How the selection works
The formulas below describe automatic raw scores, not the publisher_assigned exceptions.
These catalog listings are ordered by our published editorial score, highest first, with a stable tie-break when calculated scores match. Use the sort controls to change the order. Automatic scores combine available public Amazon review data with documented listing attributes under the published formula; they are not hands-on test results or Amazon customer ratings.
Manufacturer documentation and exact listing details answer different questions. A seller title identifies the listing but does not prove dimensions, performance or accessory compatibility. We do not award best value without verified prices.
Where the exact Amazon listing text states a pump pressure in bar, our documented spec-fit score is 100 × min(stated bar / 20, 1), rounded to a whole number as the documentation input to the review blend, not the final displayed rating. The stated bar figure is the seller's maximum pump rating — a marketing specification, not measured brew pressure. Machines without an explicit bar figure, and all grinder, cleaning and accessory listings, use the documentation completeness score below instead; ties use the product slug. This index is not a taste test, workflow rating or customer review.
Where a listing has no documented spec-fit inputs, our documentation completeness score is 100 × [0.5 × min(documented feature bullets / 8, 1) + 0.3 × min(product images / 5, 1) + 0.2 × (brand documented ? 1 : 0)], rounded to a whole number as the documentation input to the review blend, not the final displayed rating. Every input is read from the stored Amazon listing record, so the same listing always produces the same score. This measures how completely the listing is documented — it is not a performance test, a quality measurement or a customer review.
Where Amazon publicly displays customer reviews for a listing (average star rating and review count captured from the public product page), the raw editorial score is 100 × [0.45 × (Amazon average / 5) × min(review count / 50, 1) + 0.35 × min(log10(1 + review count) / log10(1 + 5000), 1) + 0.20 × documentation score / 100]. The confidence factor min(review count / 50, 1) damps averages based on very few reviews, and the logarithmic volume term rewards large public review volumes, so widely and highly reviewed listings rank ahead of thinly reviewed ones. Listings with no captured public review data use the documentation score alone. This combined index reflects the public Amazon reputation and the listing documentation — it is not a physical test and not our own product testing.
For formula_calculated ratings only:
The displayed editorial rating is the raw blended score divided by 10, shown to one decimal on a 0-10 scale. There is no catalog normalization, rank interpolation, forced winner, forced floor or artificial gap. Equal scores remain equal: the available data does not justify a distinction. Ranking uses the unmodified raw score descending, then listing slug for exact ties; slug is a stable identifier, not a quality signal. The same raw score always has the same display rating in every shortlist. This is not a physical test result or an Amazon customer rating.
