How the BANG Score works

The BANG Score is one number, 0 to 100, for how much game you get per dollar. A 41 is a 41. You can argue with it, and people do. That argument is the point.

Here is what sits under the number.

Reviews set the ceiling

The base of the score is the Steam review rating, shrunk toward the middle when a game has few reviews so a 100 percent from nine people cannot outrank a 96 percent from ninety thousand. A game that reviews badly cannot climb, no matter how cheap it is. Price moves you down inside that ceiling. It never lifts you past it. Reviews lead, length follows.

This ordering matters more than any single weight. An early version led with dollars per hour, and every short, brilliant game scored like a ripoff while padded grinds floated to the top. Flipping reviews to the front fixed it in one change.

Price is measured against real length

Value here is price against content, not price against a store page. A game's length comes from HowLongToBeat where we can match it. Short-by-design games get a per-genre floor, so a five-hour narrative game is measured against other narrative games instead of against a sixty-hour RPG. A game you replay rather than beat, a roguelike or a co-op shooter, gets credit for that replay depth instead of one short campaign.

When a game has no verified length at all, the score says so and carries a dock, because the biggest input is then a guess. A verified length removes that dock.

What raises and lowers a score

Every game page shows the drivers, sorted into what raises the score, what lowers it, and what sits neutral. The common ones:

• Reviews. The gate. Strong reviews unlock the top band, weak reviews cap it.
• Value. Price per hour of real content, the largest single mover.
• Reach. How many people own it, a popularity and confidence signal.
• Finish rate. The share of players who actually get through a game, read from Steam global achievements. This is a bonus that reserves the very top of the scale.
• Monetization. Loot boxes and pay-to-win apply a haircut. A clean game takes none.

What it does not do

The score rates value, not taste. Whether a game is for you is still on you. It is deterministic: the same data gives the same number every time, with no model guessing in the loop. And the formula weights stay private. The score is shown, every input fact behind it is shown, the recipe is not. A published formula gets gamed in a week.

Where it is weak, plainly

Global achievement rate is noisy, and a game with no achievements has none of it. HowLongToBeat does not list every game, and a missing length weakens the value read until it is filled in. Owner estimates are rough at the long tail. The score is at its best on games with a real review base and real length data, and it says "limited data" when it is working with thin inputs. Treat a provisional number as provisional.

The honest version of this product is the one that shows you exactly where the number is soft.