Methodology

01 Government Data Sources

Every input to True Driving Cost's calculations is official U.S. government data (EPA, DOE, EIA, BLS and BEA) - no third-party or industry data feeds are used. This site does publish a small number of its own derived metrics computed from that data (the Fuel Price Risk Score and the exact vehicle rankings described in Visualizations), and each is explicitly labeled as this site's own computation, never attributed to EPA or any government source. There are three groups of underlying data: the FuelEconomy.gov and historical price sources described next, and the Bureau of Labor Statistics and Bureau of Economic Analysis figures behind the ownership-costs panel (see Ownership Costs Beyond Fuel). The first two are:

FuelEconomy.gov REST API, maintained jointly by the U.S. Department of Energy (DOE), Office of Energy Efficiency & Renewable Energy, and the U.S. Environmental Protection Agency (EPA). This is the primary, real-time data source for every vehicle-specific figure on the page.

• Vehicle data: fueleconomy.gov/feg/ws/index.shtml
• Fuel prices: fueleconomy.gov/ws/rest/fuelprices
• EPA fuel economy program: epa.gov/fuel-economy
• EPA Green Vehicles: epa.gov/greenvehicles

All API requests for the selected vehicle's own specs are made client-side in real time. No individual vehicle data is cached, stored, or modified by True Driving Cost.

DOE Alternative Fuels Data Center historical gasoline price series, used only by the Cost Uncertainty Monte Carlo simulation, the historical trend regression, and the Sensitivity Tornado's price factor (see Visualizations). Unlike the FuelEconomy.gov data, this is not fetched live: it is embedded directly in the page's code as 76 years of nominal price levels (1950–2025) and the 75 real year-over-year percentage changes between them, sourced from the DOE's "Average Annual Retail Price of Gasoline, 1950–2023" series extended through 2025 using EIA's Short-Term Energy Outlook (September 2026 edition, Table 2) annual average regular gasoline retail prices for 2024 ($3.31) and 2025 ($3.10). This series needs one new year appended annually once EIA publishes the prior year's final annual average - see Data Freshness.

EPA/DOE Fuel Economy Guide vehicle database (Data/vehicles.csv, model year 2026, refreshed September 2026), a separate static snapshot from the live per-vehicle API above, used only to build the reference population this site compares your selected vehicle against: the class-percentile boxplots (Figs. 7 and 8), the Efficiency Gauge's population context, the EPA score percentile context, the Fuel Price Risk Score's cost-magnitude percentile, and the exact vehicle rankings. This snapshot covers 1,166 MY2026 vehicle configurations with a valid combined MPG/MPGe figure (841 of them non-EV with a valid CO₂ figure). Like the historical price series, this snapshot does not update itself and is refreshed periodically as new model-year data becomes available - see Data Freshness.

02 API Fields Used

The following fields are retrieved from the FuelEconomy.gov /vehicle/{id} endpoint for each selected vehicle:

Fuel prices are retrieved from the /fuelprices endpoint:

03 Fuel Cost Calculation

Conventional Vehicles (Gasoline, Diesel, E85, CNG)

Fuel cost is computed using EPA city and highway fuel economy ratings, weighted by the user's specified city/highway driving mix using the EPA harmonic mean formula:

The harmonic mean is used (rather than arithmetic mean) because fuel economy in MPG is a rate (miles per gallon). The harmonic mean correctly weights the proportions of city and highway driving. This is the same formula used by the EPA to calculate combined fuel economy on vehicle window stickers.

04 Electric & Plug-in Hybrid Vehicles

Battery Electric Vehicles (BEVs)

For pure electric vehicles (where atvType = "EV" and no plug-in hybrid indicator), fuel cost is calculated using the EPA electricity consumption rating, blended by the same city/highway driving mix used for gas vehicles - EPA rates city and highway electricity consumption separately for EVs, and city driving is usually somewhat more efficient due to regenerative braking:

Where cityE/highwayE are the EPA-rated electricity consumption in kWh per 100 miles. Unlike the harmonic mean used for gas MPG, this is a straight weighted average, since kWh/100mi is already energy-per-distance rather than a rate like miles-per-gallon. The default electricity rate is sourced from the FuelEconomy.gov fuel prices API. Users can override this with their local rate.

