VehicleReliability.com

Compare vehicle reliability with Data Science

Cars

Analytics

Data Science

Hey Product Hunt 👋 I built Vehicle Reliability because I got tired of the fact that "reliable" is the vaguest word in car buying. Here's what set me off. Every reliability source out there — the big consumer magazines, the ratings sites, the forums — is ultimately built on asking owners whether they were satisfied with their car. That's a survey of feelings. It can tell you a model is "above average," but it cannot answer the question you actually have when you're standing in a dealership lot: how much more reliable is this one than that one? Is it 5% better or 300% better? Nobody can tell you, because a five-star scale has no units. So I spent the last stretch of nights and weekends building the thing I wanted to exist. What it actually does I pulled two decades of real-world vehicle failure records covering 2004–2026 model years, cleaned them, and normalized every count against actual sales volumes — because 500 complaints about a car that sold two million units means something very different than 500 complaints about one that sold 40,000. Then I split reliability into the two dimensions that most sites collapse into a single number: Frequency (the hassle factor) — how often a vehicle has problems relative to its direct segment competitors Severity (the pain factor) — weighted so a failed transmission and a glitchy infotainment screen don't count the same Every score is indexed against the vehicle's own competitive cohort. 1.0 is exactly average for its class. Below 1.0 is a mathematical winner. Above 1.0 is a financial risk. That means you can compare two vehicles and get a real ratio, not a vibe. The parts I'm genuinely proud of Powertrains are scored separately. The hybrid and the gas version of the same model have meaningfully different risk profiles, and almost nobody separates them. Same badge on the tailgate, different car underneath. The Golden Year tracker. A year-over-year view of any model, which shows you the exact year a manufacturer quietly fixed a chronic problem — or the redesign that took a bulletproof car and ruined it. This turned out to be the feature I use most myself. The 10-point component X-ray. Engine, transmission, electrical, brakes, and the rest, each scored against the peer average. Useful for negotiating: walking in knowing a specific model year has an electrical failure rate well above its class changes the conversation with a salesperson. Volatility. Whether a model is consistently good or wildly hit-or-miss year to year. This matters far more on older vehicles than anyone accounts for. Try it without signing up The sample dashboard at vehiclereliability.com/sample is completely unlocked — 2022 mid-size SUVs, every filter, every component score, no account needed. Poke at it and see whether the two-axis framing makes sense to you. Full database has a 7-day free trial if you want to go deeper.