Red · Maipo Valley · Chile
Matetic Corralillo Cabernet Sauvignon
Scored from 743 calibrated Vivino reviewers, each re-centered on their own rating baseline before the bottle is ranked. Cohort: Red · Chile (444 wines).
Find this wine: view on Vivino · compare prices on Wine-Searcher
What reviewers say
“Degustação pessoal no almoço com coravin vinhos da Gran cru... Para o meu paladar e da minha esposa: primeiro lugar ficou corralillo cabernet Sauvignon 2016 segundo lugar errazuriz Max carmenere safra 2019 e em terceiro lugar errazuriz Max cabernet Sauvignon safra 2018.”
From a top-rated Vivino review for this bottle.
Summary
Immensely fruity, with spicy and distinctive balsamic and chocolate notes. A concentrated, rich palate with round tannins leads to a long and juicy aftertaste.
Matetic Corralillo Cabernet Sauvignon is a red from Maipo Valley, Chile.
The cohort it is ranked inside holds 444 Chilean reds. The calibrated figure is built from 743 reviewers whose rating history varies enough to place their own average. A broader pool of 757 reviewers with two or more ratings feeds the raw-average track instead.
How the score was built
We compare the reviewers of this bottle against every other wine those same people reviewed. Each review is scored relative to the reviewer's own baseline — four stars from someone who hands out fives means something very different from four stars from someone who rarely goes above three. Every reviewer then counts the same, so the result is a calibrated consensus rather than a star average.
- Global percentile
- Where Matetic Corralillo Cabernet Sauvignon lands against every wine we rank.
- In-cohort percentile
- The same comparison narrowed to its cohort — wines of the same type from the same country. A Chilean red is judged against Chilean reds, not against Champagne. Ranked against Red · Chile (444 wines).
- AI-adjusted percentile
- The same reviewer-normalized score, corrected for how much confidence the sample supports: thin samples are pulled toward the corpus average. Each wine keeps the share n / (n + 53) of its measured distance from the average, where n is its calibrated-reviewer count, and the result is ranked on the same scale as the global percentile.53 is the median sample size across everything we rank. Here n is 743.