Plug-in Hybrid Electric Vehicles (PHEVs)

For PHEVs, annual mileage is split between electric (charge-depleting) and gasoline (charge-sustaining) operation using the EPA's own utility factors, the estimated share of miles driven in charge-depleting mode, published separately for city and highway driving (cityUF, highwayUF) and blended with your city/highway mix:

The second term inside the parentheses covers plug-in hybrids that still burn some gasoline while running mostly on the battery (EPA's cityCD and highwayCD, gallons per 100 miles, blended the same way; zero for vehicles that do not). If a vehicle has no utility factors, the calculator falls back to its electric range divided by its total range, and if that is also unavailable, to gasoline-only operation using the conventional MPG ratings. The Fuel Price Risk Score and the cost-per-mile rankings use their own fixed reference assumptions for PHEVs (described in their sections), not this cost model.

05 Fuel Price Matching

Each vehicle's fuelType field determines which fuel price is applied. The matching logic:

Fuel prices are fetched once per session from the FuelEconomy.gov API, which returns a single national average with no regional breakdown. If the API is unavailable, fallback prices are used (currently $3.10/gal regular, matching EIA's 2025 annual average). Users can override the fuel price via the parameter adjustment interface.

State-level regional adjustment. When a state is selected, the live national price is scaled by that state's real regional price ratio (state gas price ÷ a fixed national reference price, both sourced from this site's own state pages, EIA Weekly Retail Gasoline Prices, August 2026 vintage) rather than substituting a frozen dollar figure - so the displayed price stays as current as the live national API allows while still reflecting real regional variation.

06 User Parameters & Validation

Users provide three parameters that shape the analysis:

Additional override parameters (accessible via the results interface):

All inputs are validated with a clamp(value, min, max) function at every entry point (dropdown selection, popover input, and programmatic update) to prevent invalid calculations.

07 Visualizations

All charts are rendered client-side on HTML5 canvas with devicePixelRatio scaling for crisp rendering on high-DPI displays. No external charting libraries are used.

Fig. 1: Fuel Cost Timeline

A single running-total line chart of cumulative fuel cost over the ownership period, at today's flat fuel price, with a point marking each year (hoverable for that year's exact annual and cumulative figures) and the final total labeled directly on the last point. Annual cost is not shown as a separate per-year panel: under this flat-price, constant-mileage model, annual cost is mathematically identical every year, so a bar-per-year would just repeat the same number - instead that constant rate is stated once as a corner annotation. The probabilistic range around this flat-price estimate is Fig. 5's job, not this chart's.

Fig. 2: Driving Mix Sensitivity Curve

A continuous curve plotting total fuel cost at every city/highway driving mix from 0% city (all highway) to 100% city. Computed by recalculating total fuel cost at 2% intervals across the full mix range. The user's selected mix point is highlighted with a diamond marker. Best and worst cost points are labeled. A multi-pass label collision avoidance algorithm prevents text overlap.

Fig. 3: Fuel Price Scenario Fan Chart

Four cumulative cost curves showing how total fuel cost varies under different fuel price assumptions:

• Low (−25%): Fuel price 25% below current EPA price
• Current: Current EPA price from FuelEconomy.gov
• High (+35%): Fuel price 35% above current
• Spike (+75%): Fuel price 75% above current

The shaded fan regions between curves illustrate the compounding effect of fuel price uncertainty over the ownership period. End labels use collision avoidance to prevent overlap.

Fig. 4: Efficiency Gauge

A horizontal gauge showing the vehicle's city MPG, highway MPG, and effective combined MPG at the user's driving mix. The gauge track spans from 75% of the lower rating to 125% of the higher rating. An active region highlights the operating range. The effective MPG marker shows where the vehicle operates at the selected driving mix, and a caption states whichever of city or highway is actually more efficient for this specific vehicle - for roughly 30% of MY2026 vehicles, nearly all hybrids, city MPG is higher than highway due to regenerative braking, so this is not assumed to always favor highway. Alongside the gauge, this vehicle's combined MPG is also placed against the real percentile distribution of its own body-style class (845 non-EV MY2026 vehicles), computed from the same vehicle database used for Figs. 7 and 8.

