How the Seasoned Score Works

Comparing ski resorts is straightforward when you're choosing between two. You look at the stats that matter to you, weigh them up, and decide. When you're choosing between nearly 300, it becomes impractical — manually comparing 15 stats per resort across hundreds of options is the kind of task that ends with a spreadsheet you abandon after forty minutes.

A composite score solves that problem. One number per resort, produced consistently using the same method, lets you rank the full database and identify the realistic options quickly. The alternative — asking people to eyeball hundreds of data points — isn't more rigorous. It's just less efficient.

But a composite score is only as trustworthy as its methodology. A black-box number that nobody can audit is not a useful analytical tool; it's just an assertion. We publish the methodology completely — not as a summary, but as the actual weights and the reasoning behind each one.

What the Seasoned Score Is

The Seasoned Score is a weighted average of percentile rankings across up to 15 statistics (v4). Here's exactly how it works:

1. For each stat, every resort in the database is ranked from worst to best for a seasonaire (0 = worst, 1 = best).
2. Each resort's raw value is converted to a percentile — where it falls relative to all other resorts with data for that stat.
3. Those percentiles are multiplied by the weights below and summed.
4. The result is scaled to a 0–100 range.

The weights (v4 — current):

Stat	Weight	Direction	Why
Skiable area (km²)	20%	Larger = better	A seasonaire skis the same mountain for 4–6 months, not one week. Terrain size is about not getting bored in March, not holiday variety.
Affordability (cost of living)	16%	Cheaper = better	Ranked as monthly rent + 4× weekly groceries in USD. The biggest variable in your season budget after you've accepted the job — often the difference between saving money and breaking even.
Season length (days)	15%	Longer = better	Directly tied to a seasonaire's income — every additional day is another day of wages. Nothing affects the economics of a season more directly.
Vertical drop (m)	14%	Higher = better	More vertical per run means more variety within a session. A resort with 1,500m of vertical offers a meaningfully different daily skiing experience to one with 600m.
Average annual snowfall (cm)	14%	Higher = better	Consistent snowpack across the whole season matters. A resort with high average snowfall is less likely to have the bare-patch weeks in January and the slush problem in March that affect ski quality during the days you're actually using the pass.
Nightlife & vibes	8%	Higher = better	The après-ski scene matters when you're there for 4–6 months, not just a week. A good scene = better social life, easier to meet people, better staff morale.
Staff accommodation	5%	Better = better	Whether the resort actively provides or helps staff find housing is a major practical factor. Bad staff housing makes a season significantly harder to plan.
Beer price (proxy for overall resort cost)	4%	Cheaper = better	A reliable proxy for overall resort pricing culture. Cheap beer generally means cheaper everything else — food, gear hire, socialising.
Airport distance (km)	2%	Closer = better	Seasonaires fly home mid-season, meet visiting family and friends, and travel between jobs. Proximity to an international airport matters far more than for a one-trip tourist.
Day ticket price	1%	Cheaper = better	Low weight because most seasonaires ski on a staff pass. Included as a proxy for how tourist-priced the resort feels day-to-day.
Lift count	1%	More = better	Lowest weight by design. Lift count is highly correlated with skiable area — extra lifts don't always add new terrain.
Beginner-friendliness	0% default	Higher = better	Default is 0% — not everyone arrives as a beginner. Weighted up automatically by the quiz for first-timers.
Gnarliness	0% default	Higher = better	Default is 0% — not everyone needs expert terrain. Weighted up by the quiz for advanced/freeride skiers.
Groomed ratio	0% default	Higher = better	Default is 0% — boosted by the quiz for carvers who want long groomed runs.
Backcountry access	0% default	Higher = better	Default is 0% — boosted by the quiz for backcountry and slackcountry-oriented skiers.

Stats with 0% default weight are included in the engine but inactive unless the resort picker quiz detects that they matter to you — which it will, based on your answers.

Why Seasonaire Weights Look Different to Tourist Weights

If you built a score to answer "which resort is best for a one-week ski trip," the weights above would be wrong. Season length would drop to near zero (a tourist is constrained by their holiday dates, not the resort's open season). Rent and groceries would be replaced by accommodation quality and restaurant prices. Terrain variety and lift count would weigh heavily.

The Seasoned Score doesn't do that. It's built for someone whose income, daily expenses, and quality of life for up to six months is tied to a single resort. Those people have different priorities to someone flying in for a week. The weights reflect that.

What the Score Is Not

It's not a holiday ranking. If you're planning a ski trip, use a tourist site. Skiresort.info, OnTheSnow, and Where-to-Ski are all built for your use case. The Seasoned Score is deliberately not built for it.

It's not definitive. The weights represent a considered judgment about what matters to most people doing a working season. "Most" is not "all." If you care very little about terrain and very much about snowfall quality, or if rent is irrelevant because your employer provides accommodation, the default score is a starting point rather than a final answer. The resort picker quiz lets you apply your own weights to the same underlying data.

It's not complete for every resort. Resorts without sufficient data to calculate a meaningful score receive no score rather than a misleading partial one. If a resort you care about shows no score, it means data collection for that resort is incomplete rather than that the resort scored zero.

How Costs Are Compared Across Currencies

Rent in Morzine is quoted in euros. Rent in Whistler is quoted in Canadian dollars. Rent in Niseko is in Japanese yen. Comparing these directly in local currency is meaningless.

Cost stats — rent, groceries, and ticket prices — are stored in local currency and converted to USD for scoring using exchange rates from frankfurter.app, a public, ECB-sourced currency API. The conversion rate used and the date it was applied are stored alongside the data. This means a €750 French room and a CAD 1,050 Canadian room are both represented as USD figures before the percentile calculation runs, making the comparison valid across countries.

Local currency values remain visible on resort pages alongside the converted figure — so you know what you're actually paying in the local economy, not just the abstract USD comparison number.

How the Score Will Evolve

The score formula is versioned. The current version uses only objective, externally-sourced statistics. That's a deliberate starting point — it avoids the noise of early-stage review data and keeps the methodology clean while the database is being built out.

Phase 4 of Seasoned.info adds user-submitted reviews: seasonaire ratings of the mountain, accomodation quality, community strength, and general resort livability. Once enough reviews exist to be statistically meaningful, a new version of the formula will incorporate those signals — likely percentage who would return for another season and resort rating averages. Eventually, when enough users tell us what's important to them, our seasoned score will change to represent the communities preferences.

When that happens: old scores remain attributable to their old formula version. The new formula publishes its own full transparency breakdown, identical in format to this one. Scores don't silently change meaning — you'll always be able to see which version produced a number and what that version was doing.

The Bottom Line

The Seasoned Score is a consistent, transparent starting point for comparing ski resorts from a working-season perspective. The weights are shown in full above. The methodology is reproducible. The data sources are documented on each resort's stat rows.

It's useful for narrowing nearly 300 resorts down to a realistic shortlist quickly. It's not a substitute for reading the resort pages, checking the visa situation for your nationality, and confirming the job market is there for the work you do.

For a version with your own weights applied, use the resort picker. To see how all resorts rank on the default formula, see the leaderboard.