White · Mercurey · Frankreich
Château Philippe-Le-Hardi Les Bois de Lalier Mercurey
Scored from 139 calibrated Vivino reviewers, each re-centered on their own rating baseline before the bottle is ranked. Cohort: White · Frankreich (687 wines).
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What reviewers say
“D ⤵️: Reinsortiger Chardonnay mit sehr sortentypischer Machart. Eher auf der fruchtigen, denn der floralen Seite. Mango, Lindenblüten, Weissbrot. Leichte Salznote und cremige Textur. Sehr schön. A single-varietal Chardonnay with a very typical varietal finish. More fruity than floral. Mango, linden blossom, white bread. A slight salty note and a creamy texture. Very nice.”
From a top-rated Vivino review for this bottle.
Summary
Château Philippe-Le-Hardi Les Bois de Lalier Mercurey is a white from Mercurey, France. It is made from Chardonnay.
139 Vivino reviewers rate with enough spread for a personal baseline to be measured, and those are the ones the calibrated score reads; a separate, broader pool of 140 reviewers with at least two ratings each feeds the raw-average track. The cohort it is ranked inside holds 687 French whites.
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 Château Philippe-Le-Hardi Les Bois de Lalier Mercurey 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 White · Frankreich (687 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 139.
