BR-US Shoe Size Converter

About This Tool

The BR-US Shoe Size Converter provides a domain-focused mechanism to translate sizes between Brazilian (BR) and United States (US) footwear systems. It targets online shoppers, catalog teams, retailers, and footwear designers who need precise, repeatable size guidance for cross-market product listings. By centralizing a trusted BR↔US mapping, it helps ensure consistent fit expectations across geographies and reduces sizing confusion in catalogs, marketplaces, and checkout flows.

How it works conceptually: the user enters a BR size, selects gender (Men, Women, Kids), and chooses the direction BR_to_US or US_to_BR. The tool consults standard charts, applies gender-specific offsets, and returns a closest-match size along with a human-readable label (for example US Women size 9) and a confidence score reflecting chart coverage and brand variability. It supports half sizes where data exists and notes when data is inferred rather than chart-backed.

Core features and rules include required inputs (size, gender, direction) and optional modifiers (width, brand tolerance, unisex mode). Outputs consist of mapped_size, mapped_label, and a confidence level. Validation enforces positive numeric sizes and valid enums; in cases of missing or conflicting inputs, the system returns precise errors and suggests corrective input ranges. Advanced usage includes exporting results as CSV or JSON for catalogs and ERP feeds.

Industry standards and localization: the tool uses BR and US sizing conventions and outputs language-agnostic data suitable for international product data platforms. It supports Men, Women, and Kids categories and is designed to accommodate typical brand variances while emphasizing clarity and consistency across channels.

Assumptions & exclusions: mappings are approximate, not a guarantee of fit, and do not account for brand-specific lasts or regional width differences unless width data is provided. The tool focuses on sizing translation, not brand calibration or footwear recommendations.

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