Fig. 5: Cost Uncertainty (Monte Carlo Percentile Fan)

Unlike the fixed-percentage scenarios in Fig. 3, this chart quantifies fuel-price uncertainty statistically. The model resamples (with replacement) the 75 real year-over-year percentage changes in the combined 1950–2025 gasoline price series described in Government Data Sources, compounding a randomly drawn change for each year of the ownership period, across 1,500 simulated price paths. At each year, the 10th, 25th, 50th (median), 75th, and 90th percentiles of cumulative cost across all simulated paths are plotted as a fan: a light outer band (10th–90th percentile) and a darker inner band (25th–75th percentile), with the median as a highlighted line. Because the resampling draws from actual historical annual changes rather than an assumed distribution shape (such as a normal distribution), the simulation reflects the real fat-tailed, skewed behavior of historical gasoline prices, including energy-crisis years. For battery electric vehicles, this chart renders as a flat, zero-width band, since EV charging cost is not exposed to gasoline price volatility in this model.

Fig. 5b: Outcome Distribution (Histogram + Gaussian KDE)

A 30-bin equal-width histogram of the 1,500 simulated final-year outcomes from Fig. 5, overlaid with a Gaussian kernel density estimate using Silverman's rule-of-thumb bandwidth (h = 0.9·min(σ, IQR/1.34)·n^-1/5), and a Normal distribution of the same mean and variance (dashed) for direct comparison. The gap between the KDE and the Normal curve is the same skew/kurtosis reported in the accompanying text. Mean and median are marked as separate reference lines since they diverge whenever the distribution is skewed. Renders as a single spike for BEVs (no cost variability to distribute).

Fig. 5c: Cumulative Probability (Empirical CDF)

The empirical cumulative distribution function of the same 1,500 outcomes: for any dollar value on the x-axis, the curve gives the fraction of simulations at or below it, read directly from the sorted outcome array (no distributional assumption). Plotted against the CDF of a Normal distribution with the same mean/variance (dashed) for comparison. P10/median/P90 are marked directly on the curve.

Fig. 5d: Historical Price Trend

An ordinary-least-squares regression of ln(price) on year index, fit across all 76 years of the combined nominal gas price series (1950–2025, see Government Data Sources) - a semi-log fit, the standard approach for a variable that grows multiplicatively rather than additively, so a constant compounding growth rate renders as a straight line. A 95% prediction interval band is computed with the standard formula SE_pred(x) = s·√(1 + 1/n + (x−x̄)²/S_xx). The fitted trend (solid) is then extrapolated forward through the user's own ownership-years input (dashed, shaded region, separated from the fitted range by a divider labeled with the current year, not the last year of real data - those are two different years once you're partway through the current one) and that projected price is run through the selected vehicle's real fuel-consumption numbers to produce a trend-implied total cost, compared against the calculator's primary flat-price estimate. For BEVs, this projected cost is not computed, since gasoline price trends have no bearing on electricity cost - the chart states this directly rather than showing a fabricated number.

Fig. 5e: Tail Risk (Value at Risk & Conditional VaR)

Two standard quantitative risk-management metrics, computed directly from the same 1,500 simulated outcomes as Fig. 5b/5c: Value at Risk (VaR) at the 95th and 99th percentiles (the loss threshold such that outcomes exceed it only 5% or 1% of the time), and Conditional VaR / Expected Shortfall (CVaR) at 95%, the mean of all simulated outcomes at or beyond the VaR-95 threshold. CVaR is reported because VaR alone describes only a threshold, not how severe outcomes get once you're past it - CVaR is consistently the harsher, more complete number. Both are vehicle/years/miles/mix-dependent, since they're computed from the user's own simulated outcome set. Not computed for BEVs, for the same reason as Fig. 5d.

Fig. 6: Sensitivity Tornado

A tornado diagram ranking which input variables have the largest effect on total fuel cost. Each of four inputs (annual miles, city/highway driving mix, fuel or electricity price, and vehicle efficiency) is independently perturbed by ±20% (or ±20 percentage points for driving mix, clamped to 0–100%) while holding all other inputs at the user's current settings, and the resulting low/high total-cost outcomes are plotted as horizontal bars. Bars are sorted by swing size (widest at top), with a dashed reference line marking the unperturbed base-case total. Vehicle efficiency is perturbed on the underlying city/highway MPG or MPGe rating (or kWh/100mi consumption rate for BEVs, inverted so a larger number always represents worse efficiency), not as a naive linear scaling of cost, since fuel cost is inversely related to fuel economy.

