Shift concentration
How concentrated the shifting is: largest shift over total shift.
At a glance the headline numbers for Shift concentration
How concentrated the shifting is: largest shift over total shift.
On the typical site, the largest single shift causes 1 of all layout shift.
Shift concentration the value at each percentile across all sites
Shift concentration 1.0. p75 1. p99 6.2. computed
Why this matters for the Core Web Vitals, and where to start fixing it
Two sites can have the same CLS for opposite reasons. One has a single big jump. The other moves a little, everywhere, all the time. This ratio separates them: the largest shift divided by the total. Close to one means one event causes nearly all the damage. Find that element, reserve its space, and the score follows.
A low concentration is the harder case. No single shift looks bad, but they add up. That pattern points at scroll-triggered animations, CSS transitions on layout properties, or content that streams in piece by piece. There is no one bug to fix, so it needs a structural pass instead of a patch.
Chrome field data from 189,915 sites, representing millions of real page loads. How we measured.
Live queries (2) — admin only
SELECT COUNT(*) AS count,
quantile_disc(m.cls.concentration, 0.10) AS p10,
quantile_disc(m.cls.concentration, 0.25) AS p25,
quantile_disc(m.cls.concentration, 0.50) AS p50,
quantile_disc(m.cls.concentration, 0.75) AS p75,
quantile_disc(m.cls.concentration, 0.90) AS p90,
quantile_disc(m.cls.concentration, 0.99) AS p99
FROM sites WHERE m.cls.concentration IS NOT NULL;SELECT CASE WHEN m.cls.concentration >= 0 AND m.cls.concentration < 1 THEN 0 WHEN m.cls.concentration >= 1 THEN 1 END AS bucket_idx, COUNT(*) AS n,
quantile_disc(crux."all".inp, 0.5) AS median,
COUNT(*) FILTER (WHERE crux."all".inp IS NOT NULL AND crux."all".inp <= 200) * 1.0 / NULLIF(COUNT(*) FILTER (WHERE crux."all".inp IS NOT NULL), 0) AS good_pct
FROM sites WHERE m.cls.concentration IS NOT NULL GROUP BY bucket_idx;