krBilregnskab

The fine print, in plain language

How this site works, and where it could be wrong

Every number here comes from public data or a source we can point to. Where we had to make a judgement call instead of measuring something directly, we say so on this page, not just in a footnote.

Where the data comes from

The UK reliability data is a stand-in, not a perfect match

We don't have a public, model-level Danish equivalent of the UK's MOT archive, so reliability comes from UK-market cars: UK roads, UK weather, UK road salt. A model's reliability relative to other models should carry over reasonably well, since it's mostly about how the car itself is built. The exact failure rate might not, since Danish winters, Danish roads and Danish driving habits differ from the UK's. Treat the ranking between cars as more trustworthy than the exact percentage for any one car.

We adjust for how far a car has typically been driven, so a model that's usually driven hard isn't unfairly compared to one that's usually driven gently. We only publish a reliability figure where there were enough tests to be confident in it. Where there weren't enough, we say so rather than show a shaky number.

The repair cost estimate is a rough index, not a garage quote

We count how often each part of a car fails its MOT test, then weight that by a per-brand multiplier for how expensive that brand's parts and labour tend to be. A failed headlamp bulb and a failed suspension arm currently count the same, which is a real simplification since a suspension repair costs far more. We turn that index into kroner using a flat rate of 3.000 kr per point per year, a judgement call, not a measurement, because no public dataset of Danish repair costs by model exists. At that rate, repairs are a modest slice of most cars' total cost. If the true rate is much higher, the ranking within a bracket could shift, though the overall shape of the site's findings should hold.

How we estimate a used price without scraping Danish listing sites

We don't have permission to pull prices from Bilbasen or DBA, and Denmark doesn't publish a public database of used car prices. So we built an estimate instead of leaving prices out entirely, and then checked that estimate against reality.

  1. Started from a market with almost no car tax. Poland's used car tax is negligible, so asking prices there are a reasonable stand-in for what a car is actually worth, before any country's tax is added. We used a public dataset of Polish used car listings (released into the public domain, no scraping needed) to see how each model's price changes with age.
  2. Converted to a Danish price using Denmark's real tax formula. We transcribed the actual registration tax formula from the Danish tax authority's published rate tables and applied it. This is where our estimate is weakest: Danish law technically wants a used car's tax scaled down by how much it's depreciated from new, and we don't have a reliable new price for every model to base that on. We approximate around this rather than inventing a new-car price. See "known limits" below.
  3. Checked the result against the real Danish market: real asking prices we looked up by hand across a spread of common models and price levels, and corrected the whole estimate by the gap we found. Cars under 150,000 kr were corrected separately from cars above it, since the gap wasn't quite the same size at both ends.

This calibration is honest but limited. We measured how well the correction fits the same real prices we used to build it, which will always look better than how it performs on a car we haven't checked. Treat "calibrated against real Danish listings" as true, and "accurate to within some exact percentage" as not yet proven.

Every price on this site also carries a confidence flag, low, medium or high, based on how many comparable foreign listings backed it up, and whether we had to borrow a whole brand's price pattern because one specific model didn't have enough listings of its own. You'll see this flag on any car page where it isn't "high."

Mileage matters too, and we adjust for it

A price estimate is anchored to a "typical" mileage for that car's age, not any specific odometer reading. We measured how much price actually moves with mileage from real Danish listings (about 3.9% for every extra 10,000 km), and use that to adjust a resale value when we compare a car bought at one age to the same car sold years later.

Cars we couldn't price at all

Suzuki and DS models are barely present in the foreign listings data we use, so most of them have nothing solid to build a price estimate from. For a few (Swift, Baleno, Ignis, Celerio) we found real Danish asking prices by hand and used the same shape-from-a-similar-car method as Skoda Citigo above, borrowing a same-segment model's depreciation curve and scaling it to that real price, marked "low confidence" since it rests on one or two real listings rather than a full curve. The rest still show reliability and running-cost data with no price and no ranking, clearly marked. 7 models are still unpriced.

What "most car for the money" means

Every bracket page has two lists. "Cheapest to own" ranks purely on money. "Most car for the money" blends that cost ranking with an engagement score built from power-to-weight, cylinder count and kerb weight, an equal 50/50 split, disclosed here rather than buried in the code. We measured that these two things pull in opposite directions more often than not: cars that are more fun to drive tend to cost more to run. Neither list is "more correct" than the other, they answer different questions.

What we won't do

Known limits, all in one place

Something on this page look wrong, or missing? The full pipeline and every reference file behind these numbers live in this project's repository. Nothing here is generated on request, every figure was computed ahead of time from the sources listed above.