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How to calculate team capacity for a sprint in Linear

Most sprint planning starts with a backlog and ends with a gut-feel commitment. That's how teams end up overcommitted every cycle. Capacity planning flips it: you figure out how much time the team actually has first, then decide what fits.

Here's a practical way to calculate it for a Linear cycle.

The honest formula

capacity = engineers × cycle_days × focus_hours_per_day
         − PTO
         − on-call hours
         − interview hours
         − meeting overhead
         − expected interruptions

The mistake is starting from 8 hours × 5 days × N engineers. Nobody ships 40 focused hours a week. Realistic focus time for most engineering teams lands between 3 and 5 hours per working day, and that's before on-call or interview load.

Step-by-step for a 2-week Linear cycle

1. Start with headcount-days. 6 engineers × 10 working days = 60 engineer-days.

2. Subtract time off. Check calendars. If two people take 2 days each: −4 days. Down to 56.

3. Subtract on-call. Whoever's on primary usually loses 30–50% of their cycle. If one person is on-call the full two weeks, subtract ~5 days. Down to 51.

4. Subtract interviews and recurring meetings. Estimate per-person load. If everyone loses ~1 day to meetings and two people do 4 hours of interviews: ~7 days. Down to 44.

5. Apply a focus factor. The remaining days aren't 8-hour days. Multiply by 0.5–0.6 to get effective hours. 44 × 0.55 × 8 = ~194 focus hours.

That's the real number. For most teams, it's 40–50% of the naive headcount math.

Doing this in Linear

Linear doesn't expose a native capacity view, so you have to assemble it:

Most teams skip step 3 — the non-delivery issues — and then wonder why velocity "dropped." It didn't drop; the invisible work just stayed invisible.

Common mistakes

The shortcut

If the math feels heavy: rule of thumb for most Linear teams is 40–55% of naive capacity. A 6-engineer, 2-week cycle with 480 naive hours is realistically 190–260 focus hours. Plan to that, not to 480.

Capacity planning isn't a science. But even a rough, honest number beats the ambitious fiction most teams commit to.

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