What the rating counts: an average and the ratings behind it

A rating on a store page is two numbers glued together: an average and a count. The first is what people look at; the second tells you how much weight the first can bear. On 6 November 2026 this desk read both on three listings and the split by star underneath. The table below is the reading; the text explains how to take it apart.

The rating figures and the stars

Average, number of ratings and the count and share for each number of stars.

Two figures on one Google Play page

On the Google Play page of the app titled FxPro: Trading & Investing the header shows 4.4 stars and a review count that reads “104K reviews”, 104,036 when the page's data is read in full. Lower on the same page, in the “Ratings and reviews” block, the figure is 4.3 with 102,440 ratings. They are not a mistake on this site: the page prints both and does not explain the difference, which is why the table prints both rows for each Play listing and does not choose between them. The difference between 104,036 and 102,440 is 1,596 ratings; the two averages are 4.352 and 4.340 before rounding.

That is the first lesson of reading a rating: the rounding is part of what you see. 4.352 rounds to 4.4 and 4.340 rounds to 4.3, and both are honest roundings of numbers that are a hundredth of a star apart.

The same count, split by star

The star split in the table is worked out from the counts the page gives. On the first Play listing 72,080 of 102,339 ratings in the block are five-star (70%) and 8,929 are one-star (9%). On the second Play listing the block counts 2,569 five-star (77%) against 130 one-star (4%). On the App Store, 150 of 181 ratings are five-star (83%) and 11 are one-star (6%).

An average hides a shape. Two listings can both read 4.4 with a very different distribution, one with nearly all ratings at five and one with many at five and a visible block at one. The split is the part of the page that shows the difference, and it is the reason the table lists all five bars rather than only the average.

Why the count matters more than it seems

4.6 from 181 ratings on the App Store and 4.6 from 3,463 on the second Play listing look alike. They are not equally firm. With 181 ratings, each single rating moves the average by about 0.03 of a star at most (five stars divided by the count); with 3,463 it is 0.0014, and with 104,036 ratings on the first listing, 0.00005. That is arithmetic, not a view on the apps. It means that a small count can swing from one reading to the next, and that a rating built on tens of thousands of ratings will be stable by comparison.

The count is also the reason this site shows the date. Two requests for the first Play page, made about an hour apart on the day of reading, returned 104,035 and 104,036 ratings. A rating is a moving number, and a figure without its date is half a figure.

Different stores, different populations

The Play figures and the App Store figures are not a single survey. They are collected by two companies, from two groups of phone owners, for apps that the pages show under two developer names. The App Store count of 181 was read in the India storefront; the Play pages were read in the India view with English text. Putting the two averages side by side is allowed, subtracting one from the other to say which app is better is not: nothing on the pages says that they rate the same product.

The Play page also carries the label “Ratings and reviews are verified”. This site repeats the label as the page words it and has not tested it. The App Store page puts no such label next to its stars.

What this page deliberately leaves out

The store pages also show reviews: people's own words, with their names. This site does not copy them. They are other people's writing, they change by the hour, and a handful chosen by a store's ordering are not a sample. The captured pictures on this site have the review cards hidden for the same reason, and say so.

What remains is the part of a rating that can be recomputed: an average, a count and five bars. Everything else a reader wants to know about an app, and above all whether it is right for their own trading, is beyond what a public store page can answer.

A way to read the table

Start with the count, then the average, then the one-star bar. A listing with a high average and a very small count tells you little yet. A listing with a large count and a visible one-star share tells you that many people were unhappy enough to give the lowest rating, whatever the reason; the page does not say why. A listing whose average and distribution agree across two figures on the same page is more settled than one where they differ.

None of this decides whether to install. It tells you how much a star rating can carry.