Fig. 7: Cost vs. CO₂ by Vehicle Class

A scatter plot of the median cost-per-mile against the median CO₂ tailpipe emissions for each of 12 EPA body-style classes (bubble size = number of vehicles in that class), computed directly from the Data/vehicles.csv snapshot described in Government Data Sources: 841 non-EV MY2026 vehicle configurations with a valid tailpipe CO₂ figure. A fitted trend line and Pearson correlation (computed fresh from those 12 class medians, not a fixed number) show that classes which cost more to fuel also tend to emit more CO₂ per mile. The current vehicle is marked at its own actual cost and emissions, not just its class median, so it can visibly sit off the class-median trend. Not shown for BEVs, which have zero direct tailpipe emissions. This replaced an earlier version of this chart that duplicated Fig. 8's boxplot layout for a different metric, which read as repetitive rather than as a distinct analysis.

Fig. 8: Where You Rank

A box-plot comparison of this vehicle's fuel cost per mile against 1,166 real MY2026 vehicle configurations from the same Data/vehicles.csv snapshot, grouped into 12 body-style classes. Boxes show the 25th–75th percentile of each class, whiskers the 5th–95th, with a white tick at the median. Cost per mile is computed as a fixed reference fuel or electricity price divided by each vehicle's EPA-rated combined MPG or MPGe (1 gallon-equivalent = 33.7 kWh, the standard EPA conversion factor) - $3.10 regular, $3.84 midgrade, $4.19 premium, $3.76 diesel, $0.165/kWh electricity - so gasoline, hybrid, EV, and PHEV vehicles all sit on one common, comparable axis rather than incomparable MPG/MPGe/cost units. These are fixed reference prices used only to build a consistent axis for this comparison, not the live price used in the rest of the calculator. PHEV figures blend gas-mode and electric-mode cost/mile 50/50, a default utility-factor assumption since the Fuel Economy Guide does not publish a per-vehicle electric-use share. The current vehicle's own class is highlighted, with its actual cost/mile marked and its percentile rank within that class computed by piecewise-linear interpolation between the class's known percentile breakpoints. This compares against today's MY2026 new-vehicle lineup as a whole, not specifically vehicles from the selected model year, since the Fuel Economy Guide snapshot is for one model year.

Directly above this chart, a set of exact-rank badges give a real integer position rather than an interpolated percentile - "#81 of 292," not "better than approximately 72%." This is possible here specifically because the full sorted list of values for each metric (not just its percentile breakpoints) is embedded in the page. Four rankings are shown when data allows: cost per mile within the vehicle's own class and across all 1,166 vehicles overall (cheapest = #1); CO₂ emissions within class (cleanest = #1); and combined MPG/MPGe within class (most efficient = #1). CO₂ and MPG are not given an "overall" cross-class ranking, since comparing a truck's emissions or MPG directly against a compact car's is not a fair or meaningful ranking the way a shared dollar-per-mile unit is - the population itself, not just the vehicle, changes what "efficient" means across those classes. Not shown for BEVs for CO₂/MPG (comb08 for a BEV is MPGe on a different scale than the non-EV MPG population these rankings are built from).

Fig. 9: EPA Comparison

A three-bar comparison of annual fuel cost on three different bases: EPA's own published estimate for this specific vehicle (fuelCost08, at EPA's standard 15,000 mi/yr, 55% city), the user's own parameters, and an average new vehicle on EPA's basis - the third bar derived by dividing EPA's published 5-year youSaveSpend figure by 5 and adding or subtracting it from fuelCost08, not an independently invented number. These three figures use genuinely different assumptions and are not meant to be read as three measurements of the same thing.

Fig. 10: Fuel Price Risk Score

See Fuel Price Risk Score below for the full methodology behind this chart and its underlying index.

08 EPA Scores & Ratings

Three EPA ratings are displayed directly from the API with no modification:

• EPA Fuel Economy Score (feScore): 1 to 10 scale relative to all vehicles. Higher is better. Rendered as an animated score ring.
• EPA Greenhouse Gas Rating (ghgScore): 1 to 10 scale based on CO₂ tailpipe emissions. Higher is better. Rendered as an animated score ring.
• CO₂ Tailpipe Emissions (co2TailpipeGpm): EPA-measured grams per mile. Displayed on a spectrum from 0 g/mi (BEV) through 750 g/mi (the real maximum across the 841 non-EV MY2026 vehicles in Data/vehicles.csv, not a round guessed ceiling), with a classification against that same database's real quartile boundaries (25th/50th/75th/95th percentile: 316/398/468/572 g/mi) - this site's own computation from the government database, not an EPA-published national average.

