How we calibrate budgets + stats

The three tiers

Every guide shows three daily totals: Backpacker (🎒), Mid-range (🧳), and Luxury (💎). The same labels cover four per-day categories in the cost calculator (stay, food, transit, activities), so you can mix and match — e.g. pay for a nicer room but eat where locals eat.

🎒 Backpacker — what it buys you

• Stay: hostel dorm bed or a basic guesthouse / cheapest 2-star room. Shared bathrooms are likely.
• Food: street food, markets, self-catering from supermarkets, one sit-down meal a day at most.
• Transit: buses, the metro, overnight trains. Walking when it's faster. No taxis.
• Activities: free or cheap — public parks, free museum days, self-guided walks, one paid attraction every few days.

🧳 Mid-range — what it buys you

• Stay: 3-star hotel or a well-reviewed Airbnb / private room. Consistent, comfortable, nothing fancy.
• Food: neighborhood restaurants, a mix of casual and one nicer dinner. Coffee-shop breakfasts.
• Transit: transit cards, occasional rideshare, airport express. A rental car for natural / island destinations.
• Activities: 1–2 paid attractions per day, a guided day tour every few days, one splurge experience.

💎 Luxury — what it buys you

• Stay: 4- or 5-star hotel, boutique resort, or top-tier rental. Often in a prime-location district.
• Food: fine-dining dinners, tasting menus where they exist, high-end cocktail bars, hotel breakfast.
• Transit: taxis or private car door-to-door, premium train classes, no bus commitments.
• Activities: private guides, premium experiences (hot-air balloon, Michelin-adjacent cooking class, helicopter tours where they exist).

Daily-budget $/day numbers

Each destination has a hand-calibrated triple — e.g. Bangkok is { budget: 25, mid_range: 60, luxury: 180 }. These aren't pulled from a single API; they're editorial judgements cross-checked against:

• current hotel prices at the tier implied above, sampled in shoulder season, averaged across 3–5 neighbourhoods
• typical food costs from the guide's own Typical Costs table (street meal, mid-range dinner, wine glass, coffee)
• regional transit passes / rideshare averages where the data's reliable
• for safari / remote island / polar destinations, the all-inclusive package price divided by daily nights

The cost_index(a 1–100 number you'll see in some charts) is a separate abstract measure of overall cost of living. It usually tracks mid_range $/day closely, but diverges when a destination has unusual structure — e.g. Botswana's Okavango Delta sits at cost_index 90 but real mid-range $/day is $800 because of all-inclusive safari lodge pricing. In that case, trust the dollar number.

How the split is allocated

Inside each tier's daily total, we split spending across four buckets: stay / food / transit / activities. The base split is roughly 42 / 25 / 15 / 18, then shifts per destination:

• Expensive cities skew more toward accommodation (Tokyo, Paris, London).
• Walkable cities need less transit budget, more activity budget.
• Cheap-food destinations with standout food scenes (Bangkok, Oaxaca, Hanoi, Penang) bump food share.
• National parks and islands bump activities + transit (tours, transfers, rental gear), trim food + stay.
• Multi-stop regions/countries bump transit (intercity movement).

That gives each destination a distinctive stack — a Paris day tilts toward stay, a Bangkok day toward food, a Banff day toward activities — rather than every city showing the same pie chart.

FIFA-style stat cards

Each destination page shows a stat card with up to 9 attributes on a 30–99 scale: safety, affordability, food, culture, nightlife, walkability, nature, connectivity, transit. These are not votes or survey scores — they're derived from the same underlying data that drives comparisons and badges.

• Safety maps the destination's safety index (1–100) directly; the floor is 35.
• Food, culture, nightlife, walkability, transit, connectivity, and natureeach come from a per-attribute 1–5 editorial scale, mapped onto a universal 30–99 band: 1 → 44, 2 → 58, 3 → 72, 4 → 86, 5 → 99. Culture gets a small bonus based on the number of curated attractions in a guide — destinations with a deep attraction list earn up to +10 points. Nature gets a +8 boost for destinations typed as "natural" (national parks, fjords, wilderness regions) and +6 for islands. Most destinations land in the 55–85 band.
• Naturescores are uncapped — they reflect the raw 1–5 editorial rating on the same 30–99 scale as every other attribute. National parks, fjords, and other "natural" type destinations get a +8 point boost, and islands get +6, reflecting that nature access is their core draw. A city rated 3/5 for nature lands at 72; a national park rated 5/5 lands at 99.
• Overall is a weighted composite. For cities, towns, and islands, all 9 attributes contribute: safety 16%, culture 15%, food 14%, nature 13%, walkability 11%, transit 10%, affordability 9%, nightlife 7%, connectivity 5%.
• For nature and region destinations(fjords, national parks, wilderness areas), nightlife, walkability, and transit are excluded — they don't meaningfully apply to a fjord or a national park. The remaining 6 attributes are reweighted proportionally: safety 22.2%, culture 20.8%, food 19.4%, nature 18.1%, affordability 12.5%, connectivity 6.9%. This prevents world-class nature destinations from being dragged down by irrelevant low nightlife or transit scores.
• When a playstyle is active, custom weights override both defaults.

Seasonal modifiers

Stat cards shift with the calendar. Each month, attributes like walkability, nature, culture, and affordability receive small modifiers (roughly ±3 to ±10 points) based on the destination's best months, estimated temperature, and seasonal patterns. During peak season, culture and food scores nudge upward (festivals, full restaurant scenes); in extreme heat or cold, walkability drops; off-season months get a small affordability bump.

The stat card shows these shifts with small up/down arrows next to each score, plus a season pill (Peak, Shoulder, or Off-Season) in the header. The Overall score always uses base values — seasonal arrows are informational context, not baked into the composite.

Type-aware stat cards

Not every destination is a city. For national parks, fjords, and wilderness regions (typed as "natural" or "region"), the stat card drops three attributes that don't apply — nightlife, walkability, and transit — showing 6 stats instead of 9. The subtitle changes from "9-stat city rating" to "6-stat nature rating" or "6-stat region rating." Islands show all 9 stats with an "island rating" label.

This means destinations like the Norwegian Fjords, Swiss Alps, Banff, or Patagonia show a cleaner card focused on what actually matters there: safety, affordability, food, culture, nature, and connectivity.

Affordability score

Affordability is derived from the destination's cost_index — an abstract 1–100 measure of overall cost of living, where 1 is cheapest and 100 is most expensive. The formula inverts the index: affordability = 115 − cost_index, clamped to the 30–99 range. So a cost_index of 20 (very cheap — Hanoi, Yogyakarta) yields an affordability score of 95, while a cost_index of 85 (very expensive — Maldives, Bora Bora) yields 30.

The cost_index usually tracks mid-range $/day closely, but they can diverge for destinations with unusual pricing structures — e.g. all-inclusive safari lodges where the daily rate is very high but the cost_index reflects the regional economy more broadly.

What these numbers aren't

• They aren't forecasts. Prices move — currency shifts, seasonal spikes, new taxes. Use mid-range $/day as a planning anchor, not a booking guarantee. The cost calculator lets you mix tiers per category, which is closer to how most people actually travel.
• They assume shoulder season. Peak-season hotels can run 2–3× the mid-range number in cities like Reykjavik, Santorini, or Kyoto during cherry blossom.
• They assume two travelers sharing a room. The cost calculator adjusts for solo / three+ automatically using one room per pair.
• The FIFA stats are editorial calibration, not crowd data.They're designed so the top of each category feels defensible to someone who's been there. If a score looks wrong to you, that's useful feedback — tell us and we'll look at it.