Methodology
Data source
All data comes from the DVSA anonymised MOT testing dataset, published annually by the Driver and Vehicle Standards Agency. We use the 2024 dataset, which contains 57.9 million individual MOT test results and over 100 million failure items.
The data is anonymised — it contains make, model, registration year, mileage, test result, and failure reasons, but no registration numbers or personal information.
What "pass rate" means
Pass rate is the percentage of MOT tests where the vehicle passed first time without requiring any rectification. A test result of "Pass" or "Pass after rectification at station" (PRS) counts as a pass. A result of "Fail" counts as a failure.
We calculate pass rates per model, per model-year, per make, and per fuel type. Only groups with a meaningful sample size are shown (typically 1,000+ tests for models, 100+ for year breakdowns).
What MOT pass rate tells you
- How often a model has testable defects (brakes, lights, suspension, tyres, emissions, steering, bodywork corrosion, exhaust, seatbelts)
- Which specific components fail most often for each model
- How pass rates change with vehicle age
- Comparative defect rates between similar models
If you're buying a used car and one model consistently fails for suspension while another doesn't, that's useful — suspension repairs cost real money.
What MOT pass rate does NOT tell you
- Overall reliability — the MOT doesn't test engine internals, gearbox, electrics, air conditioning, infotainment, or most things that cause breakdowns
- Running costs — a car can pass its MOT and still be expensive to maintain
- Build quality — rattles, squeaks, and interior wear aren't MOT items
- How a specific car will perform — these are averages across thousands of vehicles of different ages and conditions
What skews the numbers
- Owner demographics — luxury cars score higher partly because owners invest more in maintenance, not necessarily because the cars are better built
- Pre-MOT checks — some owners get defects fixed before the test, which inflates the pass rate
- Age mix — a model that's only been on sale for 5 years will naturally score higher than one with 20 years of older examples in the fleet
- Variant grouping — the same model name can cover very different cars across generations
How we process the data
We run the raw DVSA CSV files through a multi-pass Python pipeline that:
- Reads all 57.9 million test results, computing pass rates, mileage averages, and age distributions per model, model-year, make, and fuel type
- Processes 100+ million failure items, matching each to its test to build per-model and per-model-year failure breakdowns
- Outputs JSON data files that are statically built into this website
The pipeline code is open source on GitHub.
Thresholds
- Model pages: minimum 1,000 tests
- Year breakdowns: minimum 100 tests per year
- League tables and rankings: minimum 10,000 tests
- Manufacturer rankings: minimum 50,000 tests
- Motorcycles are excluded from car rankings
Data licence and attribution
The DVSA anonymised MOT data is published under the Open Government Licence v3.0, which permits copying, publishing, distributing, and commercial use of the data, provided the source is acknowledged.
This site contains public sector information licensed under the Open Government Licence v3.0. Source: Driver and Vehicle Standards Agency (DVSA).
Disclaimer
This website is an independent publication. It is not affiliated with, endorsed by, or connected to the DVSA, DVLA, or any vehicle manufacturer, brand, or company mentioned on this site. All manufacturer and model names are used solely to identify the vehicles in the DVSA dataset and are the trademarks of their respective owners.
The statistics presented are derived from government open data and are provided for informational purposes only. They should not be used as the sole basis for purchasing decisions. Always check an individual vehicle's MOT history and consider a professional inspection before buying a used car.