House prices in HU13 (Hessle)

This article shows price per square metre data and various charts to help you understand the housing market in HU13 - stats were last calculated on 03 December 2024.

Defining 'HU13'

This analysis is limited to properties whose postcode starts with "HU13", this is also called the postcode district. There are no official postcode district names so I've just labelled it HU13, Hessle. It is shown in red on the map below.

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Price per square metre

Knowing the average house price in HU13 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 October 2024, 29, Southfield, Hessle, HU13 0EL sold for £425,000. Given the internal area of 135 square metres recorded on the EPC, the price per sqm is £425,000 ÷ 135 sqm = £3,148.

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 HU13 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 HU13

The chart above is called a histogram, it helps you see the distribution of house price per sqm in HU13 To make this chart we put all the sales data into a series of £ per sqm 'buckets' (e.g. £1,900 to £2,000, £2,000 to £2,100, £2,100 to £2,200 etc...) we then count the number of sales with within in each bucket and plot the results. The histogram is based on 487 sales that took place in HU13, 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 HU13, Hessle. Notably, only 25% of properties that sold recently were valued at more than £2,790 sqm. For anything to be valued more than this means it has to be more desireable than the clear majority of HU13 homes.

Box plot of £ per sqm for HU13

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. Hessle. The chart above shows a boxplot for 'HU13' as well as the 'HU' 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 'HU13' is £2,240.
  • 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 487 transactions in HU13, Hessle half were sold for between £1,820 and £2,790 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; 487 for HU13, Hessle.

    • Property price map for Hessle

    Have a look at the interactive price map I created for myself. Use it to explore 'HU13' house prices all the way down to individual property plots.

    Property price heatmap for Hessle
    House price map for Hessle

    Will HU13 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 HU13 (Hessle) compared with the wider postcode area 'HU'. You can extrapolate from this based on your own views on future interest rates, inflation and other factors.

    House price index for HU13

    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 'HU13' property prices over the last 20 years. The index is calculated from the average price paid per sqm for property in HU13 and is set to 100 in 2004. The chart compares trends for HU13, Hessle against those of the broader postcode area 'HU'. 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 East Riding of Yorkshire 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 HU13
    HU area HU13 district
    Nominal Real Nominal Real
    20 yr per annum 3.5% 0.8% 2.6% -0.0%
    20 yr total 99.6% 18.2% 68.6% -0.2%
    10 yr per annum 3.4% 0.6% 3.2% 0.4%
    10 yr total 40.1% 6.4% 37.0% 4.0%
    5 yr per annum 3.2% -0.8% 3.5% -0.6%
    5 yr total 17.3% -4.0% 18.6% -2.9%
    1 yr per annum 3.4% -0.8% -1.2% -5.2%
    1 yr total 3.4% -0.8% -1.2% -5.2%

    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, HU13 district have seen a -0.0% annual change when adjusted for inflation. This translates to a total change of -0.2% in real terms.
    • Over the past 5 years, HU13 district have seen a -0.6% annual change when adjusted for inflation. This translates to a total change of -2.9% in real terms.

    Most recent HU13 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
    Richmond Road, , HU13 9D 74 sqm £2,002 23
    Barrow Lane, , HU13 0P 84 sqm £2,121 21
    Seaton Road, , HU13 9E 78 sqm £1,931 19
    Westbourne Grove, , HU13 0Q 88 sqm £1,897 18
    Penshurst Avenue, , HU13 9E 71 sqm £1,841 18
    Boothferry Road, , HU13 9A 86 sqm £1,957 17
    Cherry Avenue, , HU13 0Q 98 sqm £2,729 16
    Cottesmore Road, , HU13 9J 92 sqm £1,980 16

    Search for your street here.

    Nearby geographies

    The table below shows how 'HU13' compares to the other postcode districts nearby 'HU13'.

    District Lower quartile Median Upper quartile Sales in last 2yr
    HU9 Hull £1,040 sqm £1,390 sqm £1,740 sqm 889
    HU8 Hull £1,220 sqm £1,600 sqm £2,070 sqm 748
    HU7 Kingswood £1,410 sqm £1,980 sqm £2,380 sqm 1,066
    HU6 Hull £1,250 sqm £1,630 sqm £2,030 sqm 563
    HU5 Hull £1,320 sqm £1,630 sqm £1,950 sqm 1,297
    HU4 Hull £1,470 sqm £1,880 sqm £2,250 sqm 538
    HU3 Hull £870 sqm £1,160 sqm £1,710 sqm 695
    HU20 Little Weighton £2,140 sqm £2,620 sqm £2,930 sqm 13
    HU2 Hull £950 sqm £1,340 sqm £1,620 sqm 66
    HU19 Withernsea £1,040 sqm £1,530 sqm £1,960 sqm 185

    Raw data

    Our analysis of HU13 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
    29, Southfield, £425,000
    Oct-2024
    		 135 3,148
    86, Tranby Avenue, £350,000
    Oct-2024
    		 141 2,482
    14, Greenfield Avenue, £285,000
    Oct-2024
    		 94 3,031

    See the entire list of all sales in HU13 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.