Both the EPA Fuel Economy Score and Greenhouse Gas Rating are also shown against a real population percentile ("Beats N% of 1,172 MY2026 vehicles on this scale"), computed from the feScore/ghgScore distribution in the same vehicle database.

Scores of −1 (EPA's code for "not rated") are treated as unavailable and displayed as "--".

Score labels are assigned as follows:

09 Derived Metrics

The following metrics are derived from the computed fuel cost data using standard arithmetic:

10 EPA Comparison Data

Two EPA comparison fields are available for context:

• EPA Annual Fuel Cost (fuelCost08): The EPA's own estimate of annual fuel cost for the vehicle, calculated assuming 15,000 miles per year at 55% city / 45% highway driving at current fuel prices. Displayed for comparison alongside the user's customized estimate.
• 5-Year Savings vs Average (youSaveSpend): EPA's estimate of how much the vehicle saves (positive) or costs more (negative) in fuel over 5 years compared to the average new vehicle. Directly from the EPA database.

Both fields are visualized together in Fig. 9 (see Visualizations), alongside the user's own parameter-based estimate, on three clearly distinct bases that are not meant to be read as three measurements of the same quantity.

11 Fuel Price Risk Score

This is True Driving Cost's own synthesized metric - explicitly disclosed as such wherever it appears, never attributed to EPA or any government source. It combines two quantities already computed elsewhere on this page into one 0–100 index, using a standard risk = likelihood × magnitude framing rather than an arbitrary formula:

Both factors are shown alongside the score, not hidden behind it. Fig. 10 plots them on a continuous risk-intensity map (radiating from the low-exposure/low-cost corner) rather than a flat four-quadrant grid, with the current vehicle marked at its own exact position.

12 Ownership Costs Beyond Fuel

Below the headline fuel estimate, the calculator shows a panel of typical other costs of owning a vehicle. These are national averages, not estimates for your vehicle, and are labelled that way on the page. Every number in the panel comes from a file in this project's data folder and is checked against that file by an automated script; the full list of figures, files and locations is at the end of this section.

What is included and where it comes from

• Insurance; maintenance and repairs; registration, licenses, leases and other charges; finance charges. U.S. Bureau of Labor Statistics (BLS), Consumer Expenditure Surveys, average annual expenditures of all consumer units (households), 2024. Each is divided by the BLS figure for average vehicles per consumer unit (1.9) to give a per-vehicle amount. Because both numbers are averages across all households, including those with no vehicle, the ratio is the average per vehicle across the whole fleet, including older vehicles and vehicles bought without a loan.
• Range across income groups. BLS Table 1101, 2022, gives the same items and the number of vehicles for each income fifth of households. The ratio of each fifth's per-vehicle spending to the all-household per-vehicle spending is applied to the 2024 average. The panel shows the lowest and highest of the five results. This shows how averages differed between income groups; it is not a range for your vehicle.
• Depreciation. BLS annual depreciation rates by automobile age (Monthly Labor Review, 2024, Chart 1 data, second quarter 1996 to first quarter 2022), compounded year by year over your ownership period, applied to the average price paid for a new vehicle (U.S. Bureau of Economic Analysis, NIPA Table 7.2.5S, average consumer expenditure per new car or per new light truck, mean of the latest twelve months in the file). Light trucks include pickups, sport utility vehicles and vans. You can replace the price with your own.

Assumptions and known limits

• The BLS insurance series has a break in 2019. That year BLS changed the source of its vehicle insurance estimate from its Diary Survey to its Interview Survey, having judged the Interview Survey a better measure (see BLS, Vehicle Insurance Spending in the 2019 Annual Calendar Year Estimates). Only 2019 and later insurance figures are used. As an independent check, the BLS Producer Price Index for private passenger auto insurance rose about 2.8% from 2018 to 2019, far less than the change in reported spending.
• The depreciation rates are in constant dollars. BLS estimated them from households' reported purchase prices, controlling for make, model and model year, after converting prices to constant 1982–84 dollars (see BLS, A consumption measure for automobiles). Applying them to current prices slightly overstates the loss in current dollars. Age 0 is a newly purchased automobile and its rate is used for the first year of ownership; BLS states that its data are not sufficient to estimate rates reliably for vehicles 11 years and older, and the age 11-and-over rate is used after year 11 only for very long ownership periods.
• These are averages across all vehicles and households. The panel does not adjust for vehicle type, fuel type, age, price, state, driver or coverage, except where you enter your own price or premium.
• Non-fuel amounts do not vary with your annual mileage in this estimate. Fuel does.
• Finance charges are an average over all vehicles, including those bought without a loan.
• Amounts are rounded to the nearest $10, except the fuel figure, which repeats the calculation above.

