How we compute the data

For each make, model and year we compute an odometer distribution and report three points: the 10th percentile (low), the 50th percentile (median, what half of the cars read below) and the 90th percentile (high). The band is the range where most cars of that age fall.

The primary distribution is computed from the UK DVSA anonymised MOT record, which carries an odometer reading at every test but no VIN and no personal data. It is a fleet proxy, not a per-car history: many cars imported to the Baltics are ex-UK, so the UK pattern is a useful, honestly labelled prior. Alongside it, where the sample allows, we show the Lithuanian home-market band computed from TRANSEKSTA technical inspections, using each vehicle's latest reading only.

We publish a band only when it rests on at least 1,000 readings. Groups below that threshold are withheld rather than shown thin. The current release covers 471 make, model and year pages, drawn against a Lithuanian fleet set of 2,345 model groups.

Fail rates are initial-test (first attempt, non-retest) failure shares. For the UK proxy we use class 4 MOT tests: a pass is P or PRS, a fail is F, and aborted tests are excluded. Each rate is compared against the median for cars of the same age in the same fleet, so the figure reads as "higher than", "in line with" or "lower than" typical, not as a bare percentage. The Lithuanian first-inspection fail rate is shown from TRANSEKSTA where the sample supports it.

For a single VIN, the free mileage check lines up official READ-type odometer readings in date order and flags a possible rollback only when a later reading is strictly lower than an earlier one. We do not infer, estimate or guess a reading between records, and we mark the gaps where no official reading exists. A flag is a prompt to investigate, never a proof of fraud; a clean result is not a guarantee.

Separately, at the model level, we report the fleet rollback prevalence from the Lithuanian inspection record: the share of cars with two or more readings where a later reading falls below an earlier one at some point. Because inspection dates are week-precise and data entry adds noise, we show the larger-than-5,000-km drop share alongside the raw share so the figure is not overstated. This is fleet context, never a verdict on an individual car.

Recall signals come from three independent EU-market registers: the EU Safety Gate rapid alert system, the German KBA recall database, and the Dutch RDW open-recall prevalence. We report each source on its own and never add them together: they use different registers and different scopes, so a Safety Gate alert and a KBA campaign may describe the same defect or different ones. The feeds carry no VIN range, so a model-level match is advisory, not a per-VIN applicability claim. Verify any recall with the manufacturer against the specific car.

CO2 and fuel or energy consumption are EU type-approval figures from the European Environment Agency's monitoring of new car registrations under Regulation (EU) 2019/631, reported as a registration-weighted mean per make, model and fuel. Type-approval consumption understates real-world use, so any running-cost estimate built on it should be read as a floor, not a promise.

The free VIN decoder resolves specification from NHTSA vPIC plus an in-house pattern map, with manufacturer and build country from the ISO 3780 world manufacturer identifier. We show vehicle facts only, never owner or personal data, and we never reject a European VIN on a US check digit. A model name is emitted only on an exact pattern match; otherwise we show a model family or make and plant and offer an outbound link to the manufacturer's own decoder, rather than assert false precision.

Fleet distributions are aggregates across many cars, not the history of one car. Model-level recall and CO2 figures describe a model or a production window, not a specific vehicle. A pre-check is a screening tool: it reads what the official record holds and admits what it does not. Inspect the vehicle and its paperwork before buying.

To put this to work: browse typical mileage by model, decode a specific VIN, or run the free mileage check on one car.