horizontal line inside the box represents the median (£ per square meter). This is the midpoint of the data, meaning 50% of the prices are below this value, and 50% are above. The middle price per square metre in 'LD2' is £2,390.
  • Interquartile Range (IQR): The box spans from the 25th percentile (Q1) to the 75th percentile (Q3). This is the range where the middle 50% of the data lies, giving a good indication of the typical price spread. Of the 117 transactions in LD2, Builth Wells half were sold for between £1,910 and £3,060 per square metre.
  • Whiskers: In our case, the whiskers extend from the 9th percentile (at the lower end) to the 91st percentile (at the upper end), This provides a slightly broader view of the distribution by including the middle 82% of records. The whiskers capture most of the variation but exclude extreme outliers caused by data errors in recording sold house prices or internal area.
  • 'n=' is the number of property transactions the box plot is based on; 117 for LD2, Builth Wells.

    • Property price map for Builth Wells

    Have a look at the interactive price map I created for myself. Use it to explore 'LD2' house prices all the way down to individual property plots.

    Property price heatmap for Builth Wells
    House price map for Builth Wells

    Will LD2 house prices drop in 2025?

    I cannot tell what house prices will do in the future and don't believe anyone who says they can. However we can plot price trends, I have done this in the chart below for LD2 (Builth Wells) compared with the wider postcode area 'LD'. You can extrapolate from this based on your own views on future interest rates, inflation and other factors.

    House price index for LD2

    Tip: click on the legend items to show/hide different lines

    Download house price index as CSV (premium users only).

    The chart above shows changes in 'LD2' property prices over the last 20 years. The index is calculated from the average price paid per sqm for property in LD2 and is set to 100 in 2004. The chart compares trends for LD2, Builth Wells against those of the broader postcode area 'LD'. What is more interesting is to look at the difference between flats and houses, even those in the same area follow a very different trend, to get a robust enough sample size to see this we need to zoom out and look at house price trends for the entire Powys local authority.

    The dashed lines show nominal house price changes, the solid lines show the same data adjusted for inflation. Economists call this the 'real' price change. You have to take inflation into account when comparing prices over time. It's calculated using the formula:

    Real Rate of Return = (1 + Nominal Rate) ÷ (1 + Inflation Rate) – 1
    In this formula, the nominal rate is the rate of change before any adjustments, and the inflation rate is taken from the Consumer Price Index. The real rate of return is a more accurate measure of change in value, because £1 today does not have the same buying power as £1 in the past. For example, if a savings account pays an interest rate of 3% per year and the inflation rate is 5% per year, the real rate of return is -2%. This means that the investment's value is shrinking by 2% each year.

    Historic returns for LD2
    LD area LD2 district
    Nominal Real Nominal Real
    20 yr per annum 2.8% 0.1% 2.0% -0.6%
    20 yr total 73.2% 2.6% 48.5% -12.0%
    10 yr per annum 4.2% 1.4% 3.4% 0.6%
    10 yr total 51.4% 15.0% 39.6% 6.0%
    5 yr per annum 5.5% 1.4% 2.9% -1.2%
    5 yr total 30.9% 7.2% 15.1% -5.8%
    1 yr per annum -0.8% -4.7% -13.1% -16.6%
    1 yr total -0.8% -4.7% -13.1% -16.6%

    This table complements the house price index chart above, presenting the data in a more detailed format. It breaks down the information into 20-year, 10-year, 5-year, and 1-year periods, further categorized by property type. For each period, we display both a per annum rate of change and a total rate of change.

    The total rate of change represents the overall change over the entire period. The formula for total return is:

    Total return = (Index at end of period ÷ Index at start of period) - 1

    The per annum rate of change is the annualized rate of change over the period. This is equivalent to the annual bank savings rate you would need to achieve the same total return over the given period. This annualized return is also known as the Compound Annual Growth Rate (CAGR). The formula for CAGR is:

    CAGR = (1 + Total return) ^ (1 ÷ Number of years) - 1

    Some specific examples:

    • Over the past 20 years, LD2 district have seen a -0.6% annual change when adjusted for inflation. This translates to a total change of -12.0% in real terms.
    • Over the past 5 years, LD area have seen a 1.4% annual change when adjusted for inflation. This translates to a total change of 7.2% in real terms.

    Most recent LD2 sales

    For the most recent sales activity, rather than a summarized average, it is better to see the underlying data. This is shown in the chart below, where blue dots represent individual sales, click on them to see details. If there is an obvious trend you should be able to spot it here amid the noise from outliers.

    Tip: hover over dots to see details

    Street level data

    Street Avg size Avg £sqm Recent sales
    Oaklands, , LD2 3E 72 sqm £2,251 13
    Market Street, , LD2 3E 70 sqm £1,952 12
    Troed Y Bryn, , LD2 3F 138 sqm £2,035 11
    Garth Road, , LD2 3A 142 sqm £1,705 9
    Castle Street, , LD2 3B 101 sqm £2,236 9
    Parc Yr Irfon, , LD2 3N 105 sqm £3,098 8
    Park Road, , LD2 3A 106 sqm £2,681 7
    Brecon Road, , LD2 3E 86 sqm £1,682 7

    Search for your street here.

    Nearby geographies

    The table below shows how 'LD2' compares to the other postcode districts nearby 'LD2'.

    District Lower quartile Median Upper quartile Sales in last 2yr
    LD8 Presteigne £2,320 sqm £2,820 sqm £3,460 sqm 124
    LD7 Knighton £1,730 sqm £2,360 sqm £2,910 sqm 96
    LD6 Rhayader £1,650 sqm £2,170 sqm £3,040 sqm 55
    LD5 Llanwrtyd Wells £1,810 sqm £2,200 sqm £2,480 sqm 33
    LD4 Garth £2,270 sqm £2,660 sqm £3,070 sqm 16
    LD3 Brecon £2,310 sqm £2,830 sqm £3,330 sqm 382
    LD2 Builth Wells £1,910 sqm £2,390 sqm £3,060 sqm 117
    LD1 Llandrindod Wells £1,720 sqm £2,210 sqm £2,770 sqm 255
    HR5 Kington £2,200 sqm £2,660 sqm £3,160 sqm 98
    HR3 Hay On Wye £2,810 sqm £3,450 sqm £3,960 sqm 176

    Raw data

    Our analysis of LD2 is derived from what is essentially a big table of sold prices from Land Registry with added property size information. Below are three rows from this table to give you an idea.

    Address Paid sqm £/sqm
    Cwmgwrgi, , £580,000
    Sep-2024
    		 251 2,310
    Old Smithy, , £390,000
    Sep-2024
    		 122 3,196
    High Mead, , £185,000
    Sep-2024
    		 90 2,055

    See the entire list of all sales in LD2 here.

    About

    I created HouseMetric because I wanted to see this data and analysis myself, I also wanted to teach myself to build a website. Please give me feedback or spread the word about it. I'm constantly tinkering and adding more stuff to it.