Not used

Data from private sources (for example AAA's annual cost study) is not used, because its terms of reuse could not be confirmed. Only U.S. government data is used.

13 What Is Not Included

The headline estimate covers fuel and electricity only. The separate panel described in Ownership Costs Beyond Fuel adds national-average figures for other ownership costs; they are not specific to any vehicle. The following are not included anywhere on the page, because no per-vehicle U.S. government data source exists for them:

• Per-model depreciation, insurance, maintenance and financing: only national averages are shown (see the ownership-costs section); no federal agency publishes per-model figures.
• Tires: not shown separately (whether BLS counts tires within "maintenance and repairs" is not stated in the tables used).
• Sales tax: varies by state and locality; not included.
• Parking & tolls: vary by geography and individual usage; not included.

14 Limitations & Assumptions

Key assumptions and limitations:

• Constant fuel price in the primary estimate. The headline total cost (Sections 01–08) applies the current EPA fuel price uniformly across the entire ownership period. No inflation modeling, fuel price forecasting, or future price speculation is applied there. The fuel price scenario fan chart (Fig. 3) illustrates sensitivity to a few fixed price changes but does not predict prices. The separate Cost Uncertainty section (Fig. 5) does model future price variation statistically, by resampling real historical annual gasoline price changes. This is a backward-looking volatility model, not a forecast of where prices are actually headed, and it does not know about future events any more than a fixed price assumption does.
• EPA test conditions. Fuel economy ratings are measured under EPA laboratory test conditions. Real-world fuel economy varies based on driving style, speed, weather, terrain, cargo, tire pressure, and vehicle condition. The EPA estimates real-world fuel economy is typically 10 to 20% lower than lab results for some vehicles.
• Constant annual mileage. Annual mileage is assumed constant across all years of ownership.
• No vehicle degradation. Fuel economy is assumed constant; no battery degradation (for EVs/PHEVs) or engine efficiency loss is modeled.
• Regional gas prices. FuelEconomy.gov's live price is a national average with no regional breakdown; selecting a state applies a real regional ratio on top of it (see Fuel Price Matching), but electricity prices are not regionally adjusted and remain a national figure.
• PHEV driving pattern. PHEV electric/gasoline split uses EPA's utility factors, which are population-level estimates, not your charging behavior. Your actual electric share depends on daily driving distance, charging frequency and route patterns.
• Tank size for vehicles that don't report one. See the disclosure in Derived Metrics - a real median (24 gal), not a government-published per-vehicle figure, for the roughly 96% of vehicles without one.
• Ownership-costs panel. The non-fuel figures are national averages, not estimates for your vehicle; see the assumptions listed in Ownership Costs Beyond Fuel.
• Volatility model applies one series to every fuel type. See the disclosure in Fuel Price Risk Score.

15 Data Freshness

Not everything on this page updates itself at the same rate. It's useful to be clear about which parts are live and which are periodic snapshots:

• Fully live, every page load: the vehicle picker (year/make/model/trim) and every individual vehicle's specs, fetched from the FuelEconomy.gov API in real time with no caching, plus the current national fuel price. These never go stale on their own, as long as that API stays available.
• Static snapshot, needs periodic manual refresh: the historical gas price series (Fig. 5, 5d, and the Sensitivity Tornado's price factor) needs one new year appended annually, once EIA publishes the prior year's final annual average (typically January or February) - this is the single most time-sensitive piece, since the "current year" divider on Fig. 5d depends on it. The Data/vehicles.csv reference population behind Figs. 4, 7, 8, the EPA score percentiles, and the Fuel Price Risk Score is a September 2026 MY2026 snapshot, refreshed roughly annually as new model years become available. The state-level regional gas price ratios are an August 2026 vintage, refreshed on a similar cadence.

None of this affects the core, always-live calculator experience - it affects only how current the comparison/statistical layer built on top of it is.

This Site's calculator and content were built using AI; the underlying data is not. Figures come from the official U.S. government sources listed above, and calculated figures are computed from them by code written with AI. See our Terms of Service for the full disclosure.