How to Value a PAGA Case: Why the Settlement Number on the Docket Tells You Almost Nothing
Two California PAGA matters settle. Both for $2 million. In any summary, either one appears as the same result, and in most conversations about what a case is worth, that is exactly how they get treated.
One of them covered a few hundred employees over eighteen months. The other covered several thousand people across four years. Measured against the exposure each one actually resolved, those are not comparable outcomes. They are not close. And nothing in the gross settlement figure tells you which is which.
This is the central problem with how PAGA settlements get discussed, and it is worth being precise about why — because the fix is straightforward, and the reason almost nobody applies it is not conceptual.
A settlement figure is a numerator with no denominator
Every settlement resolves a specific quantity of alleged exposure. On the PAGA side, that quantity is measured in pay periods: the number of aggrieved employees multiplied by the number of pay periods each of them worked during the covered window. On the class side, it is measured in workweeks.
The gross settlement amount is what got paid to resolve that quantity. Quoted on its own, it is half of a ratio. It tells you the size of the payment without telling you the size of the thing being paid for, which is why two matters can share a headline figure and represent completely different outcomes for the defendant.
A $2 million settlement across 40,000 pay periods and a $2 million settlement across 8,000 pay periods differ by a factor of five in what they actually cost per unit of exposure. One of those defendants did substantially better than the other. The docket will never say so.
The unit that makes two matters comparable
Normalize the settlement to its denominator and the comparison becomes meaningful. For PAGA claims, that is value per pay period. For class claims, value per workweek. These are the units that let you put two matters side by side and say something true about them.
They are also the units that survive changes in case size. A benchmark expressed in gross dollars is only usable against matters of similar scale, which means most of any comparables set gets discarded before the analysis starts. A per-unit benchmark travels. A small matter and a large one can be compared directly, and the difference that remains is a difference in how the case was valued rather than in how many people it covered.
This is the whole argument, and everything else in settlement analytics follows from it.
What the distribution actually looks like
Two things go wrong when settlement data gets summarized. The first is using the wrong unit. The second is using the wrong measure of the middle, and the second is easier to demonstrate.
Across the California settlements Scaled Comp tracks, the mean settlement in July 2026 was roughly $726,000. The median for the same set was $399,000.
The average sits nearly twice as high as the typical outcome. That gap is not an error in the data. It is what a long right tail does to a mean: a small number of very large settlements pull the average up and away from the middle of the distribution, and almost no individual matter resolves anywhere near the resulting figure. Anyone quoting an average PAGA settlement is quoting a number that describes no real case particularly well.
This is why every settlement benchmark Scaled Comp publishes is reported as a median or a trimmed mean. The median tells you what a matter in the middle actually resolved for. A trimmed mean tells you the same thing with the extremes removed rather than merely outvoted. The distance between a set's mean and its median is itself diagnostic — a mean sitting far above its median means the set is being carried by a handful of outcomes, and any benchmark built on it will overstate what a typical case is worth.
Apply the right unit and the right measure together and you get something usable. Across a trailing three-month window through July 2026, the median PAGA settlement value worked out to roughly $7.50 per pay period across 350 matters. That is a number you can hold a new case against. A gross settlement amount is not.
Why the denominators are hard to come by
If per-unit value is so obviously the right measure, the reasonable question is why gross figures remain the default in almost every conversation.
The answer is that the denominators are not on the docket. Pay period counts and workweek counts live inside settlement agreements, and they are phrased differently depending on who drafted the document. Some agreements state the figure directly. Some give a class size and a period and leave the multiplication to the reader. Some bury it in a declaration supporting preliminary approval. Some never state it at all, and the number has to be inferred from the allocation formula.
Extracting that for a single matter is an afternoon of careful reading. Extracting it across thousands of matters, consistently enough that the resulting medians hold up, is a different kind of problem — and it is the reason so much PAGA valuation still runs on recollection and reputation rather than on numbers.
The first version of Scaled Comp's own settlement database tracked gross amounts and little else. It was close to useless for the question people actually asked it. Rebuilding around per-unit extraction turned into most of the work, and most of the cost, of building the system at all.
A per-unit benchmark still needs the right comparables
Normalization solves the unit problem. It does not, by itself, produce a defensible benchmark, because a per-unit median is only as good as the set it is computed over.
Claim mix matters — a PAGA-only matter and a matter carrying both PAGA and class claims allocate money differently, and blending them produces a figure that describes neither cleanly. Covered period length matters. Workforce size and industry matter. So does whether the underlying notice predates the 2024 PAGA reform, which changed the arithmetic enough that pre- and post-reform matters function as two distinct populations rather than one continuous series.
Change any one of those filters and the benchmark moves. Which means the useful question is never simply what comparable cases settled for, but what the comparables set was filtered on before the median was taken.
Three questions worth asking of any settlement benchmark
Whether the number comes from a report, a colleague, or a mediator's opening framing, three questions separate a usable benchmark from an anecdote with a decimal point.
First: what is the denominator? If the figure is expressed in gross dollars rather than per pay period or per workweek, it cannot be compared to a matter of a different size without adjustment.
Second: is it a median or an average? If it is an average, ask what the median was and how far apart they sit. The gap tells you how much the figure is being carried by outliers.
Third: what was it filtered on? Claim mix, period length, industry, workforce size, and reform-era status all move the number materially, and a benchmark computed without them is measuring a broader population than the one your case belongs to.
Where this leaves case valuation
None of this replaces judgment. An experienced practitioner brings pattern recognition that no dataset supplies, and the specific facts of a matter will always drive more of the outcome than any benchmark can.
But judgment built on a career is a sample selected by which matters happened to come to you, and it is not auditable by the client paying the bill. A per-unit benchmark computed over a filtered comparables set is. The two work best together — the benchmark establishes where the market sits, and judgment explains why this particular matter should sit above or below it.
What does not work is the middle path most valuation conversations still default to: a gross figure, remembered approximately, from a set of cases nobody filtered.
Scaled Comp maintains a structured index of California PAGA and class action settlements, built from court documents and linked to state filing records, covering matters from 2024 forward and growing continuously. Per-unit normalization is the reason it exists.