Rules guide · Warhammer 40K 11th Edition · paraphrased, not official text

How does Objective Control (OC) work in Warhammer 40K?

OC (Objective Control) is the stat that measures how much a model counts toward holding an objective. Each player totals the OC of their models in range of an objective; the side with the higher total controls it — and a tie means nobody does. That one stat decides most of the scoring in a game.

What does the OC stat actually do?

Every model has an OC characteristic, and holding objectives is pure arithmetic: add up the OC of your models in range, add up your opponent's, and compare. Higher total controls the objective; equal totals mean it's contested and controlled by neither player. This is why a cheap unit with many models can out-hold an expensive one — ten models contributing OC each can outweigh a single big model standing on the same objective. It's also why "how much OC can I get there, and how much can they?" is the real question behind most late-game moves. On 40 Carrot's virtual tabletop the OC math is tracked for you, so you can practice these counting fights without a calculator in hand.

How do terrain-area objectives differ from classic markers?

11th Edition adds a second flavor of objective. A terrain-area objective is a terrain footprint that is itself the objective: you contest it with models inside the footprint, not within a radius around a point. A classic objective marker is the legacy style — a 40mm marker controlled by models within 3" of it. The distinction changes how you fight for ground: a footprint objective rewards actually occupying the building or ruin, while a classic marker rewards ringing the point. 40 Carrot shows the difference visually — terrain-area objectives are marked gold, classic markers get a dashed control ring — so you can practice both styles on the same board.

Why does OC matter for practice games?

Because objectives, not kills, decide most games. Practicing the OC math — when to commit a unit to a point, when a tie is good enough to deny scoring, when a single surviving model still flips an objective — is exactly the kind of repetition that's expensive on a physical table and cheap in a browser. Set up a board, put units on objectives, and the AI tactical advisor can talk through who controls what and why.