A lot of players ask us: how exactly is my score calculated? It's not just about getting the order right — it's about how far off you are from what thousands of other players think, and some disagreements cost you more than others. Here's the full breakdown of how Blind Ranking works, from first pick to final score.
The Game in 60 Seconds
When you start a game, you're shown a category — NBA players, best movies, supermodels, 2020s hits, whatever you pick. The game randomly selects 10 items from that category's full list and presents them to you one at a time.
Your job is simple: place each item in a position from 1 to 10. Position 1 is the best, position 10 is the worst. Each position can only be used once — so you're building a ranked list as you go, and every decision locks in your previous choices.
Once all 10 items are placed, the game reveals your score and shows you exactly how far off each pick was from the community consensus. That's when it gets interesting.
What Is the "Community Consensus"?
Every time someone plays a category, their rankings are recorded. Over time, for each item in the category, we collect hundreds or thousands of individual rank choices from different players around the world.
From all those submissions, we calculate the median rank for each item — the middle value that best represents where the community as a whole tends to place it. We use a rolling 10-day window, which means the consensus stays current and reflects recent player opinion rather than being locked to old data.
Think of it like this: if 1,000 people have played the NBA Players category and most of them put LeBron James at #1 or #2, the community median for LeBron will be close to #1. If you put him at #5, that's a big miss. If you put him at #2, that's nearly perfect.
How Your Score Is Calculated
Here's where it gets a little more nuanced. Your score isn't just the average of how many positions off you were. Not all misses are equal.
Step 1 — Measure Each Gap
For every item, we calculate the difference between where you placed it and where the community median puts it. If the community median for a player is #3 and you put them at #6, your gap is 3 positions.
Step 2 — Weight by Consensus Strength
Here's the key twist: items where the community strongly agrees count more toward your score than items where the community is divided.
We measure consensus strength using the IQR (interquartile range) — a statistical measure of how spread out people's rankings are. If 80% of players put Cristiano Ronaldo at #1 or #2, the IQR is very small, meaning the community is highly aligned. If players split evenly across positions 1–8 for a particular item, the IQR is large, meaning there's no real consensus.
Items with strong consensus (low IQR) get a higher weight in your score. Items where the community can't agree (high IQR) matter less — because if nobody agrees, there's no "right" answer to miss. This is fairer and more meaningful: you should be rewarded for agreeing with the crowd on things the crowd is certain about.
Step 3 — Combine into a Final Score
We take all 10 weighted gaps, combine them into a single deviation score, and map that to a 0–100 scale:
| Score Range | Label | What It Means |
|---|---|---|
| 90–100 | Elite Taste | Almost perfectly aligned with the community |
| 75–89 | Sharp Eye | Strongly in sync, minor divergences |
| 60–74 | Good Effort | Broadly aligned with a few notable misses |
| 40–59 | Getting There | Mixed results — right on some, off on others |
| 0–39 | Unique Perspective | Significantly out of step with community consensus |
A score of 100 means you ranked all 10 items exactly where the community median puts them. A score of 0 means every pick was as far from the community as possible. In practice, most players land between 50 and 80 on their first attempt at a new category.
Why Some Picks Hurt More Than Others
Two examples from real game sessions illustrate this well:
Example A: You put Angelina Jolie at #7 in the Most Attractive Women category. The community median is #2. That's a 5-position gap. The community has very strong consensus on Angelina Jolie — she consistently lands near the top across thousands of sessions. Because the IQR is tiny, this pick is weighted heavily. A single 5-position miss on a high-consensus item will tank your score significantly.
Example B: You put a mid-tier musician at #6 and the community median is #4. That's a 2-position gap. But the community is all over the place on this artist — some love them, some don't. The IQR is large. This miss barely affects your score.
The lesson: the items that everyone agrees on are the ones you can't afford to get wrong. The controversial picks are forgiving. Get the consensus picks right first.
The 10-Day Rolling Window
The community consensus isn't frozen — it updates constantly. We recalculate median ranks using only the last 10 days of submissions. This has two important effects:
1. It stays culturally current. If a musician releases a huge album this week and suddenly 3,000 new players rank them higher, the community median shifts upward within days. Categories feel alive because they reflect current opinion.
2. It protects against stale data. A ranking submitted two years ago shouldn't define the consensus today. Cultural tastes shift. Players change their minds. The 10-day window keeps the score meaningful and tied to what the community actually thinks right now.
Why "Spot On" Feels So Good
When a pick shows "✓ Spot On", it means your placement matched the community median exactly. Given that you're placing 10 items across 10 positions without seeing any other rankings, a spot-on pick is a genuine signal that your taste and the crowd's taste are aligned on that item.
Getting 4 or 5 spot-on picks in a single game is genuinely impressive. Getting 8 or more is exceptionally rare — it means your intuition about the category is nearly identical to the collective judgment of hundreds of other players.
What Happens With New Categories?
When a brand new category goes live, there's no community data yet. We require a minimum of 3 submissions per item before community stats are calculated for that item. Until then, your score for games in that category is calculated once enough data accumulates.
This means early players in a new category are actually shaping the community consensus — their rankings directly influence what the "correct" answer looks like for everyone who comes after them. Playing early matters.
Can You Improve Your Score by Replaying?
Yes — and there's a skill element to it. After each game, you see exactly where you diverged from the community. Armed with that information, you can replay the category with a better understanding of what the crowd thinks. Many players use the results screen as a learning tool.
That said, you're always playing a random selection of 10 items from the full category list — so replaying gives you a different set of items each time. A high score requires consistent alignment across the whole category, not just a lucky draw on easy items.
The players at the top of our leaderboard have typically played categories dozens of times, refined their understanding of community preferences, and built up a genuine sense of where the crowd stands on each item. That's real skill — not luck.
TL;DR — How It Works
- → You rank 10 randomly selected items from 1 to 10
- → Your score compares your ranks to the community median (last 10 days)
- → Items where the community strongly agrees are weighted more heavily
- → Getting the high-consensus picks right is what separates good scores from great ones
- → The consensus updates in real time — play again and it may shift
Ready to test how well your taste matches the crowd? Browse all categories and start playing — it's free, no account needed.